SYMBOL INDEX (211 symbols across 38 files)

FILE: spo_training_and_inference/configs/basic_config.py
  function get_config (line 3) | def get_config():
  function basic_config (line 6) | def basic_config():

FILE: spo_training_and_inference/configs/spo_sd-v1-5_4k-prompts_num-sam-4_10ep_bs10.py
  function get_config (line 3) | def get_config():
  function exp_config (line 6) | def exp_config():

FILE: spo_training_and_inference/configs/spo_sdxl_4k-prompts_num-sam-2_3-is_10ep_bs2_gradacc2.py
  function get_config (line 3) | def get_config():
  function exp_config (line 6) | def exp_config():

FILE: spo_training_and_inference/inference_scripts/inference_spo_sd-v1-5.py
  function main (line 14) | def main():

FILE: spo_training_and_inference/inference_scripts/inference_spo_sdxl.py
  function main (line 14) | def main():

FILE: spo_training_and_inference/spo/custom_diffusers/ddim_seperate.py
  function _left_broadcast (line 9) | def _left_broadcast(t, shape):
  function _get_variance (line 13) | def _get_variance(self, timestep, prev_timestep):
  function ddim_step_fetch_x0 (line 25) | def ddim_step_fetch_x0(
  function ddim_step_fetch_x_t_1 (line 90) | def ddim_step_fetch_x_t_1(

FILE: spo_training_and_inference/spo/custom_diffusers/ddim_with_logprob.py
  function _left_broadcast (line 9) | def _left_broadcast(t, shape):
  function _get_variance (line 13) | def _get_variance(self, timestep, prev_timestep):
  function ddim_step_with_logprob (line 25) | def ddim_step_with_logprob(

FILE: spo_training_and_inference/spo/custom_diffusers/multi_sample_pipeline.py
  function multi_sample_pipeline (line 13) | def multi_sample_pipeline(

FILE: spo_training_and_inference/spo/custom_diffusers/multi_sample_pipeline_sdxl.py
  function multi_sample_pipeline_sdxl (line 20) | def multi_sample_pipeline_sdxl(

FILE: spo_training_and_inference/spo/datasets/builder.py
  function build_dataset (line 5) | def build_dataset(cfg):

FILE: spo_training_and_inference/spo/datasets/prompt_dataset.py
  class PromptDataset (line 13) | class PromptDataset(Dataset):
    method __init__ (line 14) | def __init__(self, meta_json_path, pretrained_tokenzier_path, caption_...
    method __len__ (line 23) | def __len__(self):
    method __getitem__ (line 26) | def __getitem__(self, idx):
    method collate_fn (line 45) | def collate_fn(examples, tokenizer):
    method sdxl_collate_fn (line 67) | def sdxl_collate_fn(examples, tokenizer, tokenizer_2):

FILE: spo_training_and_inference/spo/preference_models/builder.py
  function get_compare_func (line 7) | def get_compare_func(compare_func_cfg):
  function get_preference_model_func (line 14) | def get_preference_model_func(cfg, device):

FILE: spo_training_and_inference/spo/preference_models/compare_funcs.py
  function preference_score_compare (line 5) | def preference_score_compare(scores, threshold):

FILE: spo_training_and_inference/spo/preference_models/models/step_aware_preference_model.py
  class StepAwarePreferenceModel (line 14) | class StepAwarePreferenceModel(nn.Module):
    method __init__ (line 15) | def __init__(
    method get_text_features (line 52) | def get_text_features(self, *args, **kwargs):
    method get_image_features (line 55) | def get_image_features(self, *args, **kwargs):
    method forward (line 58) | def forward(self, text_inputs=None, image_inputs=None, time_cond=None):
    method logit_scale (line 67) | def logit_scale(self):
    method get_preference_score (line 70) | def get_preference_score(self, images, input_ids, timesteps):

FILE: spo_training_and_inference/spo/preference_models/models/time_conditioned_clip.py
  function modulate (line 31) | def modulate(x, shift, scale):
  class TimeConditionedCLIPEncoderLayer (line 35) | class TimeConditionedCLIPEncoderLayer(CLIPEncoderLayer):
    method __init__ (line 36) | def __init__(self, config: CLIPConfig):
    method forward (line 58) | def forward(
  class TimeConditionedCLIPEncoder (line 106) | class TimeConditionedCLIPEncoder(CLIPEncoder):
    method __init__ (line 107) | def __init__(self, config: CLIPConfig):
    method forward (line 113) | def forward(
  class TimeConditionedCLIPVisionTransformer (line 204) | class TimeConditionedCLIPVisionTransformer(CLIPVisionTransformer):
    method __init__ (line 205) | def __init__(self, config: CLIPVisionConfig):
    method forward (line 223) | def forward(
  class TimestepEmbedder (line 273) | class TimestepEmbedder(nn.Module):
    method __init__ (line 277) | def __init__(self, hidden_size, frequency_embedding_size=256):
    method timestep_embedding (line 287) | def timestep_embedding(t, dim, max_period=10000):
    method forward (line 307) | def forward(self, t):
  class HFTimeConditionedCLIPModel (line 314) | class HFTimeConditionedCLIPModel(CLIPModel):
    method __init__ (line 315) | def __init__(self, config: CLIPConfig):
    method get_image_features (line 354) | def get_image_features(
    method forward (line 411) | def forward(

FILE: spo_training_and_inference/spo/preference_models/preference_model_fns.py
  function step_aware_preference_model_func_builder (line 7) | def step_aware_preference_model_func_builder(cfg):

FILE: spo_training_and_inference/spo/utils/dist_utils.py
  function gather_tensor_with_diff_shape (line 4) | def gather_tensor_with_diff_shape(input_tensor, primary_dim_size_list):

FILE: spo_training_and_inference/train_scripts/train_spo.py
  function main (line 58) | def main(_):

FILE: spo_training_and_inference/train_scripts/train_spo_sdxl.py
  function main (line 58) | def main(_):

FILE: step_aware_preference_model/trainer/accelerators/base_accelerator.py
  function debug (line 28) | def debug(port):
  class DebugConfig (line 35) | class DebugConfig:
  class TrainingMode (line 40) | class TrainingMode(BaseEnum):
  class MetricMode (line 45) | class MetricMode(BaseEnum):
  class BaseAcceleratorConfig (line 51) | class BaseAcceleratorConfig:
  class BaseAccelerator (line 75) | class BaseAccelerator(abc.ABC):
    method __init__ (line 77) | def __init__(self, cfg: BaseAcceleratorConfig):
    method post_init (line 91) | def post_init(self):
    method set_logging_level (line 97) | def set_logging_level(self):
    method debug (line 105) | def debug(self):
    method set_seed (line 109) | def set_seed(self):
    method prepare (line 113) | def prepare(self, *args, device_placement=None):
    method get_latest_checkpoint (line 116) | def get_latest_checkpoint(self):
    method load_state_if_needed (line 125) | def load_state_if_needed(self):
    method is_main_process (line 143) | def is_main_process(self):
    method num_processes (line 147) | def num_processes(self):
    method pre_training_log (line 150) | def pre_training_log(self, cfg: DictConfig):
    method init_training (line 165) | def init_training(self, cfg: DictConfig):
    method should_skip (line 184) | def should_skip(self, epoch, step):
    method update_progbar_step (line 193) | def update_progbar_step(self):
    method log (line 196) | def log(self, data):
    method recalc_train_length_after_prepare (line 200) | def recalc_train_length_after_prepare(self, num_batches):
    method accumulate (line 208) | def accumulate(self, model):
    method gather (line 211) | def gather(self, data):
    method sync_gradients (line 215) | def sync_gradients(self):
    method update_step_loss (line 218) | def update_step_loss(self, loss):
    method update_global_step (line 221) | def update_global_step(self, loss):
    method get_allocated_cuda_memory (line 231) | def get_allocated_cuda_memory(self):
    method update_step (line 234) | def update_step(self, loss, lr):
    method wait_for_everyone (line 249) | def wait_for_everyone(self):
    method update_epoch (line 252) | def update_epoch(self):
    method update_metrics (line 259) | def update_metrics(self, metrics):
    method end_training (line 264) | def end_training(self):
    method unwrap_and_save (line 268) | def unwrap_and_save(self, model):
    method should_end (line 278) | def should_end(self):
    method backward (line 281) | def backward(self, loss):
    method clip_grad_norm_ (line 284) | def clip_grad_norm_(self, params):
    method should_eval (line 287) | def should_eval(self):
    method should_save (line 296) | def should_save(self):
    method training_stage (line 300) | def training_stage(self):
    method save_training_stage (line 310) | def save_training_stage(self, save_dir):
    method save_checkpoint (line 313) | def save_checkpoint(self):
    method gradient_state (line 334) | def gradient_state(self):
    method get_all_ckpts (line 337) | def get_all_ckpts(self):
    method load_best_checkpoint (line 340) | def load_best_checkpoint(self):
    method device (line 362) | def device(self):
    method cleanup_checkpoints (line 365) | def cleanup_checkpoints(self):
    method get_ckpts_to_delete (line 384) | def get_ckpts_to_delete(self):

FILE: step_aware_preference_model/trainer/accelerators/debug_accelerator.py
  class DebugAcceleratorConfig (line 7) | class DebugAcceleratorConfig(BaseAcceleratorConfig):
  class DebugAccelerator (line 11) | class DebugAccelerator(BaseAccelerator):
    method __init__ (line 12) | def __init__(self, cfg: DebugAcceleratorConfig):

FILE: step_aware_preference_model/trainer/accelerators/deepspeed_accelerator.py
  class MixedPrecisionConfig (line 14) | class MixedPrecisionConfig:
  class DeepSpeedConfig (line 19) | class DeepSpeedConfig:
  class DeepSpeedAcceleratorConfig (line 59) | class DeepSpeedAcceleratorConfig(BaseAcceleratorConfig):
  class DeepSpeedAccelerator (line 67) | class DeepSpeedAccelerator(BaseAccelerator):
    method __init__ (line 68) | def __init__(self, cfg: DeepSpeedAcceleratorConfig):
    method set_mixed_precision (line 86) | def set_mixed_precision(self):
    method prepare (line 97) | def prepare(self, *args, device_placement=None):

FILE: step_aware_preference_model/trainer/accelerators/utils.py
  function nvidia_smi_gpu_memory_stats (line 12) | def nvidia_smi_gpu_memory_stats():
  function get_nvidia_smi_gpu_memory_stats_str (line 42) | def get_nvidia_smi_gpu_memory_stats_str():
  function print_config (line 46) | def print_config(cfg: DictConfig):
  function _flatten_dict (line 60) | def _flatten_dict(params: MutableMapping, delimiter: str = "/", parent_k...

FILE: step_aware_preference_model/trainer/configs/configs.py
  function _locate (line 18) | def _locate(path: str) -> Any:
  function instantiate_with_cfg (line 72) | def instantiate_with_cfg(cfg: DictConfig, **kwargs):
  class DebugConfig (line 89) | class DebugConfig:
  class TrainerConfig (line 95) | class TrainerConfig:

FILE: step_aware_preference_model/trainer/criterions/spm_criterion.py
  class SPMCriterionConfig (line 8) | class SPMCriterionConfig:
  class SPMCriterion (line 23) | class SPMCriterion(_Loss):
    method __init__ (line 24) | def __init__(self, cfg: SPMCriterionConfig):
    method get_features (line 29) | def get_features(
    method gather_features (line 49) | def gather_features(features):
    method calc_loss (line 53) | def calc_loss(
    method forward (line 134) | def forward(self, model, batch):

FILE: step_aware_preference_model/trainer/datasetss/base_dataset.py
  class BaseDatasetConfig (line 7) | class BaseDatasetConfig:
  class BaseDataset (line 16) | class BaseDataset(torch.utils.data.Dataset):

FILE: step_aware_preference_model/trainer/datasetss/pick_a_pic_spm_dataset.py
  function general_collate (line 29) | def general_collate(batch, column_name):
  class ProcessorConfig (line 36) | class ProcessorConfig:
  class PickaPicSPMDatasetConfig (line 42) | class PickaPicSPMDatasetConfig(BaseDatasetConfig):
  class PickaPicSPMDataset (line 92) | class PickaPicSPMDataset(BaseDataset):
    method __init__ (line 94) | def __init__(self, cfg: PickaPicSPMDatasetConfig, split: str = "train"):
    method load_hf_dataset (line 190) | def load_hf_dataset(self, split: str) -> Dataset:
    method tokenize (line 202) | def tokenize(self, example):
    method process_image (line 213) | def process_image(self, image):
    method __getitem__ (line 224) | def __getitem__(self, idx):
    method collate_fn (line 292) | def collate_fn(self, batch):
    method __len__ (line 330) | def __len__(self):

FILE: step_aware_preference_model/trainer/lr_schedulers/constant_with_warmup.py
  class ConstantWithWarmupLRSchedulerConfig (line 8) | class ConstantWithWarmupLRSchedulerConfig:
  function instantiate_dummy_lr_scheduler (line 15) | def instantiate_dummy_lr_scheduler(cfg: ConstantWithWarmupLRSchedulerCon...

FILE: step_aware_preference_model/trainer/lr_schedulers/dummy_lr_scheduler.py
  class DummyLRSchedulerConfig (line 17) | class DummyLRSchedulerConfig:
  function instantiate_dummy_lr_scheduler (line 24) | def instantiate_dummy_lr_scheduler(cfg: DummyLRSchedulerConfig, optimizer):

FILE: step_aware_preference_model/trainer/models/base_model.py
  class BaseModelConfig (line 6) | class BaseModelConfig:

FILE: step_aware_preference_model/trainer/models/step_aware_preference_model.py
  class StepAwarePreferenceModelConfig (line 11) | class StepAwarePreferenceModelConfig(BaseModelConfig):
  class StepAwarePreferenceModel (line 18) | class StepAwarePreferenceModel(nn.Module):
    method __init__ (line 19) | def __init__(self, cfg: StepAwarePreferenceModelConfig):
    method get_text_features (line 26) | def get_text_features(self, *args, **kwargs):
    method get_image_features (line 29) | def get_image_features(self, *args, **kwargs):
    method forward (line 32) | def forward(self, text_inputs=None, image_inputs=None, time_cond=None):
    method init_adaln_paras (line 40) | def init_adaln_paras(self):
    method logit_scale (line 59) | def logit_scale(self):
    method save (line 62) | def save(self, path):

FILE: step_aware_preference_model/trainer/models/time_conditioned_clip.py
  function modulate (line 31) | def modulate(x, shift, scale):
  class TimeConditionedCLIPEncoderLayer (line 35) | class TimeConditionedCLIPEncoderLayer(CLIPEncoderLayer):
    method __init__ (line 36) | def __init__(self, config: CLIPConfig):
    method forward (line 58) | def forward(
  class TimeConditionedCLIPEncoder (line 106) | class TimeConditionedCLIPEncoder(CLIPEncoder):
    method __init__ (line 107) | def __init__(self, config: CLIPConfig):
    method forward (line 113) | def forward(
  class TimeConditionedCLIPVisionTransformer (line 204) | class TimeConditionedCLIPVisionTransformer(CLIPVisionTransformer):
    method __init__ (line 205) | def __init__(self, config: CLIPVisionConfig):
    method forward (line 223) | def forward(
  class TimestepEmbedder (line 273) | class TimestepEmbedder(nn.Module):
    method __init__ (line 277) | def __init__(self, hidden_size, frequency_embedding_size=256):
    method timestep_embedding (line 287) | def timestep_embedding(t, dim, max_period=10000):
    method forward (line 307) | def forward(self, t):
  class HFTimeConditionedCLIPModel (line 314) | class HFTimeConditionedCLIPModel(CLIPModel):
    method __init__ (line 315) | def __init__(self, config: CLIPConfig):
    method get_image_features (line 354) | def get_image_features(
    method forward (line 411) | def forward(

FILE: step_aware_preference_model/trainer/optimizers/adamw.py
  class AdamWOptimizerConfig (line 5) | class AdamWOptimizerConfig:

FILE: step_aware_preference_model/trainer/optimizers/dummy_optimizer.py
  class DummyOptimizerConfig (line 6) | class DummyOptimizerConfig:
  class BaseDummyOptim (line 14) | class BaseDummyOptim(DummyOptim):
    method __init__ (line 15) | def __init__(self, model, lr=0.001, weight_decay=0, **kwargs):

FILE: step_aware_preference_model/trainer/scripts/train_spm.py
  function load_dataloaders (line 20) | def load_dataloaders(cfg: DictConfig) -> Any:
  function load_optimizer (line 35) | def load_optimizer(cfg: DictConfig, model: nn.Module):
  function load_scheduler (line 40) | def load_scheduler(cfg: DictConfig, optimizer):
  function load_task (line 45) | def load_task(cfg: DictConfig, accelerator: BaseAccelerator):
  function verify_or_write_config (line 50) | def verify_or_write_config(cfg: TrainerConfig):
  function main (line 63) | def main(cfg: TrainerConfig) -> None:

FILE: step_aware_preference_model/trainer/tasks/base_task.py
  function flatten (line 11) | def flatten(list_of_lists):
  class BaseTaskConfig (line 16) | class BaseTaskConfig:
  class BaseTask (line 21) | class BaseTask:
    method __init__ (line 23) | def __init__(self, cfg: BaseTaskConfig, accelerator):
    method train_step (line 27) | def train_step(self, model, criterion, batch):
    method valid_step (line 30) | def valid_step(self, model, criterion, batch):
    method evaluate (line 33) | def evaluate(self, model, criterion, dataloader):
    method log_to_wandb (line 36) | def log_to_wandb(self, eval_dict, table_name="test_predictions"):
    method gather_iterable (line 55) | def gather_iterable(it, num_processes):
    method valid_step (line 61) | def valid_step(self, model, criterion, batch):
    method gather_dict (line 65) | def gather_dict(self, eval_dict):

FILE: step_aware_preference_model/trainer/tasks/spm_task.py
  function numpy_to_pil (line 31) | def numpy_to_pil(images):
  class SPMTaskConfig (line 37) | class SPMTaskConfig(BaseTaskConfig):
  class SPMTask (line 69) | class SPMTask(BaseTask):
    method __init__ (line 70) | def __init__(self, cfg: SPMTaskConfig, accelerator: BaseAccelerator):
    method train_step (line 173) | def train_step(self, model, criterion, batch):
    method features2probs (line 218) | def features2probs(model, text_features, image_0_features, image_1_fea...
    method valid_step (line 229) | def valid_step(self, model, criterion, batch):
    method pixel_values_to_pil_images (line 240) | def pixel_values_to_pil_images(pixel_values):
    method run_inference (line 246) | def run_inference(self, model, criterion, dataloader, t):
    method evaluate (line 307) | def evaluate(self, model, criterion, dataloader):
    method get_noised_imgs (line 320) | def get_noised_imgs(self, batch, timesteps):
    method update_as_pickscore_label (line 424) | def update_as_pickscore_label(self, batch, threshold=0.1):
    method sdxl_encode_prompt_embeds (line 485) | def sdxl_encode_prompt_embeds(text_encoders, text_input_ids_list):

FILE: step_aware_preference_model/trainer/utils/batchable_ddim_scheduler.py
  class BatchableDDIMScheduler (line 11) | class BatchableDDIMScheduler(DDIMScheduler):
    method _get_variance (line 12) | def _get_variance(self, timestep, prev_timestep):
    method step (line 25) | def step(