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Functions2,038 in github.com/HA-Transformer/MAT

⨍ Functions 2,038◇ Types & classes 299
Method__getitem__
(self, idx)
fairseq/data/concat_dataset.py:37
Method__getitem__
Returns a single noisy sample. Multiple samples are fed to the collater create a noising dataset batch.
fairseq/data/noising.py:282
Method__getitem__
(self, index: int)
fairseq/data/mask_tokens_dataset.py:98
Method__getitem__
(self, i)
fairseq/data/indexed_dataset.py:149
Method__getitem__
(self, i)
fairseq/data/indexed_dataset.py:218
Method__getitem__
(self, i)
fairseq/data/indexed_dataset.py:260
Method__getitem__
(self, i)
fairseq/data/indexed_dataset.py:435
Method__getitem__
(self, i)
fairseq/data/indexed_dataset.py:473
Method__getitem__
Get the item associated with index from each underlying dataset. Since index is in the range of [0, TotalNumInstances], we need to
fairseq/data/multi_corpus_sampled_dataset.py:84
Method__getitem__
(self, index)
fairseq/data/lm_context_window_dataset.py:26
Method__getitem__
(self, index)
fairseq/data/transform_eos_lang_pair_dataset.py:41
Method__getitem__
(self, index)
fairseq/data/transform_eos_dataset.py:71
Method__getitem__
(self, index)
fairseq/data/lru_cache_dataset.py:17
Method__getitem__
(self, index)
fairseq/data/numel_dataset.py:18
Method__getitem__
Returns a single sample from *tgt_dataset*. Note that backtranslation is not applied in this step; use :func:`collater` instead to ba
fairseq/data/backtranslation_dataset.py:96
Method__getitem__
( self, index: int )
fairseq/data/legacy/masked_lm_dataset.py:102
Method__getitem__
(self, index)
fairseq/data/legacy/block_pair_dataset.py:291
Method__getitem__
(self, index)
fairseq/data/audio/raw_audio_dataset.py:37
Method__getitem__
(self, index)
tests/utils.py:124
Method__getitem__
(self, index)
examples/speech_recognition/data/asr_dataset.py:59
Method__getstate__
(self)
fairseq/legacy_distributed_data_parallel.py:69
Method__getstate__
(self)
fairseq/optim/fairseq_optimizer.py:42
Method__getstate__
(self)
fairseq/data/indexed_dataset.py:450
Method__getstate__
(self)
fairseq/data/plasma_utils.py:61
Method__init__
(self, word, is_bpe)
eval_lm.py:21
Method__init__
(self, word, is_bpe)
fairseq_cli/eval_lm.py:21
Method__init__
(self)
fairseq/meters.py:11
Method__init__
(self, init=0)
fairseq/meters.py:29
Method__init__
(self)
fairseq/meters.py:51
Method__init__
(self, iterable, epoch=None, prefix=None, log_interval=1000)
fairseq/progress_bar.py:118
Method__init__
(self, iterable, epoch=None, prefix=None)
fairseq/progress_bar.py:160
Method__init__
(self, iterable, epoch=None, prefix=None, log_interval=1000)
fairseq/progress_bar.py:179
Method__init__
(self, iterable, epoch=None, prefix=None)
fairseq/progress_bar.py:207
Method__init__
(self, wrapped_bar, tensorboard_logdir, args)
fairseq/progress_bar.py:228
Method__init__
(self, tgt_dict, softmax_batch=None)
fairseq/sequence_scorer.py:15
Method__init__
Generates translations of a given source sentence. Args: tgt_dict (~fairseq.data.Dictionary): target dictionary beam_
fairseq/sequence_generator.py:15
Method__init__
(self, models)
fairseq/sequence_generator.py:522
Method__init__
(self)
fairseq/pdb.py:29
Method__init__
(self, args, task, models)
fairseq/hub_utils.py:70
Method__init__
(self, tokenizer, **kwargs)
fairseq/hub_utils.py:211
Method__init__
(self, module, world_size, process_group=None, buffer_size=2**28)
fairseq/legacy_distributed_data_parallel.py:44
Method__init__
(self)
fairseq/bleu.py:40
Method__init__
(self)
fairseq/bleu.py:73
Method__init__
(self, task, pov_replace_unk)
fairseq/bleu.py:154
Method__init__
(self, pad, eos, unk)
fairseq/bleu.py:281
Method__init__
(self, tgt_dict)
fairseq/search.py:56
Method__init__
(self, tgt_dict, min_len_a, min_len_b, max_len_a, max_len_b)
fairseq/search.py:88
Method__init__
(self, tgt_dict, num_groups, diversity_strength)
fairseq/search.py:115
Method__init__
(self, tgt_dict, sampling_topk=-1, sampling_topp=-1.0)
fairseq/search.py:169
Method__init__
(self, args, task, model, criterion, dummy_batch=None, oom_batch=None)
fairseq/trainer.py:34
Method__init__
(self, args, task)
fairseq/criterions/adaptive_loss.py:20
Method__init__
(self, args, task)
fairseq/criterions/legacy_masked_lm.py:51
Method__init__
(self, args, task)
fairseq/criterions/cross_entropy.py:17
Method__init__
(self, args, task)
fairseq/criterions/masked_lm.py:22
Method__init__
(self, args, task, underlying_criterion)
fairseq/criterions/composite_loss.py:61
Method__init__
(self, args, task)
fairseq/criterions/label_smoothed_cross_entropy.py:36
Method__init__
(self, args, task)
fairseq/criterions/binary_cross_entropy.py:18
Method__init__
(self, args, task)
fairseq/criterions/fairseq_criterion.py:11
Method__init__
(self, args, task)
fairseq/criterions/sentence_ranking.py:19
Method__init__
(self, input_size, kernel_size=1, padding_l=None, num_heads=1, weight_dropout=0., weight_soft
fairseq/modules/dynamic_convolution.py:46
Method__init__
(self, embedding_dim, padding_idx, init_size=1024)
fairseq/modules/sinusoidal_positional_embedding.py:21
Method__init__
(self, input_size, kernel_size=1, padding_l=None, num_heads=1, weight_dropout=0., weight_soft
fairseq/modules/lightweight_convolution.py:105
Method__init__
(self, weights, input_dim, num_classes)
fairseq/modules/adaptive_softmax.py:25
Method__init__
(self, vocab_size, input_dim, cutoff, dropout, factor=4., adaptive_inputs=None, tie_proj=False)
fairseq/modules/adaptive_softmax.py:57
Method__init__
( self, embedding_dim: float = 768, ffn_embedding_dim: float = 3072, num_atten
fairseq/modules/sparse_transformer_sentence_encoder_layer.py:15
Method__init__
( self, input_dim: int, num_layers: int = 1 )
fairseq/modules/highway.py:17
Method__init__
( self, padding_idx: int, vocab_size: int, num_encoder_layers: int = 6,
fairseq/modules/transformer_sentence_encoder.py:68
Method__init__
(self, in_channels, out_channels, kernel_size, **kwargs)
fairseq/modules/linearized_convolution.py:23
Method__init__
( self, num_embeddings: int, embedding_dim: int, padding_idx:
fairseq/modules/learned_positional_embedding.py:19
Method__init__
(self, in_channels, out_channels, kernel_size, padding=0)
fairseq/modules/conv_tbc.py:16
Method__init__
(self, args, no_encoder_attn=False, add_bias_kv=False, add_zero_attn=False)
fairseq/modules/transformer_layer.py:134
Method__init__
(self, beam_size=None)
fairseq/modules/beamable_mm.py:18
Method__init__
( self, out_channels, embed_dim, head_dim, head_index, dropout=0., bias=True, project_input=Tr
fairseq/modules/downsampled_multihead_attention.py:19
Method__init__
( self, out_channels, embed_dim, num_heads, dropout=0., bias=True, project_input=True, gated=F
fairseq/modules/downsampled_multihead_attention.py:154
Method__init__
( self, embedding_dim: float = 768, ffn_embedding_dim: float = 3072, num_atten
fairseq/modules/transformer_sentence_encoder_layer.py:23
Method__init__
(self, embed_dim, num_experts, dropout=None)
fairseq/modules/mean_pool_gating_network.py:18
Method__init__
( self, in_channels, out_channels, conv_kernel_size, pooling_kernel_si
fairseq/modules/vggblock.py:60
Method__init__
( self, vocab_size: int, padding_idx: int, initial_dim: int, factor: f
fairseq/modules/adaptive_input.py:15
Method__init__
( self, padding_idx: int, vocab_size: int, num_encoder_layers: int = 6,
fairseq/modules/sparse_transformer_sentence_encoder.py:17
Method__init__
( self, vocab: Dictionary, filters: List[Tuple[int, int]], cha
fairseq/modules/character_token_embedder.py:21
Method__init__
(self, embed_dim, num_heads, kdim=None, vdim=None, dropout=0., bias=True, add_bias_kv=False,
fairseq/modules/multihead_attention.py:20
Method__init__
(self, embed_dim, num_heads, kdim=None, vdim=None, dropout=0., bias=True, add_bias_kv=False,
fairseq/modules/sparse_multihead_attention.py:22
Method__init__
(self, args, params)
fairseq/optim/adadelta.py:13
Method__init__
(self, args, params, optimizer)
fairseq/optim/bmuf.py:22
Method__init__
(self, args, params)
fairseq/optim/sgd.py:13
Method__init__
(self, args, params)
fairseq/optim/adagrad.py:13
Method__init__
(self, args, params)
fairseq/optim/adafactor.py:15
Method__init__
(self, args, params)
fairseq/optim/fairseq_optimizer.py:13
Method__init__
(self, args, params)
fairseq/optim/adam.py:18
Method__init__
(self, params, lr=1e-3, bias_correction = True, betas=(0.9, 0.999), eps=1e-8
fairseq/optim/adam.py:198
Method__init__
(self, args, params)
fairseq/optim/nag.py:14
Method__init__
(self, args, params)
fairseq/optim/adamax.py:14
Method__init__
( self, init_scale=2.**15, scale_factor=2., scale_window=2000, tolerance=0.05, threshold=None,
fairseq/optim/fp16_optimizer.py:15
Method__init__
(self, args, params, optimizer)
fairseq/optim/fp16_optimizer.py:229
Method__init__
(self, args, optimizer)
fairseq/optim/lr_scheduler/reduce_lr_on_plateau.py:15
Method__init__
(self, args, optimizer)
fairseq/optim/lr_scheduler/inverse_square_root_schedule.py:29
Method__init__
(self, args, optimizer)
fairseq/optim/lr_scheduler/cosine_lr_scheduler.py:35
Method__init__
(self, args, optimizer)
fairseq/optim/lr_scheduler/triangular_lr_scheduler.py:18
Method__init__
(self, args, optimizer)
fairseq/optim/lr_scheduler/fairseq_lr_scheduler.py:11
Method__init__
(self, args, optimizer)
fairseq/optim/lr_scheduler/polynomial_decay_schedule.py:13
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