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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RegularizedBN | RegularizedBN-main/fairseq/modules/norm/mask_anchornorm.py | #! /usr/bin/env python3
# -*- coding: utf-8 -*-
# File : MaskBatchNorm.py
# Distributed under MIT License.
import torch
import torch.nn as nn
import torch.nn.init as init
import torch.nn.functional as F
from torch.nn.parameter import Parameter
import numpy as np
from scipy import io
__all__ = ['MaskAnchorNorm']
de... | 2,951 | 32.168539 | 103 | py |
RegularizedBN | RegularizedBN-main/fairseq/modules/norm/mask_groupnorm.py | #! /usr/bin/env python3
# -*- coding: utf-8 -*-
# File : groupnorm.py
# Distributed under MIT License.
import torch
import torch.nn as nn
import torch.nn.init as init
import torch.nn.functional as F
def tile(a, repeats, dim):
"""
Substitute for numpy's repeat function. Taken from https://discuss.pytorch.org... | 7,391 | 43 | 131 | py |
RegularizedBN | RegularizedBN-main/fairseq/modules/norm/mask_layernorm3d.py | #! /usr/bin/env python3
# -*- coding: utf-8 -*-
# File : MaskBatchNorm.py
# Distributed under MIT License.
import torch
import torch.nn as nn
import torch.nn.init as init
import torch.nn.functional as F
from torch.nn.parameter import Parameter
from torch.nn.modules._functions import SyncBatchNorm as sync_batch_norm
... | 2,211 | 32.515152 | 83 | py |
RegularizedBN | RegularizedBN-main/fairseq/modules/norm/mask_groupscale.py | #! /usr/bin/env python3
# -*- coding: utf-8 -*-
# File : MaskPowerNorm.py
# Distributed under MIT License.
import torch
import torch.nn as nn
import torch.nn.init as init
import torch.nn.functional as F
__all__ = ['MaskGruopScale']
def _sum_ft(tensor):
"""sum over the first and last dimention"""
return ten... | 6,418 | 34.076503 | 119 | py |
RegularizedBN | RegularizedBN-main/fairseq/modules/norm/mask_identity.py | #! /usr/bin/env python3
# -*- coding: utf-8 -*-
# File : MaskBatchNorm.py
# Distributed under MIT License.
import torch
import torch.nn as nn
import torch.nn.init as init
import torch.nn.functional as F
__all__ = ['MaskIdentity']
class MaskIdentityNorm(nn.Module):
"""
"""
def __init__(self, num_featur... | 790 | 23.71875 | 62 | py |
RegularizedBN | RegularizedBN-main/fairseq/modules/norm/mask_batchnorm3d.py | #! /usr/bin/env python3
# -*- coding: utf-8 -*-
# File : MaskBatchNorm.py
# Distributed under MIT License.
import torch
import torch.nn as nn
import torch.nn.init as init
import torch.nn.functional as F
from torch.nn.parameter import Parameter
from torch.nn.modules._functions import SyncBatchNorm as sync_batch_norm
... | 16,604 | 41.686375 | 141 | py |
RegularizedBN | RegularizedBN-main/fairseq/modules/dynamicconv_layer/setup.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 CUDAExtension, BuildExtension
setup(
name='dyna... | 613 | 24.583333 | 67 | py |
RegularizedBN | RegularizedBN-main/fairseq/modules/dynamicconv_layer/dynamicconv_layer.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.autograd import Function
import torch.nn.functional as F
import dynamicconv_cuda
from fairseq im... | 8,719 | 39.184332 | 129 | py |
RegularizedBN | RegularizedBN-main/fairseq/modules/fc/oni_fc.py | """
Orthogonalization by Newton’s Iteration
"""
import torch.nn
import torch.nn.functional as F
from torch.nn import Parameter
from torch.autograd import Variable
from typing import List
from torch.autograd.function import once_differentiable
__all__ = ['WN_Conv2d', 'OWN_Conv2d', 'ONI_Conv2d','ONI_ConvTranspose2d',
... | 12,549 | 41.398649 | 146 | py |
RegularizedBN | RegularizedBN-main/fairseq/modules/fc/dropout_fc.py | import torch
import torch.nn as nn
import torch.nn.functional as F
__all__ = ['DropoutFC']
class DropoutFC(nn.Linear):
def __init__(self, in_features, out_features, bias=True, dropout=0, scale=1.0):
super(DropoutFC, self).__init__(in_features, out_features, bias)
print('DropoutFC dropout:{}, sc... | 940 | 28.40625 | 83 | py |
RegularizedBN | RegularizedBN-main/fairseq/modules/fc/conv.py | import torch
from torch import nn
import torch.nn.functional as F
class Conv1d(nn.Conv1d):
def __init__(self,in_channels, out_channels, kernel_size=3, stride=1):
self.padding = (kernel_size-1)//2
self.stride = stride
super(Conv1d, self).__init__(in_channels, out_channels, kernel_size, stride=stride,padding=self.... | 674 | 38.705882 | 112 | py |
RegularizedBN | RegularizedBN-main/fairseq/modules/fc/wn.py | import torch.nn
import torch.nn.functional as F
from torch.nn import Parameter
from torch.autograd import Variable
from typing import List
from torch.autograd.function import once_differentiable
__all__ = ['CWN']
# norm funcitons--------------------------------
class CWNorm(torch.nn.Module):
def forward(self, ... | 3,164 | 38.5625 | 110 | py |
RegularizedBN | RegularizedBN-main/fairseq/modules/quantization/pq/em.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 random
import logging
from collections import Counter
import torch
class EM:
"""
EM algorithm used to quantize the... | 7,333 | 33.59434 | 92 | py |
RegularizedBN | RegularizedBN-main/fairseq/modules/quantization/pq/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 logging
import re
from operator import attrgetter, itemgetter
import numpy as np
import torch.nn as nn
import torch.distributed as dis... | 11,605 | 33.541667 | 110 | py |
RegularizedBN | RegularizedBN-main/fairseq/modules/quantization/pq/modules/qlinear.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... | 2,547 | 34.388889 | 86 | py |
RegularizedBN | RegularizedBN-main/fairseq/modules/quantization/pq/modules/qconv.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... | 4,245 | 35.603448 | 87 | py |
RegularizedBN | RegularizedBN-main/fairseq/modules/quantization/pq/modules/qemb.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... | 3,515 | 38.954545 | 103 | py |
RegularizedBN | RegularizedBN-main/fairseq/modules/quantization/scalar/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 logging
from operator import attrgetter
import torch.nn as nn
import torch.distributed as dist
from ..pq.utils import get_layers, att... | 2,323 | 33.176471 | 107 | py |
RegularizedBN | RegularizedBN-main/fairseq/modules/quantization/scalar/ops.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
def emulate_int(w, bits, method, scale=None, zero_point=None):
q = globals()[f"emulate_int{bits}_{method}"]
return q(w,... | 1,669 | 33.791667 | 90 | py |
RegularizedBN | RegularizedBN-main/fairseq/modules/quantization/scalar/modules/qlinear.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... | 3,596 | 31.405405 | 101 | py |
RegularizedBN | RegularizedBN-main/fairseq/modules/quantization/scalar/modules/qconv.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... | 4,415 | 29.040816 | 95 | py |
RegularizedBN | RegularizedBN-main/fairseq/modules/quantization/scalar/modules/qemb.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):
"""
... | 4,771 | 34.879699 | 103 | py |
RegularizedBN | RegularizedBN-main/fairseq/modules/quantization/scalar/modules/qact.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... | 3,033 | 36.45679 | 87 | py |
RegularizedBN | RegularizedBN-main/fairseq/modules/lightconv_layer/setup.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 CUDAExtension, BuildExtension
setup(
name='ligh... | 545 | 25 | 67 | py |
RegularizedBN | RegularizedBN-main/fairseq/modules/lightconv_layer/lightconv_layer.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.autograd import Function
import torch.nn.functional as F
import lightconv_cuda
from fairseq impo... | 4,679 | 35 | 104 | py |
RegularizedBN | RegularizedBN-main/fairseq/logging/progress_bar.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.
"""
Wrapper around various loggers and progress bars (e.g., tqdm).
"""
import atexit
import json
import logging
import os
import sys
from col... | 11,082 | 29.786111 | 89 | py |
RegularizedBN | RegularizedBN-main/fairseq/logging/metrics.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.
"""
A standalone module for aggregating metrics.
Metrics can be logged from anywhere using the `log_*` functions defined
in this module. The l... | 9,325 | 30.938356 | 81 | py |
RegularizedBN | RegularizedBN-main/fairseq/logging/meters.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
from collections import OrderedDict
import time
from typing import Dict, Optional
try:
import torch
def type_as(a, b):... | 7,885 | 26.477352 | 79 | py |
RegularizedBN | RegularizedBN-main/fairseq/criterions/fairseq_criterion.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 inspect
from typing import Any, Dict, List
from torch.nn.modules.loss import _Loss
from fairseq import metrics, utils
class Fairseq... | 4,258 | 34.491667 | 79 | py |
RegularizedBN | RegularizedBN-main/fairseq/criterions/nat_loss.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.nn.functional as F
import torch
from torch import Tensor
from fairseq import metrics, utils
from fairseq.criterions... | 6,238 | 34.856322 | 98 | py |
RegularizedBN | RegularizedBN-main/fairseq/criterions/wav2vec_criterion.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.functional as F
from fairseq import metrics, utils
from fairseq.criterions import FairseqCriterion,... | 6,437 | 39.490566 | 126 | py |
RegularizedBN | RegularizedBN-main/fairseq/criterions/legacy_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 math
import torch
import torch.nn.functional as F
from fairseq import metrics, utils
from fairseq.criterions import FairseqCriterion,... | 6,769 | 43.248366 | 136 | py |
RegularizedBN | RegularizedBN-main/fairseq/criterions/adaptive_loss.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.nn.functional as F
from fairseq import metrics, utils
from fairseq.criterions import FairseqCriterion, register_cri... | 3,981 | 38.039216 | 105 | py |
RegularizedBN | RegularizedBN-main/fairseq/criterions/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 math
import torch
import torch.nn.functional as F
from fairseq import metrics, modules, utils
from fairseq.criterions import FairseqC... | 3,159 | 34.505618 | 94 | py |
RegularizedBN | RegularizedBN-main/fairseq/criterions/ctc.py | # 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.
from argparse import Namespace
import math
import torch
import torch.nn.functi... | 9,640 | 37.875 | 134 | py |
RegularizedBN | RegularizedBN-main/fairseq/criterions/cross_entropy.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.nn.functional as F
from fairseq import metrics, utils
from fairseq.criterions import FairseqCriterion, register_cri... | 2,871 | 37.810811 | 99 | py |
RegularizedBN | RegularizedBN-main/fairseq/criterions/sentence_prediction.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.functional as F
from fairseq import metrics, utils
from fairseq.criterions import FairseqCriterion,... | 3,717 | 37.729167 | 96 | py |
RegularizedBN | RegularizedBN-main/fairseq/criterions/sentence_ranking.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.functional as F
from fairseq import metrics, utils
from fairseq.criterions import FairseqCriterion,... | 4,532 | 37.74359 | 94 | py |
RegularizedBN | RegularizedBN-main/fairseq/criterions/composite_loss.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
from fairseq import utils
from fairseq.criterions import FairseqCriterion, register_criterion
@register_criterion('com... | 3,689 | 35.9 | 96 | py |
RegularizedBN | RegularizedBN-main/fairseq/models/lstm.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 options, utils
from fairseq.models import (
Fairse... | 29,637 | 42.457478 | 103 | py |
RegularizedBN | RegularizedBN-main/fairseq/models/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 torch
import torch.nn as nn
import torch.nn.functional as F
from fairseq import utils
from fairseq.models import (
... | 15,107 | 41.798867 | 100 | py |
RegularizedBN | RegularizedBN-main/fairseq/models/model_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.
from typing import List, Optional
import torch
from torch import Tensor
@torch.jit.script
def script_skip_tensor_list(x: List[Tensor], mask... | 2,335 | 24.67033 | 103 | py |
RegularizedBN | RegularizedBN-main/fairseq/models/fairseq_encoder.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 typing import Dict, List, NamedTuple, Optional
from torch import Tensor
EncoderOut = NamedTuple(
... | 2,955 | 31.130435 | 78 | py |
RegularizedBN | RegularizedBN-main/fairseq/models/fconv.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 import utils
from fairseq.models import (
Fa... | 27,685 | 40.138187 | 127 | py |
RegularizedBN | RegularizedBN-main/fairseq/models/lightconv.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 import options, utils
from fairseq.models import... | 37,289 | 45.6125 | 165 | py |
RegularizedBN | RegularizedBN-main/fairseq/models/transformer.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, Dict, List, Optional, Tuple
import torch
import torch.nn as nn
import torch.nn.functional as F
from fairs... | 54,478 | 44.589121 | 159 | py |
RegularizedBN | RegularizedBN-main/fairseq/models/fconv_self_att.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 math
import os
import torch
import torch.nn as nn
import torch.nn.functional as F
from fairseq import checkpoint_utils... | 24,306 | 40.198305 | 111 | py |
RegularizedBN | RegularizedBN-main/fairseq/models/fairseq_decoder.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, Tuple
import torch.nn as nn
from fairseq import utils
from torch import Tensor
class FairseqDecode... | 3,064 | 32.681319 | 83 | py |
RegularizedBN | RegularizedBN-main/fairseq/models/fairseq_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.
"""
Base classes for various fairseq models.
"""
import logging
from typing import Dict, List, Optional, Tuple
import torch
import torch.nn a... | 19,311 | 34.696858 | 86 | py |
RegularizedBN | RegularizedBN-main/fairseq/models/fairseq_incremental_decoder.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 Dict, Optional
from torch import Tensor
from fairseq.models import FairseqDecoder
from fairseq.incremental... | 4,387 | 37.831858 | 103 | py |
RegularizedBN | RegularizedBN-main/fairseq/models/distributed_fairseq_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 inspect
import torch.nn as nn
from fairseq.legacy_distributed_data_parallel import LegacyDistributedDataParallel
from fairseq.models ... | 3,982 | 36.575472 | 82 | py |
RegularizedBN | RegularizedBN-main/fairseq/models/LSUV.py | from __future__ import print_function
import numpy as np
import torch
import torch.nn.init
import torch.nn as nn
gg = {}
gg['hook_position'] = 0
gg['total_fc_conv_layers'] = 0
gg['done_counter'] = -1
gg['hook'] = None
gg['act_dict'] = {}
gg['counter_to_apply_correction'] = 0
gg['correction_needed'] = False
gg['current... | 5,573 | 34.730769 | 145 | py |
RegularizedBN | RegularizedBN-main/fairseq/models/wav2vec/wav2vec.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 math
import sys
import torch
import torch.nn as nn
import torch.nn.functional as F
from fairseq.models import BaseFair... | 24,032 | 31.653533 | 131 | py |
RegularizedBN | RegularizedBN-main/fairseq/models/wav2vec/wav2vec2_asr.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 copy
import math
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from fairseq... | 22,473 | 32.344214 | 113 | py |
RegularizedBN | RegularizedBN-main/fairseq/models/wav2vec/wav2vec2.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 math
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from typing import List, Tu... | 33,259 | 31.575906 | 200 | py |
RegularizedBN | RegularizedBN-main/fairseq/models/bart/hub_interface.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 copy
import logging
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from typing import List
fr... | 6,947 | 36.15508 | 129 | py |
RegularizedBN | RegularizedBN-main/fairseq/models/bart/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.
"""
BART: Denoising Sequence-to-Sequence Pre-training for
Natural Language Generation, Translation, and Comprehension
"""
import logging
impo... | 13,648 | 41.126543 | 111 | py |
RegularizedBN | RegularizedBN-main/fairseq/models/nat/levenshtein_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.utils import new_arange
# -------------- Helper Functions --------------------------------------------------- #
d... | 9,372 | 31.887719 | 103 | py |
RegularizedBN | RegularizedBN-main/fairseq/models/nat/levenshtein_transformer.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.iterative_refinement_generator import DecoderOut
from fairseq... | 19,562 | 39.841336 | 120 | py |
RegularizedBN | RegularizedBN-main/fairseq/models/nat/fairseq_nat_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 math
import torch
from fairseq.models.transformer import TransformerModel, TransformerEncoder, TransformerDecoder
from fairseq.modules... | 4,959 | 32.972603 | 95 | py |
RegularizedBN | RegularizedBN-main/fairseq/models/nat/nonautoregressive_ensembles.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.functional as F
from fairseq.models.nat import (
_fill,
_skip,
_skip_encoder_out,
_... | 9,020 | 37.883621 | 120 | py |
RegularizedBN | RegularizedBN-main/fairseq/models/nat/insertion_transformer.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.functional as F
from fairseq.models import register_model, register_model_architecture
from f... | 10,448 | 36.185053 | 88 | py |
RegularizedBN | RegularizedBN-main/fairseq/models/nat/nonautoregressive_transformer.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.iterative_refinement_generator import DecoderOut
from fai... | 16,114 | 36.917647 | 108 | py |
RegularizedBN | RegularizedBN-main/fairseq/models/nat/iterative_nonautoregressive_transformer.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.models import register_model, register_model_architecture
from fairseq.models.nat import NATransformerModel
def _... | 8,427 | 39.912621 | 99 | py |
RegularizedBN | RegularizedBN-main/fairseq/models/roberta/hub_interface.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 fairseq import utils
from fairseq.data import enco... | 8,410 | 40.029268 | 114 | py |
RegularizedBN | RegularizedBN-main/fairseq/models/roberta/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.
"""
RoBERTa: A Robustly Optimized BERT Pretraining Approach.
"""
import logging
import torch
import torch.nn as nn
import torch.nn.functional... | 17,539 | 42.9599 | 122 | py |
RegularizedBN | RegularizedBN-main/fairseq/models/roberta/alignment_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.
from collections import Counter
from typing import List
import torch
def align_bpe_to_words(roberta, bpe_tokens: torch.LongTensor, other_to... | 4,074 | 34.12931 | 98 | py |
RegularizedBN | RegularizedBN-main/fairseq/models/huggingface/hf_gpt2.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
from typing import Dict, List, Optional
import torch
from fairseq.models import (
FairseqIncrementalD... | 7,034 | 34.175 | 86 | py |
RegularizedBN | RegularizedBN-main/fairseq/model_parallel/modules/transformer_sentence_encoder_layer.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.modules import (
TransformerSentenceEncoderLayer
)
fr... | 2,356 | 28.4625 | 84 | py |
RegularizedBN | RegularizedBN-main/fairseq/model_parallel/modules/multihead_attention.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, Tuple
import torch
import torch.nn.functional as F
from fairseq import utils
from torch import Tensor, nn
... | 12,558 | 39.124601 | 98 | py |
RegularizedBN | RegularizedBN-main/fairseq/model_parallel/modules/transformer_sentence_encoder.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
import torch.nn.functional as F
from fairseq.modules import (
Layer... | 1,884 | 28 | 77 | py |
RegularizedBN | RegularizedBN-main/fairseq/model_parallel/models/transformer.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.nn as nn
import torch.nn.functional as F
from fairseq.models import (
register_model,
)
from fairseq.models... | 3,642 | 31.238938 | 107 | py |
RegularizedBN | RegularizedBN-main/fairseq/model_parallel/models/transformer_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 torch.nn as nn
from fairseq.models import register_model, register_model_architecture
from fairseq.models.transformer_lm import (
... | 3,752 | 41.168539 | 116 | py |
RegularizedBN | RegularizedBN-main/fairseq/model_parallel/models/roberta/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.
"""
RoBERTa: A Robustly Optimized BERT Pretraining Approach.
"""
import logging
import torch
import torch.nn as nn
import torch.nn.functional... | 10,367 | 37.542751 | 122 | py |
RegularizedBN | RegularizedBN-main/fairseq/optim/bmuf.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.distributed as dist
from . import FairseqOptimizer
class FairseqBMUF(FairseqOptimizer):
"""
Implements in... | 8,282 | 34.857143 | 90 | py |
RegularizedBN | RegularizedBN-main/fairseq/optim/nag.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.optim.optimizer import Optimizer, required
from . import FairseqOptimizer, register_optimizer
@register_optimizer('... | 3,485 | 32.519231 | 92 | py |
RegularizedBN | RegularizedBN-main/fairseq/optim/sgd.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
from . import FairseqOptimizer, register_optimizer
@register_optimizer('sgd')
class SGD(FairseqOptimizer):
def __ini... | 1,430 | 31.522727 | 92 | py |
RegularizedBN | RegularizedBN-main/fairseq/optim/radam.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 math
import types
import t... | 5,993 | 38.695364 | 188 | py |
RegularizedBN | RegularizedBN-main/fairseq/optim/adamax.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.optim
from . import FairseqOptimizer, register_optimizer
@register_optimizer('adamax')
class FairseqAdamax(Fairse... | 6,084 | 37.27044 | 93 | py |
RegularizedBN | RegularizedBN-main/fairseq/optim/fp16_optimizer.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 itertools import chain
import torch
from fairseq import optim, utils
from .dynamic_loss_scaler import DynamicLossScaler
class _FP16O... | 15,719 | 36.163121 | 103 | py |
RegularizedBN | RegularizedBN-main/fairseq/optim/adam.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 math
import types
import torch
import torch.optim
import torch.distributed as dist
from fairseq.optim import FairseqOp... | 8,497 | 39.084906 | 116 | py |
RegularizedBN | RegularizedBN-main/fairseq/optim/adafactor.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.optim
from . import FairseqOptimizer, register_optimizer
@register_optimizer('adafactor')
class Fairs... | 10,509 | 43.159664 | 105 | py |
RegularizedBN | RegularizedBN-main/fairseq/optim/fused_adam.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 types
import torch
def get_fused_adam_class():
"""
Look for the FusedAdam optimizer from apex. We first try to load the
... | 13,372 | 41.72524 | 109 | py |
RegularizedBN | RegularizedBN-main/fairseq/optim/adagrad.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
from . import FairseqOptimizer, register_optimizer
@register_optimizer('adagrad')
class Adagrad(FairseqOptimizer):
d... | 1,266 | 29.902439 | 92 | py |
RegularizedBN | RegularizedBN-main/fairseq/optim/fairseq_optimizer.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
class FairseqOptimizer(object):
def __init__(self, args):
super().__init__()
se... | 4,361 | 31.552239 | 87 | py |
RegularizedBN | RegularizedBN-main/fairseq/optim/adadelta.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
from . import FairseqOptimizer, register_optimizer
@register_optimizer('adadelta')
class Adadelta(FairseqOptimizer):
... | 1,823 | 37 | 105 | py |
RegularizedBN | RegularizedBN-main/fairseq/optim/lr_scheduler/inverse_square_root_schedule.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 FairseqLRScheduler, register_lr_scheduler
@register_lr_scheduler('inverse_sqrt')
class InverseSquareRootSchedule(FairseqLRSche... | 2,952 | 38.905405 | 97 | py |
RegularizedBN | RegularizedBN-main/fairseq/optim/lr_scheduler/tri_stage_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.
from . import FairseqLRScheduler, register_lr_scheduler
import math
@register_lr_scheduler('tri_stage')
class TriStageLRSchedule(FairseqLRSc... | 5,062 | 29.871951 | 87 | py |
RegularizedBN | RegularizedBN-main/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 FairseqLRScheduler, register_lr_scheduler
@register_lr_scheduler('reduce_lr_on_plateau')
clas... | 4,743 | 40.982301 | 97 | py |
RegularizedBN | RegularizedBN-main/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(FairseqLRSchedul... | 4,758 | 38.991597 | 105 | py |
RegularizedBN | RegularizedBN-main/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 |
RegularizedBN | RegularizedBN-main/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 |
RegularizedBN | RegularizedBN-main/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 FairseqTask, re... | 3,605 | 28.801653 | 84 | py |
RegularizedBN | RegularizedBN-main/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 FairseqTask, re... | 3,840 | 29.007813 | 84 | py |
RegularizedBN | RegularizedBN-main/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 FairseqTask, re... | 3,532 | 28.689076 | 84 | py |
RegularizedBN | RegularizedBN-main/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__)
... | 19,691 | 41.715835 | 107 | py |
RegularizedBN | RegularizedBN-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
class TokenBlockDataset(FairseqDataset):
"""Break... | 5,961 | 34.700599 | 96 | py |
RegularizedBN | RegularizedBN-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... | 2,103 | 28.222222 | 101 | py |
RegularizedBN | RegularizedBN-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 |
RegularizedBN | RegularizedBN-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 __i... | 1,808 | 24.842857 | 70 | py |
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