Full Code of apple/corenet for AI

gitextract_0z54odcq/

├── .dockerignore
├── .flake8
├── .gitattributes
├── .gitignore
├── ACKNOWLEDGEMENTS
├── CODE_OF_CONDUCT.md
├── CONTRIBUTING.md
├── LICENSE
├── Makefile
├── README.md
├── conftest.py
├── corenet/
│   ├── __init__.py
│   ├── __main__.py
│   ├── __version__.py
│   ├── cli/
│   │   ├── __init__.py
│   │   ├── entrypoints.py
│   │   ├── main.py
│   │   ├── main_benchmark.py
│   │   ├── main_conversion.py
│   │   ├── main_eval.py
│   │   ├── main_eval_llmadapters.py
│   │   └── main_train.py
│   ├── constants.py
│   ├── data/
│   │   ├── __init__.py
│   │   ├── collate_fns/
│   │   │   ├── __init__.py
│   │   │   ├── byteformer_collate_functions.py
│   │   │   └── collate_functions.py
│   │   ├── data_loaders.py
│   │   ├── datasets/
│   │   │   ├── __init__.py
│   │   │   ├── audio_classification/
│   │   │   │   ├── __init__.py
│   │   │   │   └── speech_commands_v2.py
│   │   │   ├── classification/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── base_image_classification_dataset.py
│   │   │   │   ├── base_imagenet_shift_dataset.py
│   │   │   │   ├── coco.py
│   │   │   │   ├── imagenet.py
│   │   │   │   ├── imagenet_a.py
│   │   │   │   ├── imagenet_r.py
│   │   │   │   ├── imagenet_sketch.py
│   │   │   │   ├── imagenet_synsets.py
│   │   │   │   ├── imagenet_v2.py
│   │   │   │   ├── places365.py
│   │   │   │   └── wordnet_tagged_classification.py
│   │   │   ├── dataset_base.py
│   │   │   ├── detection/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── base_detection.py
│   │   │   │   ├── coco_base.py
│   │   │   │   ├── coco_mask_rcnn.py
│   │   │   │   └── coco_ssd.py
│   │   │   ├── language_modeling/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── base_lm.py
│   │   │   │   ├── commonsense_170k.py
│   │   │   │   └── general_lm.py
│   │   │   ├── multi_modal_img_text/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── base_multi_modal_img_text.py
│   │   │   │   ├── flickr.py
│   │   │   │   ├── img_text_tar_dataset.py
│   │   │   │   └── zero_shot_image_classification/
│   │   │   │       ├── __init__.py
│   │   │   │       ├── base_zero_shot_image_classification.py
│   │   │   │       ├── imagenet.py
│   │   │   │       ├── imagenet_a.py
│   │   │   │       ├── imagenet_class_names.py
│   │   │   │       ├── imagenet_r.py
│   │   │   │       ├── imagenet_sketch.py
│   │   │   │       └── templates.py
│   │   │   ├── segmentation/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── ade20k.py
│   │   │   │   ├── base_segmentation.py
│   │   │   │   ├── coco_segmentation.py
│   │   │   │   ├── coco_stuff.py
│   │   │   │   └── pascal_voc.py
│   │   │   └── utils/
│   │   │       ├── __init__.py
│   │   │       ├── common.py
│   │   │       ├── text.py
│   │   │       └── video.py
│   │   ├── io/
│   │   │   ├── __init__.py
│   │   │   └── transfer_clients.py
│   │   ├── loader/
│   │   │   ├── __init__.py
│   │   │   └── dataloader.py
│   │   ├── sampler/
│   │   │   ├── __init__.py
│   │   │   ├── base_sampler.py
│   │   │   ├── batch_sampler.py
│   │   │   ├── chain_sampler.py
│   │   │   ├── multi_scale_sampler.py
│   │   │   ├── utils.py
│   │   │   ├── variable_batch_sampler.py
│   │   │   ├── video_batch_sampler.py
│   │   │   ├── video_clip_batch_sampler.py
│   │   │   └── video_variable_seq_sampler.py
│   │   ├── text_tokenizer/
│   │   │   ├── __init__.py
│   │   │   ├── base_tokenizer.py
│   │   │   ├── clip_tokenizer.py
│   │   │   └── sentencepiece_tokenizer.py
│   │   ├── transforms/
│   │   │   ├── __init__.py
│   │   │   ├── audio.py
│   │   │   ├── audio_aux/
│   │   │   │   ├── __init__.py
│   │   │   │   └── mfccs.py
│   │   │   ├── audio_bytes.py
│   │   │   ├── base_transforms.py
│   │   │   ├── common.py
│   │   │   ├── image_bytes.py
│   │   │   ├── image_pil.py
│   │   │   ├── image_torch.py
│   │   │   ├── utils.py
│   │   │   └── video.py
│   │   └── video_reader/
│   │       ├── __init__.py
│   │       ├── base_av_reader.py
│   │       ├── decord_reader.py
│   │       ├── ffmpeg_reader.py
│   │       ├── ffmpeg_utils.py
│   │       └── pyav_reader.py
│   ├── engine/
│   │   ├── __init__.py
│   │   ├── default_trainer.py
│   │   ├── detection_utils/
│   │   │   ├── __init__.py
│   │   │   └── coco_map.py
│   │   ├── eval_detection.py
│   │   ├── eval_segmentation.py
│   │   ├── evaluation_engine.py
│   │   ├── fsdp_trainer.py
│   │   ├── segmentation_utils/
│   │   │   ├── __init__.py
│   │   │   └── cityscapes_iou.py
│   │   └── utils.py
│   ├── loss_fn/
│   │   ├── __init__.py
│   │   ├── base_criteria.py
│   │   ├── classification/
│   │   │   ├── __init__.py
│   │   │   ├── base_classification_criteria.py
│   │   │   ├── binary_cross_entropy.py
│   │   │   ├── cross_entropy.py
│   │   │   └── focal_loss.py
│   │   ├── composite_loss.py
│   │   ├── detection/
│   │   │   ├── __init__.py
│   │   │   ├── base_detection_criteria.py
│   │   │   ├── mask_rcnn_loss.py
│   │   │   └── ssd_multibox_loss.py
│   │   ├── distillation/
│   │   │   ├── __init__.py
│   │   │   ├── base_distillation.py
│   │   │   ├── hard_distillation.py
│   │   │   └── soft_kl_distillation.py
│   │   ├── language_modeling/
│   │   │   ├── __init__.py
│   │   │   ├── base_lm.py
│   │   │   ├── cross_entropy.py
│   │   │   └── cross_entropy_for_kv_prediction.py
│   │   ├── multi_modal_img_text/
│   │   │   ├── __init__.py
│   │   │   ├── base_multi_modal_img_text_criteria.py
│   │   │   └── contrastive_loss_clip.py
│   │   ├── neural_augmentation.py
│   │   ├── segmentation/
│   │   │   ├── __init__.py
│   │   │   ├── base_segmentation_criteria.py
│   │   │   └── cross_entropy.py
│   │   └── utils/
│   │       ├── __init__.py
│   │       ├── build_helper.py
│   │       └── class_weighting.py
│   ├── metrics/
│   │   ├── __init__.py
│   │   ├── average_precision.py
│   │   ├── coco_map.py
│   │   ├── confusion_mat.py
│   │   ├── image_text_retrieval.py
│   │   ├── intersection_over_union.py
│   │   ├── metric_base.py
│   │   ├── metric_base_test.py
│   │   ├── misc.py
│   │   ├── multiclass_classification_pr.py
│   │   ├── probability_histograms.py
│   │   ├── psnr.py
│   │   ├── retrieval_cmc.py
│   │   ├── stats.py
│   │   ├── topk_accuracy.py
│   │   └── vqa_preset_score.py
│   ├── modeling/
│   │   ├── __init__.py
│   │   ├── anchor_generator/
│   │   │   ├── __init__.py
│   │   │   ├── base_anchor_generator.py
│   │   │   └── ssd_anchor_generator.py
│   │   ├── image_projection_layers/
│   │   │   ├── __init__.py
│   │   │   ├── attention_pool_2d.py
│   │   │   ├── base_image_projection.py
│   │   │   ├── global_pool_2d.py
│   │   │   └── simple_projection_head.py
│   │   ├── layers/
│   │   │   ├── __init__.py
│   │   │   ├── activation/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── gelu.py
│   │   │   │   ├── hard_sigmoid.py
│   │   │   │   ├── hard_swish.py
│   │   │   │   ├── leaky_relu.py
│   │   │   │   ├── prelu.py
│   │   │   │   ├── relu.py
│   │   │   │   ├── relu6.py
│   │   │   │   ├── sigmoid.py
│   │   │   │   ├── swish.py
│   │   │   │   └── tanh.py
│   │   │   ├── adaptive_pool.py
│   │   │   ├── base_layer.py
│   │   │   ├── conv_layer.py
│   │   │   ├── dropout.py
│   │   │   ├── embedding.py
│   │   │   ├── flash_multi_head_attention.py
│   │   │   ├── flatten.py
│   │   │   ├── global_pool.py
│   │   │   ├── identity.py
│   │   │   ├── linear_attention.py
│   │   │   ├── linear_layer.py
│   │   │   ├── multi_head_attention.py
│   │   │   ├── normalization/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── batch_norm.py
│   │   │   │   ├── group_norm.py
│   │   │   │   ├── instance_norm.py
│   │   │   │   ├── layer_norm.py
│   │   │   │   ├── rms_norm.py
│   │   │   │   └── sync_batch_norm.py
│   │   │   ├── normalization_layers.py
│   │   │   ├── pixel_shuffle.py
│   │   │   ├── pooling.py
│   │   │   ├── positional_embedding.py
│   │   │   ├── positional_encoding.py
│   │   │   ├── random_layers.py
│   │   │   ├── rotary_embeddings.py
│   │   │   ├── single_head_attention.py
│   │   │   ├── softmax.py
│   │   │   ├── stochastic_depth.py
│   │   │   ├── token_merging.py
│   │   │   └── upsample.py
│   │   ├── matcher_det/
│   │   │   ├── __init__.py
│   │   │   ├── base_matcher.py
│   │   │   └── ssd_matcher.py
│   │   ├── misc/
│   │   │   ├── __init__.py
│   │   │   ├── averaging_utils.py
│   │   │   ├── box_utils.py
│   │   │   ├── common.py
│   │   │   └── init_utils.py
│   │   ├── models/
│   │   │   ├── __init__.py
│   │   │   ├── audio_classification/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── audio_byteformer.py
│   │   │   │   └── base_audio_classification.py
│   │   │   ├── base_model.py
│   │   │   ├── classification/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── base_image_encoder.py
│   │   │   │   ├── byteformer.py
│   │   │   │   ├── config/
│   │   │   │   │   ├── __init__.py
│   │   │   │   │   ├── byteformer.py
│   │   │   │   │   ├── efficientnet.py
│   │   │   │   │   ├── fastvit.py
│   │   │   │   │   ├── mobilenetv1.py
│   │   │   │   │   ├── mobilenetv2.py
│   │   │   │   │   ├── mobilenetv3.py
│   │   │   │   │   ├── mobileone.py
│   │   │   │   │   ├── mobilevit.py
│   │   │   │   │   ├── mobilevit_v2.py
│   │   │   │   │   ├── regnet.py
│   │   │   │   │   ├── resnet.py
│   │   │   │   │   ├── swin_transformer.py
│   │   │   │   │   └── vit.py
│   │   │   │   ├── efficientnet.py
│   │   │   │   ├── fastvit.py
│   │   │   │   ├── mobilenetv1.py
│   │   │   │   ├── mobilenetv2.py
│   │   │   │   ├── mobilenetv3.py
│   │   │   │   ├── mobileone.py
│   │   │   │   ├── mobilevit.py
│   │   │   │   ├── mobilevit_v2.py
│   │   │   │   ├── regnet.py
│   │   │   │   ├── resnet.py
│   │   │   │   ├── swin_transformer.py
│   │   │   │   └── vit.py
│   │   │   ├── detection/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── base_detection.py
│   │   │   │   ├── mask_rcnn.py
│   │   │   │   ├── ssd.py
│   │   │   │   └── utils/
│   │   │   │       ├── __init__.py
│   │   │   │       └── rcnn_utils.py
│   │   │   ├── fsdp_wrapper.py
│   │   │   ├── language_modeling/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── base_lm.py
│   │   │   │   ├── general_gpt.py
│   │   │   │   └── kv_prediction.py
│   │   │   ├── multi_modal_img_text/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── base_multi_modal_img_text.py
│   │   │   │   └── clip.py
│   │   │   ├── segmentation/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── base_seg.py
│   │   │   │   ├── enc_dec.py
│   │   │   │   └── heads/
│   │   │   │       ├── __init__.py
│   │   │   │       ├── base_seg_head.py
│   │   │   │       ├── deeplabv3.py
│   │   │   │       ├── pspnet.py
│   │   │   │       └── simple_seg_head.py
│   │   │   └── video_classification/
│   │   │       ├── __init__.py
│   │   │       └── base_video_encoder.py
│   │   ├── modules/
│   │   │   ├── __init__.py
│   │   │   ├── aspp_block.py
│   │   │   ├── base_module.py
│   │   │   ├── efficientnet.py
│   │   │   ├── fastvit.py
│   │   │   ├── feature_pyramid.py
│   │   │   ├── flash_transformer.py
│   │   │   ├── mobilenetv2.py
│   │   │   ├── mobileone_block.py
│   │   │   ├── mobilevit_block.py
│   │   │   ├── pspnet_module.py
│   │   │   ├── regnet_modules.py
│   │   │   ├── resnet_modules.py
│   │   │   ├── squeeze_excitation.py
│   │   │   ├── ssd_heads.py
│   │   │   ├── swin_transformer_block.py
│   │   │   ├── transformer.py
│   │   │   └── windowed_transformer.py
│   │   ├── neural_augmentor/
│   │   │   ├── __init__.py
│   │   │   ├── neural_aug.py
│   │   │   └── utils/
│   │   │       ├── __init__.py
│   │   │       └── neural_aug_utils.py
│   │   └── text_encoders/
│   │       ├── __init__.py
│   │       ├── base_text_encoder.py
│   │       └── transformer.py
│   ├── optims/
│   │   ├── __init__.py
│   │   ├── adam.py
│   │   ├── adamw.py
│   │   ├── base_optim.py
│   │   ├── scheduler/
│   │   │   ├── __init__.py
│   │   │   ├── base_scheduler.py
│   │   │   ├── cosine.py
│   │   │   ├── cyclic.py
│   │   │   ├── fixed.py
│   │   │   ├── multi_step.py
│   │   │   └── polynomial.py
│   │   └── sgd.py
│   ├── options/
│   │   ├── __init__.py
│   │   ├── errors.py
│   │   ├── opts.py
│   │   ├── parse_args.py
│   │   └── utils.py
│   ├── third_party/
│   │   ├── __init__.py
│   │   ├── data/
│   │   │   ├── __init__.py
│   │   │   └── text_tokenizer/
│   │   │       ├── __init__.py
│   │   │       └── openai_clip_tokenizer.py
│   │   └── modeling/
│   │       ├── __init__.py
│   │       ├── lora.py
│   │       └── ssd_utils.py
│   ├── train_eval_pipelines/
│   │   ├── __init__.py
│   │   ├── base.py
│   │   ├── default_train_eval.py
│   │   └── fsdp_train_eval.py
│   └── utils/
│       ├── __init__.py
│       ├── activation_checkpointing_wrapper.py
│       ├── check.py
│       ├── checkpoint_utils.py
│       ├── color_map.py
│       ├── common_utils.py
│       ├── context_managers.py
│       ├── ddp_utils.py
│       ├── dict_utils.py
│       ├── download_utils.py
│       ├── file_logger.py
│       ├── fpdb.py
│       ├── hf_adapter_utils.py
│       ├── import_utils.py
│       ├── io_utils.py
│       ├── logger.py
│       ├── math_utils.py
│       ├── object_utils.py
│       ├── object_utils_test.py
│       ├── pytorch_to_coreml.py
│       ├── registry.py
│       ├── registry_test.py
│       ├── resources.py
│       ├── retry_utils.py
│       ├── tensor_utils.py
│       └── visualization_utils.py
├── mlx_examples/
│   ├── clip/
│   │   ├── README.md
│   │   ├── __init__.py
│   │   ├── clip.py
│   │   ├── image_processor.py
│   │   ├── main_clip_to_mlx.py
│   │   ├── main_test_clip_mlx.py
│   │   ├── model.py
│   │   ├── requirements.txt
│   │   ├── results/
│   │   │   └── .gitkeep
│   │   └── tokenizer.py
│   ├── open_elm/
│   │   ├── README.md
│   │   ├── __init__.py
│   │   ├── convert.py
│   │   ├── inference.py
│   │   └── open_elm.py
│   └── requirements.txt
├── projects/
│   ├── byteformer/
│   │   ├── README.md
│   │   ├── imagenet_file_encodings/
│   │   │   ├── encoding_type=PNG.yaml
│   │   │   ├── encoding_type=TIFF.yaml
│   │   │   ├── encoding_type=fCHW.yaml
│   │   │   └── encoding_type=fHWC.yaml
│   │   ├── imagenet_jpeg_q100/
│   │   │   ├── conv_kernel_size=16.yaml
│   │   │   ├── conv_kernel_size=32.yaml
│   │   │   └── conv_kernel_size=8.yaml
│   │   ├── imagenet_jpeg_q60/
│   │   │   ├── conv_kernel_size=16,window_sizes=[128].yaml
│   │   │   ├── conv_kernel_size=16,window_sizes=[32].yaml
│   │   │   ├── conv_kernel_size=32,window_sizes=[128].yaml
│   │   │   ├── conv_kernel_size=32,window_sizes=[32].yaml
│   │   │   ├── conv_kernel_size=4,window_sizes=[128].yaml
│   │   │   ├── conv_kernel_size=4,window_sizes=[32].yaml
│   │   │   ├── conv_kernel_size=8,window_sizes=[128].yaml
│   │   │   └── conv_kernel_size=8,window_sizes=[32].yaml
│   │   ├── imagenet_jpeg_shuffle_bytes/
│   │   │   ├── mode=cyclic_half_length.yaml
│   │   │   ├── mode=random_shuffle.yaml
│   │   │   ├── mode=reverse.yaml
│   │   │   ├── mode=stride.yaml
│   │   │   └── mode=window_shuffle.yaml
│   │   ├── imagenet_obfuscation/
│   │   │   ├── width_range=[-10,10].yaml
│   │   │   ├── width_range=[-20,20].yaml
│   │   │   ├── width_range=[-5,5].yaml
│   │   │   └── width_range=[0,0].yaml
│   │   ├── imagenet_privacy_preserving_camera/
│   │   │   ├── keep_frac=0.03,conv_kernel_size=4.yaml
│   │   │   ├── keep_frac=0.05,conv_kernel_size=4.yaml
│   │   │   ├── keep_frac=0.1,conv_kernel_size=4.yaml
│   │   │   ├── keep_frac=0.25,conv_kernel_size=8.yaml
│   │   │   ├── keep_frac=0.5,conv_kernel_size=16.yaml
│   │   │   └── keep_frac=0.75,conv_kernel_size=32.yaml
│   │   ├── speech_commands_mp3/
│   │   │   ├── conv_kernel_size=4,window_size=[128].yaml
│   │   │   ├── conv_kernel_size=4,window_size=[32].yaml
│   │   │   ├── conv_kernel_size=8,window_size=[128].yaml
│   │   │   └── conv_kernel_size=8,window_size=[32].yaml
│   │   └── speech_commands_wav/
│   │       ├── encoding_dtype=float32,conv_kernel_size=16.yaml
│   │       ├── encoding_dtype=float32,conv_kernel_size=32.yaml
│   │       ├── encoding_dtype=int16,conv_kernel_size=16.yaml
│   │       ├── encoding_dtype=int16,conv_kernel_size=32.yaml
│   │       ├── encoding_dtype=int16,conv_kernel_size=8.yaml
│   │       ├── encoding_dtype=int32,conv_kernel_size=16.yaml
│   │       ├── encoding_dtype=int32,conv_kernel_size=32.yaml
│   │       ├── encoding_dtype=uint8,conv_kernel_size=16.yaml
│   │       ├── encoding_dtype=uint8,conv_kernel_size=32.yaml
│   │       ├── encoding_dtype=uint8,conv_kernel_size=4.yaml
│   │       └── encoding_dtype=uint8,conv_kernel_size=8.yaml
│   ├── catlip/
│   │   ├── README-multi-label-object-classification.md
│   │   ├── README-object-detection.md
│   │   ├── README-pretraining.md
│   │   ├── README-semantic-segmentation.md
│   │   ├── README-single-label-object-classification.md
│   │   ├── README.md
│   │   ├── image_classification/
│   │   │   ├── imagenet/
│   │   │   │   ├── vit_base.yaml
│   │   │   │   ├── vit_base_512x512.yaml
│   │   │   │   ├── vit_huge.yaml
│   │   │   │   ├── vit_huge_512x512.yaml
│   │   │   │   ├── vit_large.yaml
│   │   │   │   └── vit_large_512x512.yaml
│   │   │   └── places365/
│   │   │       ├── vit_base.yaml
│   │   │       ├── vit_base_512x512.yaml
│   │   │       ├── vit_huge.yaml
│   │   │       ├── vit_huge_512x512.yaml
│   │   │       ├── vit_large.yaml
│   │   │       └── vit_large_512x512.yaml
│   │   ├── multi_label_image_classification/
│   │   │   ├── vit_base.yaml
│   │   │   └── vit_large.yaml
│   │   ├── object_detection/
│   │   │   ├── maskrcnn_vit_base.yaml
│   │   │   ├── maskrcnn_vit_huge.yaml
│   │   │   └── maskrcnn_vit_large.yaml
│   │   ├── pretraining/
│   │   │   ├── vit_base.yaml
│   │   │   ├── vit_huge.yaml
│   │   │   └── vit_large.yaml
│   │   └── semantic_segmentation/
│   │       ├── deeplabv3_vit_base.yaml
│   │       ├── deeplabv3_vit_huge.yaml
│   │       └── deeplabv3_vit_large.yaml
│   ├── clip/
│   │   ├── README.md
│   │   └── clip_vit_base.yaml
│   ├── fastvit/
│   │   ├── README.md
│   │   └── classification/
│   │       └── fastvit_t8_in1k.yaml
│   ├── kv-prediction/
│   │   ├── README.md
│   │   ├── openelm/
│   │   │   ├── openelm_1_1B_0_25.yaml
│   │   │   ├── openelm_1_1B_0_50.yaml
│   │   │   ├── openelm_1_1B_0_75.yaml
│   │   │   ├── openelm_1_1B_kvp_c_270M.yaml
│   │   │   ├── openelm_1_1B_kvp_c_450M.yaml
│   │   │   ├── openelm_1_1B_kvp_lp_0_25.yaml
│   │   │   ├── openelm_1_1B_kvp_lp_0_50.yaml
│   │   │   ├── openelm_1_1B_kvp_lp_0_75.yaml
│   │   │   ├── openelm_3B_kvp_c_1_1B.yaml
│   │   │   ├── openelm_3B_kvp_c_270M.yaml
│   │   │   ├── openelm_3B_kvp_c_450M.yaml
│   │   │   ├── openelm_3B_kvp_lp_0_25.yaml
│   │   │   ├── openelm_3B_kvp_lp_0_50.yaml
│   │   │   ├── openelm_3B_kvp_lp_0_75.yaml
│   │   │   ├── openelm_base_3B_aux_0_25l.yaml
│   │   │   ├── openelm_base_3B_aux_0_50l.yaml
│   │   │   └── openelm_base_3B_aux_0_75l.yaml
│   │   └── triviaqa-template.yaml
│   ├── mobilenet_v1/
│   │   ├── README.md
│   │   └── classification/
│   │       └── mobilenetv1_1.0_in1k.yaml
│   ├── mobilenet_v2/
│   │   ├── README.md
│   │   ├── classification/
│   │   │   └── mobilenetv2_1.0_in1k.yaml
│   │   └── segmentation/
│   │       └── deeplabv3_ade20k.yaml
│   ├── mobilenet_v3/
│   │   ├── README.md
│   │   └── classification/
│   │       └── mobilenetv3_large_in1k.yaml
│   ├── mobileone/
│   │   ├── README.md
│   │   └── classification/
│   │       └── mobileone_s1_in1k.yaml
│   ├── mobilevit/
│   │   └── README.md
│   ├── mobilevit_v2/
│   │   ├── README.md
│   │   ├── classification/
│   │   │   ├── mobilevitv2_2.0_ft_384x384.yaml
│   │   │   └── mobilevitv2_2.0_in1k.yaml
│   │   ├── detection/
│   │   │   └── mobilevitv2_2.0_ssd_coco.yaml
│   │   └── segmentation/
│   │       └── deeplabv3_mobilevitv2_1.0_ade20k.yaml
│   ├── openelm/
│   │   ├── README-instruct.md
│   │   ├── README-peft.md
│   │   ├── README-pretraining.md
│   │   ├── README.md
│   │   ├── instruction_tuning/
│   │   │   └── openelm-instruct.yaml
│   │   ├── peft_configs/
│   │   │   ├── openelm_lora_1_1B.yaml
│   │   │   ├── openelm_lora_270M.yaml
│   │   │   ├── openelm_lora_270M_eval.yaml
│   │   │   ├── openelm_lora_3B.yaml
│   │   │   └── openelm_lora_450M.yaml
│   │   └── pretraining_configs/
│   │       ├── openelm_1_1B.yaml
│   │       ├── openelm_270M.yaml
│   │       ├── openelm_3B.yaml
│   │       └── openelm_450M.yaml
│   ├── range_augment/
│   │   ├── README-classification.md
│   │   ├── README-clip.md
│   │   ├── README-distillation.md
│   │   ├── README-object-detection.md
│   │   ├── README-segmentation.md
│   │   ├── README.md
│   │   ├── classification/
│   │   │   ├── efficientnet_b0.yaml
│   │   │   ├── efficientnet_b1.yaml
│   │   │   ├── efficientnet_b2.yaml
│   │   │   ├── efficientnet_b3.yaml
│   │   │   ├── mobilenet_v1.yaml
│   │   │   ├── mobilenet_v2.yaml
│   │   │   ├── mobilenet_v3.yaml
│   │   │   ├── mobilevit_v1.yaml
│   │   │   ├── regnety_16gf.yaml
│   │   │   ├── resnet_101.yaml
│   │   │   ├── resnet_50.yaml
│   │   │   ├── se_resnet_50.yaml
│   │   │   ├── swin_transformer_small.yaml
│   │   │   └── swin_transformer_tiny.yaml
│   │   ├── clip/
│   │   │   ├── clip_vit_base.yaml
│   │   │   └── clip_vit_huge.yaml
│   │   ├── clip_finetune_imagenet/
│   │   │   ├── clip_vit_base.yaml
│   │   │   └── clip_vit_huge.yaml
│   │   ├── detection/
│   │   │   ├── maskrcnn_efficientnet_b3.yaml
│   │   │   ├── maskrcnn_mobilenet_v1.yaml
│   │   │   ├── maskrcnn_mobilenet_v2.yaml
│   │   │   ├── maskrcnn_mobilenet_v3.yaml
│   │   │   ├── maskrcnn_mobilevit.yaml
│   │   │   ├── maskrcnn_resnet_101.yaml
│   │   │   └── maskrcnn_resnet_50.yaml
│   │   ├── distillation/
│   │   │   ├── teacher_resnet101_student_mobilenet_v1.yaml
│   │   │   ├── teacher_resnet101_student_mobilenet_v2.yaml
│   │   │   ├── teacher_resnet101_student_mobilenet_v3.yaml
│   │   │   └── teacher_resnet101_student_mobilevit.yaml
│   │   └── segmentation/
│   │       ├── ade20k/
│   │       │   ├── deeplabv3_efficientnet_b3.yaml
│   │       │   ├── deeplabv3_mobilenet_v1.yaml
│   │       │   ├── deeplabv3_mobilenet_v2.yaml
│   │       │   ├── deeplabv3_mobilenet_v3.yaml
│   │       │   ├── deeplabv3_mobilevit.yaml
│   │       │   ├── deeplabv3_resnet_101.yaml
│   │       │   └── deeplabv3_resnet_50.yaml
│   │       └── pascal_voc/
│   │           ├── deeplabv3_efficientnet_b3.yaml
│   │           ├── deeplabv3_mobilenet_v1.yaml
│   │           ├── deeplabv3_mobilenet_v2.yaml
│   │           ├── deeplabv3_mobilenet_v3.yaml
│   │           ├── deeplabv3_resnet_101.yaml
│   │           └── deeplabv3_resnet_50.yaml
│   ├── resnet/
│   │   ├── README.md
│   │   ├── classification/
│   │   │   └── resnet50_in1k.yaml
│   │   └── detection/
│   │       └── ssd_resnet50_coco.yaml
│   └── vit/
│       ├── README.md
│       └── classification/
│           └── vit_base_in1k.yaml
├── pyproject.toml
├── requirements-optional.txt
├── requirements.txt
├── setup.py
├── tests/
│   ├── __init__.py
│   ├── configs.py
│   ├── data/
│   │   ├── __init__.py
│   │   ├── coco/
│   │   │   └── annotations/
│   │   │       ├── instances_train2017.json
│   │   │       └── instances_val2017.json
│   │   ├── collate_fns/
│   │   │   ├── __init__.py
│   │   │   ├── test_byteformer_collate_fn.py
│   │   │   └── test_collate_functions.py
│   │   ├── datasets/
│   │   │   ├── __init__.py
│   │   │   ├── audio_classification/
│   │   │   │   ├── __init__.py
│   │   │   │   └── test_speech_commands_v2.py
│   │   │   ├── classification/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── dummy_configs/
│   │   │   │   │   ├── coco.yaml
│   │   │   │   │   ├── image_classification_dataset.yaml
│   │   │   │   │   ├── imagenet.yaml
│   │   │   │   │   ├── imagenet_a.yaml
│   │   │   │   │   ├── imagenet_r.yaml
│   │   │   │   │   ├── imagenet_sketch.yaml
│   │   │   │   │   └── wordnet_tagged_classification.yaml
│   │   │   │   ├── mock_coco.py
│   │   │   │   ├── mock_imagenet.py
│   │   │   │   ├── mock_wordnet_tagged_classification.py
│   │   │   │   ├── test_base_image_classification_dataset.py
│   │   │   │   ├── test_mock_coco.py
│   │   │   │   ├── test_mock_imagenet.py
│   │   │   │   └── test_wordnet_tagged_classification.py
│   │   │   ├── detection/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── mock_coco_mask_rcnn.py
│   │   │   │   └── mock_coco_ssd.py
│   │   │   ├── language_modeling/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── dummy_commonsense_170k.yaml
│   │   │   │   ├── dummy_lm_dataset.yaml
│   │   │   │   ├── mock_general_lm.py
│   │   │   │   ├── test_commonsense_170k.py
│   │   │   │   └── test_general_lm.py
│   │   │   ├── multi_modal_img_text/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── dummy_img_text_tar_dataset.yaml
│   │   │   │   ├── mock_img_text_tar_dataset.py
│   │   │   │   ├── test_img_text_tar_dataset.py
│   │   │   │   └── zero_shot_image_classification/
│   │   │   │       ├── __init__.py
│   │   │   │       ├── dummy_configs/
│   │   │   │       │   ├── imagenet.yaml
│   │   │   │       │   ├── imagenet_a.yaml
│   │   │   │       │   ├── imagenet_r.yaml
│   │   │   │       │   └── imagenet_sketch.yaml
│   │   │   │       ├── mock_imagenet.py
│   │   │   │       └── test_mock_imagenet.py
│   │   │   ├── segmentation/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── dummy_ade20k_config.yaml
│   │   │   │   ├── dummy_cocostuff_config.yaml
│   │   │   │   ├── mock_ade20k.py
│   │   │   │   ├── mock_coco_stuff.py
│   │   │   │   ├── test_mock_ade20k.py
│   │   │   │   └── test_mock_coco_stuff.py
│   │   │   ├── test_dataset_base.py
│   │   │   ├── test_image_pil.py
│   │   │   └── utils/
│   │   │       ├── __init__.py
│   │   │       ├── test_common.py
│   │   │       └── test_video.py
│   │   ├── io/
│   │   │   ├── __init__.py
│   │   │   └── test_transfer_clients.py
│   │   ├── samplers/
│   │   │   ├── __init__.py
│   │   │   ├── test_batch_sampler_config.yaml
│   │   │   ├── test_chain_sampler.py
│   │   │   ├── test_chain_sampler_config.yaml
│   │   │   ├── test_data_samplers.py
│   │   │   ├── test_multi_scale_sampler_config.yaml
│   │   │   ├── test_variable_batch_sampler_config.yaml
│   │   │   └── test_video_clip_batch_sampler_config.yaml
│   │   ├── text_tokenizer/
│   │   │   ├── __init__.py
│   │   │   ├── test_clip_tokenizer.py
│   │   │   └── test_openai_clip_tokenizer.py
│   │   └── video_reader/
│   │       ├── __init__.py
│   │       ├── test_av_reader.py
│   │       └── test_ffmpeg_utils.py
│   ├── engine/
│   │   ├── __init__.py
│   │   ├── dummy_configs/
│   │   │   ├── ade20k_segmentation/
│   │   │   │   └── deeplabv3_mobilenetv2.yaml
│   │   │   ├── coco_detection/
│   │   │   │   ├── resnet_mask_rcnn.yaml
│   │   │   │   └── resnet_ssd.yaml
│   │   │   ├── image_text_clip/
│   │   │   │   └── clip_vit.yaml
│   │   │   ├── imagenet_classification/
│   │   │   │   ├── efficientnet_b0.yaml
│   │   │   │   ├── mobilevit.yaml
│   │   │   │   └── mobilevit_v2.yaml
│   │   │   └── language_modeling_gpt/
│   │   │       └── gpt.yaml
│   │   └── test_training_engine.py
│   ├── loss_fns/
│   │   ├── __init__.py
│   │   ├── language_modeling/
│   │   │   ├── __init__.py
│   │   │   ├── test_cross_entropy.py
│   │   │   └── test_cross_entropy_for_kv_prediction.py
│   │   ├── test_class_weighting.py
│   │   ├── test_classification_loss.py
│   │   ├── test_composite_loss.py
│   │   ├── test_contrastive_loss.py
│   │   ├── test_detection_loss.py
│   │   ├── test_focal_loss.py
│   │   ├── test_neural_aug.py
│   │   ├── test_neural_aug_compatibility.py
│   │   └── test_segmentation_loss.py
│   ├── metrics/
│   │   ├── __init__.py
│   │   ├── base.py
│   │   ├── test_coco_map.py
│   │   ├── test_image_text_retrieval_metrics.py
│   │   ├── test_iou.py
│   │   ├── test_misc.py
│   │   ├── test_multiclass_classification_pr.py
│   │   ├── test_probability_histogram.py
│   │   ├── test_psnr.py
│   │   ├── test_retrieval_cmc_metrics.py
│   │   ├── test_topk_accuracy.py
│   │   └── test_vqa_preset_score_metrics.py
│   ├── misc/
│   │   ├── __init__.py
│   │   ├── dummy_clip_config.yaml
│   │   ├── dummy_linear_probe_config.yaml
│   │   └── test_common.py
│   ├── modeling/
│   │   ├── __init__.py
│   │   ├── layers/
│   │   │   ├── __init__.py
│   │   │   ├── normalization_layers/
│   │   │   │   ├── __init__.py
│   │   │   │   └── test_rms_norm.py
│   │   │   ├── test_conv_layer.py
│   │   │   ├── test_multi_head_attn.py
│   │   │   ├── test_pos_embeddings.py
│   │   │   ├── test_rotary_embeddings.py
│   │   │   └── test_token_merging.py
│   │   ├── models/
│   │   │   ├── __init__.py
│   │   │   ├── audio_classification/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── test_base_audio_classification.py
│   │   │   │   └── test_byteformer.py
│   │   │   ├── classification/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── config/
│   │   │   │   │   ├── __init__.py
│   │   │   │   │   ├── test_byteformer.py
│   │   │   │   │   └── vit_config.yaml
│   │   │   │   ├── test_byteformer.py
│   │   │   │   └── test_vit.py
│   │   │   ├── language_modeling/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── config/
│   │   │   │   │   ├── gpt_config.yaml
│   │   │   │   │   └── kv_prediction_config.yaml
│   │   │   │   ├── test_general_gpt.py
│   │   │   │   └── test_kv_prediction.py
│   │   │   ├── test_activation_checkpointing_wrapper.py
│   │   │   ├── test_lora.py
│   │   │   └── test_neural_aug_utils.py
│   │   ├── modules/
│   │   │   ├── __init__.py
│   │   │   ├── test_transformer.py
│   │   │   └── test_windowed_transformer.py
│   │   └── test_model.py
│   ├── optims/
│   │   ├── __init__.py
│   │   └── scheduler/
│   │       ├── __init__.py
│   │       └── test_scheduler.py
│   ├── options/
│   │   ├── __init__.py
│   │   ├── test_parse_args.py
│   │   └── test_utils.py
│   ├── test_conventions.py
│   ├── test_utils.py
│   ├── transforms/
│   │   ├── __init__.py
│   │   ├── test_audio.py
│   │   ├── test_audio_bytes.py
│   │   ├── test_image.py
│   │   ├── test_image_bytes.py
│   │   └── test_video.py
│   └── utils/
│       ├── __init__.py
│       ├── test_check.py
│       ├── test_common_utils.py
│       ├── test_dict_utils.py
│       ├── test_download_utils.py
│       ├── test_file_logger.py
│       └── test_import_utils.py
├── tools/
│   ├── __init__.py
│   └── converter_coco_stuff.py
├── tox.ini
└── tutorials/
    ├── clip.ipynb
    ├── guide_slurm_and_multi_node_training.md
    ├── object_detection.ipynb
    ├── semantic_segmentation.ipynb
    └── train_a_new_model_on_a_new_dataset_from_scratch.ipynb

SYMBOL INDEX (2560 symbols across 412 files)

FILE: conftest.py
  function handle_timeout (line 32) | def handle_timeout(signum: int, frame: Optional[FrameType] = None) -> None:
  function pytest_sessionstart (line 39) | def pytest_sessionstart():
  function pytest_runtest_logfinish (line 57) | def pytest_runtest_logfinish(nodeid, location):
  function set_random_seed (line 63) | def set_random_seed(request):

FILE: corenet/__init__.py
  function suppress_known_warnings (line 55) | def suppress_known_warnings() -> None:

FILE: corenet/cli/main.py
  function main (line 19) | def main(args: Optional[List[str]] = None) -> None:

FILE: corenet/cli/main_benchmark.py
  function cpu_timestamp (line 21) | def cpu_timestamp(*args, **kwargs):
  function cuda_timestamp (line 26) | def cuda_timestamp(cuda_sync=False, device=None, *args, **kwargs):
  function step (line 33) | def step(
  function main_benchmark (line 47) | def main_benchmark():

FILE: corenet/cli/main_conversion.py
  function main_worker_conversion (line 20) | def main_worker_conversion(args: Optional[List[str]] = None):

FILE: corenet/cli/main_eval.py
  function main (line 14) | def main(train_eval_pipeline: BaseTrainEvalPipeline):
  function main_worker (line 27) | def main_worker(args: Optional[List[str]] = None):
  function main_worker_segmentation (line 36) | def main_worker_segmentation(args: Optional[List[str]] = None, **kwargs):
  function main_worker_detection (line 42) | def main_worker_detection(args: Optional[List[str]] = None, **kwargs):

FILE: corenet/cli/main_eval_llmadapters.py
  class CoreNetLMEvalWrapper (line 61) | class CoreNetLMEvalWrapper(HFLM):
    method __init__ (line 69) | def __init__(self, opts: argparse.Namespace) -> None:
  function main_eval_llmadapters (line 97) | def main_eval_llmadapters(args: Optional[List[str]] = None) -> None:
  function main_generation (line 140) | def main_generation(
  function evaluate_sample_with_generation (line 210) | def evaluate_sample_with_generation(
  function extract_answer_from_generation (line 265) | def extract_answer_from_generation(dataset: str, sentence: str) -> str:
  function main_multiple_choice (line 312) | def main_multiple_choice(
  function evaluate_likelihood (line 390) | def evaluate_likelihood(
  function get_loglikelihood_inputs (line 430) | def get_loglikelihood_inputs(data: Dict[str, str]) -> List[Request]:

FILE: corenet/cli/main_train.py
  function callback (line 18) | def callback(train_eval_pipeline: BaseTrainEvalPipeline) -> None:
  function main_worker (line 31) | def main_worker(args: Optional[List[str]] = None):

FILE: corenet/constants.py
  function get_corenet_env (line 43) | def get_corenet_env() -> Literal["pytest", "default", "external"]:
  function is_test_env (line 83) | def is_test_env() -> bool:
  function is_external_env (line 99) | def is_external_env() -> bool:
  function if_test_env (line 108) | def if_test_env(then: Any, otherwise: Any) -> Any:

FILE: corenet/data/collate_fns/__init__.py
  function arguments_collate_fn (line 18) | def arguments_collate_fn(parser: argparse.ArgumentParser) -> argparse.Ar...
  function build_collate_fn (line 43) | def build_collate_fn(opts, *args, **kwargs):
  function build_test_collate_fn (line 64) | def build_test_collate_fn(opts, *args, **kwargs):

FILE: corenet/data/collate_fns/byteformer_collate_functions.py
  function byteformer_image_collate_fn (line 29) | def byteformer_image_collate_fn(
  function apply_padding (line 53) | def apply_padding(
  function apply_pil_save (line 118) | def apply_pil_save(
  function apply_shuffle_bytes (line 139) | def apply_shuffle_bytes(
  function apply_mask_positions (line 160) | def apply_mask_positions(
  function apply_random_uniform_noise (line 180) | def apply_random_uniform_noise(
  function apply_byte_permutation (line 200) | def apply_byte_permutation(
  function apply_torchaudio_save (line 220) | def apply_torchaudio_save(
  function byteformer_audio_collate_fn (line 241) | def byteformer_audio_collate_fn(

FILE: corenet/data/collate_fns/collate_functions.py
  function pytorch_default_collate_fn (line 17) | def pytorch_default_collate_fn(batch: Any, *args, **kwargs) -> Any:
  function unlabeled_image_data_collate_fn (line 24) | def unlabeled_image_data_collate_fn(
  function image_classification_data_collate_fn (line 64) | def image_classification_data_collate_fn(
  function default_collate_fn (line 109) | def default_collate_fn(

FILE: corenet/data/data_loaders.py
  function create_test_loader (line 22) | def create_test_loader(opts: argparse.Namespace) -> CoreNetDataLoader:
  function create_train_val_loader (line 85) | def create_train_val_loader(
  function get_num_data_samples_as_int_or_mapping (line 194) | def get_num_data_samples_as_int_or_mapping(

FILE: corenet/data/datasets/__init__.py
  function build_dataset_from_registry (line 44) | def build_dataset_from_registry(
  function get_test_dataset (line 89) | def get_test_dataset(opts: argparse.Namespace, *args, **kwargs) -> BaseD...
  function get_train_val_datasets (line 110) | def get_train_val_datasets(
  function arguments_dataset (line 143) | def arguments_dataset(parser: argparse.ArgumentParser) -> argparse.Argum...

FILE: corenet/data/datasets/audio_classification/speech_commands_v2.py
  class SpeechCommandsv2Dataset (line 24) | class SpeechCommandsv2Dataset(dataset_base.BaseDataset):
    method __init__ (line 35) | def __init__(
    method _process_dataset_config (line 52) | def _process_dataset_config(self) -> None:
    method add_arguments (line 87) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method _training_transforms (line 96) | def _training_transforms(self, *args, **kwargs) -> BaseTransformation:
    method _validation_transforms (line 110) | def _validation_transforms(self, *args, **kwargs) -> BaseTransformation:
    method get_sample (line 117) | def get_sample(self, index: int) -> Tuple[Tensor, float, Tensor]:
    method __getitem__ (line 129) | def __getitem__(
    method get_transformed_sample (line 185) | def get_transformed_sample(
    method __len__ (line 224) | def __len__(self) -> int:

FILE: corenet/data/datasets/classification/base_image_classification_dataset.py
  class BaseImageClassificationDataset (line 19) | class BaseImageClassificationDataset(BaseImageDataset, ImageFolder):
    method __init__ (line 36) | def __init__(
    method add_arguments (line 111) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method _training_transforms (line 134) | def _training_transforms(
    method _validation_transforms (line 187) | def _validation_transforms(self, *args, **kwargs) -> image_pil.BaseTra...
    method __getitem__ (line 210) | def __getitem__(
    method __len__ (line 255) | def __len__(self) -> int:
    method extra_repr (line 258) | def extra_repr(self) -> str:

FILE: corenet/data/datasets/classification/base_imagenet_shift_dataset.py
  class BaseImageNetShiftDataset (line 14) | class BaseImageNetShiftDataset(BaseImageClassificationDataset):
    method __init__ (line 25) | def __init__(
    method post_init_checks (line 45) | def post_init_checks(self) -> None:
    method class_id_to_imagenet_class_id (line 59) | def class_id_to_imagenet_class_id(class_id: int) -> int:
    method __getitem__ (line 65) | def __getitem__(

FILE: corenet/data/datasets/classification/coco.py
  class COCOClassification (line 23) | class COCOClassification(BaseImageDataset):
    method __init__ (line 30) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method __len__ (line 44) | def __len__(self) -> int:
    method _training_transforms (line 48) | def _training_transforms(
    method _validation_transforms (line 63) | def _validation_transforms(
    method __getitem__ (line 75) | def __getitem__(
    method n_classes (line 135) | def n_classes(self):
    method class_names (line 139) | def class_names(self) -> List[str]:

FILE: corenet/data/datasets/classification/imagenet.py
  class ImageNetDataset (line 15) | class ImageNetDataset(BaseImageClassificationDataset):
    method __init__ (line 24) | def __init__(

FILE: corenet/data/datasets/classification/imagenet_a.py
  class ImageNetADataset (line 24) | class ImageNetADataset(BaseImageNetShiftDataset):
    method __init__ (line 39) | def __init__(
    method class_id_to_imagenet_class_id (line 49) | def class_id_to_imagenet_class_id(class_id: int) -> int:

FILE: corenet/data/datasets/classification/imagenet_r.py
  class ImageNetRDataset (line 24) | class ImageNetRDataset(BaseImageNetShiftDataset):
    method __init__ (line 43) | def __init__(
    method class_id_to_imagenet_class_id (line 53) | def class_id_to_imagenet_class_id(class_id: int) -> int:

FILE: corenet/data/datasets/classification/imagenet_sketch.py
  class ImageNetSketchDataset (line 15) | class ImageNetSketchDataset(BaseImageNetShiftDataset):
    method __init__ (line 31) | def __init__(
    method class_id_to_imagenet_class_id (line 41) | def class_id_to_imagenet_class_id(class_id: int) -> int:

FILE: corenet/data/datasets/classification/imagenet_v2.py
  class Imagenetv2Dataset (line 37) | class Imagenetv2Dataset(BaseImageDataset):
    method __init__ (line 45) | def __init__(
    method add_arguments (line 80) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method _validation_transforms (line 100) | def _validation_transforms(self, *args, **kwargs):
    method __getitem__ (line 116) | def __getitem__(self, sample_size_and_index: Tuple) -> Dict:
    method __len__ (line 166) | def __len__(self) -> int:

FILE: corenet/data/datasets/classification/places365.py
  class Places365Dataset (line 15) | class Places365Dataset(BaseImageClassificationDataset):
    method __init__ (line 24) | def __init__(

FILE: corenet/data/datasets/classification/wordnet_tagged_classification.py
  function extract_pos_offset_info_from_synset (line 59) | def extract_pos_offset_info_from_synset(synset: Synset) -> str:
  function check_valid_noun_synset (line 73) | def check_valid_noun_synset(synset: Synset, word: str) -> bool:
  class WordnetTaggedClassificationDataset (line 87) | class WordnetTaggedClassificationDataset(BaseImageDataset):
    method __init__ (line 97) | def __init__(
    method __post_init__ (line 113) | def __post_init__(self) -> None:
    method _get_vocab (line 118) | def _get_vocab(self) -> List[str]:
    method _metadata_file_path (line 168) | def _metadata_file_path(self) -> str:
    method _metadata (line 182) | def _metadata(self):
    method _download_and_extract_tar_file (line 215) | def _download_and_extract_tar_file(self, sample_index: int) -> int:
    method _convert_caption_to_labels (line 274) | def _convert_caption_to_labels(self, captions_str: str) -> List[int]:
    method _read_sample_with_wordnet_label_mining (line 313) | def _read_sample_with_wordnet_label_mining(
    method _training_transforms (line 358) | def _training_transforms(self, *args, **kwargs) -> BaseTransformation:
    method add_arguments (line 368) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method _get_transfer_client (line 395) | def _get_transfer_client(self, file_path: str) -> BaseClient:
    method __getitem__ (line 422) | def __getitem__(
    method __len__ (line 461) | def __len__(self) -> int:
    method cache_loc (line 465) | def cache_loc(self) -> str:
    method vocab_size (line 469) | def vocab_size(self):
    method total_tar_files (line 473) | def total_tar_files(self) -> int:
    method max_files_per_tar (line 479) | def max_files_per_tar(self) -> int:
    method extra_repr (line 484) | def extra_repr(self) -> str:

FILE: corenet/data/datasets/dataset_base.py
  class BaseDataset (line 28) | class BaseDataset(data.Dataset, ABC):
    method __init__ (line 52) | def __init__(
    method add_arguments (line 88) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method load_from_server (line 224) | def load_from_server(
    method _training_transforms (line 244) | def _training_transforms(self, *args, **kwargs) -> BaseTransformation:
    method _validation_transforms (line 248) | def _validation_transforms(self, *args, **kwargs) -> BaseTransformation:
    method _evaluation_transforms (line 252) | def _evaluation_transforms(self, *args, **kwargs) -> BaseTransformation:
    method get_augmentation_transforms (line 256) | def get_augmentation_transforms(self, *args, **kwargs) -> BaseTransfor...
    method share_dataset_arguments (line 267) | def share_dataset_arguments(self) -> Dict[str, Any]:
    method __len__ (line 275) | def __len__(self) -> int:
    method __getitem__ (line 278) | def __getitem__(self, sample_size_and_index: Any) -> Any:
    method extra_repr (line 282) | def extra_repr(self) -> str:
    method __repr__ (line 289) | def __repr__(self) -> str:
    method get_item_metadata (line 298) | def get_item_metadata(self, item_idx: int) -> Dict:
    method worker_id (line 313) | def worker_id(self) -> int:
    method num_workers (line 328) | def num_workers(self) -> int:
    method is_master_node (line 343) | def is_master_node(self) -> bool:
    method is_start_rank_node (line 355) | def is_start_rank_node(self) -> bool:
    method world_size (line 367) | def world_size(self) -> int:
    method rank (line 376) | def rank(self) -> int:
  class BaseImageDataset (line 389) | class BaseImageDataset(BaseDataset, ABC):
    method read_image_pil (line 393) | def read_image_pil(path: str) -> Optional[Image.Image]:
    method extra_repr (line 410) | def extra_repr(self) -> str:
  class BaseVideoDataset (line 422) | class BaseVideoDataset(BaseDataset, ABC):
    method __init__ (line 429) | def __init__(
    method clips_per_video (line 443) | def clips_per_video(self) -> int:
    method _deprecated_set_clips_per_video (line 453) | def _deprecated_set_clips_per_video(self, value: int) -> None:
    method n_frames_per_clip (line 457) | def n_frames_per_clip(self) -> int:
    method _deprecated_set_n_frames_per_clip (line 467) | def _deprecated_set_n_frames_per_clip(self, value: int) -> None:
    method add_arguments (line 471) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method get_item_metadata (line 494) | def get_item_metadata(self, item_idx: int) -> VideoMetadataDict:
    method get_item_local_path (line 510) | def get_item_local_path(self, item_idx: int) -> str:
  class VideoMetadataDict (line 526) | class VideoMetadataDict(TypedDict, total=False):
  class BaseIterableDataset (line 540) | class BaseIterableDataset(BaseDataset, data.IterableDataset):

FILE: corenet/data/datasets/detection/base_detection.py
  class BaseDetectionDataset (line 11) | class BaseDetectionDataset(BaseImageDataset):
    method add_arguments (line 15) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...

FILE: corenet/data/datasets/detection/coco_base.py
  class COCODetection (line 24) | class COCODetection(BaseDetectionDataset):
    method __init__ (line 37) | def __init__(
    method add_arguments (line 76) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method _evaluation_transforms (line 89) | def _evaluation_transforms(
    method __getitem__ (line 106) | def __getitem__(
    method __len__ (line 172) | def __len__(self):
    method get_boxes_and_labels (line 175) | def get_boxes_and_labels(
    method _xywh2xyxy (line 245) | def _xywh2xyxy(
    method get_image (line 257) | def get_image(self, image_id: int) -> Tuple:
    method extra_repr (line 264) | def extra_repr(self) -> str:
    method class_names (line 268) | def class_names() -> List[str]:

FILE: corenet/data/datasets/detection/coco_mask_rcnn.py
  class COCODetectionMaskRCNN (line 20) | class COCODetectionMaskRCNN(COCODetection):
    method add_arguments (line 24) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method _training_transforms (line 38) | def _training_transforms(
    method _validation_transforms (line 71) | def _validation_transforms(
    method __getitem__ (line 90) | def __getitem__(
  function coco_mask_rcnn_collate_fn (line 163) | def coco_mask_rcnn_collate_fn(

FILE: corenet/data/datasets/detection/coco_ssd.py
  class COCODetectionSSD (line 24) | class COCODetectionSSD(COCODetection):
    method __init__ (line 31) | def __init__(
    method _training_transforms (line 54) | def _training_transforms(self, size: Tuple[int, int], *args, **kwargs)...
    method _validation_transforms (line 77) | def _validation_transforms(self, size: Tuple[int, int], *args, **kwarg...
    method generate_anchors (line 95) | def generate_anchors(self, height: int, width: int) -> Tensor:
    method __getitem__ (line 121) | def __getitem__(
    method extra_repr (line 183) | def extra_repr(self) -> str:
  function coco_ssd_collate_fn (line 193) | def coco_ssd_collate_fn(

FILE: corenet/data/datasets/language_modeling/base_lm.py
  function _process_text (line 19) | def _process_text(text: str) -> str:
  class BaseLMIterableDataset (line 46) | class BaseLMIterableDataset(BaseIterableDataset):
    method __init__ (line 53) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method pad_token_id (line 71) | def pad_token_id(self) -> int:
    method vocab_size (line 76) | def vocab_size(self) -> int:
    method seed (line 81) | def seed(self) -> int:
    method _tokenize_text (line 86) | def _tokenize_text(self, text: str) -> Optional[Dict[str, Tensor]]:
    method add_arguments (line 130) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method generate_sample (line 169) | def generate_sample(
    method __iter__ (line 198) | def __iter__(self) -> Iterator[Dict[str, Tensor]]:
    method extra_repr (line 213) | def extra_repr(self) -> str:

FILE: corenet/data/datasets/language_modeling/commonsense_170k.py
  class CommonSense170k (line 23) | class CommonSense170k(BaseLMIterableDataset):
    method __init__ (line 41) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method generate_sample (line 54) | def generate_sample(
    method add_arguments (line 69) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method _download_if_required (line 83) | def _download_if_required(self, remote_file_path: str) -> str:
  function generate_prompt_and_response (line 117) | def generate_prompt_and_response(data_point: Dict[str, str]) -> str:

FILE: corenet/data/datasets/language_modeling/general_lm.py
  function check_list_of_dicts_with_mandatory_keys (line 30) | def check_list_of_dicts_with_mandatory_keys(
  class GeneralLMDataset (line 57) | class GeneralLMDataset(BaseLMIterableDataset):
    method __init__ (line 71) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method add_arguments (line 83) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method _reset_data_state (line 123) | def _reset_data_state(self) -> None:
    method extra_repr (line 146) | def extra_repr(self) -> str:
    method reader_chunk_size (line 154) | def reader_chunk_size(self) -> int:
    method save_loc (line 161) | def save_loc(self) -> str:
    method num_files (line 170) | def num_files(self) -> int:
    method document_split_size (line 175) | def document_split_size(self) -> int:
    method _load_data_state (line 181) | def _load_data_state(self) -> None:
    method _save_data_state (line 215) | def _save_data_state(self, **kwargs) -> None:
    method _prepare_dataset (line 269) | def _prepare_dataset(self) -> Dict[str, List[str]]:
    method _download_if_required (line 366) | def _download_if_required(self, remote_file_path: str) -> str:
    method _skip_document_chunks (line 407) | def _skip_document_chunks(self, chunks: Iterable[Any]) -> Iterator[Any]:
    method _split_document_into_sequences (line 424) | def _split_document_into_sequences(
    method _read_data_from_parquet (line 446) | def _read_data_from_parquet(
    method _read_data_from_json (line 473) | def _read_data_from_json(
    method _get_file_reader (line 498) | def _get_file_reader(self, file_path: str) -> Callable:
    method generate_sample (line 512) | def generate_sample(
    method _shuffle_fn (line 601) | def _shuffle_fn(

FILE: corenet/data/datasets/multi_modal_img_text/__init__.py
  function arguments_multi_modal_img_text (line 16) | def arguments_multi_modal_img_text(

FILE: corenet/data/datasets/multi_modal_img_text/base_multi_modal_img_text.py
  class BaseMultiModalImgText (line 28) | class BaseMultiModalImgText(BaseImageDataset):
    method __init__ (line 40) | def __init__(
    method get_image_text_dataset (line 65) | def get_image_text_dataset(self) -> Optional[Any]:
    method _get_transfer_client (line 76) | def _get_transfer_client(self, file_path: str) -> BaseClient:
    method vocab_size (line 107) | def vocab_size(self) -> int:
    method padding_index (line 112) | def padding_index(self) -> Optional[int]:
    method context_length (line 122) | def context_length(self) -> int:
    method add_arguments (line 130) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method _transform_text (line 160) | def _transform_text(self, text_tensor: Tensor) -> Tuple[Tensor, int]:
    method _training_transforms (line 184) | def _training_transforms(
    method _validation_transforms (line 226) | def _validation_transforms(
    method _process_img_caption (line 246) | def _process_img_caption(
    method get_zero_shot_image_text_pair (line 333) | def get_zero_shot_image_text_pair(
    method get_image_text_dataset_pair (line 351) | def get_image_text_dataset_pair(self, sample_index: int) -> Tuple[Imag...
    method __getitem__ (line 358) | def __getitem__(
    method __len__ (line 424) | def __len__(self) -> int:
    method __repr__ (line 427) | def __repr__(self) -> str:
  function multi_modal_img_text_collate_fn (line 434) | def multi_modal_img_text_collate_fn(

FILE: corenet/data/datasets/multi_modal_img_text/flickr.py
  class FlickrDataset (line 17) | class FlickrDataset(BaseMultiModalImgText):
    method get_image_text_dataset (line 35) | def get_image_text_dataset(self) -> List[Dict[str, str]]:
    method __getitem__ (line 76) | def __getitem__(

FILE: corenet/data/datasets/multi_modal_img_text/img_text_tar_dataset.py
  class ImgTextTarDataset (line 39) | class ImgTextTarDataset(BaseMultiModalImgText):
    method _metadata_file_path (line 90) | def _metadata_file_path(self) -> str:
    method _metadata (line 104) | def _metadata(self):
    method total_tar_files (line 138) | def total_tar_files(self) -> int:
    method max_files_per_tar (line 144) | def max_files_per_tar(self) -> int:
    method get_image_text_dataset (line 149) | def get_image_text_dataset(self) -> None:
    method _get_folder_index (line 156) | def _get_folder_index(self, sample_index) -> int:
    method add_arguments (line 171) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method _download_and_extract_tar_file (line 185) | def _download_and_extract_tar_file(self, sample_index: int) -> int:
    method get_image_text_dataset_pair (line 244) | def get_image_text_dataset_pair(self, sample_index: int) -> Tuple[Imag...
    method __len__ (line 283) | def __len__(self) -> int:
    method extra_repr (line 298) | def extra_repr(self) -> str:

FILE: corenet/data/datasets/multi_modal_img_text/zero_shot_image_classification/__init__.py
  function arguments_zero_shot_image_classification_dataset (line 23) | def arguments_zero_shot_image_classification_dataset(
  function build_zero_shot_image_classification_dataset (line 32) | def build_zero_shot_image_classification_dataset(

FILE: corenet/data/datasets/multi_modal_img_text/zero_shot_image_classification/base_zero_shot_image_classification.py
  class BaseZeroShotImageClassificationDataset (line 17) | class BaseZeroShotImageClassificationDataset(BaseImageClassificationData...
    method add_arguments (line 26) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method __getitem__ (line 38) | def __getitem__(self, img_index: int) -> Tuple[str, List[List[str]], i...
    method class_names (line 51) | def class_names(self) -> List[str]:
    method text_prompts (line 63) | def text_prompts(self) -> List[List[str]]:
    method generate_text_prompts (line 75) | def generate_text_prompts(self, class_name: str) -> List[str]:

FILE: corenet/data/datasets/multi_modal_img_text/zero_shot_image_classification/imagenet.py
  class ImageNetDatasetZeroShot (line 19) | class ImageNetDatasetZeroShot(BaseZeroShotImageClassificationDataset):
    method class_names (line 23) | def class_names(self) -> List[str]:

FILE: corenet/data/datasets/multi_modal_img_text/zero_shot_image_classification/imagenet_a.py
  class ImageNetADatasetZeroShot (line 24) | class ImageNetADatasetZeroShot(BaseZeroShotImageClassificationDataset):
    method class_names (line 28) | def class_names(self) -> List[str]:

FILE: corenet/data/datasets/multi_modal_img_text/zero_shot_image_classification/imagenet_r.py
  class ImageNetRDatasetZeroShot (line 24) | class ImageNetRDatasetZeroShot(
    method class_names (line 30) | def class_names(self) -> List[str]:

FILE: corenet/data/datasets/multi_modal_img_text/zero_shot_image_classification/imagenet_sketch.py
  class ImageNetSketchDatasetZeroShot (line 21) | class ImageNetSketchDatasetZeroShot(
    method class_names (line 27) | def class_names(self) -> List[str]:

FILE: corenet/data/datasets/multi_modal_img_text/zero_shot_image_classification/templates.py
  function generate_text_prompts_clip (line 92) | def generate_text_prompts_clip(class_name) -> List[str]:

FILE: corenet/data/datasets/segmentation/ade20k.py
  class ADE20KDataset (line 19) | class ADE20KDataset(BaseImageSegmentationDataset):
    method __init__ (line 34) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method adjust_mask_value (line 65) | def adjust_mask_value() -> int:
    method color_palette (line 71) | def color_palette() -> List[int]:
    method class_names (line 231) | def class_names() -> List[str]:

FILE: corenet/data/datasets/segmentation/base_segmentation.py
  class BaseImageSegmentationDataset (line 22) | class BaseImageSegmentationDataset(BaseImageDataset):
    method __init__ (line 30) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method add_arguments (line 41) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method check_dataset (line 108) | def check_dataset(self) -> None:
    method _training_transforms (line 119) | def _training_transforms(self, size: Tuple[int, int]) -> T.BaseTransfo...
    method _validation_transforms (line 161) | def _validation_transforms(
    method _evaluation_transforms (line 177) | def _evaluation_transforms(
    method adjust_mask_value (line 225) | def adjust_mask_value() -> int:
    method __len__ (line 231) | def __len__(self) -> int:
    method color_palette (line 236) | def color_palette() -> List[int]:
    method class_names (line 243) | def class_names() -> List[str]:
    method read_mask_pil (line 249) | def read_mask_pil(path: str) -> Optional[Image.Image]:
    method convert_mask_to_tensor (line 260) | def convert_mask_to_tensor(mask: Image.Image) -> Tensor:
    method __getitem__ (line 268) | def __getitem__(

FILE: corenet/data/datasets/segmentation/coco_segmentation.py
  class COCOSegmentationDataset (line 22) | class COCOSegmentationDataset(BaseImageSegmentationDataset):
    method __init__ (line 29) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method __getitem__ (line 45) | def __getitem__(
    method _gen_seg_mask (line 104) | def _gen_seg_mask(self, target, h: int, w: int) -> np.ndarray:
    method __len__ (line 125) | def __len__(self) -> int:
    method class_names (line 129) | def class_names() -> List[str]:
    method coco_to_pascal_mapping (line 156) | def coco_to_pascal_mapping() -> List[int]:

FILE: corenet/data/datasets/segmentation/coco_stuff.py
  class COCOStuffDataset (line 19) | class COCOStuffDataset(BaseImageSegmentationDataset):
    method __init__ (line 50) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method color_palette (line 76) | def color_palette() -> List[int]:
    method class_names (line 258) | def class_names() -> List[str]:

FILE: corenet/data/datasets/segmentation/pascal_voc.py
  class PascalVOCDataset (line 19) | class PascalVOCDataset(BaseImageSegmentationDataset):
    method __init__ (line 37) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method add_arguments (line 91) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method color_palette (line 112) | def color_palette() -> List[int]:
    method class_names (line 143) | def class_names() -> List[str]:

FILE: corenet/data/datasets/utils/common.py
  function file_has_valid_image_extension (line 24) | def file_has_valid_image_extension(filename: str) -> bool:
  function file_has_allowed_extension (line 28) | def file_has_allowed_extension(
  function get_image_paths (line 43) | def get_image_paths(directory: str) -> List[str]:
  function select_random_subset (line 55) | def select_random_subset(
  function select_samples_by_category (line 113) | def select_samples_by_category(

FILE: corenet/data/datasets/utils/text.py
  function caption_preprocessing (line 12) | def caption_preprocessing(caption: str) -> str:

FILE: corenet/data/datasets/utils/video.py
  function _simultaneous (line 38) | def _simultaneous(
  function _before (line 46) | def _before(this_timestamp: float, other_timestamp: float) -> bool:
  function fetch_labels_from_timestamps (line 53) | def fetch_labels_from_timestamps(
  function _make_fake_bbox (line 129) | def _make_fake_bbox(
  function _fetch_frame_label (line 162) | def _fetch_frame_label(
  function _assert_progress_repr (line 302) | def _assert_progress_repr(
  function _search_for_label_edge_timestamp (line 321) | def _search_for_label_edge_timestamp(
  function _interpolate_bounding_box (line 391) | def _interpolate_bounding_box(

FILE: corenet/data/io/transfer_clients.py
  class BaseClient (line 30) | class BaseClient(object):
    method __init__ (line 47) | def __init__(
    method add_arguments (line 75) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method start_rank_node (line 83) | def start_rank_node(self) -> bool:
    method sync_distributed_ranks (line 89) | def sync_distributed_ranks(self) -> bool:
    method _download_fn (line 96) | def _download_fn(self, remote_path: str, local_path: str) -> None:
    method _download_with_retries (line 107) | def _download_with_retries(self, remote_path: str, local_path: str) ->...
    method _download_single_file (line 116) | def _download_single_file(self, remote_path: str, dst_dir: str) -> str:
    method _download_multiple_files (line 169) | def _download_multiple_files(
    method download (line 200) | def download(
  class S3Client (line 233) | class S3Client(BaseClient):
    method __init__ (line 236) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method transfer_config (line 249) | def transfer_config(self) -> TransferConfig:
    method init_client (line 257) | def init_client(
    method add_arguments (line 291) | def add_arguments(cls, parser: ArgumentParser) -> ArgumentParser:
    method _download_fn (line 333) | def _download_fn(self, remote_path: str, local_path: str) -> None:
  class HTTPClient (line 343) | class HTTPClient(BaseClient):
    method __init__ (line 346) | def __init__(self, opts, *args, **kwargs) -> None:
    method proxies (line 350) | def proxies(self):
    method _download_fn (line 356) | def _download_fn(self, remote_path: str, local_path: str) -> None:
  class HTTPSClient (line 369) | class HTTPSClient(HTTPClient):
    method __init__ (line 372) | def __init__(self, opts, *args, **kwargs) -> None:
  function get_transfer_client (line 376) | def get_transfer_client(
  function transfer_client_arguments (line 430) | def transfer_client_arguments(

FILE: corenet/data/loader/dataloader.py
  class CoreNetDataLoader (line 16) | class CoreNetDataLoader(DataLoader):
    method __init__ (line 39) | def __init__(
    method update_indices (line 74) | def update_indices(self, new_indices: List, *args, **kwargs):
    method __len__ (line 81) | def __len__(self) -> int:
    method get_sample_indices (line 97) | def get_sample_indices(self) -> List:

FILE: corenet/data/sampler/__init__.py
  function build_sampler (line 23) | def build_sampler(
  function add_sampler_arguments (line 64) | def add_sampler_arguments(

FILE: corenet/data/sampler/base_sampler.py
  class BaseSampler (line 18) | class BaseSampler(Sampler):
    method __init__ (line 30) | def __init__(
    method add_arguments (line 69) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method get_indices (line 114) | def get_indices(self) -> List[int]:
    method __iter__ (line 140) | def __iter__(self) -> Iterator[Tuple[Any, ...]]:
    method __len__ (line 143) | def __len__(self) -> int:
    method set_epoch (line 146) | def set_epoch(self, epoch: int) -> None:
    method update_scales (line 150) | def update_scales(
    method update_indices (line 158) | def update_indices(self, new_indices: List[int]) -> None:
    method extra_repr (line 162) | def extra_repr(self) -> str:
    method __repr__ (line 169) | def __repr__(self) -> str:
  class BaseSamplerDDP (line 173) | class BaseSamplerDDP(Sampler):
    method __init__ (line 185) | def __init__(
    method get_indices_rank_i (line 241) | def get_indices_rank_i(self) -> List[int]:
    method __iter__ (line 329) | def __iter__(self) -> Iterator[Tuple[Any, ...]]:
    method __len__ (line 332) | def __len__(self) -> int:
    method add_arguments (line 338) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method set_epoch (line 359) | def set_epoch(self, epoch: int) -> None:
    method update_scales (line 363) | def update_scales(
    method update_indices (line 371) | def update_indices(self, new_indices: List[int]) -> None:
    method extra_repr (line 375) | def extra_repr(self) -> str:
    method __repr__ (line 384) | def __repr__(self):
  function get_batch_size_from_opts (line 388) | def get_batch_size_from_opts(

FILE: corenet/data/sampler/batch_sampler.py
  class BatchSampler (line 15) | class BatchSampler(BaseSampler):
    method __init__ (line 25) | def __init__(
    method __iter__ (line 43) | def __iter__(self) -> Iterator[Tuple[int, int, int]]:
    method extra_repr (line 61) | def extra_repr(self) -> str:
    method add_arguments (line 70) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
  class BatchSamplerDDP (line 91) | class BatchSamplerDDP(BaseSamplerDDP):
    method __init__ (line 100) | def __init__(
    method __iter__ (line 121) | def __iter__(self) -> Iterator[Tuple[int, int, int]]:
    method extra_repr (line 141) | def extra_repr(self) -> str:

FILE: corenet/data/sampler/chain_sampler.py
  class ChainSampler (line 22) | class ChainSampler(Sampler):
    method __init__ (line 69) | def __init__(
    method add_arguments (line 94) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method build_chain_sampler (line 112) | def build_chain_sampler(
    method _sequential_sampling (line 215) | def _sequential_sampling(self) -> List[Tuple]:
    method _interleave_sampling (line 231) | def _interleave_sampling(self) -> List[Tuple]:
    method __iter__ (line 264) | def __iter__(self) -> Iterator[Tuple]:
    method __len__ (line 270) | def __len__(self) -> int:
    method set_epoch (line 278) | def set_epoch(self, epoch: int) -> None:
    method update_scales (line 290) | def update_scales(
    method update_indices (line 308) | def update_indices(self, new_indices: List[int]) -> None:
    method __repr__ (line 323) | def __repr__(self) -> str:

FILE: corenet/data/sampler/multi_scale_sampler.py
  class MultiScaleSampler (line 18) | class MultiScaleSampler(BaseSampler):
    method __init__ (line 28) | def __init__(
    method add_arguments (line 87) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method __iter__ (line 152) | def __iter__(self) -> Iterator[Tuple[int, int, int]]:
    method update_scales (line 170) | def update_scales(
    method extra_repr (line 182) | def extra_repr(self) -> str:
  class MultiScaleSamplerDDP (line 193) | class MultiScaleSamplerDDP(BaseSamplerDDP):
    method __init__ (line 202) | def __init__(
    method __iter__ (line 259) | def __iter__(self) -> Iterator[Tuple[int, int, int]]:
    method extra_repr (line 278) | def extra_repr(self) -> str:
    method update_scales (line 287) | def update_scales(

FILE: corenet/data/sampler/utils.py
  function image_batch_pairs (line 13) | def image_batch_pairs(
  function make_video_pairs (line 70) | def make_video_pairs(
  function create_intervallic_integer_list (line 123) | def create_intervallic_integer_list(
  function make_tuple_list (line 149) | def make_tuple_list(*val_list: List) -> List[Tuple]:

FILE: corenet/data/sampler/variable_batch_sampler.py
  class VariableBatchSampler (line 18) | class VariableBatchSampler(BaseSampler):
    method __init__ (line 28) | def __init__(
    method __iter__ (line 91) | def __iter__(self) -> Iterator[Tuple[int, int, int]]:
    method update_scales (line 109) | def update_scales(
    method extra_repr (line 144) | def extra_repr(self) -> str:
    method add_arguments (line 159) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
  class VariableBatchSamplerDDP (line 243) | class VariableBatchSamplerDDP(BaseSamplerDDP):
    method __init__ (line 252) | def __init__(
    method __iter__ (line 315) | def __iter__(self) -> Iterator[Tuple[int, int, int]]:
    method update_scales (line 333) | def update_scales(self, epoch: int, is_master_node=False, *args, **kwa...
    method extra_repr (line 366) | def extra_repr(self) -> str:

FILE: corenet/data/sampler/video_batch_sampler.py
  class VideoBatchSampler (line 14) | class VideoBatchSampler(BatchSampler):
    method __init__ (line 24) | def __init__(
    method __iter__ (line 39) | def __iter__(self) -> Iterator[Tuple[int, int, int, int, int]]:
    method add_arguments (line 65) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Na...
    method extra_repr (line 84) | def extra_repr(self) -> str:
  class VideoBatchSamplerDDP (line 94) | class VideoBatchSamplerDDP(BatchSamplerDDP):
    method __init__ (line 103) | def __init__(
    method __iter__ (line 117) | def __iter__(self) -> Iterator[Tuple[int, int, int, int, int]]:
    method extra_repr (line 144) | def extra_repr(self) -> str:

FILE: corenet/data/sampler/video_clip_batch_sampler.py
  class VideoClipBatchSampler (line 23) | class VideoClipBatchSampler(VariableBatchSampler):
    method add_arguments (line 57) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method __init__ (line 131) | def __init__(
    method __iter__ (line 173) | def __iter__(self) -> Iterator[List]:
    method __repr__ (line 244) | def __repr__(self) -> str:
  class VideoClipBatchSamplerDDP (line 260) | class VideoClipBatchSamplerDDP(BaseSamplerDDP):
    method __init__ (line 269) | def __init__(
    method __iter__ (line 277) | def __iter__(self) -> Iterator[List]:
    method __len__ (line 290) | def __len__(self) -> int:
    method set_epoch (line 293) | def set_epoch(self, epoch: int) -> None:
    method update_scales (line 297) | def update_scales(self, *args, **kwargs) -> None:
    method update_indices (line 300) | def update_indices(self, new_indices: List[int]) -> None:
    method extra_repr (line 303) | def extra_repr(self) -> str:

FILE: corenet/data/sampler/video_variable_seq_sampler.py
  class VideoVariableSeqSampler (line 20) | class VideoVariableSeqSampler(VariableBatchSampler):
    method __init__ (line 31) | def __init__(
    method add_arguments (line 77) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method __iter__ (line 123) | def __iter__(self) -> Iterator[Tuple[int, int, int, int, int]]:
    method update_scales (line 158) | def update_scales(
    method extra_repr (line 170) | def extra_repr(self) -> str:
  class VideoVariableSeqSamplerDDP (line 180) | class VideoVariableSeqSamplerDDP(VariableBatchSamplerDDP):
    method __init__ (line 189) | def __init__(
    method __iter__ (line 235) | def __iter__(self) -> Iterator[Tuple[int, int, int, int, int]]:
    method update_scales (line 270) | def update_scales(
    method extra_repr (line 281) | def extra_repr(self) -> str:

FILE: corenet/data/text_tokenizer/__init__.py
  function arguments_tokenizer (line 23) | def arguments_tokenizer(parser: argparse.ArgumentParser) -> argparse.Arg...
  function build_tokenizer (line 32) | def build_tokenizer(opts, *args, **kwargs) -> BaseTextTokenizer:

FILE: corenet/data/text_tokenizer/base_tokenizer.py
  class BaseTextTokenizer (line 14) | class BaseTextTokenizer(nn.Module):
    method __init__ (line 21) | def __init__(self, opts: argparse.Namespace) -> None:
    method add_arguments (line 26) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method vocab_size (line 59) | def vocab_size(self) -> int:
    method eot_token (line 64) | def eot_token(self) -> str:
    method eot_token_id (line 74) | def eot_token_id(self) -> int:
    method sot_token (line 79) | def sot_token(self) -> str:
    method sot_token_id (line 89) | def sot_token_id(self) -> int:
    method pad_token (line 94) | def pad_token(self) -> str:
    method pad_token_id (line 104) | def pad_token_id(self) -> int:
    method tok_encode (line 108) | def tok_encode(self, input_sentence: str) -> Tensor:
    method tok_decode (line 112) | def tok_decode(self, token_ids: Any) -> str:
    method forward (line 116) | def forward(self, input_sentence: str) -> Tensor:

FILE: corenet/data/text_tokenizer/clip_tokenizer.py
  class ClipTokenizer (line 18) | class ClipTokenizer(BaseTextTokenizer):
    method __init__ (line 28) | def __init__(self, opts: argparse.Namespace) -> None:
    method add_arguments (line 56) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method vocab_size (line 76) | def vocab_size(self) -> int:
    method eot_token (line 81) | def eot_token(self) -> str:
    method eot_token_id (line 86) | def eot_token_id(self) -> int:
    method sot_token (line 91) | def sot_token(self) -> str:
    method sot_token_id (line 96) | def sot_token_id(self) -> int:
    method tok_encode (line 100) | def tok_encode(self, input_sentence: str) -> Tensor:

FILE: corenet/data/text_tokenizer/sentencepiece_tokenizer.py
  class SentencePieceTokenizer (line 21) | class SentencePieceTokenizer(BaseTextTokenizer):
    method __init__ (line 35) | def __init__(self, opts: Namespace) -> None:
    method add_arguments (line 60) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method vocab_size (line 92) | def vocab_size(self) -> int:
    method sot_token_id (line 101) | def sot_token_id(self) -> int:
    method eot_token_id (line 110) | def eot_token_id(self) -> int:
    method pad_token_id (line 119) | def pad_token_id(self) -> int:
    method tok_encode (line 143) | def tok_encode(self, input_sentence: str) -> Tensor:
    method tok_decode (line 170) | def tok_decode(self, token_ids: Union[torch.Tensor, List[int]]) -> str:

FILE: corenet/data/transforms/__init__.py
  function arguments_augmentation (line 19) | def arguments_augmentation(parser: argparse.ArgumentParser) -> argparse....

FILE: corenet/data/transforms/audio.py
  class Gain (line 20) | class Gain(BaseTransformation):
    method __init__ (line 25) | def __init__(self, opts, *args, **kwargs) -> None:
    method add_arguments (line 34) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method __call__ (line 56) | def __call__(self, data: Dict) -> Dict:
    method __repr__ (line 84) | def __repr__(self) -> str:
  class Noise (line 94) | class Noise(BaseTransformation):
    method __init__ (line 99) | def __init__(
    method load_noise_files (line 132) | def load_noise_files(self, cache_size: int) -> List[torch.TensorType]:
    method add_arguments (line 148) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method __call__ (line 185) | def __call__(self, data: Dict) -> Dict:
    method __repr__ (line 232) | def __repr__(self) -> str:
  class SetFixedLength (line 242) | class SetFixedLength(BaseTransformation):
    method __init__ (line 245) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method add_arguments (line 251) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method __call__ (line 269) | def __call__(
    method __repr__ (line 297) | def __repr__(self) -> str:
  class Roll (line 302) | class Roll(BaseTransformation):
    method __init__ (line 305) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method add_arguments (line 311) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method __call__ (line 329) | def __call__(
    method __repr__ (line 359) | def __repr__(self) -> str:
  class MFCCs (line 364) | class MFCCs(BaseTransformation):
    method __init__ (line 365) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method add_arguments (line 372) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method __call__ (line 397) | def __call__(self, data: Dict, *args, **kwargs) -> Dict:
    method __repr__ (line 431) | def __repr__(self) -> str:
  class LambdaAudio (line 438) | class LambdaAudio(BaseTransformation):
    method __init__ (line 444) | def __init__(
    method __call__ (line 454) | def __call__(self, data: Dict, *args, **kwargs) -> Dict:
  class AudioResample (line 460) | class AudioResample(BaseTransformation):
    method add_arguments (line 464) | def add_arguments(cls, parser: argparse.ArgumentParser) -> None:
    method __init__ (line 481) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method __call__ (line 487) | def __call__(self, data: Dict, *args, **kwargs) -> Dict:
    method __repr__ (line 526) | def __repr__(self) -> str:
  class StandardizeChannels (line 531) | class StandardizeChannels(BaseTransformation):
    method __init__ (line 532) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method add_arguments (line 539) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method __call__ (line 557) | def __call__(self, data: Dict, *args, **kwargs) -> Dict:
    method __repr__ (line 603) | def __repr__(self) -> str:
  class GaussianAudioNoise (line 608) | class GaussianAudioNoise(BaseTransformation):
    method __init__ (line 612) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method add_arguments (line 619) | def add_arguments(cls, parser: argparse.ArgumentParser) -> None:
    method __call__ (line 638) | def __call__(self, data: Dict, *args, **kwargs) -> Dict:
    method __repr__ (line 661) | def __repr__(self) -> str:

FILE: corenet/data/transforms/audio_aux/mfccs.py
  function get_mfccs (line 12) | def get_mfccs(
  function calculate_mfccs (line 57) | def calculate_mfccs(
  function get_mfcc_features (line 98) | def get_mfcc_features(
  function get_padded_features (line 138) | def get_padded_features(

FILE: corenet/data/transforms/audio_bytes.py
  function _stream_to_wav (line 17) | def _stream_to_wav(x: torch.Tensor, dtype: str, audio_fps: int, backend:...
  class TorchaudioSave (line 58) | class TorchaudioSave(BaseTransformation):
    method __init__ (line 66) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method __call__ (line 75) | def __call__(
    method __repr__ (line 132) | def __repr__(self) -> str:
    method add_arguments (line 136) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...

FILE: corenet/data/transforms/base_transforms.py
  class BaseTransformation (line 10) | class BaseTransformation(object):
    method __init__ (line 15) | def __init__(self, opts, *args, **kwargs) -> None:
    method __call__ (line 18) | def __call__(self, data: Dict) -> Dict:
    method __repr__ (line 21) | def __repr__(self) -> str:
    method add_arguments (line 25) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...

FILE: corenet/data/transforms/common.py
  class Compose (line 11) | class Compose(BaseTransformation):
    method __init__ (line 16) | def __init__(self, opts, img_transforms: List, *args, **kwargs) -> None:
    method __call__ (line 20) | def __call__(self, data: Dict) -> Dict:
    method __repr__ (line 25) | def __repr__(self) -> str:
  class Identity (line 32) | class Identity(BaseTransformation):
    method __call__ (line 37) | def __call__(self, data: Dict) -> Dict:
    method __repr__ (line 40) | def __repr__(self) -> str:

FILE: corenet/data/transforms/image_bytes.py
  function _image_to_bytes (line 17) | def _image_to_bytes(x: torch.Tensor, **kwargs) -> io.BytesIO:
  function _bytes_to_int32 (line 41) | def _bytes_to_int32(byte_array: io.BytesIO) -> torch.Tensor:
  class PILSave (line 58) | class PILSave(BaseTransformation):
    method __init__ (line 63) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method __call__ (line 69) | def __call__(
    method __repr__ (line 102) | def __repr__(self) -> str:
    method add_arguments (line 106) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
  class ShuffleBytes (line 131) | class ShuffleBytes(BaseTransformation):
    method __init__ (line 136) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method __call__ (line 143) | def __call__(
    method add_arguments (line 194) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
  class MaskPositions (line 231) | class MaskPositions(BaseTransformation):
    method __init__ (line 236) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method _generate_masks (line 241) | def _generate_masks(self, N: int) -> torch.Tensor:
    method __call__ (line 253) | def __call__(
    method add_arguments (line 273) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
  class BytePermutation (line 292) | class BytePermutation(BaseTransformation):
    method __init__ (line 297) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method __call__ (line 304) | def __call__(
    method add_arguments (line 326) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
  class RandomUniformNoise (line 339) | class RandomUniformNoise(BaseTransformation):
    method __init__ (line 344) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method __call__ (line 352) | def __call__(
    method add_arguments (line 378) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...

FILE: corenet/data/transforms/image_pil.py
  function _interpolation_modes_from_str (line 34) | def _interpolation_modes_from_str(name: str) -> T.InterpolationMode:
  function _crop_fn (line 38) | def _crop_fn(data: Dict, top: int, left: int, height: int, width: int) -...
  function _resize_fn (line 90) | def _resize_fn(
  function _pad_fn (line 173) | def _pad_fn(
  class FixedSizeCrop (line 210) | class FixedSizeCrop(BaseTransformation):
    method __init__ (line 211) | def __init__(
    method add_arguments (line 235) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method __call__ (line 265) | def __call__(self, data: Dict, *args, **kwargs) -> Dict:
    method __repr__ (line 294) | def __repr__(self):
  class ScaleJitter (line 305) | class ScaleJitter(BaseTransformation):
    method __init__ (line 308) | def __init__(self, opts, *args, **kwargs) -> None:
    method add_arguments (line 356) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method __call__ (line 387) | def __call__(self, data: Dict, *args, **kwargs) -> Dict:
    method __repr__ (line 408) | def __repr__(self):
  class RandomResizedCrop (line 418) | class RandomResizedCrop(BaseTransformation, T.RandomResizedCrop):
    method __init__ (line 423) | def __init__(
    method add_arguments (line 443) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method get_rrc_params (line 476) | def get_rrc_params(self, image: Image.Image) -> Tuple[int, int, int, i...
    method __call__ (line 481) | def __call__(self, data: Dict) -> Dict:
    method __repr__ (line 497) | def __repr__(self) -> str:
  class AutoAugment (line 508) | class AutoAugment(BaseTransformation, T.AutoAugment):
    method __init__ (line 513) | def __init__(self, opts, *args, **kwargs) -> None:
    method add_arguments (line 532) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method __call__ (line 555) | def __call__(self, data: Dict) -> Dict:
    method __repr__ (line 568) | def __repr__(self) -> str:
  class RandAugment (line 575) | class RandAugment(BaseTransformation, T.RandAugment):
    method __init__ (line 580) | def __init__(self, opts, *args, **kwargs) -> None:
    method add_arguments (line 604) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method __call__ (line 640) | def __call__(self, data: Dict) -> Dict:
    method __repr__ (line 653) | def __repr__(self) -> str:
  class TrivialAugmentWide (line 664) | class TrivialAugmentWide(BaseTransformation, T.TrivialAugmentWide):
    method __init__ (line 669) | def __init__(self, opts, *args, **kwargs) -> None:
    method add_arguments (line 693) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method __call__ (line 717) | def __call__(self, data: Dict) -> Dict:
    method __repr__ (line 730) | def __repr__(self) -> str:
  class RandomHorizontalFlip (line 739) | class RandomHorizontalFlip(BaseTransformation):
    method __init__ (line 744) | def __init__(self, opts, *args, **kwargs) -> None:
    method add_arguments (line 750) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method __call__ (line 766) | def __call__(self, data: Dict) -> Dict:
    method __repr__ (line 792) | def __repr__(self) -> str:
  class RandomRotate (line 797) | class RandomRotate(BaseTransformation):
    method __init__ (line 802) | def __init__(self, opts, *args, **kwargs) -> None:
    method add_arguments (line 808) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method __call__ (line 830) | def __call__(self, data: Dict) -> Dict:
    method __repr__ (line 854) | def __repr__(self) -> str:
  class Resize (line 861) | class Resize(BaseTransformation):
    method __init__ (line 874) | def __init__(
    method add_arguments (line 921) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method __call__ (line 947) | def __call__(self, data: Dict) -> Dict:
    method __repr__ (line 950) | def __repr__(self) -> str:
  class CenterCrop (line 960) | class CenterCrop(BaseTransformation):
    method __init__ (line 968) | def __init__(self, opts, *args, **kwargs) -> None:
    method add_arguments (line 985) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method __call__ (line 1003) | def __call__(self, data: Dict) -> Dict:
    method __repr__ (line 1009) | def __repr__(self) -> str:
  class SSDCroping (line 1016) | class SSDCroping(BaseTransformation):
    method __init__ (line 1021) | def __init__(self, opts, *args, **kwargs) -> None:
    method add_arguments (line 1038) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method __call__ (line 1074) | def __call__(self, data: Dict) -> Dict:
  class PhotometricDistort (line 1194) | class PhotometricDistort(BaseTransformation):
    method __init__ (line 1202) | def __init__(self, opts, *args, **kwargs) -> None:
    method __repr__ (line 1246) | def __repr__(self) -> str:
    method add_arguments (line 1256) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method _apply_transformations (line 1326) | def _apply_transformations(self, image):
    method __call__ (line 1354) | def __call__(self, data: Dict) -> Dict:
  class BoxPercentCoords (line 1361) | class BoxPercentCoords(BaseTransformation):
    method __init__ (line 1366) | def __init__(self, opts, *args, **kwargs) -> None:
    method __call__ (line 1369) | def __call__(self, data: Dict) -> Dict:
  class InstanceProcessor (line 1385) | class InstanceProcessor(BaseTransformation):
    method __init__ (line 1390) | def __init__(
    method __call__ (line 1400) | def __call__(self, data: Dict) -> Dict:
  class RandomResize (line 1454) | class RandomResize(BaseTransformation):
    method __init__ (line 1459) | def __init__(self, opts, *args, **kwargs) -> None:
    method add_arguments (line 1498) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method __call__ (line 1540) | def __call__(self, data: Dict) -> Dict:
    method __repr__ (line 1566) | def __repr__(self) -> str:
  class RandomShortSizeResize (line 1578) | class RandomShortSizeResize(BaseTransformation):
    method __init__ (line 1583) | def __init__(self, opts, *args, **kwargs) -> None:
    method add_arguments (line 1638) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method __call__ (line 1673) | def __call__(self, data: Dict) -> Dict:
    method __repr__ (line 1684) | def __repr__(self) -> str:
  class RandomErasing (line 1694) | class RandomErasing(BaseTransformation, T.RandomErasing):
    method __init__ (line 1700) | def __init__(self, opts, *args, **kwargs) -> None:
    method add_arguments (line 1708) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method __call__ (line 1725) | def __call__(self, data: Dict) -> Dict:
    method __repr__ (line 1729) | def __repr__(self) -> str:
  class RandomGaussianBlur (line 1736) | class RandomGaussianBlur(BaseTransformation):
    method __init__ (line 1741) | def __init__(self, opts, *args, **kwargs):
    method add_arguments (line 1746) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method __call__ (line 1763) | def __call__(self, data: Dict) -> Dict:
  class RandomCrop (line 1773) | class RandomCrop(BaseTransformation):
    method __init__ (line 1782) | def __init__(
    method add_arguments (line 1807) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method get_params (line 1837) | def get_params(img_h, img_w, target_h, target_w):
    method get_params_from_box (line 1846) | def get_params_from_box(boxes, img_h, img_w):
    method get_params_from_mask (line 1856) | def get_params_from_mask(self, data, i, j, h, w):
    method _resize_if_needed (line 1886) | def _resize_if_needed(self, data: Dict) -> Dict:
    method _pad_if_needed (line 1897) | def _pad_if_needed(self, data: Dict) -> Dict:
    method __call__ (line 1916) | def __call__(self, data: Dict) -> Dict:
    method __repr__ (line 1944) | def __repr__(self) -> str:
  class ToTensor (line 1955) | class ToTensor(BaseTransformation):
    method __init__ (line 1960) | def __init__(self, opts, *args, **kwargs) -> None:
    method add_arguments (line 2004) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method __repr__ (line 2033) | def __repr__(self):
    method __call__ (line 2050) | def __call__(self, data: Dict) -> Dict:
  class RandomOrder (line 2098) | class RandomOrder(BaseTransformation):
    method __init__ (line 2103) | def __init__(self, opts, img_transforms: List, *args, **kwargs) -> None:
    method add_arguments (line 2113) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method __call__ (line 2130) | def __call__(self, data: Dict) -> Dict:
    method __repr__ (line 2136) | def __repr__(self):
  class RandAugmentTimm (line 2145) | class RandAugmentTimm(BaseTransformation):
    method __init__ (line 2151) | def __init__(self, opts, *args, **kwargs) -> None:
    method add_arguments (line 2170) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method __call__ (line 2186) | def __call__(self, data: Dict) -> Dict:
    method __repr__ (line 2204) | def __repr__(self) -> str:

FILE: corenet/data/transforms/image_torch.py
  class RandomMixup (line 22) | class RandomMixup(BaseTransformation):
    method __init__ (line 32) | def __init__(
    method add_arguments (line 53) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method _apply_mixup_transform (line 99) | def _apply_mixup_transform(
    method __call__ (line 139) | def __call__(self, data: Dict) -> Dict:
    method __repr__ (line 206) | def __repr__(self) -> str:
  class RandomCutmix (line 213) | class RandomCutmix(BaseTransformation):
    method __init__ (line 223) | def __init__(
    method add_arguments (line 244) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method _apply_cutmix_transform (line 290) | def _apply_cutmix_transform(
    method __call__ (line 344) | def __call__(self, data: Dict) -> Dict:
    method __repr__ (line 410) | def __repr__(self) -> str:
  function apply_mixing_transforms (line 416) | def apply_mixing_transforms(opts: argparse.Namespace, data: Dict) -> Dict:

FILE: corenet/data/transforms/utils.py
  function setup_size (line 11) | def setup_size(size: Any, error_msg="Need a tuple of length 2"):
  function intersect (line 26) | def intersect(box_a, box_b):
  function jaccard_numpy (line 34) | def jaccard_numpy(box_a: np.ndarray, box_b: np.ndarray):

FILE: corenet/data/transforms/video.py
  function _check_interpolation (line 32) | def _check_interpolation(interpolation):
  function _crop_fn (line 41) | def _crop_fn(data: Dict, i: int, j: int, h: int, w: int) -> Dict:
  function _resize_fn (line 75) | def _resize_fn(
  function check_rgb_video_tensor (line 145) | def check_rgb_video_tensor(clip: torch.Tensor) -> None:
  class ToTensor (line 161) | class ToTensor(BaseTransformation):
    method __init__ (line 176) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method __call__ (line 179) | def __call__(self, data: Dict) -> Dict:
  class ToPixelArray (line 196) | class ToPixelArray(BaseTransformation):
    method __call__ (line 208) | def __call__(self, data: Dict) -> Dict:
  class SaveInputs (line 217) | class SaveInputs(BaseTransformation):
    method __init__ (line 218) | def __init__(
    method __call__ (line 258) | def __call__(self, data: Dict) -> Dict:
    method add_arguments (line 281) | def add_arguments(cls, parser: argparse.ArgumentParser) -> None:
    method _srt_format_timestamp (line 322) | def _srt_format_timestamp(t: float) -> str:
    method save_video_with_annotations (line 330) | def save_video_with_annotations(
    method __repr__ (line 418) | def __repr__(self) -> str:
  class RandomResizedCrop (line 431) | class RandomResizedCrop(BaseTransformation):
    method __init__ (line 436) | def __init__(self, opts, size: Union[Tuple, int], *args, **kwargs) -> ...
    method add_arguments (line 479) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method get_params (line 518) | def get_params(self, height: int, width: int) -> (int, int, int, int):
    method __call__ (line 548) | def __call__(self, data: Dict) -> Dict:
    method __repr__ (line 558) | def __repr__(self) -> str:
  class RandomShortSizeResizeCrop (line 569) | class RandomShortSizeResizeCrop(BaseTransformation):
    method __init__ (line 579) | def __init__(self, opts, size: Union[Tuple, int], *args, **kwargs) -> ...
    method add_arguments (line 624) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method get_params (line 656) | def get_params(self, height, width) -> Tuple[int, int, int, int]:
    method __call__ (line 666) | def __call__(self, data: Dict) -> Dict:
    method __repr__ (line 678) | def __repr__(self) -> str:
  class RandomCrop (line 690) | class RandomCrop(BaseTransformation):
    method __init__ (line 699) | def __init__(self, opts, size: Union[Tuple, int], *args, **kwargs) -> ...
    method add_arguments (line 706) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method get_params (line 719) | def get_params(self, height: int, width: int) -> Tuple[int, int, int, ...
    method __call__ (line 729) | def __call__(self, data: Dict) -> Dict:
    method __repr__ (line 736) | def __repr__(self) -> str:
  class RandomHorizontalFlip (line 743) | class RandomHorizontalFlip(BaseTransformation):
    method __init__ (line 748) | def __init__(self, opts, *args, **kwargs) -> None:
    method add_arguments (line 755) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method __call__ (line 773) | def __call__(self, data: Dict) -> Dict:
    method __repr__ (line 787) | def __repr__(self) -> str:
  class CenterCrop (line 795) | class CenterCrop(BaseTransformation):
    method __init__ (line 804) | def __init__(self, opts, size: Union[Sequence, int], *args, **kwargs) ...
    method add_arguments (line 818) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method __call__ (line 831) | def __call__(self, data: Dict) -> Dict:
    method __repr__ (line 837) | def __repr__(self) -> str:
  class Resize (line 844) | class Resize(BaseTransformation):
    method __init__ (line 855) | def __init__(self, opts, *args, **kwargs) -> None:
    method add_arguments (line 883) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method __call__ (line 914) | def __call__(self, data: Dict) -> Dict:
    method __repr__ (line 917) | def __repr__(self) -> str:
  class CropByBoundingBox (line 924) | class CropByBoundingBox(BaseTransformation):
    method __init__ (line 939) | def __init__(
    method __call__ (line 972) | def __call__(self, data: Dict, *args, **kwargs) -> Dict:
    method expand_boxes (line 1071) | def expand_boxes(
    method get_new_x0 (line 1119) | def get_new_x0(cls, multiplier: float) -> float:
    method add_arguments (line 1126) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method __repr__ (line 1184) | def __repr__(self) -> str:
  class ShuffleAudios (line 1194) | class ShuffleAudios(BaseTransformation):
    method __init__ (line 1195) | def __init__(
    method add_arguments (line 1244) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method _single_cycle_permutation (line 1304) | def _single_cycle_permutation(
    method _random_outcome (line 1348) | def _random_outcome(self, n: int) -> torch.Tensor:
    method _random_participants_mask (line 1365) | def _random_participants_mask(self, n: int) -> torch.BoolTensor:
    method __call__ (line 1373) | def __call__(self, data: Dict) -> Dict:

FILE: corenet/data/video_reader/__init__.py
  function arguments_video_reader (line 21) | def arguments_video_reader(parser: argparse.ArgumentParser):
  function get_video_reader (line 29) | def get_video_reader(

FILE: corenet/data/video_reader/base_av_reader.py
  class VideoDurationDoesNotMatchAudioDurationError (line 26) | class VideoDurationDoesNotMatchAudioDurationError(AssertionError):
  function check_audio_video_duration (line 33) | def check_audio_video_duration(
  class BaseAVReader (line 47) | class BaseAVReader(object):
    method add_arguments (line 57) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method __init__ (line 93) | def __init__(
    method get_frame_transform (line 118) | def get_frame_transform(
    method __repr__ (line 163) | def __repr__(self):
    method check_video (line 170) | def check_video(self, filename: str) -> bool:
    method read_video (line 182) | def read_video(
    method build_video_metadata (line 194) | def build_video_metadata(
    method num_frames (line 213) | def num_frames(self, filename: str) -> int:
    method random_sampling (line 223) | def random_sampling(
    method uniform_sampling (line 262) | def uniform_sampling(
    method read_video_file_into_clips (line 305) | def read_video_file_into_clips(
    method _generate_video_clips (line 454) | def _generate_video_clips(
    method _generate_audio_clips (line 546) | def _generate_audio_clips(
    method dummy_audio_video_clips (line 600) | def dummy_audio_video_clips(
  function _downsample_frame_indices (line 647) | def _downsample_frame_indices(

FILE: corenet/data/video_reader/decord_reader.py
  class DecordAVReader (line 26) | class DecordAVReader(BaseAVReader):
    method __init__ (line 31) | def __init__(self, *args, **kwargs):
    method read_video (line 35) | def read_video(
    method build_video_metadata (line 97) | def build_video_metadata(
    method build_audio_metadata (line 126) | def build_audio_metadata(
    method _get_total_audio_frames (line 166) | def _get_total_audio_frames(video_path: str, sample_rate: Union[int, f...

FILE: corenet/data/video_reader/ffmpeg_reader.py
  class FFMPEGReader (line 29) | class FFMPEGReader(BaseAVReader):
    method __init__ (line 37) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method read_video (line 41) | def read_video(
    method _transform_video_frames (line 209) | def _transform_video_frames(
    method read_audio (line 237) | def read_audio(
    method build_video_metadata (line 298) | def build_video_metadata(cls, video_path: str) -> Dict[str, Union[str,...
    method build_audio_metadata (line 318) | def build_audio_metadata(cls, video_path: str) -> Dict[str, Union[str,...

FILE: corenet/data/video_reader/ffmpeg_utils.py
  class FFMPEGError (line 45) | class FFMPEGError(Exception):
    method __init__ (line 46) | def __init__(self, message: str, stderr: Union[IOBase, bytes, str]):
  function _parse_stream_duration (line 54) | def _parse_stream_duration(stream: Dict[str, Any]) -> float:
  function ffprobe (line 74) | def ffprobe(video_path: str, parse_json: bool = True) -> Union[str, Dict...
  function get_video_metadata (line 117) | def get_video_metadata(
  function get_audio_metadata (line 210) | def get_audio_metadata(
  function get_flags_to_replicate_audio_codec (line 256) | def get_flags_to_replicate_audio_codec(input_filename: str) -> Dict:
  function transform_video_file (line 314) | def transform_video_file(
  function _kill_subprocess (line 643) | def _kill_subprocess(process: subprocess.Popen, timeout_seconds: float =...
  function write_video (line 658) | def write_video(
  function write_audio (line 732) | def write_audio(

FILE: corenet/data/video_reader/pyav_reader.py
  class PyAVReader (line 18) | class PyAVReader(BaseAVReader):
    method read_video (line 23) | def read_video(
    method build_video_metadata (line 105) | def build_video_metadata(

FILE: corenet/engine/default_trainer.py
  class DefaultTrainer (line 41) | class DefaultTrainer(object):
    method __init__ (line 60) | def __init__(
    method compute_grad_norm (line 139) | def compute_grad_norm(self) -> torch.Tensor:
    method _zero_grad (line 161) | def _zero_grad(self) -> None:
    method _set_training_mode (line 174) | def _set_training_mode(self) -> None:
    method _set_eval_mode (line 181) | def _set_eval_mode(self) -> None:
    method _save_and_evaluate_interval_checkpoint (line 188) | def _save_and_evaluate_interval_checkpoint(
    method train_epoch (line 249) | def train_epoch(self, epoch: int) -> Tuple[float, float]:
    method val_epoch (line 408) | def val_epoch(
    method run (line 516) | def run(

FILE: corenet/engine/detection_utils/coco_map.py
  function coco_evaluation (line 19) | def coco_evaluation(
  function compute_quant_scores (line 105) | def compute_quant_scores(opts, predictions: List, *args, **kwargs) -> None:

FILE: corenet/engine/eval_detection.py
  function predict_and_save (line 39) | def predict_and_save(
  function read_and_process_image (line 172) | def read_and_process_image(
  function predict_labeled_dataset (line 205) | def predict_labeled_dataset(opts: argparse.Namespace) -> None:
  function predict_image (line 261) | def predict_image(opts: argparse.Namespace, file_path: str) -> None:
  function predict_images_in_folder (line 300) | def predict_images_in_folder(opts: argparse.Namespace) -> None:
  function main_detection_evaluation (line 356) | def main_detection_evaluation(args: Optional[List[str]] = None) -> None:

FILE: corenet/engine/eval_segmentation.py
  function predict_and_save (line 43) | def predict_and_save(
  function save_segmentation_masks (line 167) | def save_segmentation_masks(
  function apply_color_map_to_segmentation_masks (line 196) | def apply_color_map_to_segmentation_masks(
  function read_and_process_image (line 278) | def read_and_process_image(
  function predict_labeled_dataset (line 313) | def predict_labeled_dataset(opts: argparse.Namespace) -> None:
  function predict_image (line 396) | def predict_image(opts: argparse.Namespace, file_path: str) -> None:
  function predict_images_in_folder (line 441) | def predict_images_in_folder(opts: argparse.Namespace) -> None:
  function main_segmentation_evaluation (line 511) | def main_segmentation_evaluation(args: Optional[List[str]] = None) -> None:

FILE: corenet/engine/evaluation_engine.py
  class Evaluator (line 24) | class Evaluator:
    method __init__ (line 25) | def __init__(
    method eval_fn (line 70) | def eval_fn(self) -> None:
    method run (line 129) | def run(self) -> None:

FILE: corenet/engine/fsdp_trainer.py
  class FSDPTrainer (line 30) | class FSDPTrainer(DefaultTrainer):
    method __init__ (line 48) | def __init__(
    method train_epoch (line 90) | def train_epoch(self, epoch: int) -> Tuple[float, float]:

FILE: corenet/engine/segmentation_utils/cityscapes_iou.py
  function eval_cityscapes (line 14) | def eval_cityscapes(pred_dir: str, gt_dir: str) -> None:

FILE: corenet/engine/utils.py
  function autocast_fn (line 23) | def autocast_fn(enabled: bool, amp_precision: Optional[str] = "float16"):
  function get_batch_size (line 43) | def get_batch_size(x: Union[Tensor, Dict, List]) -> int:
  function log_metrics (line 57) | def log_metrics(
  function flatten (line 78) | def flatten(
  function step_log_metrics (line 103) | def step_log_metrics(
  function get_log_writers (line 130) | def get_log_writers(opts: argparse.Namespace, save_location: Optional[st...

FILE: corenet/loss_fn/__init__.py
  function build_loss_fn (line 22) | def build_loss_fn(
  function add_loss_fn_arguments (line 65) | def add_loss_fn_arguments(parser: argparse.ArgumentParser) -> argparse.A...

FILE: corenet/loss_fn/base_criteria.py
  class BaseCriteria (line 15) | class BaseCriteria(nn.Module, abc.ABC):
    method __init__ (line 22) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method add_arguments (line 29) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method forward (line 45) | def forward(
    method extra_repr (line 57) | def extra_repr(self) -> str:
    method __repr__ (line 60) | def __repr__(self) -> str:

FILE: corenet/loss_fn/classification/base_classification_criteria.py
  class BaseClassificationCriteria (line 14) | class BaseClassificationCriteria(BaseCriteria):
    method __init__ (line 21) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method add_arguments (line 25) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method _compute_loss (line 40) | def _compute_loss(
    method forward (line 54) | def forward(

FILE: corenet/loss_fn/classification/binary_cross_entropy.py
  class BinaryCrossEntropy (line 18) | class BinaryCrossEntropy(BaseClassificationCriteria):
    method __init__ (line 25) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method add_arguments (line 33) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method _compute_loss (line 49) | def _compute_loss(
    method extra_repr (line 88) | def extra_repr(self) -> str:

FILE: corenet/loss_fn/classification/cross_entropy.py
  class CrossEntropy (line 19) | class CrossEntropy(BaseClassificationCriteria):
    method __init__ (line 26) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method add_arguments (line 40) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method _compute_loss (line 68) | def _compute_loss(
    method extra_repr (line 97) | def extra_repr(self) -> str:

FILE: corenet/loss_fn/classification/focal_loss.py
  class FocalLoss (line 19) | class FocalLoss(BaseClassificationCriteria):
    method __init__ (line 33) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method add_arguments (line 41) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method _compute_loss (line 62) | def _compute_loss(
    method extra_repr (line 96) | def extra_repr(self) -> str:

FILE: corenet/loss_fn/composite_loss.py
  class CompositeLoss (line 21) | class CompositeLoss(BaseCriteria):
    method __init__ (line 53) | def __init__(
    method build_composite_loss_fn (line 70) | def build_composite_loss_fn(
    method add_arguments (line 150) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method forward (line 160) | def forward(
    method train (line 209) | def train(self, mode: bool = True) -> None:
    method eval (line 214) | def eval(self) -> None:
    method __repr__ (line 219) | def __repr__(self) -> str:

FILE: corenet/loss_fn/detection/base_detection_criteria.py
  class BaseDetectionCriteria (line 10) | class BaseDetectionCriteria(BaseCriteria):
    method __init__ (line 17) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method add_arguments (line 21) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...

FILE: corenet/loss_fn/detection/mask_rcnn_loss.py
  class MaskRCNNLoss (line 18) | class MaskRCNNLoss(BaseDetectionCriteria):
    method __init__ (line 26) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method add_arguments (line 45) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method forward (line 82) | def forward(
    method extra_repr (line 153) | def extra_repr(self) -> str:

FILE: corenet/loss_fn/detection/ssd_multibox_loss.py
  class SSDLoss (line 22) | class SSDLoss(BaseDetectionCriteria):
    method __init__ (line 29) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method reset_unscaled_loss_values (line 59) | def reset_unscaled_loss_values(self) -> None:
    method add_arguments (line 66) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method forward (line 102) | def forward(
    method extra_repr (line 216) | def extra_repr(self) -> str:

FILE: corenet/loss_fn/distillation/base_distillation.py
  class BaseDistillationCriteria (line 16) | class BaseDistillationCriteria(BaseCriteria):
    method __init__ (line 23) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method add_arguments (line 29) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method _logits_from_teacher (line 44) | def _logits_from_teacher(self, input_sample: Tensor) -> Tensor:
    method _forward_distill (line 72) | def _forward_distill(
    method forward (line 90) | def forward(

FILE: corenet/loss_fn/distillation/hard_distillation.py
  class HardDistillationLoss (line 18) | class HardDistillationLoss(BaseDistillationCriteria):
    method __init__ (line 26) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method add_arguments (line 45) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method _forward_distill (line 66) | def _forward_distill(
    method extra_repr (line 128) | def extra_repr(self) -> str:

FILE: corenet/loss_fn/distillation/soft_kl_distillation.py
  class SoftKLLoss (line 18) | class SoftKLLoss(BaseDistillationCriteria):
    method __init__ (line 26) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method add_arguments (line 38) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method _forward_distill (line 52) | def _forward_distill(
    method extra_repr (line 80) | def extra_repr(self) -> str:

FILE: corenet/loss_fn/language_modeling/base_lm.py
  class BaseLanguageModelingCriteria (line 16) | class BaseLanguageModelingCriteria(BaseCriteria):
    method add_arguments (line 27) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method _compute_loss (line 39) | def _compute_loss(self, prediction: Tensor, target: Tensor) -> Tensor:
    method forward (line 53) | def forward(

FILE: corenet/loss_fn/language_modeling/cross_entropy.py
  class CrossEntropyLM (line 17) | class CrossEntropyLM(BaseLanguageModelingCriteria):
    method __init__ (line 24) | def __init__(self, opts: argparse.Namespace) -> None:
    method add_arguments (line 46) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method _compute_loss (line 78) | def _compute_loss(
    method extra_repr (line 117) | def extra_repr(self) -> str:

FILE: corenet/loss_fn/language_modeling/cross_entropy_for_kv_prediction.py
  class CrossEntropyForKVPrediction (line 20) | class CrossEntropyForKVPrediction(BaseCriteria):
    method __init__ (line 29) | def __init__(self, opts: argparse.Namespace) -> None:
    method add_arguments (line 62) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method forward (line 113) | def forward(
    method _compute_loss (line 179) | def _compute_loss(
    method extra_repr (line 276) | def extra_repr(self) -> str:
  function get_cache_losses (line 292) | def get_cache_losses(

FILE: corenet/loss_fn/multi_modal_img_text/base_multi_modal_img_text_criteria.py
  class BaseMultiModalImageTextCriteria (line 10) | class BaseMultiModalImageTextCriteria(BaseCriteria):
    method __init__ (line 17) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method add_arguments (line 21) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...

FILE: corenet/loss_fn/multi_modal_img_text/contrastive_loss_clip.py
  class ContrastiveLossClip (line 21) | class ContrastiveLossClip(BaseMultiModalImageTextCriteria):
    method __init__ (line 28) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method _forward_clip (line 35) | def _forward_clip(
    method forward (line 105) | def forward(
  function gather_features (line 144) | def gather_features(

FILE: corenet/loss_fn/neural_augmentation.py
  class NeuralAugmentation (line 20) | class NeuralAugmentation(BaseCriteria):
    method __init__ (line 30) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method add_arguments (line 142) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method _forward_psnr (line 178) | def _forward_psnr(
    method _compute_loss (line 220) | def _compute_loss(
    method forward (line 246) | def forward(
    method extra_repr (line 300) | def extra_repr(self) -> str:
  function linear_curriculum (line 314) | def linear_curriculum(start: int, end: int, period: int) -> Tensor:
  function cosine_curriculum (line 328) | def cosine_curriculum(start: int, end: int, period: int) -> Tensor:

FILE: corenet/loss_fn/segmentation/base_segmentation_criteria.py
  class BaseSegmentationCriteria (line 10) | class BaseSegmentationCriteria(BaseCriteria):
    method __init__ (line 17) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method add_arguments (line 21) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...

FILE: corenet/loss_fn/segmentation/cross_entropy.py
  class SegCrossEntropy (line 21) | class SegCrossEntropy(BaseSegmentationCriteria):
    method __init__ (line 28) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method add_arguments (line 40) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method _compute_loss (line 77) | def _compute_loss(
    method _forward_seg (line 120) | def _forward_seg(
    method forward (line 192) | def forward(
    method extra_repr (line 256) | def extra_repr(self) -> str:

FILE: corenet/loss_fn/utils/build_helper.py
  function build_cls_teacher_from_opts (line 14) | def build_cls_teacher_from_opts(opts: argparse.Namespace) -> nn.Module:

FILE: corenet/loss_fn/utils/class_weighting.py
  function compute_class_weights (line 10) | def compute_class_weights(

FILE: corenet/metrics/__init__.py
  function arguments_stats (line 17) | def arguments_stats(parser: argparse.ArgumentParser):

FILE: corenet/metrics/average_precision.py
  class AveragePrecisionMetric (line 21) | class AveragePrecisionMetric(EpochMetric):
    method compute_with_aggregates (line 22) | def compute_with_aggregates(

FILE: corenet/metrics/coco_map.py
  class COCOEvaluator (line 27) | class COCOEvaluator(BaseMetric):
    method __init__ (line 28) | def __init__(
    method reset (line 68) | def reset(self) -> None:
    method update (line 71) | def update(
    method prepare_cache_results (line 120) | def prepare_cache_results(
    method summarize_coco_results (line 213) | def summarize_coco_results(self) -> Dict:
    method compute (line 245) | def compute(self) -> Dict[str, float]:

FILE: corenet/metrics/confusion_mat.py
  class ConfusionMatrix (line 19) | class ConfusionMatrix(BaseMetric):
    method reset (line 24) | def reset(self):
    method update (line 28) | def update(
    method compute (line 62) | def compute(self) -> Union[Number, Dict[str, Union[Number, List[Number...

FILE: corenet/metrics/image_text_retrieval.py
  class ImageTextRetrievalMetric (line 21) | class ImageTextRetrievalMetric(BaseMetric):
    method __init__ (line 39) | def __init__(
    method add_arguments (line 60) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method reset (line 72) | def reset(self) -> None:
    method update (line 76) | def update(
    method get_aggregates (line 104) | def get_aggregates(self) -> Tuple[Tensor, Tensor]:
    method _text2image (line 110) | def _text2image(
    method _image2text (line 135) | def _image2text(
    method compute (line 161) | def compute(self) -> Union[Number, Dict[str, Number]]:
    method _rank_metrics (line 185) | def _rank_metrics(self, ranks: torch.LongTensor) -> Dict[str, Number]:

FILE: corenet/metrics/intersection_over_union.py
  function compute_miou_batch (line 18) | def compute_miou_batch(
  class IOUMetric (line 57) | class IOUMetric(AverageMetric):
    method gather_metrics (line 58) | def gather_metrics(
    method compute (line 86) | def compute(self) -> Union[Number, Dict[str, Number]]:

FILE: corenet/metrics/metric_base.py
  class BaseMetric (line 24) | class BaseMetric(abc.ABC):
    method __init__ (line 25) | def __init__(
    method add_arguments (line 41) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method reset (line 46) | def reset(self) -> None:
    method update (line 54) | def update(
    method compute (line 76) | def compute(
    method preprocess_predictions (line 94) | def preprocess_predictions(
    method preprocess_targets (line 102) | def preprocess_targets(self, target: Union[Tensor, Dict]) -> Union[Ten...
    method summary_string (line 108) | def summary_string(self, name: str, sep: str, values: Dict[str, Any]) ...
    method is_epoch_summary_enabled_for_metric (line 126) | def is_epoch_summary_enabled_for_metric(
    method flatten_metric (line 147) | def flatten_metric(
  class AverageMetric (line 165) | class AverageMetric(BaseMetric):
    method reset (line 166) | def reset(self):
    method gather_metrics (line 171) | def gather_metrics(
    method _aggregate_ddp_sum (line 181) | def _aggregate_ddp_sum(
    method update (line 200) | def update(
    method compute (line 239) | def compute(self) -> Union[Number, List, Dict[str, Any]]:
  class EpochMetric (line 249) | class EpochMetric(BaseMetric):
    method __init__ (line 250) | def __init__(
    method reset (line 261) | def reset(self):
    method update (line 265) | def update(
    method get_aggregates (line 304) | def get_aggregates(self) -> Tuple[Tensor, Tensor]:
    method compute_with_aggregates (line 318) | def compute_with_aggregates(self, predictions: Tensor, targets: Tensor):
    method compute (line 330) | def compute(self) -> Union[Number, List, Dict[str, Any]]:

FILE: corenet/metrics/metric_base_test.py
  class DummyMetric (line 14) | class DummyMetric(AverageMetric):
    method gather_metrics (line 15) | def gather_metrics(
  function test_average_metric_distributed_batchsize (line 24) | def test_average_metric_distributed_batchsize(mocker):

FILE: corenet/metrics/misc.py
  class LossMetric (line 18) | class LossMetric(AverageMetric):
    method gather_metrics (line 19) | def gather_metrics(
  class GradNormMetric (line 61) | class GradNormMetric(AverageMetric):
    method gather_metrics (line 62) | def gather_metrics(

FILE: corenet/metrics/multiclass_classification_pr.py
  function get_recall_at_precision (line 21) | def get_recall_at_precision(
  function compute_oi_f1 (line 56) | def compute_oi_f1(predictions: Tensor, targets: Tensor) -> Tuple[float, ...
  class MulticlassClassificationPR (line 133) | class MulticlassClassificationPR(BaseMetric):
    method __init__ (line 149) | def __init__(
    method add_arguments (line 170) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method reset (line 198) | def reset(self) -> None:
    method update (line 206) | def update(
    method compute (line 289) | def compute(self) -> Dict[str, Union[Number, List[List[Number]]]]:
    method is_epoch_summary_enabled_for_metric (line 393) | def is_epoch_summary_enabled_for_metric(
    method flatten_metric (line 427) | def flatten_metric(
    method summary_string (line 448) | def summary_string(self, name: str, sep: str, values: Dict[str, Any]) ...

FILE: corenet/metrics/probability_histograms.py
  class ProbabilityHistogramMetric (line 20) | class ProbabilityHistogramMetric(EpochMetric):
    method __init__ (line 21) | def __init__(
    method add_arguments (line 32) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method compute_with_aggregates (line 40) | def compute_with_aggregates(

FILE: corenet/metrics/psnr.py
  function compute_psnr (line 16) | def compute_psnr(
  class PSNRMetric (line 34) | class PSNRMetric(AverageMetric):
    method gather_metrics (line 35) | def gather_metrics(

FILE: corenet/metrics/retrieval_cmc.py
  function cosine_distance_matrix (line 25) | def cosine_distance_matrix(x: torch.Tensor, y: torch.Tensor) -> torch.Te...
  function l2_distance_matrix (line 47) | def l2_distance_matrix(x: torch.Tensor, y: torch.Tensor) -> torch.Tensor:
  class RetrievalCMC (line 64) | class RetrievalCMC(EpochMetric):
    method __init__ (line 69) | def __init__(
    method add_arguments (line 97) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method compute_with_aggregates (line 125) | def compute_with_aggregates(
  function cmc_calculation (line 174) | def cmc_calculation(
  function mean_ap (line 204) | def mean_ap(

FILE: corenet/metrics/stats.py
  class Statistics (line 23) | class Statistics(object):
    method __init__ (line 24) | def __init__(
    method update (line 57) | def update(
    method _avg_statistics_all (line 94) | def _avg_statistics_all(self, sep=": ", metrics=None) -> List[str]:
    method _compute_avg_statistics_all (line 111) | def _compute_avg_statistics_all(self) -> Dict[str, Union[float, Dict]]:
    method avg_statistics (line 122) | def avg_statistics(
    method iter_summary (line 163) | def iter_summary(
    method epoch_summary (line 196) | def epoch_summary(

FILE: corenet/metrics/topk_accuracy.py
  function top_k_accuracy (line 15) | def top_k_accuracy(
  class TopKMetric (line 33) | class TopKMetric(AverageMetric):
    method gather_metrics (line 36) | def gather_metrics(
  class Top1Metric (line 109) | class Top1Metric(TopKMetric):
  class Top5Metric (line 114) | class Top5Metric(TopKMetric):

FILE: corenet/metrics/vqa_preset_score.py
  function vqa_preset_score_metric (line 17) | def vqa_preset_score_metric(output: Tensor, target: Tensor) -> list:
  class VQAPresetScoreMetric (line 43) | class VQAPresetScoreMetric(AverageMetric):
    method gather_metrics (line 46) | def gather_metrics(

FILE: corenet/modeling/__init__.py
  function modeling_arguments (line 21) | def modeling_arguments(parser: argparse.ArgumentParser) -> argparse.Argu...

FILE: corenet/modeling/anchor_generator/__init__.py
  function arguments_anchor_gen (line 21) | def arguments_anchor_gen(parser: argparse.ArgumentParser) -> argparse.Ar...
  function build_anchor_generator (line 33) | def build_anchor_generator(opts, *args, **kwargs):

FILE: corenet/modeling/anchor_generator/base_anchor_generator.py
  class BaseAnchorGenerator (line 13) | class BaseAnchorGenerator(torch.nn.Module):
    method __init__ (line 18) | def __init__(self, *args, **kwargs) -> None:
    method add_arguments (line 23) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method num_anchors_per_os (line 29) | def num_anchors_per_os(self):
    method _generate_anchors (line 34) | def _generate_anchors(
    method _get_anchors (line 46) | def _get_anchors(
    method forward (line 71) | def forward(

FILE: corenet/modeling/anchor_generator/ssd_anchor_generator.py
  class SSDAnchorGenerator (line 19) | class SSDAnchorGenerator(BaseAnchorGenerator):
    method __init__ (line 25) | def __init__(self, opts, *args, **kwargs) -> None:
    method __repr__ (line 74) | def __repr__(self):
    method add_arguments (line 85) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method num_anchors_per_os (line 135) | def num_anchors_per_os(self) -> List:
    method _generate_anchors (line 142) | def _generate_anchors(

FILE: corenet/modeling/image_projection_layers/__init__.py
  function arguments_image_projection_head (line 23) | def arguments_image_projection_head(
  function build_image_projection_head (line 35) | def build_image_projection_head(

FILE: corenet/modeling/image_projection_layers/attention_pool_2d.py
  class AttentionPool2dHead (line 21) | class AttentionPool2dHead(BaseImageProjectionHead):
    method __init__ (line 26) | def __init__(self, opts, in_dim: int, out_dim: int, *args, **kwargs) -...
    method add_arguments (line 80) | def add_arguments(cls, parser: argparse.ArgumentParser):
    method reset_parameters (line 116) | def reset_parameters(self):
    method forward (line 121) | def forward(self, x: Tensor, *args, **kwargs) -> Tensor:

FILE: corenet/modeling/image_projection_layers/base_image_projection.py
  class BaseImageProjectionHead (line 15) | class BaseImageProjectionHead(nn.Module):
    method __init__ (line 18) | def __init__(self, opts, *args, **kwargs) -> None:
    method add_arguments (line 24) | def add_arguments(cls, parser: argparse.ArgumentParser):
    method reset_parameters (line 44) | def reset_parameters(self) -> None:
    method get_trainable_parameters (line 48) | def get_trainable_parameters(
    method forward (line 62) | def forward(self, input: Dict, *args, **kwargs) -> Dict:
  function get_in_feature_dimension (line 66) | def get_in_feature_dimension(image_classifier: nn.Module) -> int:

FILE: corenet/modeling/image_projection_layers/global_pool_2d.py
  class GlobalPool2D (line 22) | class GlobalPool2D(BaseImageProjectionHead):
    method __init__ (line 25) | def __init__(self, opts, in_dim: int, out_dim: int, *args, **kwargs) -...
    method add_arguments (line 55) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method reset_parameters (line 73) | def reset_parameters(self):
    method forward (line 76) | def forward(self, x: Tensor, *args, **kwargs) -> Tensor:

FILE: corenet/modeling/image_projection_layers/simple_projection_head.py
  class SimpleImageProjectionHead (line 21) | class SimpleImageProjectionHead(BaseImageProjectionHead):
    method __init__ (line 24) | def __init__(self, opts, in_dim: int, out_dim: int, *args, **kwargs) -...
    method add_arguments (line 53) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method reset_parameters (line 71) | def reset_parameters(self):
    method forward (line 74) | def forward(self, x: Tensor, *args, **kwargs) -> Tensor:

FILE: corenet/modeling/layers/__init__.py
  function layer_specific_args (line 82) | def layer_specific_args(parser: argparse.ArgumentParser):
  function arguments_nn_layers (line 101) | def arguments_nn_layers(parser: argparse.ArgumentParser):

FILE: corenet/modeling/layers/activation/__init__.py
  function register_act_fn (line 19) | def register_act_fn(name):
  function arguments_activation_fn (line 32) | def arguments_activation_fn(parser: argparse.ArgumentParser):
  function build_activation_layer (line 58) | def build_activation_layer(

FILE: corenet/modeling/layers/activation/gelu.py
  class GELU (line 12) | class GELU(nn.GELU):
    method __init__ (line 17) | def __init__(self, *args, **kwargs) -> None:

FILE: corenet/modeling/layers/activation/hard_sigmoid.py
  class Hardsigmoid (line 15) | class Hardsigmoid(nn.Hardsigmoid):
    method __init__ (line 20) | def __init__(self, inplace: Optional[bool] = False, *args, **kwargs) -...
    method forward (line 23) | def forward(self, input: Tensor, *args, **kwargs) -> Tensor:

FILE: corenet/modeling/layers/activation/hard_swish.py
  class Hardswish (line 15) | class Hardswish(nn.Hardswish):
    method __init__ (line 21) | def __init__(self, inplace: Optional[bool] = False, *args, **kwargs) -...
    method forward (line 24) | def forward(self, input: Tensor, *args, **kwargs) -> Tensor:

FILE: corenet/modeling/layers/activation/leaky_relu.py
  class LeakyReLU (line 14) | class LeakyReLU(nn.LeakyReLU):
    method __init__ (line 20) | def __init__(

FILE: corenet/modeling/layers/activation/prelu.py
  class PReLU (line 14) | class PReLU(nn.PReLU):
    method __init__ (line 19) | def __init__(

FILE: corenet/modeling/layers/activation/relu.py
  class ReLU (line 14) | class ReLU(nn.ReLU):
    method __init__ (line 19) | def __init__(self, inplace: Optional[bool] = False, *args, **kwargs) -...

FILE: corenet/modeling/layers/activation/relu6.py
  class ReLU6 (line 14) | class ReLU6(nn.ReLU6):
    method __init__ (line 19) | def __init__(self, inplace: Optional[bool] = False, *args, **kwargs) -...

FILE: corenet/modeling/layers/activation/sigmoid.py
  class Sigmoid (line 12) | class Sigmoid(nn.Sigmoid):
    method __init__ (line 17) | def __init__(self, *args, **kwargs) -> None:

FILE: corenet/modeling/layers/activation/swish.py
  class Swish (line 14) | class Swish(nn.SiLU):
    method __init__ (line 19) | def __init__(self, inplace: Optional[bool] = False, *args, **kwargs) -...

FILE: corenet/modeling/layers/activation/tanh.py
  class Tanh (line 12) | class Tanh(nn.Tanh):
    method __init__ (line 17) | def __init__(self, *args, **kwargs) -> None:

FILE: corenet/modeling/layers/adaptive_pool.py
  class AdaptiveAvgPool2d (line 11) | class AdaptiveAvgPool2d(nn.AdaptiveAvgPool2d):
    method __init__ (line 25) | def __init__(

FILE: corenet/modeling/layers/base_layer.py
  class BaseLayer (line 14) | class BaseLayer(nn.Module):
    method __init__ (line 19) | def __init__(self, *args, **kwargs) -> None:
    method add_arguments (line 23) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method get_trainable_parameters (line 27) | def get_trainable_parameters(
    method forward (line 58) | def forward(self, *args, **kwargs) -> Any:
    method __repr__ (line 62) | def __repr__(self):

FILE: corenet/modeling/layers/conv_layer.py
  class Conv2d (line 18) | class Conv2d(nn.Conv2d):
    method __init__ (line 42) | def __init__(
  class _BaseConvNormActLayer (line 69) | class _BaseConvNormActLayer(BaseLayer):
    method ndim (line 110) | def ndim(self) -> int:
    method module_cls (line 114) | def module_cls(self) -> Type[nn.Module]:
    method __init__ (line 117) | def __init__(
    method add_arguments (line 236) | def add_arguments(cls, parser: argparse.ArgumentParser):
    method forward (line 254) | def forward(self, x: Tensor) -> Tensor:
    method __repr__ (line 257) | def __repr__(self):
  class ConvLayer1d (line 270) | class ConvLayer1d(_BaseConvNormActLayer):
  class ConvLayer2d (line 275) | class ConvLayer2d(_BaseConvNormActLayer):
  class ConvLayer3d (line 280) | class ConvLayer3d(_BaseConvNormActLayer):
  class TransposeConvLayer2d (line 285) | class TransposeConvLayer2d(BaseLayer):
    method __init__ (line 316) | def __init__(
    method forward (line 435) | def forward(self, x: Tensor) -> Tensor:
    method __repr__ (line 438) | def __repr__(self):
  class NormActLayer (line 451) | class NormActLayer(BaseLayer):
    method __init__ (line 464) | def __init__(self, opts, num_features, *args, **kwargs):
    method forward (line 484) | def forward(self, x: Tensor) -> Tensor:
    method __repr__ (line 487) | def __repr__(self):
  class _BaseSeparableConv (line 494) | class _BaseSeparableConv(BaseLayer):
    method __init__ (line 528) | def __init__(
    method conv_layer_cls (line 582) | def conv_layer_cls(self):
    method __repr__ (line 585) | def __repr__(self):
    method forward (line 596) | def forward(self, x: Tensor) -> Tensor:
  class SeparableConv1d (line 602) | class SeparableConv1d(_BaseSeparableConv):
  class SeparableConv2d (line 606) | class SeparableConv2d(_BaseSeparableConv):
  class SeparableConv3d (line 610) | class SeparableConv3d(_BaseSeparableConv):

FILE: corenet/modeling/layers/dropout.py
  class Dropout (line 11) | class Dropout(nn.Dropout):
    method __init__ (line 26) | def __init__(
  class Dropout2d (line 32) | class Dropout2d(nn.Dropout2d):
    method __init__ (line 48) | def __init__(self, p: float = 0.5, inplace: bool = False):

FILE: corenet/modeling/layers/embedding.py
  class Embedding (line 16) | class Embedding(nn.Embedding):
    method __init__ (line 33) | def __init__(
    method reset_parameters (line 48) | def reset_parameters(self) -> None:

FILE: corenet/modeling/layers/flash_multi_head_attention.py
  class FlashMultiHeadSelfAttention (line 18) | class FlashMultiHeadSelfAttention(BaseLayer):
    method __init__ (line 32) | def __init__(
    method forward (line 75) | def forward(self, x: Tensor) -> Tensor:

FILE: corenet/modeling/layers/flatten.py
  class Flatten (line 11) | class Flatten(nn.Flatten):
    method __init__ (line 26) | def __init__(self, start_dim: Optional[int] = 1, end_dim: Optional[int...

FILE: corenet/modeling/layers/global_pool.py
  class GlobalPool (line 16) | class GlobalPool(BaseLayer):
    method __init__ (line 31) | def __init__(
    method add_arguments (line 49) | def add_arguments(cls, parser: argparse.ArgumentParser):
    method _global_pool (line 60) | def _global_pool(self, x: Tensor, dims: List):
    method forward (line 73) | def forward(self, x: Tensor) -> Tensor:
    method __repr__ (line 82) | def __repr__(self):

FILE: corenet/modeling/layers/identity.py
  class Identity (line 11) | class Identity(BaseLayer):
    method __init__ (line 16) | def __init__(self):
    method forward (line 19) | def forward(self, x: Tensor) -> Tensor:

FILE: corenet/modeling/layers/linear_attention.py
  class LinearSelfAttention (line 16) | class LinearSelfAttention(BaseLayer):
    method __init__ (line 40) | def __init__(
    method __repr__ (line 73) | def __repr__(self):
    method visualize_context_scores (line 79) | def visualize_context_scores(context_scores):
    method _forward_self_attn (line 134) | def _forward_self_attn(self, x: Tensor, *args, **kwargs) -> Tensor:
    method _forward_cross_attn (line 163) | def _forward_cross_attn(
    method forward (line 209) | def forward(

FILE: corenet/modeling/layers/linear_layer.py
  class LinearLayer (line 17) | class LinearLayer(BaseLayer):
    method __init__ (line 33) | def __init__(
    method add_arguments (line 53) | def add_arguments(cls, parser: argparse.ArgumentParser):
    method reset_params (line 68) | def reset_params(self):
    method forward (line 74) | def forward(self, x: Tensor) -> Tensor:
    method __repr__ (line 93) | def __repr__(self):
  class GroupLinear (line 106) | class GroupLinear(BaseLayer):
    method __init__ (line 124) | def __init__(
    method add_arguments (line 166) | def add_arguments(cls, parser: argparse.ArgumentParser):
    method reset_params (line 181) | def reset_params(self):
    method _forward (line 187) | def _forward(self, x: Tensor) -> Tensor:
    method forward (line 211) | def forward(self, x: Tensor) -> Tensor:
    method __repr__ (line 223) | def __repr__(self):

FILE: corenet/modeling/layers/multi_head_attention.py
  class MultiHeadAttention (line 18) | class MultiHeadAttention(BaseLayer):
    method __init__ (line 38) | def __init__(
    method __repr__ (line 76) | def __repr__(self):
    method forward_tracing (line 81) | def forward_tracing(
    method forward_default (line 139) | def forward_default(
    method forward_pytorch (line 249) | def forward_pytorch(
    method forward (line 283) | def forward(

FILE: corenet/modeling/layers/normalization/__init__.py
  function register_norm_fn (line 21) | def register_norm_fn(name):
  function build_normalization_layer (line 35) | def build_normalization_layer(
  function arguments_norm_layers (line 91) | def arguments_norm_layers(parser: argparse.ArgumentParser):

FILE: corenet/modeling/layers/normalization/batch_norm.py
  class BatchNorm2d (line 16) | class BatchNorm2d(nn.BatchNorm2d):
    method __init__ (line 33) | def __init__(
  class BatchNorm2dFP32 (line 53) | class BatchNorm2dFP32(BatchNorm2d):
    method __init__ (line 58) | def __init__(
    method forward (line 78) | def forward(self, input: Tensor) -> Tensor:
  class BatchNorm1d (line 84) | class BatchNorm1d(nn.BatchNorm1d):
    method __init__ (line 101) | def __init__(
  class BatchNorm3d (line 121) | class BatchNorm3d(nn.BatchNorm3d):
    method __init__ (line 122) | def __init__(

FILE: corenet/modeling/layers/normalization/group_norm.py
  class GroupNorm (line 14) | class GroupNorm(nn.GroupNorm):
    method __init__ (line 34) | def __init__(

FILE: corenet/modeling/layers/normalization/instance_norm.py
  class InstanceNorm2d (line 15) | class InstanceNorm2d(nn.InstanceNorm2d):
    method __init__ (line 32) | def __init__(
  class InstanceNorm1d (line 52) | class InstanceNorm1d(nn.InstanceNorm1d):
    method __init__ (line 69) | def __init__(

FILE: corenet/modeling/layers/normalization/layer_norm.py
  class LayerNorm (line 15) | class LayerNorm(nn.LayerNorm):
    method __init__ (line 37) | def __init__(
    method forward (line 51) | def forward(self, x: Tensor) -> Tensor:
  class LayerNorm2D_NCHW (line 77) | class LayerNorm2D_NCHW(nn.GroupNorm):
    method __init__ (line 92) | def __init__(
    method __repr__ (line 105) | def __repr__(self):
  class LayerNormFP32 (line 112) | class LayerNormFP32(LayerNorm):
    method __init__ (line 117) | def __init__(
    method forward (line 133) | def forward(self, x: Tensor) -> Tensor:

FILE: corenet/modeling/layers/normalization/rms_norm.py
  class RMSNorm (line 13) | class RMSNorm(nn.Module):
    method __init__ (line 14) | def __init__(
    method _norm (line 29) | def _norm(self, x: Tensor) -> Tensor:
    method forward (line 42) | def forward(self, x: Tensor) -> Tensor:
    method extra_repr (line 60) | def extra_repr(self) -> str:

FILE: corenet/modeling/layers/normalization/sync_batch_norm.py
  class SyncBatchNorm (line 15) | class SyncBatchNorm(nn.SyncBatchNorm):
    method __init__ (line 33) | def __init__(
  class SyncBatchNormFP32 (line 53) | class SyncBatchNormFP32(SyncBatchNorm):
    method __init__ (line 58) | def __init__(
    method forward (line 76) | def forward(self, x: Tensor, *args, **kwargs) -> Tensor:

FILE: corenet/modeling/layers/pixel_shuffle.py
  class PixelShuffle (line 9) | class PixelShuffle(nn.PixelShuffle):
    method __init__ (line 22) | def __init__(self, upscale_factor: int, *args, **kwargs) -> None:
    method __repr__ (line 25) | def __repr__(self):

FILE: corenet/modeling/layers/pooling.py
  class MaxPool2d (line 11) | class MaxPool2d(nn.MaxPool2d):
    method __init__ (line 27) | def __init__(
    method __repr__ (line 37) | def __repr__(self):
  class AvgPool2d (line 43) | class AvgPool2d(nn.AvgPool2d):
    method __init__ (line 62) | def __init__(
    method __repr__ (line 80) | def __repr__(self):

FILE: corenet/modeling/layers/positional_embedding.py
  class PositionalEmbedding (line 16) | class PositionalEmbedding(BaseLayer):
    method __init__ (line 17) | def __init__(
    method forward (line 46) | def forward(self, seq_len: int, *args, **kwargs) -> Tensor:
    method __repr__ (line 49) | def __repr__(self):
  class LearnablePositionalEmbedding (line 53) | class LearnablePositionalEmbedding(nn.Module):
    method __init__ (line 56) | def __init__(
    method reset_parameters (line 77) | def reset_parameters(self) -> None:
    method forward (line 83) | def forward(self, seq_len: int, *args, **kwargs) -> Tensor:
    method __repr__ (line 105) | def __repr__(self):
  class SinusoidalPositionalEmbedding (line 115) | class SinusoidalPositionalEmbedding(nn.Module):
    method __init__ (line 116) | def __init__(
    method get_weights (line 135) | def get_weights(self) -> Tensor:
    method forward (line 155) | def forward(self, seq_len: int, *args, **kwargs) -> Tensor:
    method __repr__ (line 173) | def __repr__(self):

FILE: corenet/modeling/layers/positional_encoding.py
  class SinusoidalPositionalEncoding (line 16) | class SinusoidalPositionalEncoding(BaseLayer):
    method __init__ (line 34) | def __init__(
    method forward_patch_last (line 69) | def forward_patch_last(
    method forward_others (line 84) | def forward_others(
    method forward (line 99) | def forward(self, x, indices: Optional[Tensor] = None, *args, **kwargs...
    method __repr__ (line 105) | def __repr__(self):
  class LearnablePositionEncoding (line 109) | class LearnablePositionEncoding(BaseLayer):
    method __init__ (line 126) | def __init__(
    method forward (line 142) | def forward(self, x, *args, **kwargs) -> Tensor:
    method __repr__ (line 150) | def __repr__(self):

FILE: corenet/modeling/layers/random_layers.py
  class RandomApply (line 15) | class RandomApply(BaseLayer):
    method __init__ (line 24) | def __init__(
    method forward (line 35) | def forward(self, x: Tensor) -> Tensor:
    method __repr__ (line 45) | def __repr__(self):

FILE: corenet/modeling/layers/rotary_embeddings.py
  function _negate_half (line 12) | def _negate_half(x: Tensor) -> Tensor:
  function _apply_rotary_pos_emb (line 26) | def _apply_rotary_pos_emb(x: Tensor, pos_sin: Tensor, pos_cos: Tensor) -...
  class RotaryEmbedding (line 43) | class RotaryEmbedding(torch.nn.Module):
    method __init__ (line 56) | def __init__(
    method extra_repr (line 75) | def extra_repr(self) -> str:
    method _compute_sin_cos_embeddings (line 78) | def _compute_sin_cos_embeddings(
    method forward (line 131) | def forward(

FILE: corenet/modeling/layers/single_head_attention.py
  class SingleHeadAttention (line 17) | class SingleHeadAttention(BaseLayer):
    method __init__ (line 33) | def __init__(
    method __repr__ (line 56) | def __repr__(self) -> str:
    method forward (line 61) | def forward(

FILE: corenet/modeling/layers/softmax.py
  class Softmax (line 11) | class Softmax(nn.Softmax):
    method __init__ (line 23) | def __init__(self, dim: Optional[int] = -1, *args, **kwargs):

FILE: corenet/modeling/layers/stochastic_depth.py
  class StochasticDepth (line 10) | class StochasticDepth(StochasticDepthTorch):
    method __init__ (line 17) | def __init__(self, p: float, mode: str) -> None:

FILE: corenet/modeling/layers/token_merging.py
  class TokenMerging (line 16) | class TokenMerging(nn.Module):
    method __init__ (line 29) | def __init__(self, dim: int, window: int = 2) -> None:
    method forward (line 36) | def forward(
    method extra_repr (line 75) | def extra_repr(self) -> str:
  function pad_x_and_mask (line 79) | def pad_x_and_mask(

FILE: corenet/modeling/layers/upsample.py
  class UpSample (line 12) | class UpSample(nn.Upsample):
    method __init__ (line 29) | def __init__(

FILE: corenet/modeling/matcher_det/__init__.py
  function arguments_box_matcher (line 21) | def arguments_box_matcher(parser: argparse.ArgumentParser):
  function build_matcher (line 34) | def build_matcher(opts, *args, **kwargs):

FILE: corenet/modeling/matcher_det/base_matcher.py
  class BaseMatcher (line 9) | class BaseMatcher(object):
    method __init__ (line 14) | def __init__(self, opts, *args, **kwargs) -> None:
    method add_arguments (line 19) | def add_arguments(cls, parser: argparse.ArgumentParser):
    method __call__ (line 23) | def __call__(self, *args, **kwargs):

FILE: corenet/modeling/matcher_det/ssd_matcher.py
  class SSDMatcher (line 25) | class SSDMatcher(BaseMatcher):
    method __init__ (line 44) | def __init__(self, opts, bg_class_id: Optional[int] = 0, *args, **kwar...
    method __repr__ (line 61) | def __repr__(self):
    method add_arguments (line 70) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method __call__ (line 96) | def __call__(
    method convert_to_boxes (line 131) | def convert_to_boxes(
  function check_variable (line 150) | def check_variable(val, args_str: str):

FILE: corenet/modeling/misc/averaging_utils.py
  class EMA (line 14) | class EMA(object):
    method __init__ (line 24) | def __init__(
    method update_parameters (line 43) | def update_parameters(self, model):
  function arguments_ema (line 58) | def arguments_ema(parser: argparse.ArgumentParser):

FILE: corenet/modeling/misc/box_utils.py
  function convert_locations_to_boxes (line 15) | def convert_locations_to_boxes(
  function convert_boxes_to_locations (line 51) | def convert_boxes_to_locations(
  function center_form_to_corner_form (line 82) | def center_form_to_corner_form(boxes: Tensor) -> Tensor:
  function corner_form_to_center_form (line 103) | def corner_form_to_center_form(boxes: torch.Tensor) -> torch.Tensor:

FILE: corenet/modeling/misc/common.py
  function clean_strip (line 20) | def clean_strip(
  function load_pretrained_model (line 35) | def load_pretrained_model(
  function parameter_list (line 122) | def parameter_list(
  function freeze_module (line 179) | def freeze_module(module: torch.nn.Module, force_eval: bool = True) -> t...
  function freeze_modules_based_on_opts (line 213) | def freeze_modules_based_on_opts(
  function get_tensor_sizes (line 280) | def get_tensor_sizes(data: Union[Dict, Tensor]) -> Union[List[str], List...

FILE: corenet/modeling/misc/init_utils.py
  function _init_nn_layers (line 31) | def _init_nn_layers(
  function initialize_conv_layer (line 79) | def initialize_conv_layer(
  function initialize_fc_layer (line 88) | def initialize_fc_layer(
  function initialize_norm_layers (line 98) | def initialize_norm_layers(module) -> None:
  function initialize_weights (line 110) | def initialize_weights(opts, modules) -> None:

FILE: corenet/modeling/models/__init__.py
  function get_model (line 28) | def get_model(
  function arguments_model (line 86) | def arguments_model(parser: argparse.ArgumentParser) -> argparse.Argumen...

FILE: corenet/modeling/models/audio_classification/audio_byteformer.py
  class AudioByteFormer (line 19) | class AudioByteFormer(ByteFormer, BaseAudioClassification):
    method forward (line 23) | def forward(self, x: Dict[str, Tensor], *args, **kwargs) -> Tensor:
    method dummy_input_and_label (line 38) | def dummy_input_and_label(self, batch_size: int) -> Dict:

FILE: corenet/modeling/models/audio_classification/base_audio_classification.py
  class BaseAudioClassification (line 12) | class BaseAudioClassification(BaseAnyNNModel):
    method __init__ (line 19) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method add_arguments (line 23) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...

FILE: corenet/modeling/models/base_model.py
  class BaseAnyNNModel (line 24) | class BaseAnyNNModel(nn.Module):
    method __init__ (line 27) | def __init__(self, opts, *args, **kwargs) -> None:
    method add_arguments (line 32) | def add_arguments(cls, parser: argparse.ArgumentParser):
    method reset_parameters (line 88) | def reset_parameters(self, opts: argparse.Namespace) -> None:
    method forward (line 92) | def forward(self, x: Any, *args, **kwargs) -> Any:
    method _apply_layer_wise_lr (line 96) | def _apply_layer_wise_lr(
    method get_trainable_parameters (line 111) | def get_trainable_parameters(
    method dummy_input_and_label (line 144) | def dummy_input_and_label(self, batch_size: int) -> Dict:
    method get_exportable_model (line 150) | def get_exportable_model(self) -> nn.Module:
    method freeze_norm_layers (line 159) | def freeze_norm_layers(
    method build_model (line 187) | def build_model(cls, opts: argparse.Namespace, *args, **kwargs) -> Bas...
    method info (line 203) | def info(self) -> None:
    method get_fsdp_wrap_policy (line 279) | def get_fsdp_wrap_policy(self) -> Optional[Callable[[nn.Module, bool, ...
    method get_activation_checkpoint_submodule_class (line 297) | def get_activation_checkpoint_submodule_class(self) -> Callable:

FILE: corenet/modeling/models/classification/base_image_encoder.py
  class BaseImageEncoder (line 21) | class BaseImageEncoder(BaseAnyNNModel):
    method __init__ (line 24) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method n_classes (line 65) | def n_classes(self) -> int:
    method add_arguments (line 75) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method check_model (line 164) | def check_model(self) -> None:
    method update_classifier (line 180) | def update_classifier(self, opts: argparse.Namespace, n_classes: int) ...
    method _forward_layer (line 210) | def _forward_layer(self, layer: nn.Module, x: Tensor) -> Tensor:
    method extract_end_points_all (line 216) | def extract_end_points_all(
    method extract_end_points_l4 (line 265) | def extract_end_points_l4(self, x: Tensor, *args, **kwargs) -> Dict[st...
    method extract_features (line 271) | def extract_features(self, x: Tensor, *args, **kwargs) -> Tensor:
    method forward_classifier (line 286) | def forward_classifier(self, x: Tensor, *args, **kwargs) -> Tensor:
    method forward (line 295) | def forward(self, x: Any, *args, **kwargs) -> Any:
    method get_trainable_parameters (line 313) | def get_trainable_parameters(
    method dummy_input_and_label (line 345) | def dummy_input_and_label(self, batch_size: int) -> Dict:
    method get_exportable_model (line 367) | def get_exportable_model(self) -> nn.Module:
    method build_model (line 377) | def build_model(cls, opts: argparse.Namespace, *args, **kwargs) -> Bas...
  function set_model_specific_opts_before_model_building (line 401) | def set_model_specific_opts_before_model_building(
  function unset_model_specific_opts_after_model_building (line 441) | def unset_model_specific_opts_after_model_building(

FILE: corenet/modeling/models/classification/byteformer.py
  function unfold_tokens (line 27) | def unfold_tokens(t: Tensor, kernel_size: int) -> Tensor:
  class ByteFormer (line 49) | class ByteFormer(BaseAnyNNModel):
    method __init__ (line 54) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method add_arguments (line 169) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method dummy_input_and_label (line 275) | def dummy_input_and_label(self, batch_size: int) -> Dict:
    method apply_token_reduction_net (line 298) | def apply_token_reduction_net(
    method get_backbone_inputs (line 329) | def get_backbone_inputs(self, x: Tensor) -> Tuple[Tensor, Tensor]:
    method backbone_forward (line 357) | def backbone_forward(
    method get_downsampler_name (line 383) | def get_downsampler_name(self, idx: int) -> str:
    method get_downsampler (line 395) | def get_downsampler(self, idx: int) -> Optional[nn.Module]:
    method forward (line 411) | def forward(self, x: Tensor, *args, **kwargs) -> Tensor:
    method build_model (line 434) | def build_model(cls, opts: argparse.Namespace, *args, **kwargs) -> Bas...

FILE: corenet/modeling/models/classification/config/byteformer.py
  function get_configuration (line 11) | def get_configuration(opts: argparse.Namespace) -> Dict:

FILE: corenet/modeling/models/classification/config/efficientnet.py
  class CompoundScalingConfig (line 16) | class CompoundScalingConfig:
  class EfficientNetBlockConfig (line 25) | class EfficientNetBlockConfig:
    method __init__ (line 32) | def __init__(
  function get_configuration (line 51) | def get_configuration(opts) -> Dict:

FILE: corenet/modeling/models/classification/config/fastvit.py
  function get_configuration (line 13) | def get_configuration(opts: argparse.Namespace) -> Dict:

FILE: corenet/modeling/models/classification/config/mobilenetv1.py
  function get_configuration (line 12) | def get_configuration(opts) -> Dict:

FILE: corenet/modeling/models/classification/config/mobilenetv2.py
  function get_configuration (line 9) | def get_configuration(opts) -> Dict:

FILE: corenet/modeling/models/classification/config/mobilenetv3.py
  function get_configuration (line 11) | def get_configuration(opts) -> Dict:

FILE: corenet/modeling/models/classification/config/mobileone.py
  function get_configuration (line 11) | def get_configuration(opts: argparse.Namespace) -> Dict:

FILE: corenet/modeling/models/classification/config/mobilevit.py
  function get_configuration (line 11) | def get_configuration(opts) -> Dict:

FILE: corenet/modeling/models/classification/config/mobilevit_v2.py
  function get_configuration (line 11) | def get_configuration(opts) -> Dict:

FILE: corenet/modeling/models/classification/config/regnet.py
  class BlockParamsConfig (line 44) | class BlockParamsConfig:
    method __init__ (line 63) | def __init__(
    method _make_widths_compatible (line 127) | def _make_widths_compatible(
    method extra_repr (line 160) | def extra_repr(self) -> str:
    method __repr__ (line 171) | def __repr__(self) -> str:
  function get_configuration (line 175) | def get_configuration(

FILE: corenet/modeling/models/classification/config/resnet.py
  function add_squeeze_channels (line 11) | def add_squeeze_channels(
  function get_configuration (line 26) | def get_configuration(opts) -> Dict:

FILE: corenet/modeling/models/classification/config/swin_transformer.py
  function get_configuration (line 11) | def get_configuration(opts) -> Dict:

FILE: corenet/modeling/models/classification/config/vit.py
  function get_configuration (line 12) | def get_configuration(opts: argparse.Namespace) -> Dict:

FILE: corenet/modeling/models/classification/efficientnet.py
  class EfficientNet (line 23) | class EfficientNet(BaseImageEncoder):
    method __init__ (line 28) | def __init__(
    method _make_layer (line 118) | def _make_layer(
    method add_arguments (line 176) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method get_activation_checkpoint_submodule_class (line 190) | def get_activation_checkpoint_submodule_class(self) -> Callable:

FILE: corenet/modeling/models/classification/fastvit.py
  function basic_blocks (line 25) | def basic_blocks(
  class FastViT (line 101) | class FastViT(BaseImageEncoder):
    method __init__ (line 106) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method add_arguments (line 249) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method get_exportable_model (line 290) | def get_exportable_model(self) -> nn.Module:

FILE: corenet/modeling/models/classification/mobilenetv1.py
  class MobileNetv1 (line 26) | class MobileNetv1(BaseImageEncoder):
    method __init__ (line 31) | def __init__(self, opts, *args, **kwargs) -> None:
    method add_arguments (line 130) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method _make_layer (line 142) | def _make_layer(

FILE: corenet/modeling/models/classification/mobilenetv2.py
  class MobileNetV2 (line 20) | class MobileNetV2(BaseImageEncoder):
    method __init__ (line 25) | def __init__(self, opts, *args, **kwargs) -> None:
    method add_arguments (line 148) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method _make_layer (line 158) | def _make_layer(

FILE: corenet/modeling/models/classification/mobilenetv3.py
  class MobileNetV3 (line 21) | class MobileNetV3(BaseImageEncoder):
    method __init__ (line 26) | def __init__(self, opts, *args, **kwargs) -> None:
    method _make_layer (line 164) | def _make_layer(
    method add_arguments (line 207) | def add_arguments(cls, parser: argparse.ArgumentParser):

FILE: corenet/modeling/models/classification/mobileone.py
  class MobileOne (line 18) | class MobileOne(BaseImageEncoder):
    method __init__ (line 23) | def __init__(self, opts, *args, **kwargs) -> None:
    method add_arguments (line 125) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method _make_stage (line 142) | def _make_stage(
    method get_exportable_model (line 201) | def get_exportable_model(self) -> nn.Module:

FILE: corenet/modeling/models/classification/mobilevit.py
  class MobileViT (line 20) | class MobileViT(BaseImageEncoder):
    method __init__ (line 25) | def __init__(self, opts, *args, **kwargs) -> None:
    method add_arguments (line 127) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method _make_layer (line 186) | def _make_layer(
    method _make_mobilenet_layer (line 206) | def _make_mobilenet_layer(
    method _make_mit_layer (line 228) | def _make_mit_layer(
    method get_activation_checkpoint_submodule_class (line 301) | def get_activation_checkpoint_submodule_class(self) -> Callable:

FILE: corenet/modeling/models/classification/mobilevit_v2.py
  class MobileViTv2 (line 20) | class MobileViTv2(BaseImageEncoder):
    method __init__ (line 25) | def __init__(self, opts, *args, **kwargs) -> None:
    method add_arguments (line 104) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method _make_layer (line 138) | def _make_layer(
    method _make_mobilenet_layer (line 152) | def _make_mobilenet_layer(
    method _make_mit_layer (line 174) | def _make_mit_layer(

FILE: corenet/modeling/models/classification/regnet.py
  class RegNet (line 29) | class RegNet(BaseImageEncoder):
    method __init__ (line 34) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method _make_stage (line 134) | def _make_stage(
    method add_arguments (line 167) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...

FILE: corenet/modeling/models/classification/resnet.py
  class ResNet (line 27) | class ResNet(BaseImageEncoder):
    method __init__ (line 37) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method _block_stochastic_depth_prob (line 173) | def _block_stochastic_depth_prob(
    method _make_layer (line 185) | def _make_layer(
    method add_arguments (line 249) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...

FILE: corenet/modeling/models/classification/swin_transformer.py
  class SwinTransformer (line 29) | class SwinTransformer(BaseImageEncoder):
    method __init__ (line 37) | def __init__(self, opts, *args, **kwargs) -> None:
    method extract_end_points_all (line 190) | def extract_end_points_all(
    method add_arguments (line 253) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...

FILE: corenet/modeling/models/classification/vit.py
  class VisionTransformer (line 35) | class VisionTransformer(BaseImageEncoder):
    method __init__ (line 52) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method _build_patch_embedding_layer (line 155) | def _build_patch_embedding_layer(
    method _build_naive_transformer_layer (line 221) | def _build_naive_transformer_layer(
    method _build_transformer_layer_with_flash_attention (line 268) | def _build_transformer_layer_with_flash_attention(
    method update_layer_norm_eps (line 335) | def update_layer_norm_eps(self) -> None:
    method reset_simple_fpn_params (line 341) | def reset_simple_fpn_params(self) -> None:
    method _apply_layer_wise_lr (line 348) | def _apply_layer_wise_lr(
    method _build_simple_fpn_layers (line 481) | def _build_simple_fpn_layers(
    method add_arguments (line 562) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method extract_patch_embeddings (line 621) | def extract_patch_embeddings(self, x: Tensor) -> Tuple[Tensor, Tuple[i...
    method _features_from_transformer (line 660) | def _features_from_transformer(self, x: Tensor) -> Tuple[Tensor, Tuple...
    method extract_features (line 676) | def extract_features(
    method forward_classifier (line 721) | def forward_classifier(
    method forward (line 744) | def forward(
    method extract_end_points_all (line 781) | def extract_end_points_all(
    method get_activation_checkpoint_submodule_class (line 836) | def get_activation_checkpoint_submodule_class(self) -> Callable:
    method get_fsdp_wrap_policy (line 843) | def get_fsdp_wrap_policy(

FILE: corenet/modeling/models/detection/base_detection.py
  class BaseDetection (line 18) | class BaseDetection(BaseAnyNNModel):
    method __init__ (line 26) | def __init__(
    method add_arguments (line 55) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method reset_layer_parameters (line 103) | def reset_layer_parameters(layer: nn.Module, opts: argparse.Namespace)...
    method build_model (line 108) | def build_model(cls, opts: argparse.Namespace, *args, **kwargs) -> Bas...
  function check_feature_map_output_channels (line 126) | def check_feature_map_output_channels(config: Dict, layer_name: str) -> ...

FILE: corenet/modeling/models/detection/mask_rcnn.py
  class MaskRCNNEncoder (line 34) | class MaskRCNNEncoder(nn.Module):
    method __init__ (line 35) | def __init__(
    method get_augmented_tensor (line 122) | def get_augmented_tensor(self) -> Tensor:
    method forward (line 125) | def forward(self, x: Tensor) -> Dict[str, Tensor]:
    method get_trainable_parameters (line 159) | def get_trainable_parameters(
    method get_activation_checkpoint_submodule_class (line 261) | def get_activation_checkpoint_submodule_class(self) -> Callable:
  class MaskRCNNDetector (line 267) | class MaskRCNNDetector(BaseDetection):
    method __init__ (line 275) | def __init__(self, opts, encoder: BaseImageEncoder, *args, **kwargs) -...
    method update_layer_norm_eps (line 495) | def update_layer_norm_eps(self):
    method set_norm_layer_opts (line 500) | def set_norm_layer_opts(self):
    method reset_norm_layer_opts (line 511) | def reset_norm_layer_opts(self, default_norm):
    method add_arguments (line 515) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method reset_generalized_rcnn_transform (line 734) | def reset_generalized_rcnn_transform(self, height, width):
    method get_trainable_parameters (line 737) | def get_trainable_parameters(
    method forward (line 793) | def forward(
    method predict (line 844) | def predict(self, x: Tensor, *args, **kwargs) -> DetectionPredTuple:
    method dummy_input_and_label (line 890) | def dummy_input_and_label(self, batch_size: int) -> Dict:
    method get_activation_checkpoint_submodule_class (line 929) | def get_activation_checkpoint_submodule_class(self) -> Callable:

FILE: corenet/modeling/models/detection/ssd.py
  class SingleShotMaskDetector (line 29) | class SingleShotMaskDetector(BaseDetection):
    method __init__ (line 40) | def __init__(self, opts, encoder: BaseImageEncoder) -> None:
    method add_arguments (line 186) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method reset_layers (line 287) | def reset_layers(module) -> None:
    method process_anchors_ar (line 293) | def process_anchors_ar(anchor_ar: List) -> List:
    method get_backbone_features (line 302) | def get_backbone_features(self, x: Tensor) -> Dict[str, Tensor]:
    method ssd_forward (line 326) | def ssd_forward(
    method forward (line 359) | def forward(
    method predict (line 396) | def predict(self, x: Tensor, *args, **kwargs) -> DetectionPredTuple:
    method postprocess_detections (line 421) | def postprocess_detections(
    method dummy_input_and_label (line 489) | def dummy_input_and_label(self, batch_size: int) -> Dict:

FILE: corenet/modeling/models/detection/utils/rcnn_utils.py
  class FastRCNNConvFCHead (line 22) | class FastRCNNConvFCHead(nn.Sequential):
    method __init__ (line 23) | def __init__(
  class RPNHead (line 75) | class RPNHead(nn.Module):
    method __init__ (line 85) | def __init__(self, opts, in_channels: int, num_anchors: int, conv_dept...
    method forward (line 131) | def forward(self, x: List[Tensor]) -> Tuple[List[Tensor], List[Tensor]]:
  class MaskRCNNHeads (line 141) | class MaskRCNNHeads(nn.Sequential):
    method __init__ (line 142) | def __init__(self, opts, in_channels: int, layers: List, dilation: int):
  class MaskRCNNPredictor (line 181) | class MaskRCNNPredictor(nn.Sequential):
    method __init__ (line 182) | def __init__(
  class FastRCNNPredictor (line 220) | class FastRCNNPredictor(nn.Module):
    method __init__ (line 230) | def __init__(self, in_channels: int, num_classes: int) -> None:
    method forward (line 239) | def forward(self, x: Tensor) -> Tuple[Tensor, Tensor]:
  function replace_syncbn_with_syncbnfp32 (line 252) | def replace_syncbn_with_syncbnfp32(opts, num_features: int) -> nn.Module:

FILE: corenet/modeling/models/fsdp_wrapper.py
  class FullyShardedDataParallelWrapper (line 55) | class FullyShardedDataParallelWrapper(FullyShardedDataParallel):
    method __init__ (line 56) | def __init__(
    method add_arguments (line 131) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
  function get_fsdp_model_optimizer_state_dict_on_rank0 (line 194) | def get_fsdp_model_optimizer_state_dict_on_rank0(

FILE: corenet/modeling/models/language_modeling/base_lm.py
  class BaseLanguageModel (line 16) | class BaseLanguageModel(BaseAnyNNModel):
    method add_arguments (line 24) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method dummy_input_and_label (line 44) | def dummy_input_and_label(self, batch_size: int) -> Dict[str, Tensor]:
    method build_model (line 59) | def build_model(cls, opts: argparse.Namespace, *args, **kwargs) -> Bas...

FILE: corenet/modeling/models/language_modeling/general_gpt.py
  function compute_heads (line 32) | def compute_heads(model_dim: int, head_dim: int) -> int:
  class GPTConfig (line 52) | class GPTConfig:
    method __post_init__ (line 83) | def __post_init__(self) -> None:
    method from_name (line 163) | def from_name(
  class MultiHeadCausalAttention (line 248) | class MultiHeadCausalAttention(nn.Module):
    method __init__ (line 257) | def __init__(
    method extra_repr (line 312) | def extra_repr(self) -> str:
    method forward (line 318) | def forward(
  class FeedForwardNetwork (line 437) | class FeedForwardNetwork(nn.Module):
    method __init__ (line 446) | def __init__(
    method extra_repr (line 488) | def extra_repr(self) -> str:
    method forward (line 491) | def forward(self, x: Tensor) -> Tensor:
  class TransformerDecoderLayer (line 509) | class TransformerDecoderLayer(nn.Module):
    method __init__ (line 518) | def __init__(
    method forward (line 539) | def forward(
  class GeneralGPTModel (line 584) | class GeneralGPTModel(BaseLanguageModel):
    method __init__ (line 593) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method add_arguments (line 655) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method forward (line 686) | def forward(
    method get_fsdp_wrap_policy (line 815) | def get_fsdp_wrap_policy(
    method get_activation_checkpoint_submodule_class (line 825) | def get_activation_checkpoint_submodule_class(self) -> Callable:
    method reset_parameters (line 829) | def reset_parameters(self, model_config: GPTConfig) -> None:
    method head_dim_at_layer (line 861) | def head_dim_at_layer(self, i: int) -> int:
    method k_dim_at_layer (line 864) | def k_dim_at_layer(self, i: int) -> int:
    method v_dim_at_layer (line 867) | def v_dim_at_layer(self, i: int) -> int:
    method k_num_heads_at_layer (line 870) | def k_num_heads_at_layer(self, i: int) -> int:
    method v_num_heads_at_layer (line 873) | def v_num_heads_at_layer(self, i: int) -> int:

FILE: corenet/modeling/models/language_modeling/kv_prediction.py
  class LayerPrunedGPTConfig (line 32) | class LayerPrunedGPTConfig(general_gpt.GPTConfig):
    method __post_init__ (line 35) | def __post_init__(self) -> None:
    method from_name (line 46) | def from_name(
  class LayerPrunedGeneralGPTModel (line 206) | class LayerPrunedGeneralGPTModel(general_gpt.GeneralGPTModel):
  class AuxLayerToBaseLayer (line 216) | class AuxLayerToBaseLayer(nn.Module):
    method __init__ (line 230) | def __init__(self, auxkv_num_layers_to_basekv_num_layers: List[int]) -...
    method forward (line 236) | def forward(
  class LinearAuxKVToBaseKV (line 253) | class LinearAuxKVToBaseKV(nn.Module):
    method __init__ (line 273) | def __init__(
    method forward (line 301) | def forward(
    method set_as_identity (line 347) | def set_as_identity(self) -> None:
  class KVPredicter (line 359) | class KVPredicter(nn.Module):
    method __init__ (line 382) | def __init__(
    method base_layers (line 406) | def base_layers(self) -> int:
    method auxiliary_layers (line 410) | def auxiliary_layers(self) -> int:
    method build_kv_cache_predicters (line 413) | def build_kv_cache_predicters(self) -> None:
    method forward (line 447) | def forward(
  function get_overrided_opts (line 477) | def get_overrided_opts(
  class KVPredictionLLM (line 498) | class KVPredictionLLM(BaseLanguageModel):
    method __init__ (line 505) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method add_arguments (line 562) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method predict_kv_cache (line 584) | def predict_kv_cache(self, auxiliary_outputs: Dict[str, Any]) -> List[...
    method forward (line 610) | def forward(
    method merge_outputs (line 821) | def merge_outputs(self, aux_logits: Tensor, base_logits: Tensor) -> Te...
    method get_fsdp_wrap_policy (line 833) | def get_fsdp_wrap_policy(
    method get_activation_checkpoint_submodule_class (line 839) | def get_activation_checkpoint_submodule_class(self) -> Callable:

FILE: corenet/modeling/models/multi_modal_img_text/base_multi_modal_img_text.py
  class BaseMultiModalImageText (line 12) | class BaseMultiModalImageText(BaseAnyNNModel):
    method __init__ (line 19) | def __init__(self, opts, *args, **kwargs) -> None:
    method add_arguments (line 29) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...

FILE: corenet/modeling/models/multi_modal_img_text/clip.py
  class CLIP (line 28) | class CLIP(BaseMultiModalImageText):
    method __init__ (line 39) | def __init__(
    method add_arguments (line 56) | def add_arguments(cls, parser: argparse.ArgumentParser):
    method reset_parameters (line 68) | def reset_parameters(self) -> None:
    method get_trainable_parameters (line 75) | def get_trainable_parameters(
    method dummy_input_and_label (line 135) | def dummy_input_and_label(
    method _exponentiate_and_clip_logits (line 168) | def _exponentiate_and_clip_logits(self, max_scale: float = 100.0) -> T...
    method _reset_cached_text_features (line 181) | def _reset_cached_text_features(self, mode_str: str) -> None:
    method train (line 194) | def train(self, mode: bool = True):
    method forward (line 207) | def forward(self, input: Dict[str, Optional[Tensor]]) -> Dict[str, Ten...
    method build_model (line 300) | def build_model(cls, opts: argparse.Namespace, *args, **kwargs) -> Bas...
    method get_activation_checkpoint_submodule_class (line 341) | def get_activation_checkpoint_submodule_class(
  function update_image_classifier (line 362) | def update_image_classifier(

FILE: corenet/modeling/models/segmentation/base_seg.py
  class BaseSegmentation (line 16) | class BaseSegmentation(BaseAnyNNModel):
    method __init__ (line 24) | def __init__(self, opts, encoder: BaseImageEncoder, *args, **kwargs) -...
    method add_arguments (line 35) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method maybe_seg_norm_layer (line 150) | def maybe_seg_norm_layer(self):
    method set_default_norm_layer (line 156) | def set_default_norm_layer(self):
    method dummy_input_and_label (line 159) | def dummy_input_and_label(self, batch_size: int) -> Dict:
    method update_classifier (line 175) | def update_classifier(self, opts, n_classes: int) -> None:
    method set_model_specific_opts_before_model_building (line 180) | def set_model_specific_opts_before_model_building(
  function set_model_specific_opts_before_model_building (line 214) | def set_model_specific_opts_before_model_building(
  function unset_model_specific_opts_after_model_building (line 253) | def unset_model_specific_opts_after_model_building(

FILE: corenet/modeling/models/segmentation/enc_dec.py
  class SegEncoderDecoder (line 21) | class SegEncoderDecoder(BaseSegmentation):
    method __init__ (line 31) | def __init__(
    method get_trainable_parameters (line 47) | def get_trainable_parameters(
    method forward (line 95) | def forward(
    method update_classifier (line 113) | def update_classifier(self, opts, n_classes: int) -> None:
    method build_model (line 121) | def build_model(cls, opts: argparse.Namespace, *args, **kwargs) -> Bas...

FILE: corenet/modeling/models/segmentation/heads/base_seg_head.py
  class BaseSegHead (line 19) | class BaseSegHead(BaseAnyNNModel):
    method __init__ (line 24) | def __init__(
    method forward_aux_head (line 93) | def forward_aux_head(self, enc_out: Dict) -> Tensor:
    method forward_seg_head (line 97) | def forward_seg_head(self, enc_out: Dict) -> Tensor:
    method forward (line 100) | def forward(self, enc_out: Dict, *args, **kwargs) -> Union[Tensor, Tup...
    method reset_head_parameters (line 117) | def reset_head_parameters(self, opts) -> None:
    method add_arguments (line 122) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method get_trainable_parameters (line 137) | def get_trainable_parameters(
    method update_classifier (line 153) | def update_classifier(self, opts, n_classes: int) -> None:
    method build_model (line 160) | def build_model(cls, opts: argparse.Namespace, *args, **kwargs) -> Bas...
  function _check_out_channels (line 164) | def _check_out_channels(config: dict, layer_name: str) -> int:

FILE: corenet/modeling/models/segmentation/heads/deeplabv3.py
  class DeeplabV3 (line 22) | class DeeplabV3(BaseSegHead):
    method __init__ (line 51) | def __init__(
    method add_arguments (line 101) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method forward_seg_head (line 135) | def forward_seg_head(self, enc_out: Dict) -> Tensor:
  class MultiScaleDeeplabV3 (line 156) | class MultiScaleDeeplabV3(DeeplabV3):
    method __init__ (line 187) | def __init__(self, opts, enc_conf: Dict, *args, **kwargs) -> None:
    method add_arguments (line 247) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method forward_seg_head (line 267) | def forward_seg_head(self, enc_out: Dict) -> Tensor:

FILE: corenet/modeling/models/segmentation/heads/pspnet.py
  class PSPNet (line 19) | class PSPNet(BaseSegHead):
    method __init__ (line 28) | def __init__(
    method update_classifier (line 63) | def update_classifier(self, opts, n_classes: int) -> None:
    method add_arguments (line 83) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method forward_seg_head (line 106) | def forward_seg_head(self, enc_out: Dict) -> Tensor:

FILE: corenet/modeling/models/segmentation/heads/simple_seg_head.py
  class SimpleSegHead (line 17) | class SimpleSegHead(BaseSegHead):
    method __init__ (line 27) | def __init__(
    method add_arguments (line 51) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method forward_seg_head (line 54) | def forward_seg_head(self, enc_out: Dict) -> Tensor:

FILE: corenet/modeling/models/video_classification/base_video_encoder.py
  class BaseVideoEncoder (line 14) | class BaseVideoEncoder(BaseAnyNNModel):
    method __init__ (line 21) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method add_arguments (line 30) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method reset_module_parameters (line 101) | def reset_module_parameters(opts, module) -> None:

FILE: corenet/modeling/modules/aspp_block.py
  class ASPP (line 24) | class ASPP(BaseModule):
    method __init__ (line 41) | def __init__(
    method forward (line 110) | def forward(self, x: Tensor, *args, **kwargs) -> Tensor:
    method __repr__ (line 119) | def __repr__(self):
  class ASPPConv2d (line 130) | class ASPPConv2d(ConvLayer2d):
    method __init__ (line 144) | def __init__(
    method adjust_atrous_rate (line 158) | def adjust_atrous_rate(self, rate: int) -> None:
  class ASPPSeparableConv2d (line 166) | class ASPPSeparableConv2d(SeparableConv2d):
    method __init__ (line 180) | def __init__(
    method adjust_atrous_rate (line 194) | def adjust_atrous_rate(self, rate: int) -> None:
  class ASPPPooling (line 202) | class ASPPPooling(BaseLayer):
    method __init__ (line 215) | def __init__(
    method forward (line 239) | def forward(self, x: Tensor) -> Tensor:
    method __repr__ (line 245) | def __repr__(self):

FILE: corenet/modeling/modules/base_module.py
  class BaseModule (line 12) | class BaseModule(nn.Module):
    method __init__ (line 15) | def __init__(self, *args, **kwargs):
    method forward (line 18) | def forward(self, x: Any, *args, **kwargs) -> Any:
    method __repr__ (line 21) | def __repr__(self):

FILE: corenet/modeling/modules/efficientnet.py
  class EfficientNetBlock (line 12) | class EfficientNetBlock(InvertedResidualSE):
    method __init__ (line 27) | def __init__(self, stochastic_depth_prob: float, *args, **kwargs) -> N...
    method forward (line 31) | def forward(self, x: Tensor, *args, **kwargs) -> Tensor:
    method __repr__ (line 40) | def __repr__(self) -> str:

FILE: corenet/modeling/modules/fastvit.py
  function convolutional_stem (line 17) | def convolutional_stem(
  class PatchEmbed (line 72) | class PatchEmbed(BaseModule):
    method __init__ (line 84) | def __init__(
    method forward (line 124) | def forward(self, x: torch.Tensor, *args, **kwargs) -> torch.Tensor:
  class RepMixer (line 139) | class RepMixer(BaseModule):
    method __init__ (line 155) | def __init__(
    method forward (line 205) | def forward(self, x: torch.Tensor, *args, **kwargs) -> torch.Tensor:
    method reparameterize (line 226) | def reparameterize(self) -> None:
  class ConvFFN (line 267) | class ConvFFN(BaseModule):
    method __init__ (line 279) | def __init__(
    method forward (line 314) | def forward(self, x: torch.Tensor, *args, **kwargs) -> torch.Tensor:
  class RepMixerBlock (line 332) | class RepMixerBlock(BaseModule):
    method __init__ (line 350) | def __init__(
    method forward (line 390) | def forward(self, x: torch.Tensor, *args, **kwargs) -> torch.Tensor:
  class AttentionBlock (line 409) | class AttentionBlock(BaseModule):
    method __init__ (line 425) | def __init__(
    method _apply_mhsa (line 464) | def _apply_mhsa(self, x: torch.Tensor) -> torch.Tensor:
    method forward (line 483) | def forward(self, x: torch.Tensor, *args, **kwargs) -> torch.Tensor:
  class RepCPE (line 502) | class RepCPE(BaseModule):
    method __init__ (line 516) | def __init__(
    method forward (line 565) | def forward(self, x: torch.Tensor, *args, **kwargs) -> torch.Tensor:
    method reparameterize (line 583) | def reparameterize(self) -> None:

FILE: corenet/modeling/modules/feature_pyramid.py
  class FeaturePyramidNetwork (line 21) | class FeaturePyramidNetwork(BaseModule):
    method __init__ (line 33) | def __init__(
    method reset_weights (line 91) | def reset_weights(self) -> None:
    method forward (line 99) | def forward(self, x: Dict[str, Tensor], *args, **kwargs) -> Dict[str, ...
    method __repr__ (line 127) | def __repr__(self):

FILE: corenet/modeling/modules/flash_transformer.py
  class FlashTransformerEncoder (line 24) | class FlashTransformerEncoder(BaseModule):
    method __init__ (line 51) | def __init__(
    method forward (line 108) | def forward(self, x: Tensor) -> Tensor:

FILE: corenet/modeling/modules/mobilenetv2.py
  class InvertedResidualSE (line 16) | class InvertedResidualSE(BaseModule):
    method __init__ (line 39) | def __init__(
    method forward (line 123) | def forward(self, x: Tensor, *args, **kwargs) -> Tensor:
    method __repr__ (line 127) | def __repr__(self) -> str:
  class InvertedResidual (line 141) | class InvertedResidual(BaseModule):
    method __init__ (line 163) | def __init__(
    method forward (line 231) | def forward(self, x: Tensor, *args, **kwargs) -> Tensor:
    method __repr__ (line 237) | def __repr__(self) -> str:

FILE: corenet/modeling/modules/mobileone_block.py
  class MobileOneBlock (line 17) | class MobileOneBlock(BaseModule):
    method __init__ (line 25) | def __init__(
    method forward (line 137) | def forward(self, x: torch.Tensor, *args, **kwargs) -> torch.Tensor:
    method reparameterize (line 171) | def reparameterize(self) -> None:
    method _get_kernel_bias (line 207) | def _get_kernel_bias(self) -> Tuple[torch.Tensor, torch.Tensor]:
    method _fuse_branch_ops (line 243) | def _fuse_branch_ops(
    method _fuse_conv_bn (line 277) | def _fuse_conv_bn(
  class RepLKBlock (line 304) | class RepLKBlock(BaseModule):
    method __init__ (line 322) | def __init__(
    method forward (line 390) | def forward(self, x: torch.Tensor, *args, **kwargs) -> torch.Tensor:
    method _get_kernel_bias (line 411) | def _get_kernel_bias(self) -> Tuple[torch.Tensor, torch.Tensor]:
    method reparameterize (line 433) | def reparameterize(self) -> None:

FILE: corenet/modeling/modules/mobilevit_block.py
  class MobileViTBlock (line 19) | class MobileViTBlock(BaseModule):
    method __init__ (line 41) | def __init__(
    method __repr__ (line 150) | def __repr__(self) -> str:
    method unfolding (line 186) | def unfolding(self, feature_map: Tensor) -> Tuple[Tensor, Dict]:
    method folding (line 233) | def folding(self, patches: Tensor, info_dict: Dict) -> Tensor:
    method forward_spatial (line 269) | def forward_spatial(self, x: Tensor) -> Tensor:
    method forward_temporal (line 290) | def forward_temporal(
    method forward (line 316) | def forward(
  class MobileViTBlockv2 (line 329) | class MobileViTBlockv2(BaseModule):
    method __init__ (line 349) | def __init__(
    method _compute_unfolding_weights (line 438) | def _compute_unfolding_weights(self) -> Tensor:
    method _build_attn_layer (line 449) | def _build_attn_layer(
    method __repr__ (line 497) | def __repr__(self) -> str:
    method unfolding_pytorch (line 526) | def unfolding_pytorch(self, feature_map: Tensor) -> Tuple[Tensor, Tupl...
    method folding_pytorch (line 542) | def folding_pytorch(self, patches: Tensor, output_size: Tuple[int, int...
    method unfolding_coreml (line 557) | def unfolding_coreml(self, feature_map: Tensor) -> Tuple[Tensor, Tuple...
    method folding_coreml (line 578) | def folding_coreml(self, patches: Tensor, output_size: Tuple[int, int]...
    method resize_input_if_needed (line 595) | def resize_input_if_needed(self, x):
    method forward_spatial (line 605) | def forward_spatial(self, x: Tensor, *args, **kwargs) -> Tensor:
    method forward_temporal (line 628) | def forward_temporal(
    method forward (line 657) | def forward(

FILE: corenet/modeling/modules/pspnet_module.py
  class PSP (line 17) | class PSP(BaseModule):
    method __init__ (line 29) | def __init__(
    method _make_psp_layer (line 78) | def _make_psp_layer(
    method forward (line 94) | def forward(self, x: Tensor, *args, **kwargs) -> Tensor:
    method __repr__ (line 106) | def __repr__(self):

FILE: corenet/modeling/modules/regnet_modules.py
  class XRegNetBlock (line 16) | class XRegNetBlock(BaseModule):
    method __init__ (line 34) | def __init__(
    method forward (line 131) | def forward(self, x: Tensor) -> Tensor:
    method __repr__ (line 151) | def __repr__(self) -> str:
  class AnyRegNetStage (line 164) | class AnyRegNetStage(BaseModule):
    method __init__ (line 185) | def __init__(
    method forward (line 227) | def forward(self, x: Tensor) -> Tensor:
    method __repr__ (line 242) | def __repr__(self) -> str:

FILE: corenet/modeling/modules/resnet_modules.py
  class BasicResNetBlock (line 16) | class BasicResNetBlock(BaseModule):
    method __init__ (line 39) | def __init__(
    method forward (line 129) | def forward(self, x: Tensor, *args, **kwargs) -> Tensor:
    method __repr__ (line 137) | def __repr__(self) -> str:
  class BottleneckResNetBlock (line 150) | class BottleneckResNetBlock(BaseModule):
    method __init__ (line 172) | def __init__(
    method forward (line 279) | def forward(self, x: Tensor, *args, **kwargs) -> Tensor:
    method __repr__ (line 287) | def __repr__(self) -> str:

FILE: corenet/modeling/modules/squeeze_excitation.py
  class SqueezeExcitation (line 17) | class SqueezeExcitation(BaseModule):
    method __init__ (line 33) | def __init__(
    method forward (line 80) | def forward(self, x: Tensor, *args, **kwargs) -> Tensor:
    method __repr__ (line 83) | def __repr__(self) -> str:

FILE: corenet/modeling/modules/ssd_heads.py
  class SSDHead (line 17) | class SSDHead(BaseModule):
    method __init__ (line 34) | def __init__(
    method __repr__ (line 91) | def __repr__(self) -> str:
    method reset_parameters (line 107) | def reset_parameters(self) -> None:
    method _sample_fm (line 112) | def _sample_fm(self, x: Tensor) -> Tensor:
    method forward (line 135) | def forward(self, x: Tensor, *args, **kwargs) -> Tuple[Tensor, Tensor]:
  class SSDInstanceHead (line 159) | class SSDInstanceHead(BaseModule):
    method __init__ (line 164) | def __init__(
    method __repr__ (line 224) | def __repr__(self) -> str:
    method reset_parameters (line 232) | def reset_parameters(self) -> None:
    method forward (line 237) | def forward(self, x: Tensor, boxes: Tensor, *args, **kwargs) -> Tensor:

FILE: corenet/modeling/modules/swin_transformer_block.py
  function _patch_merging_pad (line 26) | def _patch_merging_pad(x):
  class Permute (line 32) | class Permute(BaseModule):
    method __init__ (line 38) | def __init__(self, dims: List[int]):
    method forward (line 42) | def forward(self, x: Tensor) -> Tensor:
    method __repr__ (line 45) | def __repr__(self) -> str:
  class PatchMerging (line 50) | class PatchMerging(BaseModule):
    method __init__ (line 58) | def __init__(self, opts, dim: int, norm_layer: str, strided: Optional[...
    method forward (line 69) | def forward(self, x: Tensor, *args, **kwargs) -> Tensor:
    method __repr__ (line 91) | def __repr__(self) -> str:
  function shifted_window_attention (line 96) | def shifted_window_attention(
  class ShiftedWindowAttention (line 234) | class ShiftedWindowAttention(BaseModule):
    method __init__ (line 239) | def __init__(
    method __repr__ (line 290) | def __repr__(self) -> str:
    method forward (line 301) | def forward(self, x: Tensor, *args, **kwargs) -> Tensor:
  class SwinTransformerBlock (line 331) | class SwinTransformerBlock(BaseModule):
    method __init__ (line 347) | def __init__(
    method __repr__ (line 400) | def __repr__(self) -> str:
    method forward (line 412) | def forward(self, x: Tensor, *args, **kwargs) -> Tensor:

FILE: corenet/modeling/modules/transformer.py
  class TransformerEncoder (line 26) | class TransformerEncoder(BaseModule):
    method __init__ (line 46) | def __init__(
    method __repr__ (line 116) | def __repr__(self) -> str:
    method forward (line 129) | def forward(
  class LinearAttnFFN (line 159) | class LinearAttnFFN(BaseModule):
    method __init__ (line 177) | def __init__(
    method __repr__ (line 237) | def __repr__(self) -> str:
    method forward (line 248) | def forward(

FILE: corenet/modeling/modules/windowed_transformer.py
  function window_partition (line 16) | def window_partition(t: torch.Tensor, window_size: int) -> torch.Tensor:
  function window_partition_reverse (line 41) | def window_partition_reverse(
  function get_windows_shift_mask (line 61) | def get_windows_shift_mask(
  function window_x_and_key_padding_mask (line 90) | def window_x_and_key_padding_mask(
  function unwindow_x (line 135) | def unwindow_x(x_windows: torch.Tensor, B: int, N: int, C: int, window_s...
  class WindowedTransformerEncoder (line 162) | class WindowedTransformerEncoder(transformer.TransformerEncoder):
    method __init__ (line 190) | def __init__(
    method forward (line 224) | def forward(
    method __repr__ (line 270) | def __repr__(self) -> str:

FILE: corenet/modeling/neural_augmentor/__init__.py
  function arguments_neural_augmentor (line 13) | def arguments_neural_augmentor(

FILE: corenet/modeling/neural_augmentor/neural_aug.py
  class BaseNeuralAugmentor (line 27) | class BaseNeuralAugmentor(nn.Module):
    method __init__ (line 32) | def __init__(self, opts, *args, **kwargs):
    method _is_valid_aug_fn_list (line 48) | def _is_valid_aug_fn_list(self, aug_fns):
    method get_trainable_parameters (line 57) | def get_trainable_parameters(
    method __repr__ (line 72) | def __repr__(self):
    method add_arguments (line 101) | def add_arguments(cls, parser: argparse.ArgumentParser):
    method _build_aug_fns (line 141) | def _build_aug_fns(self, opts) -> List:
    method _apply_brightness (line 144) | def _apply_brightness(self, x: Tensor, *args, **kwargs) -> Tensor:
    method _apply_contrast (line 161) | def _apply_contrast(self, x: Tensor, *args, **kwargs) -> Tensor:
    method _apply_noise (line 179) | def _apply_noise(self, x: Tensor, *args, **kwargs) -> Tensor:
    method forward (line 194) | def forward(self, x: Tensor, *args, **kwargs) -> Tensor:
  class BasicNeuralAugmentor (line 219) | class BasicNeuralAugmentor(BaseNeuralAugmentor):
    method __init__ (line 227) | def __init__(self, opts, *args, **kwargs) -> None:
    method _build_aug_fns (line 235) | def _build_aug_fns(self, opts) -> List:
  class DistributionNeuralAugmentor (line 256) | class DistributionNeuralAugmentor(BaseNeuralAugmentor):
    method __init__ (line 264) | def __init__(self, opts, *args, **kwargs) -> None:
    method _build_aug_fns_with_uniform_dist (line 271) | def _build_aug_fns_with_uniform_dist(self, opts) -> List:
  function build_neural_augmentor (line 304) | def build_neural_augmentor(opts, *args, **kwargs):

FILE: corenet/modeling/neural_augmentor/utils/neural_aug_utils.py
  class Clip (line 12) | class Clip(nn.Module):
    method __init__ (line 13) | def __init__(
    method forward (line 26) | def forward(self, x: Any) -> Any:
    method __repr__ (line 33) | def __repr__(self):
  class Identity (line 42) | class Identity(nn.Module):
    method __init__ (line 43) | def __init__(self, *args, **kwargs):
    method forward (line 46) | def forward(self, x: Any) -> Any:
  class FixedSampler (line 50) | class FixedSampler(nn.Module):
    method __init__ (line 51) | def __init__(
    method forward (line 62) | def forward(
    method __repr__ (line 68) | def __repr__(self):
  class UniformSampler (line 75) | class UniformSampler(nn.Module):
    method __init__ (line 76) | def __init__(
    method forward (line 91) | def forward(
    method high (line 99) | def high(self):
    method low (line 103) | def low(self):
    method __repr__ (line 106) | def __repr__(self):
  function random_noise (line 114) | def random_noise(x: Tensor, variance: Tensor, *args, **kwargs) -> Tensor:
  function random_contrast (line 121) | def random_contrast(x: Tensor, magnitude: Tensor, *args, **kwargs) -> Te...
  function random_brightness (line 131) | def random_brightness(x: Tensor, magnitude: Tensor, *args, **kwargs) -> ...
  function identity (line 139) | def identity(x: Tensor, *args, **kwargs) -> Tensor:

FILE: corenet/modeling/text_encoders/__init__.py
  function arguments_text_encoder (line 20) | def arguments_text_encoder(parser: argparse.ArgumentParser) -> argparse....
  function build_text_encoder (line 30) | def build_text_encoder(opts, projection_dim: int, *args, **kwargs) -> Ba...

FILE: corenet/modeling/text_encoders/base_text_encoder.py
  class BaseTextEncoder (line 18) | class BaseTextEncoder(nn.Module):
    method __init__ (line 21) | def __init__(self, opts, projection_dim: int, *args, **kwargs) -> None:
    method vocab_size (line 29) | def vocab_size(self):
    method context_length (line 37) | def context_length(self):
    method add_arguments (line 45) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method padding_index (line 79) | def padding_index(self) -> int:
    method reset_parameters (line 87) | def reset_parameters(self):
    method get_trainable_parameters (line 91) | def get_trainable_parameters(
    method freeze_norm_layers (line 108) | def freeze_norm_layers(self) -> None:
    method forward (line 116) | def forward(
    method dummy_input_and_label (line 126) | def dummy_input_and_label(self, batch_size: int) -> Dict:
    method get_activation_checkpoint_submodule_class (line 137) | def get_activation_checkpoint_submodule_class(self) -> Callable:

FILE: corenet/modeling/text_encoders/transformer.py
  class TextTransformer (line 25) | class TextTransformer(BaseTextEncoder):
    method __init__ (line 33) | def __init__(self, opts, projection_dim: int, *args, **kwargs) -> None:
    method build_causal_attention_mask (line 159) | def build_causal_attention_mask(
    method reset_parameters_clip_style (line 194) | def reset_parameters_clip_style(self) -> None:
    method add_arguments (line 222) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method forward_embedding (line 326) | def forward_embedding(self, text_tokens: Tensor) -> Tensor:
    method encode_text (line 345) | def encode_text(
    method forward_zero_shot (line 395) | def forward_zero_shot(
    method forward (line 479) | def forward(
    method get_activation_checkpoint_submodule_class (line 543) | def get_activation_checkpoint_submodule_class(self) -> Callable:

FILE: corenet/optims/__init__.py
  function check_trainable_parameters (line 24) | def check_trainable_parameters(
  function remove_param_name_key (line 86) | def remove_param_name_key(model_params: List) -> None:
  function build_optimizer (line 115) | def build_optimizer(model: torch.nn.Module, opts, *args, **kwargs) -> Ba...
  function arguments_optimizer (line 150) | def arguments_optimizer(parser: argparse.ArgumentParser) -> argparse.Arg...

FILE: corenet/optims/adam.py
  class AdamOptimizer (line 17) | class AdamOptimizer(BaseOptim, Adam):
    method __init__ (line 26) | def __init__(
    method add_arguments (line 49) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...

FILE: corenet/optims/adamw.py
  class AdamWOptimizer (line 17) | class AdamWOptimizer(BaseOptim, AdamW):
    method __init__ (line 26) | def __init__(
    method add_arguments (line 49) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...

FILE: corenet/optims/base_optim.py
  class BaseOptim (line 11) | class BaseOptim(object):
    method __init__ (line 18) | def __init__(self, opts: argparse.Namespace, *args, **kwargs) -> None:
    method add_arguments (line 24) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method __repr__ (line 64) | def __repr__(self) -> str:

FILE: corenet/optims/scheduler/__init__.py
  function build_scheduler (line 20) | def build_scheduler(opts: argparse.Namespace, *args, **kwargs) -> BaseLR...
  function general_lr_sch_args (line 33) | def general_lr_sch_args(parser: argparse.ArgumentParser) -> argparse.Arg...
  function arguments_scheduler (line 78) | def arguments_scheduler(parser: argparse.ArgumentParser) -> argparse.Arg...

FILE: corenet/optims/scheduler/base_scheduler.py
  class BaseLRScheduler (line 11) | class BaseLRScheduler(object):
    method __init__ (line 12) | def __init__(self, opts) -> None:
    method add_arguments (line 34) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method get_lr (line 37) | def get_lr(self, epoch: int, curr_iter: int):
    method update_lr (line 40) | def update_lr(self, optimizer, epoch: int, curr_iter: int):
    method retrieve_lr (line 55) | def retrieve_lr(optimizer) -> list:
    method extra_repr (line 61) | def extra_repr(self) -> str:
    method __repr__ (line 66) | def __repr__(self) -> str:

FILE: corenet/optims/scheduler/cosine.py
  class CosineScheduler (line 14) | class CosineScheduler(BaseLRScheduler):
    method __init__ (line 19) | def __init__(self, opts, **kwargs) -> None:
    method add_arguments (line 42) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method get_lr (line 61) | def get_lr(self, epoch: int, curr_iter: int) -> float:
    method __repr__ (line 82) | def __repr__(self) -> str:

FILE: corenet/optims/scheduler/cyclic.py
  class CyclicLRScheduler (line 19) | class CyclicLRScheduler(BaseLRScheduler):
    method __init__ (line 24) | def __init__(self, opts, **kwargs) -> None:
    method _lr_per_cycle (line 77) | def _lr_per_cycle(self) -> None:
    method add_arguments (line 85) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method get_lr (line 135) | def get_lr(self, epoch: int, curr_iter: int) -> float:
    method __repr__ (line 162) | def __repr__(self):

FILE: corenet/optims/scheduler/fixed.py
  class FixedLRScheduler (line 13) | class FixedLRScheduler(BaseLRScheduler):
    method __init__ (line 18) | def __init__(self, opts, **kwargs) -> None:
    method add_arguments (line 41) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method get_lr (line 52) | def get_lr(self, epoch: int, curr_iter: int) -> float:
    method __repr__ (line 59) | def __repr__(self) -> str:

FILE: corenet/optims/scheduler/multi_step.py
  class MultiStepLRScheduler (line 13) | class MultiStepLRScheduler(BaseLRScheduler):
    method __init__ (line 18) | def __init__(self, opts, **kwargs) -> None:
    method add_arguments (line 50) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method get_lr (line 74) | def get_lr(self, epoch: int, curr_iter: int) -> float:
    method __repr__ (line 83) | def __repr__(self) -> str:

FILE: corenet/optims/scheduler/polynomial.py
  class PolynomialScheduler (line 13) | class PolynomialScheduler(BaseLRScheduler):
    method __init__ (line 18) | def __init__(self, opts, **kwargs) -> None:
    method add_arguments (line 39) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method get_lr (line 65) | def get_lr(self, epoch: int, curr_iter: int) -> float:
    method __repr__ (line 81) | def __repr__(self) -> str:

FILE: corenet/optims/sgd.py
  class SGDOptimizer (line 17) | class SGDOptimizer(BaseOptim, SGD):
    method __init__ (line 26) | def __init__(
    method add_arguments (line 47) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...

FILE: corenet/options/errors.py
  class UnrecognizedYamlConfigEntry (line 9) | class UnrecognizedYamlConfigEntry(Warning):
    method __init__ (line 11) | def __init__(self, key: str) -> None:

FILE: corenet/options/opts.py
  class ParseKwargs (line 29) | class ParseKwargs(argparse.Action):
    method __call__ (line 30) | def __call__(self, parser, namespace, values, option_string=None):
  function arguments_common (line 77) | def arguments_common(parser: argparse.ArgumentParser) -> argparse.Argume...
  function arguments_ddp (line 255) | def arguments_ddp(parser: argparse.ArgumentParser) -> argparse.ArgumentP...
  function arguments_train_eval_pipeline (line 302) | def arguments_train_eval_pipeline(
  function arguments_lm_eval (line 318) | def arguments_lm_eval(parser: argparse.ArgumentParser) -> argparse.Argum...
  function parser_to_opts (line 389) | def parser_to_opts(parser: argparse.ArgumentParser, args: Optional[List[...
  function get_training_arguments (line 396) | def get_training_arguments(
  function get_lm_eval_arguments (line 475) | def get_lm_eval_arguments(
  function get_conversion_arguments (line 490) | def get_conversion_arguments(args: Optional[List[str]] = None):
  function get_benchmarking_arguments (line 540) | def get_benchmarking_arguments(args: Optional[List[str]] = None):

FILE: corenet/options/parse_args.py
  function parse_validation_metric_names (line 10) | def parse_validation_metric_names(opts):
  class JsonValidator (line 48) | class JsonValidator:
    method __init__ (line 49) | def __init__(self, expected_type: type):
    method _validate_and_cast (line 64) | def _validate_and_cast(cls, json_value: Any, expected_type: Any):
    method __call__ (line 114) | def __call__(self, str_value: str) -> Any:
    method __repr__ (line 121) | def __repr__(self):

FILE: corenet/options/utils.py
  function flatten_yaml_as_dict (line 38) | def flatten_yaml_as_dict(d, parent_key="", sep="."):
  function load_config_file (line 49) | def load_config_file(opts):
  function extend_selected_args_with_prefix (line 107) | def extend_selected_args_with_prefix(
  function extract_opts_with_prefix_replacement (line 157) | def extract_opts_with_prefix_replacement(

FILE: corenet/third_party/data/text_tokenizer/openai_clip_tokenizer.py
  function bytes_to_unicode (line 21) | def bytes_to_unicode() -> Dict[int, str]:
  function get_pairs (line 47) | def get_pairs(word: Tuple[str, ...]) -> Set[Tuple[str, str]]:
  class OpenAIClipTokenizer (line 60) | class OpenAIClipTokenizer(BaseTextTokenizer):
    method __init__ (line 84) | def __init__(self, opts: argparse.Namespace) -> None:
    method add_arguments (line 133) | def add_arguments(cls, parser: argparse.ArgumentParser) -> argparse.Ar...
    method vocab_size (line 149) | def vocab_size(self) -> int:
    method eot_token (line 154) | def eot_token(self) -> str:
    method eot_token_id (line 159) | def eot_token_id(self) -> int:
    method sot_token (line 164) | def sot_token(self) -> str:
    method sot_token_id (line 169) | def sot_token_id(self) -> int:
    method pad_token_id (line 174) | def pad_token_id(self) -> int:
    method _bpe (line 178) | def _bpe(self, token: str) -> str:
    method tok_encode (line 227) | def tok_encode(self, input_sentence: str) -> Tensor:
    method tok_decode (line 254) | def tok_decode(self, token_ids: Union[List[int], Tensor]) -> str:

FILE: corenet/third_party/modeling/lora.py
  function check_adapters_to_merge (line 27) | def check_adapters_to_merge(
  class BaseTunerLayer (line 61) | class BaseTunerLayer(ABC):
    method get_base_layer (line 88) | def get_base_layer(self) -> nn.Module:
    method weight (line 103) | def weight(self) -> torch.Tensor:
    method bias (line 113) | def bias(self) -> torch.Tensor:
    method merge (line 122) | def merge(
    method unmerge (line 137) | def unmerge(self) -> None:
    method merged (line 144) | def merged(self) -> bool:
    method disable_adapters (line 154) | def disable_adapters(self) -> bool:
    method active_adapter (line 166) | def active_adapter(self) -> Union[List[str], str]:
    method active_adapters (line 178) | def active_adapters(self) -> List[str]:
    method enable_adapters (line 190) | def enable_adapters(self, enabled: bool) -> None:
    method set_adapter (line 208) | def set_adapter(self, adapter_names: Union[str, List[str]]) -> None:
    method _all_available_adapter_names (line 239) | def _all_available_adapter_names(self) -> List[str]:
    method delete_adapter (line 255) | def delete_adapter(self, adapter_name: str) -> None:
  class LoraLayer (line 293) | class LoraLayer(BaseTunerLayer):
    method __init__ (line 309) | def __init__(self, base_layer: nn.Module) -> None:
    method update_layer (line 342) | def update_layer(
    method reset_lora_parameters (line 365) | def reset_lora_parameters(
    method _get_weight_norm (line 395) | def _get_weight_norm(
    method dora_init (line 419) | def dora_init(self, adapter_name: str) -> None:
    method _cache_store (line 446) | def _cache_store(self, key: str, value: Any) -> None:
    method _cache_pop (line 456) | def _cache_pop(self, key: str) -> Any:
    method _apply_dora (line 469) | def _apply_dora(
    method set_scale (line 515) | def set_scale(self, adapter: str, scale: float) -> None:
    method scale_layer (line 529) | def scale_layer(self, scale: float) -> None:
    method unscale_layer (line 543) | def unscale_layer(self, scale: float = None) -> None:
    method _check_forward_args (line 561) | def _check_forward_args(
    method _mixed_batch_forward (line 595) | def _mixed_batch_forward(
  class Linear (line 642) | class Linear(nn.Module, LoraLayer):
    method __init__ (line 658) | def __init__(
    method update_layer (line 683) | def update_layer(
    method merge (line 740) | def merge(
    method unmerge (line 815) | def unmerge(self) -> None:
    method get_delta_weight (line 837) | def get_delta_weight(self, adapter: str) -> torch.Tensor:
    method forward (line 875) | def forward(
    method __repr__ (line 923) | def __repr__(self) -> str:
  class Embedding (line 934) | class Embedding(nn.Module, LoraLayer):
    method __init__ (line 950) | def __init__(
    method update_layer (line 979) | def update_layer(
    method merge (line 1034) | def merge(
    method unmerge (line 1074) | def unmerge(self) -> None:
    method get_delta_weight (line 1088) | def get_delta_weight(self, adapter: str) -> torch.Tensor:
    method _mixed_batch_forward (line 1126) | def _mixed_batch_forward(
    method _embed (line 1172) | def _embed(self, input: torch.Tensor, weight: torch.Tensor) -> torch.T...
    method forward (line 1193) | def forward(
    method __repr__ (line 1234) | def __repr__(self) -> str:
  class LoRAParams (line 1246) | class LoRAParams:
    method from_json (line 1270) | def from_json(cls, config: Dict[str, Any]) -> LayerConfig:
    method to_json (line 1282) | def to_json(self) -> Dict[str, Any]:
  class LayerConfig (line 1293) | class LayerConfig:
    method from_json (line 1309) | def from_json(cls, config: Dict[str, Any]) -> LayerConfig:
  class LoRAConfig (line 1327) | class LoRAConfig:
    method from_json (line 1338) | def from_json(cls, config: Dict[str, Any]) -> LoRAConfig:
  function make_lora_layer (line 1355) | def make_lora_layer(module: nn.Module, layer_config: LoRAConfig) -> Lora...
  function get_module_to_parents (line 1371) | def get_module_to_parents(
  function add_lora_layers (line 1395) | def add_lora_layers(model: nn.Module, lora_config: Dict[str, Any]) -> None:

FILE: corenet/third_party/modeling/ssd_utils.py
  function assign_priors (line 22) | def assign_priors(
  function box_iou (line 70) | def box_iou(
  function hard_negative_mining (line 105) | def hard_negative_mining(

FILE: corenet/train_eval_pipelines/base.py
  function Callback (line 14) | def Callback(Protocol):
  class BaseTrainEvalPipeline (line 18) | class BaseTrainEvalPipeline:
    method __init__ (line 19) | def __init__(
    method __init_subclass__ (line 38) | def __init_subclass__(cls) -> None:
    method __getstate__ (line 50) | def __getstate__(self) -> argparse.Namespace:
    method __setstate__ (line 53) | def __setstate__(self, opts: argparse.Namespace) -> None:
    method evaluation_engine (line 57) | def evaluation_engine(self) -> Evaluator:
    method training_engine (line 62) | def training_engine(self) -> DefaultTrainer:
    method launcher (line 67) | def launcher(self) -> Callable[[Callback], None]:

FILE: corenet/train_eval_pipelines/default_train_eval.py
  class DefaultTrainEvalPipeline (line 48) | class DefaultTrainEvalPipeline(BaseTrainEvalPipeline):
    method is_master_node (line 64) | def is_master_node(self) -> bool:
    method device (line 76) | def device(self) -> torch.device:
    method _train_val_loader_sampler (line 80) | def _train_val_loader_sampler(
    method train_val_loader (line 90) | def train_val_loader(self) -> Tuple[CoreNetDataLoader, CoreNetDataLoad...
    method train_sampler (line 98) | def train_sampler(self) -> BaseSampler:
    method test_loader (line 106) | def test_loader(self) -> CoreNetDataLoader:
    method scheduler (line 111) | def scheduler(self) -> BaseLRScheduler:
    method _prepare_model (line 140) | def _prepare_model(self) -> Tuple[BaseAnyNNModel, Optional[torch.nn.Mo...
    method model (line 174) | def model(self) -> torch.nn.Module:
    method criteria (line 212) | def criteria(self) -> BaseCriteria:
    method optimizer (line 224) | def optimizer(self) -> BaseOptim:
    method gradient_scaler (line 236) | def gradient_scaler(self) -> GradScaler:
    method launcher (line 245) | def launcher(self) -> Callable[[Callback], None]:
    method model_ema (line 317) | def model_ema(self) -> Optional[EMA]:
    method training_engine (line 334) | def training_engine(self) -> DefaultTrainer:
    method evaluation_engine (line 395) | def evaluation_engine(self) -> Evaluator:
    method _launcher_distributed_spawn_fn (line 405) | def _launcher_distributed_spawn_fn(

FILE: corenet/train_eval_pipelines/fsdp_train_eval.py
  class FSDPTrainEvalPipeline (line 26) | class FSDPTrainEvalPipeline(DefaultTrainEvalPipeline):
    method gradient_scaler (line 35) | def gradient_scaler(self) -> GradScaler:
    method model (line 41) | def model(self) -> torch.nn.Module:
    method training_engine (line 57) | def training_engine(self) -> FSDPTrainer:

FILE: corenet/utils/activation_checkpointing_wrapper.py
  function activation_checkpointing (line 13) | def activation_checkpointing(

FILE: corenet/utils/check.py
  function check (line 12) | def check(

FILE: corenet/utils/checkpoint_utils.py
  function get_model_optimizer_state_dict (line 28) | def get_model_optimizer_state_dict(
  function load_state_dict (line 52) | def load_state_dict(
  function average_ckpts (line 73) | def average_ckpts(ckpt_loc_list: List[str]) -> Dict[str, Any]:
  function avg_and_save_k_checkpoints (line 105) | def avg_and_save_k_checkpoints(
  function get_training_state (line 169) | def get_training_state(
  function save_checkpoint (line 221) | def save_checkpoint(
  function load_checkpoint (line 366) | def load_checkpoint(
  function load_model_state (line 463) | def load_model_state(

FILE: corenet/utils/color_map.py
  class Colormap (line 11) | class Colormap(object):
    method __init__ (line 19) | def __init__(self, n: Optional[int] = 256, normalized: Optional[bool] ...
    method get_bit_at_idx (line 25) | def get_bit_at_idx(val, idx):
    method get_color_map (line 28) | def get_color_map(self) -> np.ndarray:
    method get_box_color_codes (line 45) | def get_box_color_codes(self) -> List:
    method get_color_map_list (line 59) | def get_color_map_list(self) -> List:

FILE: corenet/utils/common_utils.py
  function construct_local_path_from_remote (line 23) | def construct_local_path_from_remote(remote_path: str, local_dir: str) -...
  function unwrap_model_fn (line 51) | def unwrap_model_fn(model: torch.nn.Module) -> torch.nn.Module:
  function check_compatibility (line 76) | def check_compatibility() -> None:
  function check_frozen_norm_layer (line 86) | def check_frozen_norm_layer(model: torch.nn.Module) -> Tuple[bool, int]:
  function device_setup (line 100) | def device_setup(opts: argparse.Namespace) -> argparse.Namespace:
  function create_directories (line 157) | def create_directories(dir_path: str, is_master_node: bool) -> None:
  function move_to_device (line 168) | def move_to_device(
  function is_coreml_conversion (line 191) | def is_coreml_conversion(opts) -> bool:

FILE: corenet/utils/context_managers.py
  function context_env_vars (line 11) | def context_env_vars(**env: str) -> ContextManager[None]:
  function context_tensor_threads (line 41) | def context_tensor_threads(num_cpu_threads: int) -> ContextManager[None]:

FILE: corenet/utils/ddp_utils.py
  function is_master (line 17) | def is_master(opts) -> bool:
  function dist_barrier (line 22) | def dist_barrier():
  function dist_monitored_barrier (line 26) | def dist_monitored_barrier(
  function is_start_rank_node (line 34) | def is_start_rank_node(opts) -> bool:
  function get_world_size (line 40) | def get_world_size():
  function get_node_rank (line 44) | def get_node_rank():
  function distributed_init (line 48) | def distributed_init(opts) -> int:
  function is_rank_0_worker_0 (line 99) | def is_rank_0_worker_0(opts: argparse.Namespace) -> bool:

FILE: corenet/utils/dict_utils.py
  function filter_keys (line 8) | def filter_keys(

FILE: corenet/utils/download_utils.py
  function get_local_path (line 21) | def get_local_path(
  class DownloadFunc (line 77) | class DownloadFunc(Protocol):
    method __call__ (line 78) | def __call__(
  function download_assets_in_parallel (line 91) | def download_assets_in_parallel(

FILE: corenet/utils/file_logger.py
  class FileLogger (line 14) | class FileLogger:
    method __init__ (line 19) | def __init__(self, fname: str) -> None:
    method add_scalar (line 43) | def add_scalar(
    method close (line 62) | def close(self) -> None:

FILE: corenet/utils/fpdb.py
  class _ForkedPdb (line 11) | class _ForkedPdb(pdb.Pdb):
    method __init__ (line 26) | def __init__(self, lockfile: str) -> None:
    method interaction (line 30) | def interaction(self, *args, **kwargs) -> None:
  function set_trace (line 49) | def set_trace(lockfile: str = "/tmp/_corenet_fpdb.lockfile") -> None:

FILE: corenet/utils/hf_adapter_utils.py
  class CorenetToHFPretrainedConfig (line 22) | class CorenetToHFPretrainedConfig(PretrainedConfig):
    method __init__ (line 35) | def __init__(self, **kwargs: Dict[str, Any]) -> None:
  class CorenetToHFPretrainedModel (line 39) | class CorenetToHFPretrainedModel(PreTrainedModel):
    method __init__ (line 55) | def __init__(self, config: CorenetToHFPretrainedConfig, vocab_size: in...
    method forward (line 67) | def forward(
    method prepare_inputs_for_generation (line 184) | def prepare_inputs_for_generation(

FILE: corenet/utils/import_utils.py
  function import_modules_from_folder (line 16) | def import_modules_from_folder(
  function ensure_library_is_available (line 64) | def ensure_library_is_available(module_name: str) -> None:
  function import_core_modules (line 103) | def import_core_modules():

FILE: corenet/utils/io_utils.py
  function make_temp_file (line 10) | def make_temp_file(

FILE: corenet/utils/logger.py
  function get_curr_time_stamp (line 25) | def get_curr_time_stamp() -> str:
  function error (line 29) | def error(message: str) -> None:
  function color_text (line 53) | def color_text(in_text: str) -> str:
  function log (line 57) | def log(message: str, end="\n") -> None:
  function warning (line 65) | def warning(message: Union[str, Warning]) -> None:
  function ignore_exception_with_warning (line 79) | def ignore_exception_with_warning(message: str) -> None:
  function info (line 99) | def info(message: str, print_line: Optional[bool] = False) -> None:
  function debug (line 109) | def debug(message: str) -> None:
  function double_dash_line (line 120) | def double_dash_line(dashes: Optional[int] = 75) -> None:
  function singe_dash_line (line 124) | def singe_dash_line(dashes: Optional[int] = 67) -> None:
  function print_header (line 128) | def print_header(header: str) -> None:
  function print_header_minor (line 140) | def print_header_minor(header: str) -> None:
  function disable_printing (line 150) | def disable_printing():
  function enable_printing (line 154) | def enable_printing():
  function match_warning_message (line 158) | def match_warning_message(*message_segments: str) -> str:
  function indent (line 183) | def indent(multiline_str: str, prefix: str = "\t") -> str:
  function truncate (line 200) | def truncate(text: str, max_len: int = 79) -> str:

FILE: corenet/utils/math_utils.py
  function make_divisible (line 9) | def make_divisible(
  function bound_fn (line 33) | def bound_fn(

FILE: corenet/utils/object_utils.py
  function is_iterable (line 14) | def is_iterable(x):
  function apply_recursively (line 18) | def apply_recursively(x, cb, *args, **kwargs):
  function flatten_to_dict (line 28) | def flatten_to_dict(
  function is_pytest_environment (line 62) | def is_pytest_environment() -> bool:

FILE: corenet/utils/object_utils_test.py
  function test_apply_on_values (line 9) | def test_apply_on_values():
  function test_flatten_to_dict (line 22) | def test_flatten_to_dict():

FILE: corenet/utils/pytorch_to_coreml.py
  function convert_pytorch_to_coreml (line 20) | def convert_pytorch_to_coreml(
  function assertion_check (line 137) | def assertion_check(

FILE: corenet/utils/registry.py
  class Registry (line 26) | class Registry:
    method __init__ (line 51) | def __init__(
    method _load_all (line 82) | def _load_all(self) -> None:
    method items (line 99) | def items(self) -> List[Tuple[str, RegistryItem]]:
    method keys (line 103) | def keys(self) -> List[str]:
    method __iter__ (line 107) | def __iter__(self) -> Iterable[str]:
    method __getitem__ (line 111) | def __getitem__(self, key: Union[Tuple[str, str], str]) -> RegistryItem:
    method __contains__ (line 141) | def __contains__(self, key: str) -> bool:
    method register (line 146) | def register(self, name: str, type: str = "") -> Callable:
    method all_arguments (line 173) | def all_arguments(self, parser: argparse.ArgumentParser) -> argparse.A...
    method parse_key (line 187) | def parse_key(self, key: str) -> Tuple[str, Dict[str, str]]:

FILE: corenet/utils/registry_test.py
  function test_functional_registry (line 9) | def test_functional_registry() -> None:
  function test_basic_registration (line 21) | def test_basic_registration() -> None:

FILE: corenet/utils/retry_utils.py
  function run_with_retries (line 13) | def run_with_retries(

FILE: corenet/utils/tensor_utils.py
  function image_size_from_opts (line 22) | def image_size_from_opts(opts) -> Tuple[int, int]:
  function video_size_from_opts (line 40) | def video_size_from_opts(opts) -> Tuple[int, int, int]:
  function create_rand_tensor (line 62) | def create_rand_tensor(
  function reduce_tensor (line 95) | def reduce_tensor(inp_tensor: torch.Tensor) -> torch.Tensor:
  function reduce_tensor_sum (line 104) | def reduce_tensor_sum(inp_tensor: torch.Tensor) -> torch.Tensor:
  function all_gather_list (line 111) | def all_gather_list(data: Union[List, Tensor, Dict[str, Tensor]]):
  function gather_all_features (line 119) | def gather_all_features(features: Tensor, dim=0):
  function tensor_to_python_float (line 128) | def tensor_to_python_float(
  function to_numpy (line 163) | def to_numpy(img_tensor: torch.Tensor) -> np.ndarray:

FILE: corenet/utils/visualization_utils.py
  function visualize_boxes_xyxy (line 30) | def visualize_boxes_xyxy(image: np.ndarray, boxes: np.ndarray) -> np.nda...
  function create_colored_mask (line 50) | def create_colored_mask(
  function draw_bounding_boxes (line 64) | def draw_bounding_boxes(
  function convert_to_cityscape_format (line 128) | def convert_to_cityscape_format(img: Tensor) -> Tensor:

FILE: mlx_examples/clip/clip.py
  function load (line 18) | def load(model_dir: str) -> Tuple[CLIPModel, CLIPTokenizer, CLIPImagePro...
  function main (line 25) | def main() -> None:

FILE: mlx_examples/clip/image_processor.py
  class CLIPImageProcessor (line 17) | class CLIPImageProcessor:
    method __init__ (line 24) | def __init__(
    method __call__ (line 43) | def __call__(self, images: List[Image]) -> mx.array:
    method _preprocess (line 48) | def _preprocess(self, image: Image) -> mx.array:
    method from_pretrained (line 60) | def from_pretrained(path: str) -> "CLIPImageProcessor":
  function resize (line 67) | def resize(image: Image, short_size: int) -> Image:
  function center_crop (line 82) | def center_crop(image: Image, size: Tuple[int, int]) -> Image:
  function rescale (line 97) | def rescale(image: mx.array) -> mx.array:
  function normalize (line 102) | def normalize(image: mx.array, mean: mx.array, std: mx.array) -> mx.array:

FILE: mlx_examples/clip/main_clip_to_mlx.py
  function is_apple_silicon_macos (line 29) | def is_apple_silicon_macos() -> bool:
  function mlx_naming_remap (line 33) | def mlx_naming_remap(corenet_k: str) -> str:
  function make_shards (line 87) | def make_shards(
  function save_weights (line 106) | def save_weights(save_path: Union[str, Path], weights: Dict[str, Any]) -...
  function get_hf_clip_model_path (line 158) | def get_hf_clip_model_path() -> Path:
  function ascontiguousarray (line 178) | def ascontiguousarray(mx_array: mx.array) -> mx.array:
  function sanitize (line 190) | def sanitize(state_dict: Dict[str, mx.array]) -> Dict[str, mx.array]:
  function torch_to_mx (line 234) | def torch_to_mx(a: torch.Tensor, *, dtype: str) -> mx.array:
  function main (line 241) | def main() -> None:

FILE: mlx_examples/clip/main_test_clip_mlx.py
  function load_mlx_model (line 43) | def load_mlx_model(model_dir: str) -> CLIPModel:
  function get_mlx_output (line 51) | def get_mlx_output(
  function transform_image (line 65) | def transform_image(img: Image.Image, size: int = 224) -> torch.Tensor:
  function text_transform (line 75) | def text_transform(tokeized_text_tensor: torch.Tensor) -> torch.Tensor:
  function get_tokenized_input (line 83) | def get_tokenized_input(
  function get_preprocessed_img (line 100) | def get_preprocessed_img(class_names: List[str]) -> torch.Tensor:
  function get_input_images_and_tokenized_text (line 112) | def get_input_images_and_tokenized_text(
  function get_torch_output (line 121) | def get_torch_output(
  function torch_to_mx (line 143) | def torch_to_mx(a: torch.Tensor, *, dtype: str) -> mx.array:
  function main_test (line 150) | def main_test() -> None:

FILE: mlx_examples/clip/model.py
  class CLIPVisionOutput (line 24) | class CLIPVisionOutput:
  class CLIPTextOutput (line 31) | class CLIPTextOutput:
  class CLIPModelOutput (line 37) | class CLIPModelOutput:
  class CLIPTextConfig (line 46) | class CLIPTextConfig:
  class CLIPVisionConfig (line 59) | class CLIPVisionConfig:
  class CLIPConfig (line 73) | class CLIPConfig:
  function quick_gelu (line 80) | def quick_gelu(x: mx.array) -> mx.array:
  function get_hidden_act (line 87) | def get_hidden_act(
  function clip_loss (line 99) | def clip_loss(logits: mx.array) -> mx.array:
  class Attention (line 107) | class Attention(nn.Module):
    method __init__ (line 110) | def __init__(
    method __call__ (line 141) | def __call__(
  class MLP (line 168) | class MLP(nn.Module):
    method __init__ (line 171) | def __init__(self, config: CLIPTextConfig) -> None:
    method __call__ (line 178) | def __call__(self, x: mx.array) -> mx.array:
  class EncoderLayer (line 184) | class EncoderLayer(nn.Module):
    method __init__ (line 187) | def __init__(self, config: CLIPTextConfig) -> None:
    method __call__ (line 198) | def __call__(self, x: mx.array, mask: Optional[mx.array] = None) -> mx...
  class TextEmbeddings (line 207) | class TextEmbeddings(nn.Module):
    method __init__ (line 210) | def __init__(self, config: CLIPTextConfig) -> None:
    method __call__ (line 219) | def __call__(self, x: mx.array) -> mx.array:
  class Encoder (line 225) | class Encoder(nn.Module):
    method __init__ (line 228) | def __init__(self, config: Union[CLIPTextConfig, CLIPVisionConfig]) ->...
    method __call__ (line 231) | def __call__(self) -> None:
  function create_additive_causual_mask (line 235) | def create_additive_causual_mask(
  class ClipTextModel (line 247) | class ClipTextModel(nn.Module):
    method __init__ (line 250) | def __init__(self, config: CLIPTextConfig) -> None:
    method __call__ (line 257) | def __call__(self, x: mx.array) -> CLIPTextOutput:
  class VisionEmbeddings (line 273) | class VisionEmbeddings(nn.Module):
    method __init__ (line 276) | def __init__(self, config: CLIPVisionConfig) -> None:
    method __call__ (line 328) | def __call__(self, x: mx.array) -> mx.array:
  class ClipVisionModel (line 363) | class ClipVisionModel(nn.Module):
    method __init__ (line 366) | def __init__(self, config: CLIPVisionConfig) -> None:
    method __call__ (line 376) | def __call__(
  class CLIPModel (line 401) | class CLIPModel(nn.Module):
    method __init__ (line 404) | def __init__(self, config: CLIPConfig) -> None:
    method get_text_features (line 418) | def get_text_features(self, x: mx.array) -> mx.array:
    method get_image_features (line 421) | def get_image_features(self, x: mx.array) -> mx.array:
    method __call__ (line 424) | def __call__(
    method from_pretrained (line 465) | def from_pretrained(path: str) -> "CLIPModel":
    method sanitize (line 521) | def sanitize(weights: Dict[str, mx.array]) -> Dict[str, mx.array]:

FILE: mlx_examples/clip/tokenizer.py
  class CLIPTokenizer (line 16) | class CLIPTokenizer:
    method __init__ (line 22) | def __init__(self, bpe_ranks: Dict[Tuple[str], int], vocab: Dict[str, ...
    method bos (line 32) | def bos(self) -> str:
    method bos_token (line 36) | def bos_token(self) -> int:
    method eos (line 40) | def eos(self) -> str:
    method eos_token (line 44) | def eos_token(self) -> int:
    method bpe (line 47) | def bpe(self, text: str) -> List[str]:
    method __call__ (line 92) | def __call__(self, *args: Any, **kwargs: Any) -> Any:
    method tokenize (line 95) | def tokenize(
    method from_pretrained (line 120) | def from_pretrained(path: str) -> "CLIPTokenizer":

FILE: mlx_examples/open_elm/convert.py
  function torch_to_mlx (line 29) | def torch_to_mlx(x: torch.Tensor) -> mx.array:
  function quantize_weights (line 48) | def quantize_weights(
  function convert_open_elm (line 81) | def convert_open_elm(

FILE: mlx_examples/open_elm/inference.py
  function generate_token (line 24) | def generate_token(
  function generate (line 74) | def generate(

FILE: mlx_examples/open_elm/open_elm.py
  function get_normalization_layer (line 18) | def get_normalization_layer(num_features: int, norm_type: str) -> nn.Mod...
  function compute_heads (line 24) | def compute_heads(model_dim: int, head_dim: int) -> int:
  function make_divisible (line 33) | def make_divisible(val: Union[int, float], divisor: int) -> int:
  class GPTConfig (line 55) | class GPTConfig:
    method __post_init__ (line 88) | def __post_init__(self) -> None:
    method from_name (line 172) | def from_name(
  class MultiHeadCausalAttention (line 231) | class MultiHeadCausalAttention(nn.Module):
    method __init__ (line 239) | def __init__(self, model_config: GPTConfig, layer_idx: int) -> None:
    method extra_repr (line 289) | def extra_repr(self) -> str:
    method __call__ (line 297) | def __call__(
  class FeedForwardNetwork (line 386) | class FeedForwardNetwork(nn.Module):
    method __init__ (line 395) | def __init__(self, model_config: GPTConfig, layer_idx: int) -> None:
    method extra_repr (line 436) | def extra_repr(self) -> str:
    method __call__ (line 439) | def __call__(self, x):
  class TransformerDecoderLayer (line 457) | class TransformerDecoderLayer(nn.Module):
    method __init__ (line 466) | def __init__(self, model_config: GPTConfig, layer_idx: int) -> None:
    method __call__ (line 481) | def __call__(
  class OpenELM (line 514) | class OpenELM(nn.Module):
    method __init__ (line 526) | def __init__(
    method __call__ (line 563) | def __call__(
    method reset_parameters (line 614) | def reset_parameters(self, model_config: GPTConfig) -> None:
  function load_model (line 655) | def load_model(

FILE: setup.py
  function is_apple_silicon_macos (line 16) | def is_apple_silicon_macos() -> bool:
  function parse_requirements (line 20) | def parse_requirements(path: str) -> List[str]:
  function main (line 33) | def main() -> None:
  function get_files (line 120) | def get_files(path, relative_to=".") -> List[str]:

FILE: tests/configs.py
  function get_config (line 14) | def get_config(
  function default_training_opts (line 56) | def default_training_opts() -> argparse.Namespace:
  function modify_attr (line 61) | def modify_attr(opts: argparse.Namespace, key: str, value: Any) -> None:

FILE: tests/data/collate_fns/test_byteformer_collate_fn.py
  function test_byteformer_image_collate_fn (line 13) | def test_byteformer_image_collate_fn() -> None:
  function test_wav_collate (line 46) | def test_wav_collate() -> None:

FILE: tests/data/collate_fns/test_collate_functions.py
  function test_image_data_collate_functions (line 28) | def test_image_data_collate_functions(

FILE: tests/data/datasets/audio_classification/test_speech_commands_v2.py
  function mock_load (line 20) | def mock_load(filepath: str) -> Tuple[Tensor, int]:
  function mock_process_dataset_config (line 28) | def mock_process_dataset_config(self) -> None:
  function test_getitem (line 52) | def test_getitem(

FILE: tests/data/datasets/classification/mock_coco.py
  class MockCOCOClassification (line 16) | class MockCOCOClassification(COCOClassification):
    method read_image_pil (line 18) | def read_image_pil(path: str) -> Optional[Image.Image]:

FILE: tests/data/datasets/classification/mock_imagenet.py
  class MockImageNetDataset (line 28) | class MockImageNetDataset(ImageNetDataset):
    method __init__ (line 29) | def __init__(
    method n_classes (line 55) | def n_classes(self):
    method read_image_pil (line 59) | def read_image_pil(path: str) -> Optional[Image.Image]:
  class MockImageN

[
  {
    "path": ".dockerignore",
    "chars": 712,
    "preview": "# Docker-specific:\n**/Dockerfile\nsetup_bolt.sh\n.git\n.gitignore\n.dockerignore\n\n# Mirroring .gitignore\n# Note: dockerignor"
  },
  {
    "path": ".flake8",
    "chars": 51,
    "preview": "[flake8]\nmax-line-length = 88\nextend-ignore = E203\n"
  },
  {
    "path": ".gitattributes",
    "chars": 941,
    "preview": "*.tar filter=lfs diff=lfs merge=lfs -text\n*.gz filter=lfs diff=lfs merge=lfs -text\n*.zip filter=lfs diff=lfs merge=lfs -"
  },
  {
    "path": ".gitignore",
    "chars": 441,
    "preview": "# Note: please mirror changes of this file to .dockerignore.\n\n.vscode/\n.coverage\n*.pyc\n__pycache__\n.DS_STORE\n.idea\n*.swp"
  },
  {
    "path": "ACKNOWLEDGEMENTS",
    "chars": 65727,
    "preview": "Acknowledgements\nPortions of this Software may utilize the following copyrighted material, the use of which is hereby ac"
  },
  {
    "path": "CODE_OF_CONDUCT.md",
    "chars": 3358,
    "preview": "# Code of Conduct\n\n## Our Pledge\n\nIn the interest of fostering an open and welcoming environment, we as\ncontributors and"
  },
  {
    "path": "CONTRIBUTING.md",
    "chars": 748,
    "preview": "# Contribution Guide\n\nThanks for your interest in contributing. This project was released to accompany a research paper "
  },
  {
    "path": "LICENSE",
    "chars": 2672,
    "preview": "Copyright (C) 2024 Apple Inc. All Rights Reserved.\n\nDisclaimer: IMPORTANT:  This Apple software is supplied to you by Ap"
  },
  {
    "path": "Makefile",
    "chars": 6222,
    "preview": "SHELL := /bin/bash\nYEAR = $$(date +%Y)\nLAST_YEAR = $$(($(YEAR) - 1))\nCOLOR_LOG = \\033[34m\nCOLOR_INFO = \\033[32m\nCOLOR_WA"
  },
  {
    "path": "README.md",
    "chars": 11534,
    "preview": "# CoreNet: A library for training deep neural networks\n\nCoreNet is a deep neural network toolkit that allows researchers"
  },
  {
    "path": "conftest.py",
    "chars": 1788,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport os\nimpor"
  },
  {
    "path": "corenet/__init__.py",
    "chars": 3651,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport warnings"
  },
  {
    "path": "corenet/__main__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "corenet/__version__.py",
    "chars": 122,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\nversion = \"0.1.1"
  },
  {
    "path": "corenet/cli/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "corenet/cli/entrypoints.py",
    "chars": 1309,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nfrom typing imp"
  },
  {
    "path": "corenet/cli/main.py",
    "chars": 1326,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/cli/main_benchmark.py",
    "chars": 3756,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport time\nfro"
  },
  {
    "path": "corenet/cli/main_conversion.py",
    "chars": 3064,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport os\nfrom "
  },
  {
    "path": "corenet/cli/main_eval.py",
    "chars": 1671,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\nfrom typing impo"
  },
  {
    "path": "corenet/cli/main_eval_llmadapters.py",
    "chars": 16103,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\n\"\"\"\nEvaluate co"
  },
  {
    "path": "corenet/cli/main_train.py",
    "chars": 1284,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nfrom typing imp"
  },
  {
    "path": "corenet/constants.py",
    "chars": 3703,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\nimport os\nimport"
  },
  {
    "path": "corenet/data/__init__.py",
    "chars": 187,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nfrom corenet.da"
  },
  {
    "path": "corenet/data/collate_fns/__init__.py",
    "chars": 2313,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/collate_fns/byteformer_collate_functions.py",
    "chars": 8036,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\n\"\"\"This file co"
  },
  {
    "path": "corenet/data/collate_fns/collate_functions.py",
    "chars": 5307,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\nimport argparse\n"
  },
  {
    "path": "corenet/data/data_loaders.py",
    "chars": 7991,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/datasets/__init__.py",
    "chars": 5736,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/datasets/audio_classification/__init__.py",
    "chars": 104,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n"
  },
  {
    "path": "corenet/data/datasets/audio_classification/speech_commands_v2.py",
    "chars": 7807,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/datasets/classification/__init__.py",
    "chars": 104,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n"
  },
  {
    "path": "corenet/data/datasets/classification/base_image_classification_dataset.py",
    "chars": 10593,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\nimport argparse\n"
  },
  {
    "path": "corenet/data/datasets/classification/base_imagenet_shift_dataset.py",
    "chars": 3411,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\"\"\"Base class fo"
  },
  {
    "path": "corenet/data/datasets/classification/coco.py",
    "chars": 6972,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/datasets/classification/imagenet.py",
    "chars": 968,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/datasets/classification/imagenet_a.py",
    "chars": 1546,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\"\"\"ImageNetA dat"
  },
  {
    "path": "corenet/data/datasets/classification/imagenet_r.py",
    "chars": 1876,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\"\"\"ImageNetR dat"
  },
  {
    "path": "corenet/data/datasets/classification/imagenet_sketch.py",
    "chars": 1499,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\"\"\"ImageNetSketc"
  },
  {
    "path": "corenet/data/datasets/classification/imagenet_synsets.py",
    "chars": 24154,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\n# Folder names/"
  },
  {
    "path": "corenet/data/datasets/classification/imagenet_v2.py",
    "chars": 6010,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/datasets/classification/places365.py",
    "chars": 976,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/datasets/classification/wordnet_tagged_classification.py",
    "chars": 18161,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/datasets/dataset_base.py",
    "chars": 19099,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nfrom __future__"
  },
  {
    "path": "corenet/data/datasets/detection/__init__.py",
    "chars": 104,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n"
  },
  {
    "path": "corenet/data/datasets/detection/base_detection.py",
    "chars": 1852,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/datasets/detection/coco_base.py",
    "chars": 11501,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/datasets/detection/coco_mask_rcnn.py",
    "chars": 6884,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/datasets/detection/coco_ssd.py",
    "chars": 9098,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/datasets/language_modeling/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "corenet/data/datasets/language_modeling/base_lm.py",
    "chars": 9019,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/datasets/language_modeling/commonsense_170k.py",
    "chars": 5237,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\n\nimport argpars"
  },
  {
    "path": "corenet/data/datasets/language_modeling/general_lm.py",
    "chars": 25142,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\n\nimport argpars"
  },
  {
    "path": "corenet/data/datasets/multi_modal_img_text/__init__.py",
    "chars": 629,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/datasets/multi_modal_img_text/base_multi_modal_img_text.py",
    "chars": 19129,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/datasets/multi_modal_img_text/flickr.py",
    "chars": 4693,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport json\nimp"
  },
  {
    "path": "corenet/data/datasets/multi_modal_img_text/img_text_tar_dataset.py",
    "chars": 11926,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/datasets/multi_modal_img_text/zero_shot_image_classification/__init__.py",
    "chars": 1505,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/datasets/multi_modal_img_text/zero_shot_image_classification/base_zero_shot_image_classification.py",
    "chars": 2831,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/datasets/multi_modal_img_text/zero_shot_image_classification/imagenet.py",
    "chars": 852,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/datasets/multi_modal_img_text/zero_shot_image_classification/imagenet_a.py",
    "chars": 1216,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nfrom typing imp"
  },
  {
    "path": "corenet/data/datasets/multi_modal_img_text/zero_shot_image_classification/imagenet_class_names.py",
    "chars": 18947,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\n\nIMAGENET_CLASS"
  },
  {
    "path": "corenet/data/datasets/multi_modal_img_text/zero_shot_image_classification/imagenet_r.py",
    "chars": 1228,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nfrom typing imp"
  },
  {
    "path": "corenet/data/datasets/multi_modal_img_text/zero_shot_image_classification/imagenet_sketch.py",
    "chars": 1086,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nfrom typing imp"
  },
  {
    "path": "corenet/data/datasets/multi_modal_img_text/zero_shot_image_classification/templates.py",
    "chars": 3462,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nfrom typing imp"
  },
  {
    "path": "corenet/data/datasets/segmentation/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "corenet/data/datasets/segmentation/ade20k.py",
    "chars": 10026,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/datasets/segmentation/base_segmentation.py",
    "chars": 12904,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/datasets/segmentation/coco_segmentation.py",
    "chars": 5380,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/datasets/segmentation/coco_stuff.py",
    "chars": 11478,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/datasets/segmentation/pascal_voc.py",
    "chars": 5809,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/datasets/utils/__init__.py",
    "chars": 104,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n"
  },
  {
    "path": "corenet/data/datasets/utils/common.py",
    "chars": 6173,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport collecti"
  },
  {
    "path": "corenet/data/datasets/utils/text.py",
    "chars": 724,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport re\nimpor"
  },
  {
    "path": "corenet/data/datasets/utils/video.py",
    "chars": 17322,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\"\"\"Contains help"
  },
  {
    "path": "corenet/data/io/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "corenet/data/io/transfer_clients.py",
    "chars": 17162,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\n\nimport argpars"
  },
  {
    "path": "corenet/data/loader/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "corenet/data/loader/dataloader.py",
    "chars": 4111,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport sys\nfrom"
  },
  {
    "path": "corenet/data/sampler/__init__.py",
    "chars": 2406,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/sampler/base_sampler.py",
    "chars": 16111,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/sampler/batch_sampler.py",
    "chars": 4881,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/sampler/chain_sampler.py",
    "chars": 12773,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nfrom __future__"
  },
  {
    "path": "corenet/data/sampler/multi_scale_sampler.py",
    "chars": 11146,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/sampler/utils.py",
    "chars": 5477,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nfrom typing imp"
  },
  {
    "path": "corenet/data/sampler/variable_batch_sampler.py",
    "chars": 15165,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/sampler/video_batch_sampler.py",
    "chars": 5010,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/sampler/video_clip_batch_sampler.py",
    "chars": 12033,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/sampler/video_variable_seq_sampler.py",
    "chars": 11269,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/text_tokenizer/__init__.py",
    "chars": 1617,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/text_tokenizer/base_tokenizer.py",
    "chars": 4187,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/text_tokenizer/clip_tokenizer.py",
    "chars": 3871,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/text_tokenizer/sentencepiece_tokenizer.py",
    "chars": 7167,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/transforms/__init__.py",
    "chars": 770,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/transforms/audio.py",
    "chars": 24561,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/transforms/audio_aux/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "corenet/data/transforms/audio_aux/mfccs.py",
    "chars": 5787,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\nimport math\n\nimp"
  },
  {
    "path": "corenet/data/transforms/audio_bytes.py",
    "chars": 6091,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\nimport argparse\n"
  },
  {
    "path": "corenet/data/transforms/base_transforms.py",
    "chars": 611,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/transforms/common.py",
    "chars": 1249,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\nfrom typing impo"
  },
  {
    "path": "corenet/data/transforms/image_bytes.py",
    "chars": 14197,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/transforms/image_pil.py",
    "chars": 80622,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/transforms/image_torch.py",
    "chars": 17258,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/transforms/utils.py",
    "chars": 1396,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nfrom typing imp"
  },
  {
    "path": "corenet/data/transforms/video.py",
    "chars": 53746,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\nimport argparse\n"
  },
  {
    "path": "corenet/data/video_reader/__init__.py",
    "chars": 1765,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/video_reader/base_av_reader.py",
    "chars": 28970,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/video_reader/decord_reader.py",
    "chars": 7017,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport sys\nfrom"
  },
  {
    "path": "corenet/data/video_reader/ffmpeg_reader.py",
    "chars": 13421,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/data/video_reader/ffmpeg_utils.py",
    "chars": 29109,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\nimport argparse\n"
  },
  {
    "path": "corenet/data/video_reader/pyav_reader.py",
    "chars": 5143,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nfrom typing imp"
  },
  {
    "path": "corenet/engine/__init__.py",
    "chars": 218,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nfrom corenet.en"
  },
  {
    "path": "corenet/engine/default_trainer.py",
    "chars": 25279,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/engine/detection_utils/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "corenet/engine/detection_utils/coco_map.py",
    "chars": 3417,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport io\nimpor"
  },
  {
    "path": "corenet/engine/eval_detection.py",
    "chars": 15241,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/engine/eval_segmentation.py",
    "chars": 21148,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\nimport argparse\n"
  },
  {
    "path": "corenet/engine/evaluation_engine.py",
    "chars": 4800,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/engine/fsdp_trainer.py",
    "chars": 8815,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/engine/segmentation_utils/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "corenet/engine/segmentation_utils/cityscapes_iou.py",
    "chars": 1465,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport glob\nimp"
  },
  {
    "path": "corenet/engine/utils.py",
    "chars": 6273,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\nimport argparse\n"
  },
  {
    "path": "corenet/loss_fn/__init__.py",
    "chars": 2725,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/loss_fn/base_criteria.py",
    "chars": 1777,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport abc\nimpo"
  },
  {
    "path": "corenet/loss_fn/classification/__init__.py",
    "chars": 104,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n"
  },
  {
    "path": "corenet/loss_fn/classification/base_classification_criteria.py",
    "chars": 3626,
    "preview": "#  For licensing see accompanying LICENSE file.\n#  Copyright (C) 2024 Apple Inc. All Rights Reserved.\n\nimport argparse\nf"
  },
  {
    "path": "corenet/loss_fn/classification/binary_cross_entropy.py",
    "chars": 3232,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/loss_fn/classification/cross_entropy.py",
    "chars": 3650,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/loss_fn/classification/focal_loss.py",
    "chars": 3561,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/loss_fn/composite_loss.py",
    "chars": 9310,
    "preview": "#  For licensing see accompanying LICENSE file.\n#  Copyright (C) 2024 Apple Inc. All Rights Reserved.\n\nfrom __future__ i"
  },
  {
    "path": "corenet/loss_fn/detection/__init__.py",
    "chars": 104,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n"
  },
  {
    "path": "corenet/loss_fn/detection/base_detection_criteria.py",
    "chars": 1116,
    "preview": "#  For licensing see accompanying LICENSE file.\n#  Copyright (C) 2024 Apple Inc. All Rights Reserved.\n\nimport argparse\n\n"
  },
  {
    "path": "corenet/loss_fn/detection/mask_rcnn_loss.py",
    "chars": 5871,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/loss_fn/detection/ssd_multibox_loss.py",
    "chars": 8907,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/loss_fn/distillation/__init__.py",
    "chars": 104,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n"
  },
  {
    "path": "corenet/loss_fn/distillation/base_distillation.py",
    "chars": 4911,
    "preview": "#  For licensing see accompanying LICENSE file.\n#  Copyright (C) 2024 Apple Inc. All Rights Reserved.\n\nimport argparse\nf"
  },
  {
    "path": "corenet/loss_fn/distillation/hard_distillation.py",
    "chars": 4833,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/loss_fn/distillation/soft_kl_distillation.py",
    "chars": 2752,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/loss_fn/language_modeling/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "corenet/loss_fn/language_modeling/base_lm.py",
    "chars": 4079,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/loss_fn/language_modeling/cross_entropy.py",
    "chars": 4955,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/loss_fn/language_modeling/cross_entropy_for_kv_prediction.py",
    "chars": 13062,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/loss_fn/multi_modal_img_text/__init__.py",
    "chars": 104,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n"
  },
  {
    "path": "corenet/loss_fn/multi_modal_img_text/base_multi_modal_img_text_criteria.py",
    "chars": 1156,
    "preview": "#  For licensing see accompanying LICENSE file.\n#  Copyright (C) 2024 Apple Inc. All Rights Reserved.\n\nimport argparse\n\n"
  },
  {
    "path": "corenet/loss_fn/multi_modal_img_text/contrastive_loss_clip.py",
    "chars": 6550,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\nimport argparse\n"
  },
  {
    "path": "corenet/loss_fn/neural_augmentation.py",
    "chars": 12941,
    "preview": "#  For licensing see accompanying LICENSE file.\n#  Copyright (C) 2024 Apple Inc. All Rights Reserved.\n\nimport argparse\ni"
  },
  {
    "path": "corenet/loss_fn/segmentation/__init__.py",
    "chars": 104,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n"
  },
  {
    "path": "corenet/loss_fn/segmentation/base_segmentation_criteria.py",
    "chars": 1112,
    "preview": "#  For licensing see accompanying LICENSE file.\n#  Copyright (C) 2024 Apple Inc. All Rights Reserved.\n\nimport argparse\n\n"
  },
  {
    "path": "corenet/loss_fn/segmentation/cross_entropy.py",
    "chars": 10386,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/loss_fn/utils/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "corenet/loss_fn/utils/build_helper.py",
    "chars": 1091,
    "preview": "#  For licensing see accompanying LICENSE file.\n#  Copyright (C) 2024 Apple Inc. All Rights Reserved.\n\nimport argparse\n\n"
  },
  {
    "path": "corenet/loss_fn/utils/class_weighting.py",
    "chars": 1528,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport torch\nfr"
  },
  {
    "path": "corenet/metrics/__init__.py",
    "chars": 1299,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/metrics/average_precision.py",
    "chars": 1653,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport tracebac"
  },
  {
    "path": "corenet/metrics/coco_map.py",
    "chars": 8875,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\nimport io\nimport"
  },
  {
    "path": "corenet/metrics/confusion_mat.py",
    "chars": 2821,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nfrom numbers im"
  },
  {
    "path": "corenet/metrics/image_text_retrieval.py",
    "chars": 7145,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
  },
  {
    "path": "corenet/metrics/intersection_over_union.py",
    "chars": 3410,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nfrom numbers im"
  },
  {
    "path": "corenet/metrics/metric_base.py",
    "chars": 11487,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport abc\nimpo"
  },
  {
    "path": "corenet/metrics/metric_base_test.py",
    "chars": 1272,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nfrom typing imp"
  },
  {
    "path": "corenet/metrics/misc.py",
    "chars": 3131,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nfrom numbers im"
  },
  {
    "path": "corenet/metrics/multiclass_classification_pr.py",
    "chars": 18279,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\nimport argparse\n"
  },
  {
    "path": "corenet/metrics/probability_histograms.py",
    "chars": 1831,
    "preview": "#\n# For licensing see accompanying LICENSE file.\n# Copyright (C) 2024 Apple Inc. All Rights Reserved.\n#\n\nimport argparse"
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  {
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]

// ... and 538 more files (download for full content)