repo stringlengths 1 99 | file stringlengths 13 215 | code stringlengths 12 59.2M | file_length int64 12 59.2M | avg_line_length float64 3.82 1.48M | max_line_length int64 12 2.51M | extension_type stringclasses 1
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rej-summ | rej-summ-main/fairseq/data/transform_eos_concat_langpair_dataset.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
from torch.utils.data.dataloader import default_collate
from fairseq.data import ConcatDataset
logger = logging... | 5,170 | 35.935714 | 111 | py |
rej-summ | rej-summ-main/fairseq/data/token_block_dataset.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
from fairseq.data import FairseqDataset, plasma_utils
from fairseq.data.indexed_dataset import best_fitting_in... | 7,652 | 35.971014 | 87 | py |
rej-summ | rej-summ-main/fairseq/data/subsample_dataset.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 numpy as np
from . import BaseWrapperDataset
logger = logging.getLogger(__name__)
class SubsampleDataset(BaseWrapp... | 2,117 | 28.013699 | 101 | py |
rej-summ | rej-summ-main/fairseq/data/prepend_dataset.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
from . import BaseWrapperDataset
class PrependDataset(BaseWrapperDataset):
def __init__(self, dataset, ... | 953 | 31.896552 | 83 | py |
rej-summ | rej-summ-main/fairseq/data/base_wrapper_dataset.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.utils.data.dataloader import default_collate
from . import FairseqDataset
class BaseWrapperDataset(FairseqDataset):
def __in... | 2,153 | 26.265823 | 70 | py |
rej-summ | rej-summ-main/fairseq/data/raw_label_dataset.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 . import FairseqDataset
class RawLabelDataset(FairseqDataset):
def __init__(self, labels):
super().__init__()... | 546 | 21.791667 | 65 | py |
rej-summ | rej-summ-main/fairseq/data/resampling_dataset.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 numpy as np
from fairseq.data import BaseWrapperDataset, plasma_utils
logger = logging.getLogger(__name__)
class Re... | 4,314 | 29.821429 | 78 | py |
rej-summ | rej-summ-main/fairseq/data/dictionary.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 os
from collections import Counter
from multiprocessing import Pool
import torch
from fairseq import utils
from fairseq.data import da... | 12,903 | 31.099502 | 96 | py |
rej-summ | rej-summ-main/fairseq/data/append_token_dataset.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
from . import BaseWrapperDataset
class AppendTokenDataset(BaseWrapperDataset):
def __init__(self, datas... | 1,065 | 24.380952 | 65 | py |
rej-summ | rej-summ-main/fairseq/data/codedataset.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 json
import logging
import os
import random
from pathlib import Path
import numpy as np
import torch
import torch.utils.data
from . ... | 18,486 | 31.039861 | 109 | py |
rej-summ | rej-summ-main/fairseq/data/fasta_dataset.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 os
import subprocess
import threading
from pathlib import Path
import numpy as np
import torch
def fasta_file_path(prefix_path):
... | 3,387 | 30.37037 | 107 | py |
rej-summ | rej-summ-main/fairseq/data/mask_tokens_dataset.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 functools import lru_cache
import numpy as np
import torch
from fairseq.data import Dictionary, data_utils
from . import BaseWrapperDat... | 8,777 | 38.719457 | 102 | py |
rej-summ | rej-summ-main/fairseq/data/concat_dataset.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 bisect
import numpy as np
from torch.utils.data.dataloader import default_collate
from . import FairseqDataset
class ConcatDataset(... | 4,645 | 36.168 | 86 | py |
rej-summ | rej-summ-main/fairseq/data/data_utils.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.
try:
from collections.abc import Iterable
except ImportError:
from collections import Iterable
import contextlib
import itertools
impo... | 21,791 | 35.019835 | 120 | py |
rej-summ | rej-summ-main/fairseq/data/nested_dictionary_dataset.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 collections import OrderedDict
import torch
from torch.utils.data.dataloader import default_collate
from . import FairseqDataset
def ... | 4,029 | 30.984127 | 86 | py |
rej-summ | rej-summ-main/fairseq/data/add_target_dataset.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 . import BaseWrapperDataset, data_utils
from fairseq.data.text_compressor import TextCompressor, TextCompressionLevel
cla... | 2,996 | 34.678571 | 88 | py |
rej-summ | rej-summ-main/fairseq/data/transform_eos_lang_pair_dataset.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 . import FairseqDataset
class TransformEosLangPairDataset(FairseqDataset):
"""A :class:... | 3,856 | 32.833333 | 98 | py |
rej-summ | rej-summ-main/fairseq/data/lm_context_window_dataset.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
from typing import Dict
from fairseq.data.monolingual_dataset import MonolingualDataset
from . import Fairse... | 3,381 | 33.510204 | 90 | py |
rej-summ | rej-summ-main/fairseq/data/span_mask_tokens_dataset.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
from . import Dictionary, FairseqDataset, data_utils
def collate(
samples,
pad_idx,
eos_idx,
... | 10,888 | 36.037415 | 206 | py |
rej-summ | rej-summ-main/fairseq/data/colorize_dataset.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 . import BaseWrapperDataset
class ColorizeDataset(BaseWrapperDataset):
"""Adds 'colors' property to net input that is... | 843 | 31.461538 | 111 | py |
rej-summ | rej-summ-main/fairseq/data/iterators.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 logging
import math
import operator
import os
import queue
import time
from threading import Thread
from typing import... | 31,799 | 34.972851 | 94 | py |
rej-summ | rej-summ-main/fairseq/data/backtranslation_dataset.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 import utils
from . import FairseqDataset
def backtranslate_samples(samples, collate_fn, generate_fn, cuda=True):... | 6,247 | 36.638554 | 84 | py |
rej-summ | rej-summ-main/fairseq/data/monolingual_dataset.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
from . import FairseqDataset, data_utils
def collate(samples, pad_idx, eos_idx, fixed_pad_length=None, pad_... | 8,832 | 33.775591 | 110 | py |
rej-summ | rej-summ-main/fairseq/data/roll_dataset.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 . import BaseWrapperDataset
class RollDataset(BaseWrapperDataset):
def __init__(self, dataset, shifts):
super... | 485 | 24.578947 | 65 | py |
rej-summ | rej-summ-main/fairseq/data/replace_dataset.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 . import BaseWrapperDataset
class ReplaceDataset(BaseWrapperDataset):
"""Replaces tokens found in the dataset by a specified replac... | 1,370 | 36.054054 | 113 | py |
rej-summ | rej-summ-main/fairseq/data/id_dataset.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 . import FairseqDataset
class IdDataset(FairseqDataset):
def __getitem__(self, index):
return index
def ... | 423 | 20.2 | 65 | py |
rej-summ | rej-summ-main/fairseq/data/indexed_dataset.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 shutil
import struct
from functools import lru_cache
import numpy as np
import torch
from fairseq.dataclass.constants import DATASET_I... | 18,265 | 30.064626 | 102 | py |
rej-summ | rej-summ-main/fairseq/data/denoising_dataset.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 . import FairseqDataset, data_utils
def collate(
samples,
pad_idx,
eos_idx,
... | 15,685 | 34.328829 | 88 | py |
rej-summ | rej-summ-main/fairseq/data/prepend_token_dataset.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
from . import BaseWrapperDataset
class PrependTokenDataset(BaseWrapperDataset):
def __init__(self, data... | 1,066 | 24.404762 | 65 | py |
rej-summ | rej-summ-main/fairseq/data/numel_dataset.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
from . import BaseWrapperDataset
class NumelDataset(BaseWrapperDataset):
def __init__(self, dataset, re... | 786 | 23.59375 | 65 | py |
rej-summ | rej-summ-main/fairseq/data/noising.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
from fairseq.data import data_utils
class WordNoising(object):
"""Generate a noisy version of a sentence... | 12,422 | 36.083582 | 88 | py |
rej-summ | rej-summ-main/fairseq/data/bucket_pad_length_dataset.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.nn.functional as F
from fairseq.data import BaseWrapperDataset
from fairseq.data.data_utils import get_buckets... | 2,360 | 28.886076 | 79 | py |
rej-summ | rej-summ-main/fairseq/data/concat_sentences_dataset.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 . import FairseqDataset
class ConcatSentencesDataset(FairseqDataset):
def __init__(self, *datasets):
super().... | 1,558 | 27.345455 | 83 | py |
rej-summ | rej-summ-main/fairseq/data/fairseq_dataset.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 numpy as np
import torch.utils.data
from fairseq.data import data_utils
logger = logging.getLogger(__name__)
class Ep... | 7,123 | 33.582524 | 91 | py |
rej-summ | rej-summ-main/fairseq/data/transform_eos_dataset.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 . import FairseqDataset
class TransformEosDataset(FairseqDataset):
"""A :class:`~fairseq.data.FairseqDataset` wrapper... | 4,575 | 36.818182 | 88 | py |
rej-summ | rej-summ-main/fairseq/data/multilingual/sampled_multi_dataset.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... | 18,339 | 38.104478 | 119 | py |
rej-summ | rej-summ-main/fairseq/data/multilingual/multilingual_utils.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... | 1,623 | 24.375 | 85 | py |
rej-summ | rej-summ-main/fairseq/data/multilingual/sampled_multi_epoch_dataset.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... | 7,823 | 38.12 | 119 | py |
rej-summ | rej-summ-main/fairseq/data/audio/hubert_dataset.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 logging
import os
import sys
from typing import Any, List, Optional, Union
import numpy as np
import torch
import to... | 12,719 | 34.630252 | 86 | py |
rej-summ | rej-summ-main/fairseq/data/audio/multi_modality_dataset.py | # Copyright (c) 2021-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the license found in the LICENSE file in
# the root directory of this source tree. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
import logging
import math
from ty... | 10,161 | 34.65614 | 93 | py |
rej-summ | rej-summ-main/fairseq/data/audio/speech_to_speech_dataset.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 dataclasses import dataclass
from pathlib import Path
from typing import Dict, List, Optional, Tuple
import torch
from f... | 13,850 | 35.45 | 99 | py |
rej-summ | rej-summ-main/fairseq/data/audio/text_to_speech_dataset.py | # Copyright (c) 2017-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the license found in the LICENSE file in
# the root directory of this source tree. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.abs
from dataclasses import datacla... | 8,669 | 33.541833 | 87 | py |
rej-summ | rej-summ-main/fairseq/data/audio/frm_text_to_speech_dataset.py | # Copyright (c) 2017-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the license found in the LICENSE file in
# the root directory of this source tree. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.abs
import csv
import logging
impor... | 6,923 | 32.61165 | 86 | py |
rej-summ | rej-summ-main/fairseq/data/audio/raw_audio_dataset.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 sys
import io
import numpy as np
import torch
import torch.nn.functional as F
from .. import FairseqDataset... | 13,679 | 33.720812 | 111 | py |
rej-summ | rej-summ-main/fairseq/data/audio/audio_utils.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
from pathlib import Path
import io
from typing import BinaryIO, List, Optional, Tuple, Union
import numpy as np
import torch
imp... | 13,330 | 33.182051 | 84 | py |
rej-summ | rej-summ-main/fairseq/data/audio/speech_to_text_dataset.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 csv
import logging
import re
from argparse import Namespace
from collections import defaultdict
from dataclasses import dataclass
from ... | 26,935 | 35.697548 | 87 | py |
rej-summ | rej-summ-main/fairseq/data/audio/speech_to_text_joint_dataset.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 pathlib import Path
from typing import Dict, List, NamedTuple, Optional
import torch
from fairseq.data import ConcatData... | 12,746 | 34.408333 | 86 | py |
rej-summ | rej-summ-main/fairseq/data/audio/dataset_transforms/noisyoverlapaugment.py | import numpy as np
import torch
from fairseq.data.audio import rand_uniform
from fairseq.data.audio.dataset_transforms import (
AudioDatasetTransform,
register_audio_dataset_transform,
)
from fairseq.data.audio.waveform_transforms.noiseaugment import (
NoiseAugmentTransform,
)
_DEFAULTS = {
"rate": 0.... | 3,743 | 34.320755 | 86 | py |
rej-summ | rej-summ-main/fairseq/data/audio/feature_transforms/delta_deltas.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
... | 1,192 | 30.394737 | 79 | py |
rej-summ | rej-summ-main/fairseq/data/encoders/utils.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... | 909 | 28.354839 | 67 | py |
rej-summ | rej-summ-main/fairseq/data/huffman/huffman_mmap_indexed_dataset.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... | 8,807 | 29.583333 | 108 | py |
rej-summ | rej-summ-main/fairseq/data/legacy/block_pair_dataset.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 ... | 12,877 | 40.275641 | 99 | py |
rej-summ | rej-summ-main/fairseq/data/legacy/masked_lm_dataset.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... | 12,168 | 39.029605 | 88 | py |
rej-summ | rej-summ-main/fairseq/tasks/text_to_speech.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 os.path as op
import torch
import torch.nn.functional as F
import numpy as np
from fairseq.data.audio.text_t... | 17,256 | 33.376494 | 88 | py |
rej-summ | rej-summ-main/fairseq/tasks/translation_from_pretrained_bart.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 import utils
from fairseq.data import LanguagePairDataset
from . import register_task
from .translation import Tran... | 5,243 | 38.428571 | 108 | py |
rej-summ | rej-summ-main/fairseq/tasks/language_modeling.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
from dataclasses import dataclass, field
from typing import Optional
import numpy as np
import torch
from fairseq im... | 13,952 | 35.335938 | 91 | py |
rej-summ | rej-summ-main/fairseq/tasks/translation.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
import itertools
import json
import logging
import os
from os import path
from typing import Optional... | 18,865 | 35.141762 | 108 | py |
rej-summ | rej-summ-main/fairseq/tasks/multilingual_masked_lm.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 numpy as np
import torch
from fairseq import utils
from fairseq.data import (
ConcatDataset,
Diction... | 12,144 | 34.825959 | 87 | py |
rej-summ | rej-summ-main/fairseq/tasks/multilingual_language_modeling.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
from dataclasses import dataclass, field
from typing import Optional
import numpy as np
import torch
from omegaconf ... | 22,960 | 35.562102 | 102 | py |
rej-summ | rej-summ-main/fairseq/tasks/online_backtranslation.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 contextlib
import json
import logging
import math
import os
from argparse import Namespace
from collections import OrderedDict, default... | 28,618 | 40.901903 | 118 | py |
rej-summ | rej-summ-main/fairseq/tasks/speech_ulm_task.py | # Copyright (c) 2017-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the license found in the LICENSE file in
# the root directory of this source tree. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
import logging
import sys
import t... | 7,533 | 32.484444 | 88 | py |
rej-summ | rej-summ-main/fairseq/tasks/multilingual_translation.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 contextlib
import logging
import os
from collections import OrderedDict
from argparse import ArgumentError
import torch
from fairseq i... | 18,165 | 38.235421 | 118 | py |
rej-summ | rej-summ-main/fairseq/tasks/translation_lev.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
import torch
from fairseq import utils
from fairseq.data import LanguagePairDataset
from fairseq.data... | 7,416 | 36.841837 | 103 | py |
rej-summ | rej-summ-main/fairseq/tasks/fairseq_task.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 warnings
from argparse import Namespace
from typing import Any, Callable, Dict, List
import torch
from fairse... | 26,707 | 37.428777 | 110 | py |
rej-summ | rej-summ-main/fairseq/tasks/speech_to_speech.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 json
import logging
import math
from argparse import Namespace
from pathlib import Path
from typing import List
import torch
import to... | 22,609 | 36.809365 | 130 | py |
rej-summ | rej-summ-main/fairseq/tasks/nlu_finetuning.py | # Copyright (c) 2017-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the license found in the LICENSE file in
# the root directory of this source tree. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
import logging
import os
import to... | 19,006 | 38.763598 | 95 | py |
rej-summ | rej-summ-main/fairseq/tasks/audio_finetuning.py | # Copyright (c) 2017-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the license found in the LICENSE file in
# the root directory of this source tree. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
import logging
import os
import to... | 13,503 | 38.255814 | 95 | py |
rej-summ | rej-summ-main/fairseq/tasks/translation_multi_simple_epoch.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 logging
import time
import torch
from fairseq.data import (
FairseqDataset,
LanguagePairDataset,
ListDatas... | 17,926 | 39.558824 | 113 | py |
rej-summ | rej-summ-main/docs/conf.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# fairseq documentation build configuration file, created by
# sphinx-quickstart on Fri Aug 17 21:45:30 2018.
#
# This file is execfile()d with the current directory set to its
# containing dir.
#
# Note that not all possible configuration values are present in this
# au... | 3,133 | 30.656566 | 79 | py |
rej-summ | rej-summ-main/fairseq_cli/generate.py | #!/usr/bin/env python3 -u
# 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.
"""
Translate pre-processed data with a trained model.
"""
import ast
import logging
import math
import os
import sy... | 15,805 | 36.813397 | 180 | py |
rej-summ | rej-summ-main/fairseq_cli/validate.py | #!/usr/bin/env python3 -u
# 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 sys
from argparse import Namespace
from itertools import chain
import torch
from om... | 5,228 | 32.954545 | 88 | py |
rej-summ | rej-summ-main/fairseq_cli/hydra_train.py | #!/usr/bin/env python3 -u
# 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 hydra
import torch
from hydra.core.hydra_config import HydraConfig
from omegaconf i... | 2,714 | 28.51087 | 116 | py |
rej-summ | rej-summ-main/fairseq_cli/eval_lm.py | #!/usr/bin/env python3 -u
# 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.
"""
Evaluate the perplexity of a trained language model.
"""
import logging
import math
import os
import sys
from a... | 11,960 | 33.37069 | 108 | py |
rej-summ | rej-summ-main/fairseq_cli/interactive.py | #!/usr/bin/env python3 -u
# 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.
"""
Translate raw text with a trained model. Batches data on-the-fly.
"""
import ast
import fileinput
import logging... | 11,465 | 35.056604 | 88 | py |
rej-summ | rej-summ-main/fairseq_cli/train.py | #!/usr/bin/env python3 -u
# 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.
"""
Train a new model on one or across multiple GPUs.
"""
import argparse
import logging
import math
import os
impor... | 19,932 | 34.279646 | 108 | py |
graphmp | graphmp-master/graphmp.py | # -*- coding: utf-8 -*-
# !/usr/bin/env python
import numpy as np
import tensorflow as tf
import argparse
import math
import glob
import tensorflow.contrib.layers as layers
import os
import random
from tensorflow.contrib import rnn
from sklearn import metrics
def pairwise_distance(cate_pattern):
"""Compute pair... | 30,765 | 46.773292 | 165 | py |
gen-efficientnet-pytorch | gen-efficientnet-pytorch-master/caffe2_validate.py | """ Caffe2 validation script
This script is created to verify exported ONNX models running in Caffe2
It utilizes the same PyTorch dataloader/processing pipeline for a
fair comparison against the originals.
Copyright 2020 Ross Wightman
"""
import argparse
import numpy as np
from caffe2.python import core, workspace, m... | 5,993 | 42.122302 | 113 | py |
gen-efficientnet-pytorch | gen-efficientnet-pytorch-master/setup.py | """ Setup
"""
from setuptools import setup, find_packages
from codecs import open
from os import path
here = path.abspath(path.dirname(__file__))
# Get the long description from the README file
with open(path.join(here, 'README.md'), encoding='utf-8') as f:
long_description = f.read()
exec(open('geffnet/version.... | 1,737 | 35.208333 | 81 | py |
gen-efficientnet-pytorch | gen-efficientnet-pytorch-master/hubconf.py | dependencies = ['torch', 'math']
from geffnet import efficientnet_b0
from geffnet import efficientnet_b1
from geffnet import efficientnet_b2
from geffnet import efficientnet_b3
from geffnet import efficientnet_es
from geffnet import efficientnet_lite0
from geffnet import mixnet_s
from geffnet import mixnet_m
from g... | 2,730 | 31.129412 | 52 | py |
gen-efficientnet-pytorch | gen-efficientnet-pytorch-master/validate.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import argparse
import time
import torch
import torch.nn as nn
import torch.nn.parallel
from contextlib import suppress
import geffnet
from data import Dataset, create_loader, resolve_data_config
from utils im... | 6,632 | 38.718563 | 94 | py |
gen-efficientnet-pytorch | gen-efficientnet-pytorch-master/caffe2_benchmark.py | """ Caffe2 validation script
This script runs Caffe2 benchmark on exported ONNX model.
It is a useful tool for reporting model FLOPS.
Copyright 2020 Ross Wightman
"""
import argparse
from caffe2.python import core, workspace, model_helper
from caffe2.proto import caffe2_pb2
parser = argparse.ArgumentParser(descript... | 2,428 | 35.80303 | 91 | py |
gen-efficientnet-pytorch | gen-efficientnet-pytorch-master/onnx_to_caffe.py | import argparse
import onnx
from caffe2.python.onnx.backend import Caffe2Backend
parser = argparse.ArgumentParser(description="Convert ONNX to Caffe2")
parser.add_argument("model", help="The ONNX model")
parser.add_argument("--c2-prefix", required=True,
help="The output file prefix for the caffe2 model init and... | 843 | 29.142857 | 84 | py |
gen-efficientnet-pytorch | gen-efficientnet-pytorch-master/onnx_export.py | """ ONNX export script
Export PyTorch models as ONNX graphs.
This export script originally started as an adaptation of code snippets found at
https://pytorch.org/tutorials/advanced/super_resolution_with_onnxruntime.html
The default parameters work with PyTorch 1.6 and ONNX 1.7 and produce an optimal ONNX graph
for h... | 5,821 | 47.115702 | 119 | py |
gen-efficientnet-pytorch | gen-efficientnet-pytorch-master/geffnet/efficientnet_builder.py | """ EfficientNet / MobileNetV3 Blocks and Builder
Copyright 2020 Ross Wightman
"""
import re
from copy import deepcopy
from .conv2d_layers import *
from geffnet.activations import *
__all__ = ['get_bn_args_tf', 'resolve_bn_args', 'resolve_se_args', 'resolve_act_layer', 'make_divisible',
'round_channels', ... | 26,514 | 37.76462 | 124 | py |
gen-efficientnet-pytorch | gen-efficientnet-pytorch-master/geffnet/conv2d_layers.py | """ Conv2D w/ SAME padding, CondConv, MixedConv
A collection of conv layers and padding helpers needed by EfficientNet, MixNet, and
MobileNetV3 models that maintain weight compatibility with original Tensorflow models.
Copyright 2020 Ross Wightman
"""
import collections.abc
import math
from functools import partial
f... | 12,093 | 38.652459 | 119 | py |
gen-efficientnet-pytorch | gen-efficientnet-pytorch-master/geffnet/gen_efficientnet.py | """ Generic Efficient Networks
A generic MobileNet class with building blocks to support a variety of models:
* EfficientNet (B0-B8, L2 + Tensorflow pretrained AutoAug/RandAug/AdvProp/NoisyStudent ports)
- EfficientNet: Rethinking Model Scaling for CNNs - https://arxiv.org/abs/1905.11946
- CondConv: Conditionally... | 59,925 | 40.299793 | 144 | py |
gen-efficientnet-pytorch | gen-efficientnet-pytorch-master/geffnet/mobilenetv3.py | """ MobileNet-V3
A PyTorch impl of MobileNet-V3, compatible with TF weights from official impl.
Paper: Searching for MobileNetV3 - https://arxiv.org/abs/1905.02244
Hacked together by / Copyright 2020 Ross Wightman
"""
import torch.nn as nn
import torch.nn.functional as F
from .activations import get_act_fn, get_act... | 15,009 | 40.123288 | 137 | py |
gen-efficientnet-pytorch | gen-efficientnet-pytorch-master/geffnet/config.py | """ Global layer config state
"""
from typing import Any, Optional
__all__ = [
'is_exportable', 'is_scriptable', 'is_no_jit', 'layer_config_kwargs',
'set_exportable', 'set_scriptable', 'set_no_jit', 'set_layer_config'
]
# Set to True if prefer to have layers with no jit optimization (includes activations)
_NO... | 3,350 | 26.024194 | 102 | py |
gen-efficientnet-pytorch | gen-efficientnet-pytorch-master/geffnet/helpers.py | """ Checkpoint loading / state_dict helpers
Copyright 2020 Ross Wightman
"""
import torch
import os
from collections import OrderedDict
try:
from torch.hub import load_state_dict_from_url
except ImportError:
from torch.utils.model_zoo import load_url as load_state_dict_from_url
def load_checkpoint(model, chec... | 2,833 | 38.361111 | 107 | py |
gen-efficientnet-pytorch | gen-efficientnet-pytorch-master/geffnet/activations/activations_jit.py | """ Activations (jit)
A collection of jit-scripted activations fn and modules with a common interface so that they can
easily be swapped. All have an `inplace` arg even if not used.
All jit scripted activations are lacking in-place variations on purpose, scripted kernel fusion does not
currently work across in-place ... | 2,294 | 27.6875 | 107 | py |
gen-efficientnet-pytorch | gen-efficientnet-pytorch-master/geffnet/activations/activations_me.py | """ Activations (memory-efficient w/ custom autograd)
A collection of activations fn and modules with a common interface so that they can
easily be swapped. All have an `inplace` arg even if not used.
These activations are not compatible with jit scripting or ONNX export of the model, please use either
the JIT or bas... | 4,549 | 25 | 108 | py |
gen-efficientnet-pytorch | gen-efficientnet-pytorch-master/geffnet/activations/activations.py | """ Activations
A collection of activations fn and modules with a common interface so that they can
easily be swapped. All have an `inplace` arg even if not used.
Copyright 2020 Ross Wightman
"""
from torch import nn as nn
from torch.nn import functional as F
def swish(x, inplace: bool = False):
"""Swish - Desc... | 2,690 | 25.126214 | 107 | py |
gen-efficientnet-pytorch | gen-efficientnet-pytorch-master/geffnet/activations/__init__.py | from geffnet import config
from geffnet.activations.activations_me import *
from geffnet.activations.activations_jit import *
from geffnet.activations.activations import *
import torch
_has_silu = 'silu' in dir(torch.nn.functional)
_ACT_FN_DEFAULT = dict(
silu=F.silu if _has_silu else swish,
swish=F.silu if _... | 4,170 | 29.224638 | 104 | py |
gen-efficientnet-pytorch | gen-efficientnet-pytorch-master/data/dataset.py | """ Quick n simple image folder dataset
Copyright 2020 Ross Wightman
"""
import torch.utils.data as data
import os
import re
import torch
from PIL import Image
IMG_EXTENSIONS = ['.png', '.jpg', '.jpeg']
def natural_key(string_):
"""See http://www.codinghorror.com/blog/archives/001018.html"""
return [int(s... | 3,000 | 31.619565 | 109 | py |
gen-efficientnet-pytorch | gen-efficientnet-pytorch-master/data/loader.py | """ Fast Collate, CUDA Prefetcher
Prefetcher and Fast Collate inspired by NVIDIA APEX example at
https://github.com/NVIDIA/apex/commit/d5e2bb4bdeedd27b1dfaf5bb2b24d6c000dee9be#diff-cf86c282ff7fba81fad27a559379d5bf
Hacked together by / Copyright 2020 Ross Wightman
"""
import torch
import torch.utils.data
from .transfo... | 3,113 | 27.568807 | 116 | py |
gen-efficientnet-pytorch | gen-efficientnet-pytorch-master/data/transforms.py | import torch
from torchvision import transforms
from PIL import Image
import math
import numpy as np
DEFAULT_CROP_PCT = 0.875
IMAGENET_DEFAULT_MEAN = (0.485, 0.456, 0.406)
IMAGENET_DEFAULT_STD = (0.229, 0.224, 0.225)
IMAGENET_INCEPTION_MEAN = (0.5, 0.5, 0.5)
IMAGENET_INCEPTION_STD = (0.5, 0.5, 0.5)
IMAGENET_DPN_MEAN ... | 4,760 | 30.529801 | 96 | py |
Log-Spectral-matching-GAN | Log-Spectral-matching-GAN-main/inference.py | import torch
import matplotlib.pyplot as plt
import pickle as pk
import numpy as np
from tqdm import tqdm
from scipy.signal import butter, lfilter
import h5py
def butter_bandpass(lowcut, highcut, fs, order=5):
nyq = 0.5 * fs
low = lowcut / nyq
high = highcut / nyq
b, a = butter(order, [low, high], btyp... | 1,562 | 29.057692 | 82 | py |
Log-Spectral-matching-GAN | Log-Spectral-matching-GAN-main/preprocessing.py | import torch
import numpy as np
import os
import matplotlib.pyplot as plt
def read_csv(file_path):
f = open(file_path)
content = f.readline().split(',')
output = []
for item in content:
output.append(float(item))
f.close()
return output
class Dataset():
def __init__(self):
... | 1,348 | 24.942308 | 96 | py |
Log-Spectral-matching-GAN | Log-Spectral-matching-GAN-main/loss_functions.py | import numpy as np
from torch.autograd.variable import Variable
import torch
import torch.nn as nn
import torch.nn.functional as F
import math
def _torch_welch(data, fs=40.0, nperseg=400, noverlap=None, average='mean',
device='cpu',return_list = False):
""" Compute PSD using Welch's method.
"""... | 8,860 | 34.874494 | 118 | py |
Log-Spectral-matching-GAN | Log-Spectral-matching-GAN-main/test_welch.py | from loss_functions import _torch_welch
from scipy.signal import welch
from PPGDataset_40hz import PPGDataloader
import torch
import matplotlib.pyplot as plt
import numpy as np
def read_csv(file_path):
f = open(file_path)
content = f.readline().split(',')
output = []
for item in content:
output... | 848 | 24.727273 | 67 | py |
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