repo stringclasses 454
values | file_path stringlengths 5 201 | extension stringclasses 1
value | content stringlengths 8 509k | num_lines int64 3 16.9k | size_bytes int64 8 511k |
|---|---|---|---|---|---|
fairseq | fairseq/data/audio/waveform_transforms/__init__.py | .py | import os
from fairseq.data.audio import (
AudioTransform,
CompositeAudioTransform,
import_transforms,
register_audio_transform,
)
class AudioWaveformTransform(AudioTransform):
pass
AUDIO_WAVEFORM_TRANSFORM_REGISTRY = {}
AUDIO_WAVEFORM_TRANSFORM_CLASS_NAMES = set()
def get_audio_waveform_trans... | 49 | 1,146 |
fairseq | fairseq/data/audio/waveform_transforms/noiseaugment.py | .py | from pathlib import Path
import numpy as np
from math import ceil
from fairseq.data.audio import rand_uniform
from fairseq.data.audio.waveform_transforms import (
AudioWaveformTransform,
register_audio_waveform_transform,
)
SNR_MIN = 5.0
SNR_MAX = 15.0
RATE = 0.25
NOISE_RATE = 1.0
NOISE_LEN_MEAN = 0.2
NOISE_... | 202 | 6,913 |
fairseq | fairseq/data/audio/feature_transforms/__init__.py | .py | import os
from fairseq.data.audio import (
AudioTransform,
CompositeAudioTransform,
import_transforms,
register_audio_transform,
)
class AudioFeatureTransform(AudioTransform):
pass
AUDIO_FEATURE_TRANSFORM_REGISTRY = {}
AUDIO_FEATURE_TRANSFORM_CLASS_NAMES = set()
def get_audio_feature_transform... | 44 | 980 |
fairseq | fairseq/data/audio/feature_transforms/utterance_cmvn.py | .py | import numpy as np
from fairseq.data.audio.feature_transforms import (
AudioFeatureTransform,
register_audio_feature_transform,
)
@register_audio_feature_transform("utterance_cmvn")
class UtteranceCMVN(AudioFeatureTransform):
"""Utterance-level CMVN (cepstral mean and variance normalization)"""
@cla... | 42 | 1,186 |
fairseq | fairseq/data/audio/feature_transforms/delta_deltas.py | .py | import numpy as np
import torch
from fairseq.data.audio.feature_transforms import (
AudioFeatureTransform,
register_audio_feature_transform,
)
@register_audio_feature_transform("delta_deltas")
class DeltaDeltas(AudioFeatureTransform):
"""Expand delta-deltas features from spectrum."""
@classmethod
... | 38 | 1,194 |
fairseq | fairseq/data/audio/feature_transforms/global_cmvn.py | .py | import numpy as np
from fairseq.data.audio.feature_transforms import (
AudioFeatureTransform,
register_audio_feature_transform,
)
@register_audio_feature_transform("global_cmvn")
class GlobalCMVN(AudioFeatureTransform):
"""Global CMVN (cepstral mean and variance normalization). The global mean
and var... | 30 | 970 |
fairseq | fairseq/data/audio/feature_transforms/specaugment.py | .py | import math
import numbers
from typing import Optional
import numpy as np
from fairseq.data.audio.feature_transforms import (
AudioFeatureTransform,
register_audio_feature_transform,
)
@register_audio_feature_transform("specaugment")
class SpecAugmentTransform(AudioFeatureTransform):
"""SpecAugment (http... | 132 | 4,492 |
fairseq | fairseq/data/huffman/huffman_coder.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import re
import typing as tp
from collections import Counter, deque
from dataclasses import dataclass
from bitarray import bitarray, util
fr... | 268 | 8,627 |
fairseq | fairseq/data/huffman/__init__.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from .huffman_coder import HuffmanCodeBuilder, HuffmanCoder
from .huffman_mmap_indexed_dataset import (
HuffmanMMapIndex,
HuffmanMMapI... | 22 | 577 |
fairseq | fairseq/data/huffman/huffman_mmap_indexed_dataset.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import mmap
import os
import shutil
import struct
import typing as tp
from functools import lru_cache
import numpy as np
import torch
from fa... | 288 | 8,807 |
fairseq | fairseq/data/multilingual/multilingual_utils.py | .py | from enum import Enum
from typing import Dict, List, Optional, Sequence
import torch
from fairseq.data import Dictionary
class EncoderLangtok(Enum):
"""
Prepend to the beginning of source sentence either the
source or target language token. (src/tgt).
"""
src = "src"
tgt = "tgt"
class Lang... | 64 | 1,623 |
fairseq | fairseq/data/multilingual/sampling_method.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import logging
from typing import List
logger = logging.getLogger(__name__)
def uniform(dataset_sizes: List[int]):
return [1.0] * len(... | 79 | 2,068 |
fairseq | fairseq/data/multilingual/multilingual_data_manager.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import itertools
import json
import logging
import math
import os
from collections import OrderedDict, defaultdict
from argparse import Argume... | 1,157 | 44,987 |
fairseq | fairseq/data/multilingual/sampled_multi_epoch_dataset.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import hashlib
import logging
import math
import numpy as np
from fairseq.data import SampledMultiDataset
from .sampled_multi_dataset impor... | 200 | 7,823 |
fairseq | fairseq/data/multilingual/sampled_multi_dataset.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import datetime
import hashlib
import logging
import time
from bisect import bisect_right
from collections import OrderedDict, defaultdict
fro... | 469 | 18,339 |
fairseq | fairseq/data/legacy/__init__.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from .block_pair_dataset import BlockPairDataset
from .masked_lm_dataset import MaskedLMDataset
from .masked_lm_dictionary import BertDictiona... | 17 | 454 |
fairseq | fairseq/data/legacy/block_pair_dataset.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import math
import numpy as np
import torch
from fairseq.data import FairseqDataset
class BlockPairDataset(FairseqDataset):
"""Break a ... | 312 | 12,877 |
fairseq | fairseq/data/legacy/masked_lm_dataset.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import math
from typing import Dict, List, Tuple
import numpy as np
import torch
from fairseq.data import Dictionary, FairseqDataset, data_ut... | 304 | 12,168 |
fairseq | fairseq/data/legacy/masked_lm_dictionary.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from fairseq.data import Dictionary
class MaskedLMDictionary(Dictionary):
"""
Dictionary for Masked Language Modelling tasks. This e... | 61 | 1,560 |
fairseq | fairseq/data/encoders/nltk_tokenizer.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from fairseq.data.encoders import register_tokenizer
from fairseq.dataclass import FairseqDataclass
@register_tokenizer("nltk", dataclass=Fa... | 25 | 755 |
fairseq | fairseq/data/encoders/sentencepiece_bpe.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from dataclasses import dataclass, field
from typing import Optional
from fairseq import file_utils
from fairseq.data.encoders import registe... | 66 | 2,334 |
fairseq | fairseq/data/encoders/fastbpe.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from dataclasses import dataclass, field
from fairseq import file_utils
from fairseq.data.encoders import register_bpe
from fairseq.dataclass... | 37 | 1,157 |
fairseq | fairseq/data/encoders/utils.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
from fairseq.data import encoders
def get_whole_word_mask(args, dictionary):
bpe = encoders.build_bpe(args)
if bpe is n... | 31 | 909 |
fairseq | fairseq/data/encoders/byte_utils.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import re
WHITESPACE_NORMALIZER = re.compile(r"\s+")
SPACE = chr(32)
SPACE_ESCAPE = chr(9601)
# excluding non-breaking space (160) here
PRIN... | 52 | 1,643 |
fairseq | fairseq/data/encoders/__init__.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import importlib
import os
from fairseq import registry
build_tokenizer, register_tokenizer, TOKENIZER_REGISTRY, _ = registry.setup_regist... | 30 | 761 |
fairseq | fairseq/data/encoders/hf_bert_bpe.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from dataclasses import dataclass, field
from typing import Optional
from fairseq.data.encoders import register_bpe
from fairseq.dataclass im... | 51 | 1,642 |
fairseq | fairseq/data/encoders/hf_byte_bpe.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from dataclasses import dataclass, field
from fairseq.data.encoders import register_bpe
from fairseq.dataclass import FairseqDataclass
from f... | 51 | 1,710 |
fairseq | fairseq/data/encoders/subword_nmt_bpe.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from dataclasses import dataclass, field
from fairseq import file_utils
from fairseq.data.encoders import register_bpe
from fairseq.dataclass... | 55 | 1,791 |
fairseq | fairseq/data/encoders/moses_tokenizer.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from dataclasses import dataclass, field
from fairseq.data.encoders import register_tokenizer
from fairseq.dataclass import FairseqDataclass
... | 50 | 1,660 |
fairseq | fairseq/data/encoders/characters.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from fairseq.data.encoders import register_bpe
SPACE = chr(32)
SPACE_ESCAPE = chr(9601)
@register_bpe("characters")
class Characters(obje... | 31 | 684 |
fairseq | fairseq/data/encoders/gpt2_bpe_utils.py | .py | """
Byte pair encoding utilities from GPT-2.
Original source: https://github.com/openai/gpt-2/blob/master/src/encoder.py
Original license: MIT
"""
import json
from functools import lru_cache
@lru_cache()
def bytes_to_unicode():
"""
Returns list of utf-8 byte and a corresponding list of unicode strings.
... | 141 | 4,594 |
fairseq | fairseq/data/encoders/bytes.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from fairseq.data.encoders import register_bpe
from fairseq.data.encoders.byte_utils import (
SPACE,
SPACE_ESCAPE,
byte_encode,
... | 35 | 837 |
fairseq | fairseq/data/encoders/space_tokenizer.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import re
from fairseq.data.encoders import register_tokenizer
from fairseq.dataclass import FairseqDataclass
@register_tokenizer("space", ... | 22 | 590 |
fairseq | fairseq/data/encoders/gpt2_bpe.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from dataclasses import dataclass, field
from fairseq import file_utils
from fairseq.data.encoders import register_bpe
from fairseq.dataclass... | 46 | 1,488 |
fairseq | fairseq/data/encoders/byte_bpe.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from dataclasses import dataclass, field
from fairseq import file_utils
from fairseq.data.encoders import register_bpe
from fairseq.data.enc... | 49 | 1,404 |
fairseq | fairseq/modules/layer_drop.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
LayerDrop as described in https://arxiv.org/abs/1909.11556.
"""
import torch
import torch.nn as nn
class LayerDropModuleList(nn.ModuleLi... | 45 | 1,409 |
fairseq | fairseq/modules/transformer_layer.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from typing import Dict, List, Optional
import torch
import torch.nn as nn
from torch import Tensor
from fairseq import utils
from fairseq.m... | 563 | 21,701 |
fairseq | fairseq/modules/dynamic_crf_layer.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
This file is to re-implemented the low-rank and beam approximation of CRF layer
Proposed by:
Sun, Zhiqing, et al.
Fast Structured Decodin... | 190 | 7,717 |
fairseq | fairseq/modules/fairseq_dropout.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import logging
from typing import List, Optional
import torch.nn as nn
import torch.nn.functional as F
logger = logging.getLogger(__name__)... | 52 | 1,703 |
fairseq | fairseq/modules/multihead_attention.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import math
from typing import Dict, List, Optional, Tuple
import torch
import torch.nn.functional as F
from torch import Tensor, nn
from tor... | 911 | 35,236 |
fairseq | fairseq/modules/positional_encoding.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch.nn as nn
import math
import torch
class PositionalEncoding(nn.Module):
"""Positional encoding.
Args:
d_model: ... | 130 | 4,950 |
fairseq | fairseq/modules/transformer_layer_aug.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from typing import Dict, List, Optional
import torch
from numpy.random import uniform
from torch import Tensor
from fairseq.modules import L... | 316 | 13,235 |
fairseq | fairseq/modules/unfold.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch.nn.functional as F
def unfold1d(x, kernel_size: int, padding_l: int, pad_value: float = 0):
"""unfold T x B x C to T x B x ... | 20 | 615 |
fairseq | fairseq/modules/gelu.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
See "Gaussian Error Linear Units (GELUs)" by Dan Hendrycks and Kevin Gimpel with
the corresponding GitHub repo: https://github.com/hendryck... | 26 | 706 |
fairseq | fairseq/modules/sinusoidal_positional_embedding.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import math
from typing import Any, Optional
import torch
import torch.onnx.operators
from fairseq import utils
from torch import nn, Tensor
... | 123 | 4,686 |
fairseq | fairseq/modules/character_token_embedder.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import logging
from typing import List, Tuple
import torch
import torch.nn.functional as F
from fairseq.data import Dictionary
from torch imp... | 215 | 6,974 |
fairseq | fairseq/modules/sparse_transformer_sentence_encoder.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch.nn as nn
from fairseq.modules import TransformerSentenceEncoder
from fairseq.modules.sparse_transformer_sentence_encoder_layer im... | 97 | 3,155 |
fairseq | fairseq/modules/scalar_bias.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
#
import torch
class ScalarBias(torch.autograd.Function):
"""
Adds a vector of scalars, used in self-attention mechanism to allow
... | 32 | 888 |
fairseq | fairseq/modules/__init__.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""isort:skip_file"""
from .adaptive_input import AdaptiveInput
from .adaptive_softmax import AdaptiveSoftmax
from .base_layer import BaseLaye... | 107 | 3,686 |
fairseq | fairseq/modules/cross_entropy.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import logging
import torch
import torch.nn.functional as F
logger = logging.getLogger(__name__)
def _cross_entropy_pytorch(logits, target... | 60 | 1,871 |
fairseq | fairseq/modules/checkpoint_activations.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import functools
from typing import Any, Dict, List, Tuple, Union
import torch
import torch.utils.checkpoint as checkpoint
from fairseq impor... | 243 | 8,825 |
fairseq | fairseq/modules/sparse_multihead_attention.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import math
import torch
from .multihead_attention import MultiheadAttention
class SparseMultiheadAttention(MultiheadAttention):
"""Sp... | 141 | 4,931 |
fairseq | fairseq/modules/transformer_sentence_encoder.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from typing import Optional, Tuple
import torch
import torch.nn as nn
from fairseq.modules import (
FairseqDropout,
LayerDropModuleLi... | 292 | 10,162 |
fairseq | fairseq/modules/transpose_last.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
transpose last 2 dimensions of the input
"""
import torch.nn as nn
class TransposeLast(nn.Module):
def __init__(self, deconstruct_id... | 22 | 623 |
fairseq | fairseq/modules/ema_module.py | .py | #!/usr/bin/env python3
"""
Used for EMA tracking a given pytorch module. The user is responsible for calling step()
and setting the appropriate decay
"""
import copy
from dataclasses import dataclass, field
import logging
import torch
from omegaconf import II
from fairseq.dataclass import FairseqDataclass
try:
... | 216 | 6,741 |
fairseq | fairseq/modules/vggblock.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from __future__ import absolute_import, division, print_function, unicode_literals
from collections.abc import Iterable
from itertools import... | 117 | 4,057 |
fairseq | fairseq/modules/fp32_group_norm.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
Layer norm done in fp32 (for fp16 training)
"""
import torch.nn as nn
import torch.nn.functional as F
class Fp32GroupNorm(nn.GroupNorm):... | 26 | 727 |
fairseq | fairseq/modules/lightweight_convolution.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
import torch.nn as nn
import torch.nn.functional as F
from fairseq import utils
from fairseq.incremental_decoding_utils import wi... | 311 | 10,919 |
fairseq | fairseq/modules/sparse_transformer_sentence_encoder_layer.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from fairseq.modules import TransformerSentenceEncoderLayer
from fairseq.modules.sparse_multihead_attention import SparseMultiheadAttention
... | 52 | 1,563 |
fairseq | fairseq/modules/quant_noise.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
import torch.nn as nn
def quant_noise(module, p, block_size):
"""
Wraps modules and applies quantization noise to the w... | 108 | 4,005 |
fairseq | fairseq/modules/fp32_instance_norm.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
Layer norm done in fp32 (for fp16 training)
"""
import torch.nn as nn
import torch.nn.functional as F
class Fp32InstanceNorm(nn.Instance... | 36 | 1,238 |
fairseq | fairseq/modules/layer_norm.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
import torch.nn as nn
import torch.nn.functional as F
try:
from apex.normalization import FusedLayerNorm as _FusedLayerNorm
... | 49 | 1,524 |
fairseq | fairseq/modules/kmeans_vector_quantizer.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
import torch.nn as nn
from fairseq.modules import Fp32GroupNorm
class KmeansVectorQuantizer(nn.Module):
def __init__(
... | 129 | 4,236 |
fairseq | fairseq/modules/espnet_multihead_attention.py | .py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2019 Shigeki Karita
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Multi-Head Attention layer definition."""
import math
import torch
from torch import nn
from fairseq.modules.rotary_positional_embedding import (
RotaryPositionalEmbeddi... | 257 | 9,673 |
fairseq | fairseq/modules/dynamic_convolution.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from typing import Dict, Optional
import torch
import torch.nn as nn
import torch.nn.functional as F
from fairseq import utils
from fairseq.i... | 527 | 19,697 |
fairseq | fairseq/modules/downsampled_multihead_attention.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
#
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
from fairseq.modules.fairseq_dropout import FairseqDropout
... | 318 | 10,672 |
fairseq | fairseq/modules/same_pad.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from torch import nn
class SamePad(nn.Module):
def __init__(self, kernel_size, causal=False):
super().__init__()
if cau... | 34 | 863 |
fairseq | fairseq/modules/kmeans_attention.py | .py | import math
from functools import reduce, wraps
from inspect import isfunction
from operator import mul
import torch
import torch.nn as nn
import torch.nn.functional as F
from aml.multimodal_video.utils.einops.lib import rearrange, repeat
from aml.multimodal_video.utils.einops.lib.layers.torch import Rearrange
from f... | 745 | 21,840 |
fairseq | fairseq/modules/conformer_layer.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from typing import Optional
import torch
from fairseq.modules import (
ESPNETMultiHeadedAttention,
LayerNorm,
MultiheadAttentio... | 302 | 9,132 |
fairseq | fairseq/modules/positional_embedding.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch.nn as nn
from .learned_positional_embedding import LearnedPositionalEmbedding
from .sinusoidal_positional_embedding import Sinus... | 38 | 1,360 |
fairseq | fairseq/modules/beamable_mm.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
import torch.nn as nn
class BeamableMM(nn.Module):
"""This module provides an optimized MM for beam decoding with attention... | 50 | 1,763 |
fairseq | fairseq/modules/fp32_batch_norm.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
batch norm done in fp32 (for fp16 training)
"""
import torch
import torch.nn as nn
class Fp32BatchNorm(nn.Module):
def __init__(self,... | 45 | 1,320 |
fairseq | fairseq/modules/linearized_convolution.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
import torch.nn.functional as F
from fairseq import utils
from fairseq.incremental_decoding_utils import with_incremental_state
... | 126 | 4,744 |
fairseq | fairseq/modules/rotary_positional_embedding.py | .py | import torch
class RotaryPositionalEmbedding(torch.nn.Module):
def __init__(self, dim, base=10000, precision=torch.half):
"""Rotary positional embedding
Reference : https://blog.eleuther.ai/rotary-embeddings/
Paper: https://arxiv.org/pdf/2104.09864.pdf
Args:
dim: Dimens... | 51 | 1,966 |
fairseq | fairseq/modules/learned_positional_embedding.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from typing import Dict, Optional
import torch
import torch.nn as nn
import torch.nn.functional as F
from fairseq import utils
from torch imp... | 62 | 2,259 |
fairseq | fairseq/modules/gumbel_vector_quantizer.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
import torch.nn as nn
import torch.nn.functional as F
class GumbelVectorQuantizer(nn.Module):
def __init__(
self,
... | 213 | 7,150 |
fairseq | fairseq/modules/grad_multiply.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
class GradMultiply(torch.autograd.Function):
@staticmethod
def forward(ctx, x, scale):
ctx.scale = scale
... | 19 | 442 |
fairseq | fairseq/modules/transformer_sentence_encoder_layer.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from typing import Callable, Optional
import torch
import torch.nn as nn
from fairseq import utils
from fairseq.modules import LayerNorm, Mul... | 140 | 4,326 |
fairseq | fairseq/modules/adaptive_softmax.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import functools
import operator
import torch
import torch.nn.functional as F
from fairseq.modules.fairseq_dropout import FairseqDropout
from... | 269 | 8,789 |
fairseq | fairseq/modules/base_layer.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch.nn as nn
import torch
import sys
from fairseq import utils
from fairseq.distributed import utils as distributed_utils
from fairse... | 171 | 6,693 |
fairseq | fairseq/modules/adaptive_input.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from typing import List
import torch
from torch import nn
from fairseq.modules.quant_noise import quant_noise
class AdaptiveInput(nn.Modu... | 82 | 2,565 |
fairseq | fairseq/modules/conv_tbc.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
from torch import nn
from torch.nn.modules.utils import _single
from torch import Tensor
class ConvTBC(torch.nn.Module):
""... | 54 | 1,683 |
fairseq | fairseq/modules/lstm_cell_with_zoneout.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch.nn as nn
class LSTMCellWithZoneOut(nn.Module):
"""
Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations... | 38 | 1,220 |
fairseq | fairseq/modules/location_attention.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch.nn as nn
import torch
import torch.nn.functional as F
class LocationAttention(nn.Module):
"""
Attention-Based Models fo... | 84 | 2,909 |
fairseq | fairseq/modules/dynamicconv_layer/setup.py | .py | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from setuptools import setup
from torch.utils.cpp_extension import BuildExtension, CUDAExtension
setup(
name="dyn... | 24 | 602 |
fairseq | fairseq/modules/dynamicconv_layer/dynamicconv_layer.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import dynamicconv_cuda
import torch
import torch.nn.functional as F
from fairseq import utils
from fairseq.incremental_decoding_utils import ... | 228 | 8,922 |
fairseq | fairseq/modules/dynamicconv_layer/cuda_function_gen.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
def gen_forward():
kernels = [3, 5, 7, 15, 31, 63, 127, 255]
blocks = [32, 64, 128, 256]
head = """
/**
* Copyright (c) Facebo... | 224 | 6,866 |
fairseq | fairseq/modules/quantization/quantization_options.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
def parse_config_yaml(yaml_data):
# Initialize to default options.
quantization_options = {
"n_centroids": {
"Lin... | 45 | 1,647 |
fairseq | fairseq/modules/quantization/pq/utils.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import logging
import re
from operator import attrgetter, itemgetter
import torch
import numpy as np
import torch.distributed as dist
import t... | 377 | 13,493 |
fairseq | fairseq/modules/quantization/pq/pq.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from .em import EM, EmptyClusterResolveError
class PQ(EM):
"""
Quantizes the layer weights W with the standard Product Quantization
... | 129 | 4,292 |
fairseq | fairseq/modules/quantization/pq/em.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import logging
import os
import random
from collections import Counter
import torch
class EM:
"""
EM algorithm used to quantize the... | 212 | 7,333 |
fairseq | fairseq/modules/quantization/pq/modules/qlinear.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
import torch.nn as nn
import torch.nn.functional as F
class PQLinear(nn.Module):
"""
Quantized counterpart of nn.Linear... | 72 | 2,547 |
fairseq | fairseq/modules/quantization/pq/modules/qemb.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
import torch.nn as nn
import torch.nn.functional as F
class PQEmbedding(nn.Module):
"""
Quantized counterpart of nn.Emb... | 108 | 3,719 |
fairseq | fairseq/modules/quantization/pq/modules/qconv.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.modules.utils import _pair
class PQConv2... | 116 | 4,245 |
fairseq | fairseq/modules/quantization/scalar/utils.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import logging
from operator import attrgetter
import torch.distributed as dist
import torch.nn as nn
from ..pq.utils import attrsetter, get... | 81 | 2,657 |
fairseq | fairseq/modules/quantization/scalar/ops.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
try:
import torch.ao.quantization as quantization
except ImportError:
import torch.quantization as quantization
def em... | 60 | 2,029 |
fairseq | fairseq/modules/quantization/scalar/modules/qlinear.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
import torch.nn as nn
import torch.nn.functional as F
from ..ops import emulate_int
class IntLinear(nn.Module):
"""
Qu... | 114 | 3,629 |
fairseq | fairseq/modules/quantization/scalar/modules/qemb.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
import torch.nn as nn
import torch.nn.functional as F
from ..ops import emulate_int
class IntEmbedding(nn.Module):
"""
... | 148 | 4,984 |
fairseq | fairseq/modules/quantization/scalar/modules/qact.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
from ..ops import emulate_int
class ActivationQuantizer:
"""
Fake scalar quantization of the activations using a forwa... | 89 | 3,077 |
fairseq | fairseq/modules/quantization/scalar/modules/qconv.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
import torch.nn.functional as F
from torch.nn.modules.conv import _ConvNd
from torch.nn.modules.utils import _pair
from ..ops im... | 150 | 4,448 |
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