SYMBOL INDEX (354 symbols across 32 files)

FILE: Explanatory_Instructions_Tuning/data/convertsation.py
  class Conversation (line 4) | class Conversation:
    method __init__ (line 8) | def __init__(self, messages=None):
    method process (line 11) | def process(self):
    method get_prompt (line 32) | def get_prompt(self):
    method append_message (line 35) | def append_message(self, role, message):
    method copy (line 38) | def copy(self):
    method load_qas (line 43) | def load_qas(self, qas: List[List[str]]):

FILE: Explanatory_Instructions_Tuning/data/item_processor.py
  function center_crop (line 17) | def center_crop(pil_image, crop_size):
  function var_center_crop (line 31) | def var_center_crop(pil_image, crop_size_list, random_top_k=1):
  function generate_crop_size_list (line 40) | def generate_crop_size_list(num_patches, patch_size, max_ratio=4.0):
  class FlexARItemProcessor (line 54) | class FlexARItemProcessor(MMConvItemProcessor):
    method __init__ (line 62) | def __init__(
    method get_n_grids_token (line 99) | def get_n_grids_token(n_grids):
    method token2id (line 102) | def token2id(self, token: str) -> int:
    method process_image (line 106) | def process_image(self, image) -> Dict:
    method process_item (line 142) | def process_item(self, item, training_mode=False, out_flatten=True):
    method decode_image (line 174) | def decode_image(self, tokens: List[int]) -> Image.Image:

FILE: Explanatory_Instructions_Tuning/demo_inference.py
  function set_seed (line 8) | def set_seed(seed):

FILE: Explanatory_Instructions_Tuning/finetune_solver.py
  class ItemProcessor (line 12) | class ItemProcessor(ItemProcessorBase):
    method process_item (line 13) | def process_item(self, data_item: dict, training_mode=False) -> Tuple[...
    method predict_item_token_length (line 29) | def predict_item_token_length(self, data_item: dict) -> int:
  class Solver (line 38) | class Solver(FinetuneSolverBase):
    method get_args_parser (line 40) | def get_args_parser(cls):
    method _model_func (line 51) | def _model_func(
    method _item_processor_func (line 85) | def _item_processor_func(self) -> ItemProcessorBase:
    method _make_and_save_starting_point (line 88) | def _make_and_save_starting_point(self, save_path: str) -> None:

FILE: Explanatory_Instructions_Tuning/inference_solver.py
  class LLMImageStartTriggeredUnbatchedClassifierFreeGuidanceLogitsProcessor (line 16) | class LLMImageStartTriggeredUnbatchedClassifierFreeGuidanceLogitsProcess...
    method __init__ (line 25) | def __init__(
    method get_unconditional_logits (line 58) | def get_unconditional_logits(self, input_ids, image_start_token_id_ind...
    method __call__ (line 95) | def __call__(self, input_ids, scores):
  class MultiModalLogitsProcessor (line 134) | class MultiModalLogitsProcessor(LogitsProcessor):
    method __init__ (line 136) | def __init__(
    method __call__ (line 172) | def __call__(self, input_ids: torch.LongTensor, scores: torch.FloatTen...
  class InterleavedTopKLogitsWarper (line 222) | class InterleavedTopKLogitsWarper(LogitsWarper):
    method __init__ (line 228) | def __init__(
    method __call__ (line 254) | def __call__(self, input_ids: torch.LongTensor, scores: torch.FloatTen...
  class FlexARInferenceSolver (line 269) | class FlexARInferenceSolver:
    method get_args_parser (line 271) | def get_args_parser(cls):
    method __init__ (line 278) | def __init__(self, model_path, precision, target_size=512):
    method get_streamer (line 288) | def get_streamer(self):
    method generate (line 292) | def generate(
    method decode_ids (line 349) | def decode_ids(self, tokens: List[int]):
    method decode_image (line 375) | def decode_image(self, tokens: List[int]):
    method create_image_grid (line 379) | def create_image_grid(images, rows, cols):
    method create_logits_processor (line 391) | def create_logits_processor(self, cfg=3.0, image_top_k=2000, text_top_...

FILE: Explanatory_Instructions_Tuning/model/chameleon/configuration_chameleon.py
  class ChameleonVQVAEConfig (line 25) | class ChameleonVQVAEConfig(PretrainedConfig):
    method __init__ (line 65) | def __init__(
  class ChameleonConfig (line 98) | class ChameleonConfig(PretrainedConfig):
    method __init__ (line 191) | def __init__(
    method _rope_scaling_validation (line 261) | def _rope_scaling_validation(self):

FILE: Explanatory_Instructions_Tuning/model/chameleon/convert_chameleon_weights_to_hf.py
  function compute_intermediate_size (line 67) | def compute_intermediate_size(n, ffn_dim_multiplier=1, multiple_of=256):
  function read_json (line 71) | def read_json(path):
  function write_json (line 76) | def write_json(text, path):
  function write_model (line 81) | def write_model(model_path, input_base_path, model_size, chameleon_versi...
  function main (line 427) | def main():

FILE: Explanatory_Instructions_Tuning/model/chameleon/image_processing_chameleon.py
  function make_batched_images (line 42) | def make_batched_images(images) -> List[List[ImageInput]]:
  class ChameleonImageProcessor (line 65) | class ChameleonImageProcessor(BaseImageProcessor):
    method __init__ (line 106) | def __init__(
    method resize (line 157) | def resize(
    method preprocess (line 206) | def preprocess(
    method blend_rgba (line 358) | def blend_rgba(self, image: ImageInput) -> ImageInput:

FILE: Explanatory_Instructions_Tuning/model/chameleon/modeling_chameleon.py
  class ChameleonRMSNorm (line 59) | class ChameleonRMSNorm(nn.Module):
    method __init__ (line 60) | def __init__(self, hidden_size, eps=1e-6):
    method forward (line 68) | def forward(self, hidden_states):
    method extra_repr (line 75) | def extra_repr(self):
    method reset_parameters (line 78) | def reset_parameters(self):
  class ChameleonRotaryEmbedding (line 87) | class ChameleonRotaryEmbedding(nn.Module):
    method __init__ (line 88) | def __init__(self, dim, max_position_embeddings=2048, base=10000, devi...
    method forward (line 100) | def forward(self, x, position_ids):
    method reset_parameters (line 115) | def reset_parameters(self):
  class ChameleonLinearScalingRotaryEmbedding (line 121) | class ChameleonLinearScalingRotaryEmbedding(ChameleonRotaryEmbedding):
    method forward (line 124) | def forward(self, x, position_ids):
    method reset_parameters (line 130) | def reset_parameters(self):
  class ChameleonDynamicNTKScalingRotaryEmbedding (line 136) | class ChameleonDynamicNTKScalingRotaryEmbedding(ChameleonRotaryEmbedding):
    method forward (line 139) | def forward(self, x, position_ids):
    method reset_parameters (line 152) | def reset_parameters(self):
  function rotate_half (line 157) | def rotate_half(x):
  function apply_rotary_pos_emb (line 165) | def apply_rotary_pos_emb(q, k, cos, sin, position_ids=None, unsqueeze_di...
  class ChameleonMLP (line 193) | class ChameleonMLP(nn.Module):
    method __init__ (line 194) | def __init__(self, config):
    method forward (line 205) | def forward(self, x):
    method reset_parameters (line 209) | def reset_parameters(self):
  class ChameleonLayerNorm (line 213) | class ChameleonLayerNorm(nn.LayerNorm):
    method __init__ (line 221) | def __init__(self, hidden_size, model_parallel_size, n_heads_per_mp, *...
    method repeat_param (line 228) | def repeat_param(self, param):
    method forward (line 231) | def forward(self, hidden_states):
    method reset_parameters (line 236) | def reset_parameters(self):
  function repeat_kv (line 241) | def repeat_kv(hidden_states: torch.Tensor, n_rep: int) -> torch.Tensor:
  class ChameleonAttention (line 253) | class ChameleonAttention(nn.Module):
    method __init__ (line 256) | def __init__(self, config: ChameleonConfig, layer_idx: Optional[int] =...
    method _init_rope (line 298) | def _init_rope(self):
    method forward (line 325) | def forward(
    method reset_parameters (line 389) | def reset_parameters(self):
  class ChameleonFlashAttention2 (line 395) | class ChameleonFlashAttention2(ChameleonAttention):
    method __init__ (line 402) | def __init__(self, *args, **kwargs):
    method forward (line 411) | def forward(
    method reset_parameters (line 511) | def reset_parameters(self):
  class ChameleonSdpaAttention (line 515) | class ChameleonSdpaAttention(ChameleonAttention):
    method forward (line 523) | def forward(
    method reset_parameters (line 607) | def reset_parameters(self):
  class ChameleonDecoderLayer (line 620) | class ChameleonDecoderLayer(nn.Module):
    method __init__ (line 621) | def __init__(self, config: ChameleonConfig, layer_idx: int):
    method forward (line 633) | def forward(
    method reset_parameters (line 695) | def reset_parameters(self):
  class ChameleonSwinDecoderLayer (line 699) | class ChameleonSwinDecoderLayer(nn.Module):
    method __init__ (line 700) | def __init__(self, config: ChameleonConfig, layer_idx: int):
    method forward (line 712) | def forward(
    method reset_parameters (line 773) | def reset_parameters(self):
  class ChameleonVQVAEVectorQuantizer (line 777) | class ChameleonVQVAEVectorQuantizer(nn.Module):
    method __init__ (line 788) | def __init__(self, config):
    method forward (line 797) | def forward(self, hidden_state: torch.Tensor):
    method reset_parameters (line 824) | def reset_parameters(self):
  class ChameleonVQVAEEncoderConvDownsample (line 828) | class ChameleonVQVAEEncoderConvDownsample(nn.Module):
    method __init__ (line 829) | def __init__(self, in_channels):
    method forward (line 833) | def forward(self, hidden_states):
  class ChameleonVQVAEEncoderResnetBlock (line 840) | class ChameleonVQVAEEncoderResnetBlock(nn.Module):
    method __init__ (line 841) | def __init__(
    method forward (line 864) | def forward(self, hidden_states):
    method reset_parameters (line 883) | def reset_parameters(self):
  class ChameleonVQVAEEncoderAttnBlock (line 887) | class ChameleonVQVAEEncoderAttnBlock(nn.Module):
    method __init__ (line 888) | def __init__(self, in_channels):
    method forward (line 898) | def forward(self, hidden_states):
    method reset_parameters (line 921) | def reset_parameters(self):
  class ChameleonVQVAEEncoder (line 925) | class ChameleonVQVAEEncoder(nn.Module):
    method __init__ (line 926) | def __init__(self, config):
    method forward (line 995) | def forward(self, pixel_values: torch.LongTensor):
    method reset_parameters (line 1021) | def reset_parameters(self):
  class ChameleonVQVAE (line 1049) | class ChameleonVQVAE(PreTrainedModel):
    method _init_weights (line 1053) | def _init_weights(self, module):
    method __init__ (line 1065) | def __init__(self, config: ChameleonVQVAEConfig):
    method encode (line 1074) | def encode(self, pixel_values: torch.LongTensor):
    method reset_parameters (line 1080) | def reset_parameters(self):
  class ChameleonImageVocabularyMapping (line 1084) | class ChameleonImageVocabularyMapping:
    method __init__ (line 1089) | def __init__(self, vocab_map):
    method val2name (line 1094) | def val2name(self):
    method image_tokens (line 1098) | def image_tokens(self):
    method bpe2img (line 1102) | def bpe2img(self):
    method img2bpe (line 1111) | def img2bpe(self):
    method bpe2img_search_tensors (line 1115) | def bpe2img_search_tensors(self):
    method img2bpe_mapping_tensor (line 1119) | def img2bpe_mapping_tensor(self):
    method convert_img2bpe (line 1125) | def convert_img2bpe(self, img_batch: torch.Tensor) -> torch.Tensor:
    method reset_parameters (line 1130) | def reset_parameters(self):
  class ChameleonPreTrainedModel (line 1155) | class ChameleonPreTrainedModel(PreTrainedModel):
    method _init_weights (line 1168) | def _init_weights(self, module):
    method reset_parameters (line 1181) | def reset_parameters(self):
  class ChameleonModel (line 1258) | class ChameleonModel(ChameleonPreTrainedModel):
    method __init__ (line 1266) | def __init__(self, config: ChameleonConfig):
    method get_input_embeddings (line 1282) | def get_input_embeddings(self):
    method set_input_embeddings (line 1285) | def set_input_embeddings(self, value):
    method get_image_tokens (line 1288) | def get_image_tokens(self, pixel_values: torch.FloatTensor):
    method forward (line 1311) | def forward(
    method _update_causal_mask (line 1433) | def _update_causal_mask(
    method reset_parameters (line 1511) | def reset_parameters(self):
  class ChameleonForConditionalGeneration (line 1519) | class ChameleonForConditionalGeneration(ChameleonPreTrainedModel):
    method __init__ (line 1522) | def __init__(self, config):
    method get_input_embeddings (line 1531) | def get_input_embeddings(self):
    method set_input_embeddings (line 1534) | def set_input_embeddings(self, value):
    method get_output_embeddings (line 1537) | def get_output_embeddings(self):
    method set_output_embeddings (line 1540) | def set_output_embeddings(self, new_embeddings):
    method set_decoder (line 1543) | def set_decoder(self, decoder):
    method get_decoder (line 1546) | def get_decoder(self):
    method forward (line 1551) | def forward(
    method prepare_inputs_for_generation (line 1650) | def prepare_inputs_for_generation(
    method reset_parameters (line 1700) | def reset_parameters(self):

FILE: Explanatory_Instructions_Tuning/model/chameleon/processing_chameleon.py
  class ChameleonProcessor (line 28) | class ChameleonProcessor(ProcessorMixin):
    method __init__ (line 51) | def __init__(self, image_processor, tokenizer, image_seq_length: int =...
    method __call__ (line 58) | def __call__(
    method batch_decode (line 142) | def batch_decode(self, *args, **kwargs):
    method decode (line 150) | def decode(self, *args, **kwargs):
    method model_input_names (line 159) | def model_input_names(self):

FILE: Explanatory_Instructions_Tuning/model/chameleon_vae_ori/image_tokenizer.py
  class ImageTokenizer (line 15) | class ImageTokenizer:
    method __init__ (line 16) | def __init__(
    method _whiten_transparency (line 45) | def _whiten_transparency(self, img: PIL.Image) -> PIL.Image:
    method img_tokens_from_pil (line 84) | def img_tokens_from_pil(self, img: PIL.Image) -> list[int]:
    method _pil_from_chw_tensor (line 95) | def _pil_from_chw_tensor(self, chw_tensor: torch.Tensor) -> PIL.Image:
    method pil_from_img_toks (line 117) | def pil_from_img_toks(self, tokens: torch.Tensor, h_latent_dim=32, w_l...
    method latent_embedding_from_pil (line 123) | def latent_embedding_from_pil(self, img: PIL.Image):

FILE: Explanatory_Instructions_Tuning/model/chameleon_vae_ori/vocab.py
  class VocabInfo (line 11) | class VocabInfo:
    method __init__ (line 12) | def __init__(self, vocab_map: dict[str, int]):
    method begin_sequence (line 23) | def begin_sequence(self) -> int:
    method end_sequence (line 27) | def end_sequence(self) -> int:
    method begin_image (line 31) | def begin_image(self) -> int:
    method end_image (line 35) | def end_image(self) -> int:
    method padding (line 39) | def padding(self) -> int:
    method end_turn (line 43) | def end_turn(self) -> int:
    method val2name (line 47) | def val2name(self) -> dict[int, str]:
    method all_tokens (line 51) | def all_tokens(self) -> list[int]:
    method image_tokens (line 55) | def image_tokens(self) -> list[int]:
    method special_tokens (line 59) | def special_tokens(self) -> list[int]:
    method text_tokens (line 63) | def text_tokens(self) -> list[int]:
  class VocabTranslation (line 67) | class VocabTranslation:
    method __init__ (line 68) | def __init__(self, vocab_info: VocabInfo, device: str | None = None):
    method bpe2img (line 73) | def bpe2img(self) -> dict[int, int]:
    method img2bpe (line 82) | def img2bpe(self) -> dict[int, int]:
    method bpe2img_search_tensors (line 86) | def bpe2img_search_tensors(self) -> tuple[torch.Tensor, torch.Tensor]:
    method img2bpe_mapping_tensor (line 92) | def img2bpe_mapping_tensor(self) -> torch.LongTensor:
    method convert_bpe2img (line 102) | def convert_bpe2img(self, bpe_batch: torch.Tensor) -> torch.Tensor:
    method convert_img2bp2 (line 106) | def convert_img2bp2(self, img_batch: torch.Tensor) -> torch.Tensor:

FILE: Explanatory_Instructions_Tuning/model/chameleon_vae_ori/vqgan.py
  class VectorQuantizer2 (line 20) | class VectorQuantizer2(nn.Module):
    method __init__ (line 29) | def __init__(
    method remap_to_used (line 65) | def remap_to_used(self, inds):
    method unmap_to_all (line 79) | def unmap_to_all(self, inds):
    method forward (line 89) | def forward(self, z, temp=None, rescale_logits=False, return_logits=Fa...
    method get_codebook_entry (line 131) | def get_codebook_entry(self, indices, shape):
  function nonlinearity (line 153) | def nonlinearity(x):
  function Normalize (line 158) | def Normalize(in_channels, num_groups=32):
  class Upsample (line 162) | class Upsample(nn.Module):
    method __init__ (line 163) | def __init__(self, in_channels, with_conv):
    method forward (line 169) | def forward(self, x):
  class Downsample (line 176) | class Downsample(nn.Module):
    method __init__ (line 177) | def __init__(self, in_channels, with_conv):
    method forward (line 184) | def forward(self, x):
  class ResnetBlock (line 194) | class ResnetBlock(nn.Module):
    method __init__ (line 195) | def __init__(
    method forward (line 223) | def forward(self, x, temb):
  class AttnBlock (line 246) | class AttnBlock(nn.Module):
    method __init__ (line 247) | def __init__(self, in_channels):
    method forward (line 257) | def forward(self, x):
  function make_attn (line 284) | def make_attn(in_channels, attn_type="vanilla"):
  class Encoder (line 295) | class Encoder(nn.Module):
    method __init__ (line 296) | def __init__(
    method forward (line 382) | def forward(self, x):
  class Decoder (line 410) | class Decoder(nn.Module):
    method __init__ (line 411) | def __init__(
    method forward (line 496) | def forward(self, z):
  class VQModel (line 532) | class VQModel(nn.Module):
    method __init__ (line 533) | def __init__(
    method init_from_ckpt (line 572) | def init_from_ckpt(self, path, ignore_keys=list()):
    method encode (line 583) | def encode(self, x):
    method decode (line 589) | def decode(self, quant):
    method decode_code (line 594) | def decode_code(self, code_b):
    method forward (line 599) | def forward(self, input):
    method get_input (line 604) | def get_input(self, batch, k):
    method get_last_layer (line 611) | def get_last_layer(self):
    method log_images (line 614) | def log_images(self, batch, **kwargs):
    method to_rgb (line 628) | def to_rgb(self, x):

FILE: Explanatory_Instructions_Tuning/model/configuration_xllmx_chameleon.py
  class ChameleonXLLMXConfig (line 9) | class ChameleonXLLMXConfig(ChameleonConfig):
    method __init__ (line 11) | def __init__(

FILE: Explanatory_Instructions_Tuning/model/modeling_xllmx_chameleon.py
  class ChameleonXLLMXForConditionalGeneration (line 20) | class ChameleonXLLMXForConditionalGeneration(ChameleonForConditionalGene...
    method __init__ (line 23) | def __init__(self, config):
    method forward (line 26) | def forward(self, input_ids=None, labels=None, training=True, **kwargs):
    method get_fsdp_wrap_module_list (line 55) | def get_fsdp_wrap_module_list(self) -> List:
    method get_checkpointing_wrap_module_list (line 61) | def get_checkpointing_wrap_module_list(self) -> List:

FILE: Explanatory_Instructions_Tuning/pre_tokenize/Adobe_5k_pre_tokenize.py
  class ItemProcessor (line 16) | class ItemProcessor(FlexARItemProcessor):
    method __init__ (line 17) | def __init__(
    method process_item (line 27) | def process_item(self, raw_item, training_mode=False, out_flatten=True):

FILE: Explanatory_Instructions_Tuning/pre_tokenize/allweather_pre_tokenize.py
  class ItemProcessor (line 16) | class ItemProcessor(FlexARItemProcessor):
    method __init__ (line 17) | def __init__(
    method process_item (line 27) | def process_item(self, raw_item, training_mode=False, out_flatten=True):

FILE: Explanatory_Instructions_Tuning/pre_tokenize/concat_record.py
  function find_sub_records (line 8) | def find_sub_records(directory: str):

FILE: Explanatory_Instructions_Tuning/pre_tokenize/seed_multi_turn_pre_tokenize.py
  class ItemProcessor (line 16) | class ItemProcessor(FlexARItemProcessor):
    method __init__ (line 17) | def __init__(
    method process_item (line 27) | def process_item(self, raw_item, training_mode=False, out_flatten=True):

FILE: Explanatory_Instructions_Tuning/xllmx/data/conversation/template.py
  class ConversationBase (line 4) | class ConversationBase:
    method __init__ (line 7) | def __init__(self, messages=None):
    method process (line 10) | def process(self):
    method get_prompt (line 13) | def get_prompt(self):
    method append_message (line 16) | def append_message(self, role, message):
    method copy (line 19) | def copy(self):
    method load_qas (line 24) | def load_qas(self, qas: List[List[str]]):

FILE: Explanatory_Instructions_Tuning/xllmx/data/data_reader.py
  function read_general (line 12) | def read_general(path) -> Union[str, BytesIO]:
  function init_ceph_client_if_needed (line 21) | def init_ceph_client_if_needed():

FILE: Explanatory_Instructions_Tuning/xllmx/data/dataset.py
  class FinetuneConversationDataset (line 22) | class FinetuneConversationDataset(Dataset):
    method __init__ (line 23) | def __init__(self, config_path, item_processor: ItemProcessorBase, cac...
    method __len__ (line 44) | def __len__(self):
    method _collect_annotations (line 47) | def _collect_annotations(self):
    method _load_meta (line 58) | def _load_meta(self, meta):
    method _collect_annotations_and_save_to_cache (line 98) | def _collect_annotations_and_save_to_cache(self, cache_dir):
    method _get_cache_dir (line 127) | def _get_cache_dir(config_path):
    method _load_annotations_from_cache (line 136) | def _load_annotations_from_cache(cache_dir):
    method get_item_func (line 146) | def get_item_func(self, meta_idx, idx_in_meta):
    method tie_index_to_meta (line 155) | def tie_index_to_meta(self, idx: int):
    method __getitem__ (line 176) | def __getitem__(self, index):

FILE: Explanatory_Instructions_Tuning/xllmx/data/item_processor.py
  class LabelAllZeroError (line 11) | class LabelAllZeroError(Exception):
    method __init__ (line 12) | def __init__(self, message=None):
    method __str__ (line 15) | def __str__(self):
  class ItemProcessorBase (line 19) | class ItemProcessorBase(ABC):
    method process_item (line 21) | def process_item(self, data_item: dict, training_mode=False) -> Tuple[...
    method predict_item_token_length (line 24) | def predict_item_token_length(self, data_item: dict) -> int:
  class MMConvItemProcessor (line 31) | class MMConvItemProcessor(ItemProcessorBase):
    method __init__ (line 32) | def __init__(
    method collect_and_process_media (line 65) | def collect_and_process_media(self, data_item):
    method replace_media_token_with_media (line 91) | def replace_media_token_with_media(
    method insert_implicit_media_symbol_in_q1 (line 111) | def insert_implicit_media_symbol_in_q1(conv_list: List[Dict], d_media:...
    method insert_implicit_media_symbol_at_beginning (line 134) | def insert_implicit_media_symbol_at_beginning(conv: str, d_media: Dict):
    method preprocess_item (line 161) | def preprocess_item(self, data_item):
    method add_speaker_and_signal (line 164) | def add_speaker_and_signal(self, source: List):
    method process_item (line 194) | def process_item(self, data_item: dict, training_mode=False) -> Tuple[...
    method predict_item_token_length (line 253) | def predict_item_token_length(self, data_item: dict) -> int:

FILE: Explanatory_Instructions_Tuning/xllmx/data/sampler.py
  function mild_shuffle (line 14) | def mild_shuffle(items: List, shuffle_factor, engine: np.random.Generator):
  class FinetuneDistSampler (line 50) | class FinetuneDistSampler(Sampler):
    method __init__ (line 51) | def __init__(
    method __iter__ (line 106) | def __iter__(self) -> Iterator:
    method __len__ (line 200) | def __len__(self) -> int:
    method set_epoch (line 203) | def set_epoch(self, epoch: int, start_iter: int = 0) -> None:

FILE: Explanatory_Instructions_Tuning/xllmx/model/components.py
  class RMSNorm (line 11) | class RMSNorm(torch.nn.Module):
    method __init__ (line 12) | def __init__(self, dim: int, eps: float = 1e-6):
    method _norm (line 29) | def _norm(self, x):
    method forward (line 42) | def forward(self, x):

FILE: Explanatory_Instructions_Tuning/xllmx/model/tokenizer.py
  class Tokenizer (line 15) | class Tokenizer:
    method __init__ (line 16) | def __init__(self, model_path: str):
    method encode (line 51) | def encode(self, s: str, bos: bool, eos: bool) -> List[int]:
    method encode_segment (line 63) | def encode_segment(self, s: str):
    method encode_wo_prefix_space (line 70) | def encode_wo_prefix_space(self, s: str):
    method _probe_tokenizer_style (line 89) | def _probe_tokenizer_style(self):
    method decode (line 111) | def decode(self, t: List[int]) -> str:
    method save (line 114) | def save(self, save_dir: str):
    method n_words (line 122) | def n_words(self):
  function probe_tokenizer_path_from_pretrained (line 131) | def probe_tokenizer_path_from_pretrained(pretrained_path: str):

FILE: Explanatory_Instructions_Tuning/xllmx/solvers/finetune/finetune.py
  class FinetuneSolverBase (line 46) | class FinetuneSolverBase(ABC):
    method __init__ (line 48) | def __init__(self, args):
    method configure_logger (line 122) | def configure_logger(self):
    method get_args_parser (line 156) | def get_args_parser(cls):
    method build_model (line 243) | def build_model(self) -> (nn.Module, Tokenizer):
    method _model_func (line 368) | def _model_func(self, init_from: str) -> (nn.Module, Tokenizer | None)...
    method _make_and_save_starting_point (line 372) | def _make_and_save_starting_point(self, save_path: str):
    method setup_fsdp_sync (line 375) | def setup_fsdp_sync(self, model: nn.Module, data_parallel: str, precis...
    method build_data (line 419) | def build_data(self):
    method _item_processor_func (line 448) | def _item_processor_func(self) -> ItemProcessorBase:
    method _dataset_func (line 451) | def _dataset_func(self):
    method resume (line 458) | def resume(self, resume_path: str):
    method run (line 509) | def run(self):
    method train_one_epoch (line 549) | def train_one_epoch(

FILE: Explanatory_Instructions_Tuning/xllmx/util/ckpt.py
  function split_ckpt_str_into_epoch_iter (line 14) | def split_ckpt_str_into_epoch_iter(ckpt_str: str):
  function remove_early_ckpts (line 25) | def remove_early_ckpts(out_dir, max_keep=2):
  function save (line 46) | def save(

FILE: Explanatory_Instructions_Tuning/xllmx/util/dist.py
  function find_free_port (line 17) | def find_free_port(start_port: int, end_port: int):
  function init_distributed_mode (line 33) | def init_distributed_mode(args=SimpleNamespace()):
  function all_reduce_mean (line 88) | def all_reduce_mean(x, group=None):

FILE: Explanatory_Instructions_Tuning/xllmx/util/lr_sched.py
  function adjust_learning_rate (line 4) | def adjust_learning_rate(optimizer, it, args):
  function adjust_learning_rate_epoch (line 24) | def adjust_learning_rate_epoch(optimizer, epoch, args):

FILE: Explanatory_Instructions_Tuning/xllmx/util/misc.py
  function random_seed (line 15) | def random_seed(seed=0):
  class SmoothedValue (line 21) | class SmoothedValue(object):
    method __init__ (line 26) | def __init__(self, window_size=1000, fmt=None):
    method update (line 34) | def update(self, value, n=1):
    method synchronize_between_processes (line 39) | def synchronize_between_processes(self):
    method median (line 51) | def median(self):
    method avg (line 56) | def avg(self):
    method global_avg (line 61) | def global_avg(self):
    method max (line 65) | def max(self):
    method value (line 69) | def value(self):
    method __str__ (line 72) | def __str__(self):
  class MetricLogger (line 78) | class MetricLogger(object):
    method __init__ (line 79) | def __init__(self, delimiter="\t"):
    method update (line 83) | def update(self, **kwargs):
    method __str__ (line 98) | def __str__(self):
    method synchronize_between_processes (line 104) | def synchronize_between_processes(self):
    method add_meter (line 108) | def add_meter(self, name, meter):
    method log_every (line 111) | def log_every(self, iterable, print_freq, header=None, start_iter=0, s...
  function add_weight_decay (line 154) | def add_weight_decay(model, lr, weight_decay=1e-5):
  function broadcast_nonmp_parameters (line 170) | def broadcast_nonmp_parameters(model):
  function mark_mp_params (line 190) | def mark_mp_params(model: torch.nn.Module):
  function print_param_status (line 206) | def print_param_status(model: torch.nn.Module) -> None:

FILE: Explanatory_Instructions_Tuning/xllmx/util/tensor_type.py
  function promote_param_to_fp32 (line 5) | def promote_param_to_fp32(param: nn.Parameter) -> None: