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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VecConstNMT | VecConstNMT-master/fairseq/optim/lr_scheduler/reduce_lr_on_plateau.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.optim.lr_scheduler
from . import register_lr_scheduler, LegacyFairseqLRScheduler
@register_lr_scheduler('reduce_lr_on_plateau'... | 4,755 | 41.088496 | 97 | py |
VecConstNMT | VecConstNMT-master/fairseq/optim/lr_scheduler/cosine_lr_scheduler.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 . import FairseqLRScheduler, register_lr_scheduler
@register_lr_scheduler('cosine')
class CosineSchedule(FairseqLRSchedule... | 4,752 | 38.941176 | 105 | py |
VecConstNMT | VecConstNMT-master/fairseq/scoring/bleu.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 ctypes
import math
import sys
import torch
from fairseq.scoring import register_scoring
class BleuStat(ctypes.Structure):
_fiel... | 4,141 | 28.169014 | 91 | py |
VecConstNMT | VecConstNMT-master/fairseq/benchmark/dummy_model.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.nn.functional as F
from fairseq.data import Dictionary
from fairseq.models import (
FairseqDecoder,
... | 2,971 | 29.958333 | 78 | py |
VecConstNMT | VecConstNMT-master/fairseq/benchmark/dummy_mt.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
from fairseq.data import Dictionary, FairseqDataset
from fairseq.tasks import register_task, ... | 3,688 | 28.99187 | 84 | py |
VecConstNMT | VecConstNMT-master/fairseq/benchmark/dummy_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 numpy as np
import torch
from fairseq.data import Dictionary, FairseqDataset
from fairseq.tasks import register_task, ... | 3,852 | 29.101563 | 84 | py |
VecConstNMT | VecConstNMT-master/fairseq/benchmark/dummy_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 numpy as np
import torch
from fairseq.data import Dictionary, FairseqDataset
from fairseq.tasks import register_task, ... | 3,544 | 28.789916 | 84 | py |
VecConstNMT | VecConstNMT-master/fairseq/data/language_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 logging
import numpy as np
import torch
from fairseq.data import data_utils, FairseqDataset
logger = logging.getLogger(__name__)
... | 23,048 | 42.162921 | 116 | py |
VecConstNMT | VecConstNMT-master/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
class TokenBlockDataset(FairseqDataset):
"""Break... | 5,966 | 34.730539 | 101 | py |
VecConstNMT | VecConstNMT-master/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... | 2,103 | 28.222222 | 101 | py |
VecConstNMT | VecConstNMT-master/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 |
VecConstNMT | VecConstNMT-master/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 __i... | 2,154 | 25.9375 | 70 | py |
VecConstNMT | VecConstNMT-master/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__(... | 547 | 20.92 | 65 | py |
VecConstNMT | VecConstNMT-master/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 R... | 4,317 | 29.624113 | 78 | py |
VecConstNMT | VecConstNMT-master/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.binarizer impo... | 12,599 | 31.390746 | 87 | py |
VecConstNMT | VecConstNMT-master/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, data... | 1,066 | 23.813953 | 65 | py |
VecConstNMT | VecConstNMT-master/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 |
VecConstNMT | VecConstNMT-master/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 data_utils, Dictionary
from . import BaseWrapperDa... | 6,973 | 38.179775 | 87 | py |
VecConstNMT | VecConstNMT-master/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(... | 4,619 | 36.560976 | 93 | py |
VecConstNMT | VecConstNMT-master/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... | 17,213 | 37.77027 | 120 | py |
VecConstNMT | VecConstNMT-master/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 ... | 3,926 | 31.454545 | 86 | py |
VecConstNMT | VecConstNMT-master/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
from . import data_utils
class AddTargetDataset(BaseWrapperDataset):
def __init__(self, d... | 2,046 | 35.553571 | 107 | py |
VecConstNMT | VecConstNMT-master/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 . import FairseqDataset
import torch
from typing import Optional
class TransformEosLangPairDataset(FairseqDataset):
"""A :class:`~... | 3,381 | 36.577778 | 110 | py |
VecConstNMT | VecConstNMT-master/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 fairseq.data.monolingual_dataset import MonolingualDataset
from . import FairseqDataset
class LMConte... | 2,910 | 35.848101 | 90 | py |
VecConstNMT | VecConstNMT-master/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 i... | 844 | 32.8 | 113 | py |
VecConstNMT | VecConstNMT-master/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
import numpy as n... | 19,023 | 33.715328 | 94 | py |
VecConstNMT | VecConstNMT-master/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)... | 6,235 | 36.566265 | 93 | py |
VecConstNMT | VecConstNMT-master/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 data_utils, FairseqDataset
def collate(samples, pad_idx, eos_idx):
if len(samples) == 0:
... | 9,109 | 37.117155 | 117 | py |
VecConstNMT | VecConstNMT-master/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):
supe... | 486 | 23.35 | 65 | py |
VecConstNMT | VecConstNMT-master/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... | 1,394 | 36.702703 | 117 | py |
VecConstNMT | VecConstNMT-master/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... | 424 | 19.238095 | 65 | py |
VecConstNMT | VecConstNMT-master/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.
from functools import lru_cache
import os
import shutil
import struct
import numpy as np
import torch
from . import FairseqDataset
from fair... | 17,020 | 30.173993 | 105 | py |
VecConstNMT | VecConstNMT-master/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 numpy as np
import torch
import math
from . import data_utils, FairseqDataset
def collate(
samples,
pad_idx,
eos_idx,
... | 15,236 | 35.98301 | 118 | py |
VecConstNMT | VecConstNMT-master/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, dat... | 1,067 | 23.837209 | 65 | py |
VecConstNMT | VecConstNMT-master/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, r... | 787 | 22.878788 | 65 | py |
VecConstNMT | VecConstNMT-master/fairseq/data/token_label_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
class TokenLabelBlockDataset(FairseqDataset):
"""... | 6,003 | 34.952096 | 101 | py |
VecConstNMT | VecConstNMT-master/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 torch
import numpy as np
from fairseq.data import data_utils
class WordNoising(object):
"""Generate a noisy version of a sentenc... | 12,184 | 37.560127 | 110 | py |
VecConstNMT | VecConstNMT-master/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
class BucketPadLengthDataset(BaseWrapperData... | 2,261 | 28 | 79 | py |
VecConstNMT | VecConstNMT-master/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()... | 1,573 | 26.614035 | 75 | py |
VecConstNMT | VecConstNMT-master/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 numpy as np
import torch.utils.data
from fairseq.data import data_utils
class EpochListening:
"""Mixin for receiving updates whe... | 6,291 | 34.348315 | 100 | py |
VecConstNMT | VecConstNMT-master/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... | 4,576 | 36.516393 | 88 | py |
VecConstNMT | VecConstNMT-master/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.
from typing import List
from enum import Enum
from collections import OrderedDict
from collections import defaultdict
from bisect import bisec... | 17,170 | 40.677184 | 119 | py |
VecConstNMT | VecConstNMT-master/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 |
VecConstNMT | VecConstNMT-master/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 math
import logging
import numpy as np
from fairseq.data import SampledMultiDataset
from .sampled_multi_dataset import ... | 7,488 | 42.04023 | 119 | py |
VecConstNMT | VecConstNMT-master/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 os
import logging
import numpy as np
import sys
import torch
import torch.nn.functional as F
from .. import FairseqDataset
logger =... | 5,341 | 28.351648 | 88 | py |
VecConstNMT | VecConstNMT-master/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... | 907 | 30.310345 | 67 | py |
VecConstNMT | VecConstNMT-master/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... | 12,878 | 40.146965 | 99 | py |
VecConstNMT | VecConstNMT-master/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
import numpy as np
import torch
from typing import Dict, List, Tuple
from fairseq.data import FairseqDataset, data_utils
from ... | 12,468 | 37.603715 | 83 | py |
VecConstNMT | VecConstNMT-master/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.data import LanguagePairDataset
from fairseq import utils
from .translation import load_langpair_dataset, Translat... | 5,522 | 42.488189 | 108 | py |
VecConstNMT | VecConstNMT-master/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
import numpy as np
import torch
from fairseq import utils
from fairseq.data import (
AppendTokenDataset,
da... | 18,496 | 41.230594 | 149 | py |
VecConstNMT | VecConstNMT-master/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 argparse import Namespace
import json
import itertools
import logging
import os
from fairseq import options
import numpy as np
from fair... | 20,348 | 44.831081 | 108 | py |
VecConstNMT | VecConstNMT-master/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.data import (
data_utils,
Dictionary,
encoders,
Concat... | 11,909 | 38.437086 | 98 | py |
VecConstNMT | VecConstNMT-master/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.
from collections import OrderedDict
import logging
import os
from fairseq import options
import contextlib
import torch
from fairseq import m... | 15,955 | 43.077348 | 117 | py |
VecConstNMT | VecConstNMT-master/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.
import os
import torch
from fairseq.data import LanguagePairDataset
from fairseq.utils import new_arange
from fairseq.tasks import register... | 7,220 | 40.5 | 108 | py |
VecConstNMT | VecConstNMT-master/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
import torch
from fairseq import metrics, search, tokenizer, utils
from fairseq.data import data_u... | 20,274 | 36.338858 | 109 | py |
VecConstNMT | VecConstNMT-master/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 logging
import datetime
import time
import torch
from fairseq.data import (
data_utils,
FairseqDataset,
iterators,
Lan... | 15,631 | 41.363144 | 117 | py |
VecConstNMT | VecConstNMT-master/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... | 4,235 | 30.849624 | 80 | py |
VecConstNMT | VecConstNMT-master/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 logging
import math
import os
import sys
import n... | 11,457 | 38.510345 | 192 | py |
VecConstNMT | VecConstNMT-master/fairseq_cli/eval_tlm.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
impor... | 5,579 | 31.068966 | 83 | py |
VecConstNMT | VecConstNMT-master/fairseq_cli/validate.py | #!/usr/bin/env python3 -u
#!/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.
from itertools import chain
import logging
import os
import sys
import torch
from fairse... | 4,389 | 31.518519 | 88 | py |
VecConstNMT | VecConstNMT-master/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
impor... | 9,000 | 33.224335 | 112 | py |
VecConstNMT | VecConstNMT-master/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.
"""
from collections import namedtuple
import ... | 10,427 | 35.083045 | 126 | py |
VecConstNMT | VecConstNMT-master/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... | 12,826 | 32.933862 | 93 | py |
a3t-dev_richard | a3t-dev_richard/setup.py | #!/usr/bin/env python3
"""ESPnet setup script."""
import os
from distutils.version import LooseVersion
from setuptools import find_packages
from setuptools import setup
requirements = {
"install": [
"setuptools>=38.5.1",
"configargparse>=1.2.1",
"typeguard>=2.7.0",
"humanfriendl... | 6,120 | 34.178161 | 87 | py |
a3t-dev_richard | a3t-dev_richard/tools/check_pytorch_cuda_compatibility.py | #!/usr/bin/env python
import argparse
from distutils.version import LooseVersion
import warnings
def check(pytorch_version: str, cuda_version: str):
# NOTE(kamo): Supported cuda version is defined
# as existing prebuilt binaries in
# https://anaconda.org/pytorch/pytorch/files
# You probably could per... | 2,999 | 34.294118 | 89 | py |
a3t-dev_richard | a3t-dev_richard/tools/check_install.py | #!/usr/bin/env python3
"""Script to check whether the installation is done correctly."""
# Copyright 2018 Nagoya University (Tomoki Hayashi)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
import importlib
import shutil
import sys
from distutils.version import LooseVersion
module_list = [
("torchau... | 4,169 | 28.160839 | 83 | py |
a3t-dev_richard | a3t-dev_richard/test/test_e2e_compatibility.py | #!/usr/bin/env python3
# coding: utf-8
# Copyright 2019 Tomoki Hayashi
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
from __future__ import print_function
import importlib
import os
from os.path import join
import re
import shutil
import subprocess
import tempfile
import chainer
import numpy as np
imp... | 3,585 | 30.734513 | 111 | py |
a3t-dev_richard | a3t-dev_richard/test/test_e2e_asr_conformer.py | import argparse
import pytest
import torch
from espnet.nets.pytorch_backend.e2e_asr_conformer import E2E
from espnet.nets.pytorch_backend.transformer import plot
def make_arg(**kwargs):
defaults = dict(
adim=2,
aheads=1,
dropout_rate=0.0,
transformer_attn_dropout_rate=None,
... | 4,493 | 25.91018 | 83 | py |
a3t-dev_richard | a3t-dev_richard/test/test_custom_transducer.py | # coding: utf-8
import argparse
import tempfile
import json
import pytest
import torch
from espnet.asr.pytorch_backend.asr_init import load_trained_model
import espnet.lm.pytorch_backend.extlm as extlm_pytorch
from espnet.nets.beam_search_transducer import BeamSearchTransducer
from espnet.nets.pytorch_backend.e2e_as... | 16,316 | 29.728814 | 87 | py |
a3t-dev_richard | a3t-dev_richard/test/test_batch_beam_search.py | from argparse import Namespace
import numpy
import os
import pytest
import torch
from espnet.nets.batch_beam_search import BatchBeamSearch
from espnet.nets.batch_beam_search import BeamSearch
from espnet.nets.beam_search import Hypothesis
from espnet.nets.lm_interface import dynamic_import_lm
from espnet.nets.scorers... | 5,938 | 29.932292 | 88 | py |
a3t-dev_richard | a3t-dev_richard/test/test_e2e_mt.py | # coding: utf-8
# Copyright 2019 Hirofumi Inaguma
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
from __future__ import division
import argparse
import importlib
import os
import tempfile
import chainer
import numpy as np
import pytest
import torch
from espnet.nets.pytorch_backend.nets_utils import pa... | 12,863 | 31.321608 | 88 | py |
a3t-dev_richard | a3t-dev_richard/test/test_multi_spkrs.py | # coding: utf-8
# Copyright 2018 Hiroshi Seki
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
import argparse
import importlib
import numpy
import re
import torch
import pytest
def make_arg(**kwargs):
defaults = dict(
aconv_chans=10,
aconv_filts=100,
adim=320,
aheads... | 7,267 | 28.544715 | 86 | py |
a3t-dev_richard | a3t-dev_richard/test/test_positional_encoding.py | import pytest
import torch
from espnet.nets.pytorch_backend.transformer.embedding import PositionalEncoding
from espnet.nets.pytorch_backend.transformer.embedding import ScaledPositionalEncoding
@pytest.mark.parametrize(
"dtype, device",
[(dt, dv) for dt in ("float32", "float64") for dv in ("cpu", "cuda")],
... | 4,331 | 31.328358 | 87 | py |
a3t-dev_richard | a3t-dev_richard/test/test_asr_init.py | # coding: utf-8
import argparse
import json
import os
import tempfile
import numpy as np
import pytest
import torch
import espnet.nets.pytorch_backend.lm.default as lm_pytorch
from espnet.asr.asr_utils import torch_save
from espnet.asr.pytorch_backend.asr_init import freeze_modules
from espnet.asr.pytorch_backend.a... | 7,631 | 25.968198 | 82 | py |
a3t-dev_richard | a3t-dev_richard/test/test_e2e_mt_transformer.py | # coding: utf-8
# Copyright 2019 Hirofumi Inaguma
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
import argparse
import pytest
import torch
from espnet.nets.pytorch_backend.e2e_mt_transformer import E2E
from espnet.nets.pytorch_backend.transformer import plot
def make_arg(**kwargs):
defaults = dic... | 3,753 | 26.202899 | 83 | py |
a3t-dev_richard | a3t-dev_richard/test/test_e2e_asr_transformer.py | import argparse
import chainer
import numpy
import pytest
import torch
import espnet.nets.chainer_backend.e2e_asr_transformer as ch
import espnet.nets.pytorch_backend.e2e_asr_transformer as th
from espnet.nets.pytorch_backend.nets_utils import rename_state_dict
from espnet.nets.pytorch_backend.transformer.add_sos_eos ... | 8,202 | 30.190114 | 87 | py |
a3t-dev_richard | a3t-dev_richard/test/test_e2e_tts_transformer.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2019 Tomoki Hayashi
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
import numpy as np
import pytest
import torch
from argparse import Namespace
from espnet.nets.pytorch_backend.e2e_tts_transformer import subsequent_mask
from espnet.nets.pytorch... | 15,668 | 32.409382 | 88 | py |
a3t-dev_richard | a3t-dev_richard/test/test_asr_interface.py | import pytest
from espnet.nets.asr_interface import dynamic_import_asr
@pytest.mark.parametrize(
"name, backend",
[(nn, backend) for nn in ("transformer", "rnn") for backend in ("pytorch",)],
)
def test_asr_build(name, backend):
model = dynamic_import_asr(name, backend).build(
10, 10, mtlalpha=0.... | 415 | 26.733333 | 81 | py |
a3t-dev_richard | a3t-dev_richard/test/test_e2e_asr.py | # coding: utf-8
# Copyright 2017 Shigeki Karita
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
from __future__ import division
import argparse
import importlib
import os
import tempfile
import chainer
import numpy as np
import pytest
import torch
from espnet.asr import asr_utils
import espnet.nets.cha... | 26,920 | 34.329396 | 88 | py |
a3t-dev_richard | a3t-dev_richard/test/test_asr_quantize.py | # Copyright 2021 Gaopeng Xu
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
import pytest
import torch
from espnet.nets.asr_interface import dynamic_import_asr
@pytest.mark.parametrize(
"name, backend",
[(nn, backend) for nn in ("transformer", "rnn") for backend in ("pytorch",)],
)
def test_asr_... | 642 | 28.227273 | 81 | py |
a3t-dev_richard | a3t-dev_richard/test/test_optimizer.py | # coding: utf-8
# Copyright 2017 Shigeki Karita
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
import chainer
import numpy
import pytest
import torch
from espnet.optimizer.factory import dynamic_import_optimizer
from espnet.optimizer.pytorch import OPTIMIZER_FACTORY_DICT
class ChModel(chainer.Chain):
... | 3,023 | 29.857143 | 83 | py |
a3t-dev_richard | a3t-dev_richard/test/test_loss.py | # Copyright 2017 Shigeki Karita
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
import chainer.functions as F
import numpy
import pytest
import torch
from espnet.nets.pytorch_backend.e2e_asr import pad_list
from espnet.nets.pytorch_backend.nets_utils import th_accuracy
@pytest.mark.parametrize("ctc_type"... | 5,646 | 35.668831 | 86 | py |
a3t-dev_richard | a3t-dev_richard/test/test_beam_search.py | from argparse import Namespace
import numpy
import pytest
import torch
from espnet.nets.asr_interface import dynamic_import_asr
from espnet.nets.beam_search import BeamSearch
from espnet.nets.lm_interface import dynamic_import_lm
from espnet.nets.scorers.length_bonus import LengthBonus
rnn_args = Namespace(
elay... | 6,366 | 27.55157 | 88 | py |
a3t-dev_richard | a3t-dev_richard/test/test_lm.py | import chainer
import numpy
import pytest
import torch
import espnet.lm.chainer_backend.lm as lm_chainer
from espnet.nets.beam_search import beam_search
from espnet.nets.lm_interface import dynamic_import_lm
import espnet.nets.pytorch_backend.lm.default as lm_pytorch
from espnet.nets.scorers.length_bonus import Length... | 6,680 | 33.261538 | 88 | py |
a3t-dev_richard | a3t-dev_richard/test/test_e2e_tts_fastspeech.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2019 Tomoki Hayashi
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
import json
import os
import shutil
import tempfile
from argparse import Namespace
import numpy as np
import pytest
import torch
from espnet.nets.pytorch_backend.e2e_tts_fastsp... | 21,141 | 32.347003 | 87 | py |
a3t-dev_richard | a3t-dev_richard/test/test_e2e_st_transformer.py | # coding: utf-8
# Copyright 2019 Hirofumi Inaguma
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
import argparse
import pytest
import torch
from espnet.nets.pytorch_backend.e2e_st_transformer import E2E
from espnet.nets.pytorch_backend.transformer import plot
def make_arg(**kwargs):
defaults = dict... | 5,351 | 28.899441 | 85 | py |
a3t-dev_richard | a3t-dev_richard/test/test_torch.py | # Copyright 2017 Shigeki Karita
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
import torch
from espnet.nets.pytorch_backend.nets_utils import pad_list
def test_pad_list():
xs = [[1, 2, 3], [1, 2], [1, 2, 3, 4]]
xs = list(map(lambda x: torch.LongTensor(x), xs))
xpad = pad_list(xs, -1)
e... | 852 | 26.516129 | 74 | py |
a3t-dev_richard | a3t-dev_richard/test/test_initialization.py | # Copyright 2017 Shigeki Karita
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
import argparse
import os
import random
import numpy
import torch
args = argparse.Namespace(
elayers=4,
subsample="1_2_2_1_1",
etype="vggblstmp",
eunits=320,
eprojs=320,
dtype="lstm",
dlayers=2,
... | 3,385 | 28.443478 | 72 | py |
a3t-dev_richard | a3t-dev_richard/test/test_e2e_st.py | # coding: utf-8
# Copyright 2019 Hirofumi Inaguma
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
from __future__ import division
import argparse
import importlib
import os
import tempfile
import chainer
import numpy as np
import pytest
import torch
from espnet.nets.pytorch_backend.nets_utils import pa... | 20,478 | 33.651438 | 88 | py |
a3t-dev_richard | a3t-dev_richard/test/test_e2e_asr_maskctc.py | import argparse
import pytest
import torch
from espnet.nets.pytorch_backend.e2e_asr_maskctc import E2E
from espnet.nets.pytorch_backend.maskctc.add_mask_token import mask_uniform
from espnet.nets.pytorch_backend.transformer import plot
def make_arg(**kwargs):
defaults = dict(
adim=2,
aheads=2,
... | 3,707 | 27.744186 | 83 | py |
a3t-dev_richard | a3t-dev_richard/test/test_e2e_asr_transducer.py | # coding: utf-8
import argparse
import tempfile
import json
import numpy as np
import pytest
import torch
from espnet.asr.pytorch_backend.asr_init import load_trained_model
import espnet.lm.pytorch_backend.extlm as extlm_pytorch
from espnet.nets.beam_search_transducer import BeamSearchTransducer
from espnet.nets.pyt... | 11,607 | 28.461929 | 88 | py |
a3t-dev_richard | a3t-dev_richard/test/test_e2e_vc_transformer.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2020 Wen-Chin Huang
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
from math import floor
import numpy as np
import pytest
import torch
from argparse import Namespace
from espnet.nets.pytorch_backend.e2e_vc_transformer import subsequent_mask
fr... | 16,087 | 32.727463 | 88 | py |
a3t-dev_richard | a3t-dev_richard/test/test_e2e_asr_mulenc.py | # coding: utf-8
# Copyright 2019 Ruizhi Li
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
from __future__ import division
import argparse
import importlib
import os
import tempfile
import numpy as np
import pytest
import torch
from espnet.nets.pytorch_backend.nets_utils import pad_list
from espnet.uti... | 21,858 | 35.431667 | 88 | py |
a3t-dev_richard | a3t-dev_richard/test/test_e2e_vc_tacotron2.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2020 Wen-Chin Huang
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
from __future__ import print_function
from __future__ import division
import numpy as np
import pytest
import torch
from argparse import Namespace
from espnet.nets.pytorch_back... | 8,660 | 27.396721 | 88 | py |
a3t-dev_richard | a3t-dev_richard/test/test_e2e_tts_tacotron2.py | #!/usr/bin/env python3
# Copyright 2019 Tomoki Hayashi
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
from __future__ import print_function
from __future__ import division
import numpy as np
import pytest
import torch
from argparse import Namespace
from espnet.nets.pytorch_backend.e2e_tts_tacotron2 im... | 8,820 | 27.63961 | 88 | py |
a3t-dev_richard | a3t-dev_richard/test/test_train_dtype.py | import pytest
import torch
from espnet.nets.asr_interface import dynamic_import_asr
@pytest.mark.parametrize(
"dtype, device, model, conf",
[
(dtype, device, nn, conf)
for nn, conf in [
(
"transformer",
dict(adim=4, eunits=3, dunits=3, elayers=2, dl... | 2,795 | 28.125 | 85 | py |
a3t-dev_richard | a3t-dev_richard/test/test_transformer_decode.py | import numpy
import pytest
import torch
from espnet.nets.pytorch_backend.transformer.decoder import Decoder
from espnet.nets.pytorch_backend.transformer.encoder import Encoder
from espnet.nets.pytorch_backend.transformer.mask import subsequent_mask
RTOL = 1e-4
@pytest.mark.parametrize("normalize_before", [True, Fa... | 4,487 | 29.951724 | 85 | py |
a3t-dev_richard | a3t-dev_richard/test/test_recog.py | # coding: utf-8
# Copyright 2018 Hiroshi Seki
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
import argparse
import numpy
import pytest
import torch
import espnet.lm.pytorch_backend.extlm as extlm_pytorch
from espnet.nets.pytorch_backend import e2e_asr
import espnet.nets.pytorch_backend.lm.default as l... | 4,644 | 28.967742 | 87 | py |
a3t-dev_richard | a3t-dev_richard/test/test_scheduler.py | from espnet.scheduler.chainer import ChainerScheduler
from espnet.scheduler.pytorch import PyTorchScheduler
from espnet.scheduler import scheduler
import chainer
import numpy
import pytest
import torch
@pytest.mark.parametrize("name", scheduler.SCHEDULER_DICT.keys())
def test_scheduler(name):
s = scheduler.dynam... | 1,247 | 26.130435 | 65 | py |
a3t-dev_richard | a3t-dev_richard/test/test_e2e_st_conformer.py | # coding: utf-8
# Copyright 2019 Hirofumi Inaguma
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
import argparse
import pytest
import torch
from espnet.nets.pytorch_backend.e2e_st_conformer import E2E
from espnet.nets.pytorch_backend.transformer import plot
def make_arg(**kwargs):
defaults = dict(
... | 4,215 | 26.555556 | 85 | py |
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