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# Copyright (c) Facebook, Inc. and 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
class DynamicLossScaler(object):
def __init__(
self... | data2vec_vision-main | infoxlm/fairseq/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.
import torch.optim
from . import FairseqOptimizer, register_optimizer
@register_optimizer('adagrad')
class Adagrad(FairseqOptimizer):
d... | data2vec_vision-main | infoxlm/fairseq/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 math
import types
import torch
import torch.optim
import torch.distributed as dist
from . import FairseqOptimizer, register_optimizer... | data2vec_vision-main | infoxlm/fairseq/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 torch.optim
from . import FairseqOptimizer, register_optimizer
@register_optimizer('adadelta')
class Adadelta(FairseqOptimizer):
... | data2vec_vision-main | infoxlm/fairseq/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.
from . import FairseqLRScheduler, register_lr_scheduler
@register_lr_scheduler('fixed')
class FixedSchedule(FairseqLRScheduler):
"""Deca... | data2vec_vision-main | infoxlm/fairseq/fairseq/optim/lr_scheduler/fixed_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.
import torch.optim.lr_scheduler
from . import FairseqLRScheduler, register_lr_scheduler
@register_lr_scheduler('reduce_lr_on_plateau')
clas... | data2vec_vision-main | infoxlm/fairseq/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 importlib
import os
from fairseq import registry
from fairseq.optim.lr_scheduler.fairseq_lr_scheduler import FairseqLRScheduler
buil... | data2vec_vision-main | infoxlm/fairseq/fairseq/optim/lr_scheduler/__init__.py |
# Copyright (c) Facebook, Inc. and 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('polynomial_decay')
class PolynomialDecaySchedule(FairseqLRSc... | data2vec_vision-main | infoxlm/fairseq/fairseq/optim/lr_scheduler/polynomial_decay_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... | data2vec_vision-main | infoxlm/fairseq/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 FairseqOptimizer
class FairseqLRScheduler(object):
def __init__(self, args, optimizer):
super().__init__()
... | data2vec_vision-main | infoxlm/fairseq/fairseq/optim/lr_scheduler/fairseq_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... | data2vec_vision-main | infoxlm/fairseq/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.
import math
from . import FairseqLRScheduler, register_lr_scheduler
@register_lr_scheduler('cosine')
class CosineSchedule(FairseqLRSchedule... | data2vec_vision-main | infoxlm/fairseq/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('triangular')
class TriangularSchedule(FairseqLR... | data2vec_vision-main | infoxlm/fairseq/fairseq/optim/lr_scheduler/triangular_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 typing import List, Optional
import torch
from torch import Tensor
@torch.jit.script
def script_skip_tensor_list(x: List[Tensor], mask... | data2vec_vision-main | infoxlm/fairseq/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.
"""
Base classes for various fairseq models.
"""
from typing import Dict, List, Optional
import torch
import torch.nn as nn
import torch.nn.f... | data2vec_vision-main | infoxlm/fairseq/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.
import torch.nn as nn
class FairseqEncoder(nn.Module):
"""Base class for encoders."""
def __init__(self, dictionary):
super... | data2vec_vision-main | infoxlm/fairseq/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 math
import os
import torch
import torch.nn as nn
import torch.nn.functional as F
from fairseq import checkpoint_utils
from fairseq.m... | data2vec_vision-main | infoxlm/fairseq/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.
from fairseq import options
from fairseq.models import (
FairseqLanguageModel,
register_model,
register_model_architecture,
)
from... | data2vec_vision-main | infoxlm/fairseq/fairseq/models/fconv_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.
from collections import OrderedDict
from fairseq import utils
from fairseq.models import (
FairseqMultiModel,
register_model,
reg... | data2vec_vision-main | infoxlm/fairseq/fairseq/models/multilingual_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.nonautoregressive_transformer import ... | data2vec_vision-main | infoxlm/fairseq/fairseq/models/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.nn as nn
from fairseq import utils
class FairseqDecoder(nn.Module):
"""Base class for decoders."""
def __init__(self,... | data2vec_vision-main | infoxlm/fairseq/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.
import argparse
import importlib
import os
from .fairseq_decoder import FairseqDecoder
from .fairseq_encoder import FairseqEncoder
from .fair... | data2vec_vision-main | infoxlm/fairseq/fairseq/models/__init__.py |
# Copyright (c) Facebook, Inc. and 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... | data2vec_vision-main | infoxlm/fairseq/fairseq/models/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 os
from typing import Any, Dict
from fairseq import checkpoint_utils
from fairseq.data.legacy.masked_lm_dictionary import MaskedLMDict... | data2vec_vision-main | infoxlm/fairseq/fairseq/models/transformer_from_pretrained_xlm.py |
# Copyright (c) Facebook, Inc. and 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.levenshtein_transformer import (
_fill,
_skip,
_ski... | data2vec_vision-main | infoxlm/fairseq/fairseq/models/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 torch
import torch.nn.functional as F
from fairseq import utils
from fairseq.iterative_refinement_generator import DecoderOut
from fai... | data2vec_vision-main | infoxlm/fairseq/fairseq/models/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 inspect
import torch.nn as nn
from fairseq.legacy_distributed_data_parallel import LegacyDistributedDataParallel
from fairseq.models ... | data2vec_vision-main | infoxlm/fairseq/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.
"""
This file implements:
Ghazvininejad, Marjan, et al.
"Constant-time machine translation with conditional masked language models."
arXiv pre... | data2vec_vision-main | infoxlm/fairseq/fairseq/models/cmlm_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.
from collections import namedtuple
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
from fairseq import option... | data2vec_vision-main | infoxlm/fairseq/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.
from fairseq import options, utils
from fairseq.models import (
FairseqLanguageModel,
register_model,
register_model_architecture,... | data2vec_vision-main | infoxlm/fairseq/fairseq/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 math
import torch
import torch.nn as nn
import torch.nn.functional as F
from fairseq import utils
from fairseq.models import (
Fai... | data2vec_vision-main | infoxlm/fairseq/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 sys
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
from . import (
BaseFairseqModel, register_mo... | data2vec_vision-main | infoxlm/fairseq/fairseq/models/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 torch
import torch.nn as nn
import torch.nn.functional as F
from fairseq import options, utils
from fairseq.models import (
Fairse... | data2vec_vision-main | infoxlm/fairseq/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.
from fairseq.models import FairseqEncoder
class CompositeEncoder(FairseqEncoder):
"""
A wrapper around a dictionary of :class:`Fairs... | data2vec_vision-main | infoxlm/fairseq/fairseq/models/composite_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 numpy as np
import torch
import torch.nn.functional as F
from fairseq.models import register_model, register_model_architecture
from f... | data2vec_vision-main | infoxlm/fairseq/fairseq/models/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 torch
import torch.nn as nn
import torch.nn.functional as F
from fairseq import utils
from fairseq.models import (
BaseFairseqMode... | data2vec_vision-main | infoxlm/fairseq/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.
from fairseq.models import FairseqDecoder
class FairseqIncrementalDecoder(FairseqDecoder):
"""Base class for incremental decoders.
... | data2vec_vision-main | infoxlm/fairseq/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 math
import torch
import torch.nn as nn
import torch.nn.functional as F
from fairseq import options, utils
from fairseq.models import... | data2vec_vision-main | infoxlm/fairseq/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.
from fairseq import options
from fairseq.models import (
FairseqLanguageModel,
register_model,
register_model_architecture,
)
from... | data2vec_vision-main | infoxlm/fairseq/fairseq/models/lightconv_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.
from .hub_interface import * # noqa
from .model import * # noqa
| data2vec_vision-main | infoxlm/fairseq/fairseq/models/bart/__init__.py |
# Copyright (c) Facebook, Inc. and 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 torch.nn as n... | data2vec_vision-main | infoxlm/fairseq/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.
import copy
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from typing import List
from fairseq impor... | data2vec_vision-main | infoxlm/fairseq/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.
from collections import Counter
from typing import List
import torch
def align_bpe_to_words(roberta, bpe_tokens: torch.LongTensor, other_to... | data2vec_vision-main | infoxlm/fairseq/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 .hub_interface import * # noqa
from .model import * # noqa
| data2vec_vision-main | infoxlm/fairseq/fairseq/models/roberta/__init__.py |
# Copyright (c) Facebook, Inc. and 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 torch
import torch.nn as nn
import torch.nn.functional as F
from fair... | data2vec_vision-main | infoxlm/fairseq/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.
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... | data2vec_vision-main | infoxlm/fairseq/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 torch
import torch.nn as nn
class BeamableMM(nn.Module):
"""This module provides an optimized MM for beam decoding with attention... | data2vec_vision-main | infoxlm/fairseq/fairseq/modules/beamable_mm.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
#
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
from fairseq.modules.scalar_bias import scalar_bias
class ... | data2vec_vision-main | infoxlm/fairseq/fairseq/modules/downsampled_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.
import math
import torch
from torch import nn
from torch.nn import Parameter
import torch.nn.functional as F
from fairseq import utils
clas... | data2vec_vision-main | infoxlm/fairseq/fairseq/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 __future__ import absolute_import, division, print_function, unicode_literals
from collections.abc import Iterable
from itertools import... | data2vec_vision-main | infoxlm/fairseq/fairseq/modules/vggblock.py |
# Copyright (c) Facebook, Inc. and 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
class MeanPoolGatingNetwork(torch.nn.Module):
"""A simple mean-pooling gating network for s... | data2vec_vision-main | infoxlm/fairseq/fairseq/modules/mean_pool_gating_network.py |
# Copyright (c) Facebook, Inc. and 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 import utils
class LearnedPositionalEmbedding(nn.Embedding):
"""
This module learns positional e... | data2vec_vision-main | infoxlm/fairseq/fairseq/modules/learned_positional_embedding.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
class GradMultiply(torch.autograd.Function):
@staticmethod
def forward(ctx, x, scale):
ctx.scale = scale
... | data2vec_vision-main | infoxlm/fairseq/fairseq/modules/grad_multiply.py |
# Copyright (c) Facebook, Inc. and 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 import nn
from typing import List, Tuple
from .highway import Highway
from fairseq.... | data2vec_vision-main | infoxlm/fairseq/fairseq/modules/character_token_embedder.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from fairseq.modules import TransformerSentenceEncoderLayer
from fairseq.modules.sparse_multihead_attention import SparseMultiheadAttention
... | data2vec_vision-main | infoxlm/fairseq/fairseq/modules/sparse_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 operator
import functools
import torch
import torch.nn.functional as F
from torch import nn
class TiedLinear(nn.Module):
def __i... | data2vec_vision-main | infoxlm/fairseq/fairseq/modules/adaptive_softmax.py |
# Copyright (c) Facebook, Inc. and 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.nn.modules.utils import _single
class ConvTBC(torch.nn.Module):
"""1D convolution over an input of shape (time x... | data2vec_vision-main | infoxlm/fairseq/fairseq/modules/conv_tbc.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch.nn.functional as F
def unfold1d(x, kernel_size, padding_l, pad_value=0):
'''unfold T x B x C to T x B x C x K'''
if ker... | data2vec_vision-main | infoxlm/fairseq/fairseq/modules/unfold.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
See "Gaussian Error Linear Units (GELUs)" by Dan Hendrycks and Kevin Gimpel with
the corresponding GitHub repo: https://github.com/hendryck... | data2vec_vision-main | infoxlm/fairseq/fairseq/modules/gelu.py |
# Copyright (c) Facebook, Inc. and 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... | data2vec_vision-main | infoxlm/fairseq/fairseq/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 .adaptive_input import AdaptiveInput
from .adaptive_softmax import AdaptiveSoftmax
from .beamable_mm import BeamableMM
from .character_to... | data2vec_vision-main | infoxlm/fairseq/fairseq/modules/__init__.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch.nn as nn
from fairseq.modules import TransformerSentenceEncoder
from fairseq.modules.sparse_transformer_sentence_encoder_layer im... | data2vec_vision-main | infoxlm/fairseq/fairseq/modules/sparse_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.
import torch
import torch.nn.functional as F
from fairseq import utils
from .conv_tbc import ConvTBC
class LinearizedConvolution(ConvTBC):... | data2vec_vision-main | infoxlm/fairseq/fairseq/modules/linearized_convolution.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
import torch.nn as nn
import torch.nn.functional as F
from fairseq import utils
from fairseq.modules import LayerNorm, MultiheadA... | data2vec_vision-main | infoxlm/fairseq/fairseq/modules/transformer_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 as nn
import torch.nn.functional as F
from fairseq import utils
from fairseq.modules import (
LayerNorm,
... | data2vec_vision-main | infoxlm/fairseq/fairseq/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
from torch import nn
class Highway(torch.nn.Module):
"""
A `Highway layer <https://arxiv.org/abs/1505.00387>`_.
Ad... | data2vec_vision-main | infoxlm/fairseq/fairseq/modules/highway.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
import torch.nn as nn
import torch.nn.functional as F
from fairseq import utils
from .unfold import unfold1d
def DynamicConv(i... | data2vec_vision-main | infoxlm/fairseq/fairseq/modules/dynamic_convolution.py |
# Copyright (c) Facebook, Inc. and 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 typing import List
class AdaptiveInput(nn.Module):
def __init__(
self,
vocab_s... | data2vec_vision-main | infoxlm/fairseq/fairseq/modules/adaptive_input.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
import torch.nn as nn
import torch.nn.functional as F
from fairseq import utils
from fairseq.modules.unfold import unfold1d
de... | data2vec_vision-main | infoxlm/fairseq/fairseq/modules/lightweight_convolution.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
#
import torch
class ScalarBias(torch.autograd.Function):
"""
Adds a vector of scalars, used in self-attention mechanism to allow
... | data2vec_vision-main | infoxlm/fairseq/fairseq/modules/scalar_bias.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
class LogSumExpMoE(torch.autograd.Function):
"""Standard LogSumExp forward pass, but use *posterior* for the backward.
... | data2vec_vision-main | infoxlm/fairseq/fairseq/modules/logsumexp_moe.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch.nn as nn
from .learned_positional_embedding import LearnedPositionalEmbedding
from .sinusoidal_positional_embedding import Sinus... | data2vec_vision-main | infoxlm/fairseq/fairseq/modules/positional_embedding.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import math
import torch
from .multihead_attention import MultiheadAttention
class SparseMultiheadAttention(MultiheadAttention):
""" Spa... | data2vec_vision-main | infoxlm/fairseq/fairseq/modules/sparse_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.
import math
import torch
import torch.nn as nn
import torch.onnx.operators
from fairseq import utils
class SinusoidalPositionalEmbedding(n... | data2vec_vision-main | infoxlm/fairseq/fairseq/modules/sinusoidal_positional_embedding.py |
# Copyright (c) Facebook, Inc. and 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 LayerNorm(normalized_shape, eps=1e-5, elementwise_affine=True, export=False):
if not export and torch.cuda.is_available... | data2vec_vision-main | infoxlm/fairseq/fairseq/modules/layer_norm.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
def gen_forward():
kernels = [3, 5, 7, 15, 31, 63, 127, 255]
seqs = [32 * x for x in [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14,... | data2vec_vision-main | infoxlm/fairseq/fairseq/modules/lightconv_layer/cuda_function_gen.py |
# Copyright (c) Facebook, Inc. and 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 .lightconv_layer import LightconvLayer # noqa
| data2vec_vision-main | infoxlm/fairseq/fairseq/modules/lightconv_layer/__init__.py |
# Copyright (c) Facebook, Inc. and 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... | data2vec_vision-main | infoxlm/fairseq/fairseq/modules/lightconv_layer/lightconv_layer.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... | data2vec_vision-main | infoxlm/fairseq/fairseq/modules/lightconv_layer/setup.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
def gen_forward():
kernels = [3, 5, 7, 15, 31, 63, 127, 255]
blocks = [32, 64, 128, 256]
head = """
/**
* Copyright (c) Facebo... | data2vec_vision-main | infoxlm/fairseq/fairseq/modules/dynamicconv_layer/cuda_function_gen.py |
# Copyright (c) Facebook, Inc. and 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 .dynamicconv_layer import DynamicconvLayer # noqa
| data2vec_vision-main | infoxlm/fairseq/fairseq/modules/dynamicconv_layer/__init__.py |
# Copyright (c) Facebook, Inc. and 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... | data2vec_vision-main | infoxlm/fairseq/fairseq/modules/dynamicconv_layer/dynamicconv_layer.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... | data2vec_vision-main | infoxlm/fairseq/fairseq/modules/dynamicconv_layer/setup.py |
# Copyright (c) Facebook, Inc. and 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 OffsetTokensDataset(BaseWrapperDataset):
def __init__(self, dataset, offset):
super().__... | data2vec_vision-main | infoxlm/fairseq/fairseq/data/offset_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 collections import OrderedDict
import torch
from torch.utils.data.dataloader import default_collate
from . import FairseqDataset
def ... | data2vec_vision-main | infoxlm/fairseq/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.
import numpy as np
from . import BaseWrapperDataset
class TruncateDataset(BaseWrapperDataset):
def __init__(self, dataset, truncation_... | data2vec_vision-main | infoxlm/fairseq/fairseq/data/truncate_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(... | data2vec_vision-main | infoxlm/fairseq/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.
from . import BaseWrapperDataset
class ReplaceDataset(BaseWrapperDataset):
"""Replaces tokens found in the dataset by a specified replac... | data2vec_vision-main | infoxlm/fairseq/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.
import torch
from fairseq import utils
from . import FairseqDataset
def backtranslate_samples(samples, collate_fn, generate_fn, cuda=True)... | data2vec_vision-main | infoxlm/fairseq/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 . import FairseqDataset
class IdDataset(FairseqDataset):
def __getitem__(self, index):
return index
def... | data2vec_vision-main | infoxlm/fairseq/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 numpy as np
import torch
from . import BaseWrapperDataset
class PrependDataset(BaseWrapperDataset):
def __init__(self, dataset, ... | data2vec_vision-main | infoxlm/fairseq/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.
from collections import OrderedDict
from typing import Callable, Dict, List
import numpy as np
from . import FairseqDataset
def uniform_sa... | data2vec_vision-main | infoxlm/fairseq/fairseq/data/multi_corpus_sampled_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
class NumSamplesDataset(FairseqDataset):
def __getitem__(self, index):
return 1
def __len__(s... | data2vec_vision-main | infoxlm/fairseq/fairseq/data/num_samples_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
import numpy as np
from fairseq.data import data_utils
class WordNoising(object):
"""Generate a noisy version of a sentenc... | data2vec_vision-main | infoxlm/fairseq/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
from . import BaseWrapperDataset
class SubsampleDataset(BaseWrapperDataset):
"""Subsamples a given dataset by a spec... | data2vec_vision-main | infoxlm/fairseq/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 numpy as np
from . import BaseWrapperDataset
class SortDataset(BaseWrapperDataset):
def __init__(self, dataset, sort_order):
... | data2vec_vision-main | infoxlm/fairseq/fairseq/data/sort_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:
... | data2vec_vision-main | infoxlm/fairseq/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.
from torch.utils.data.dataloader import default_collate
from . import FairseqDataset
class BaseWrapperDataset(FairseqDataset):
def __i... | data2vec_vision-main | infoxlm/fairseq/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.
import numpy as np
import torch
from . import BaseWrapperDataset
class NumelDataset(BaseWrapperDataset):
def __init__(self, dataset, r... | data2vec_vision-main | infoxlm/fairseq/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.
from .dictionary import Dictionary, TruncatedDictionary
from .fairseq_dataset import FairseqDataset, FairseqIterableDataset
from .base_wrapp... | data2vec_vision-main | infoxlm/fairseq/fairseq/data/__init__.py |
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