python_code stringlengths 0 992k | repo_name stringlengths 8 46 | file_path stringlengths 5 162 |
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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.
import torch
import torch.nn as nn
class BeamableMM(nn.Module):
"""This module provides an optimized MM for beam decoding with attention... | EXA-1-master | exa/models/unilm-master/edgelm/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.fairseq_dropout import FairseqDropout
f... | EXA-1-master | exa/models/unilm-master/edgelm/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 logging
import torch
import torch.nn.functional as F
logger = logging.getLogger(__name__)
def _cross_entropy_pytorch(logits, targe... | EXA-1-master | exa/models/unilm-master/edgelm/fairseq/modules/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
from typing import Dict, Optional, Tuple
import torch
import torch.nn.functional as F
from fairseq import utils
from fairseq.incr... | EXA-1-master | exa/models/unilm-master/edgelm/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... | EXA-1-master | exa/models/unilm-master/edgelm/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.
from typing import Dict, Optional
import torch
import torch.nn as nn
import torch.nn.functional as F
from fairseq import utils
from torch imp... | EXA-1-master | exa/models/unilm-master/edgelm/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
... | EXA-1-master | exa/models/unilm-master/edgelm/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 logging
from typing import List, Tuple
import torch
import torch.nn.functional as F
from fairseq.data import Dictionary
from torch imp... | EXA-1-master | exa/models/unilm-master/edgelm/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.
import functools
from typing import Any, Dict, List, Tuple, Union
import torch
import torch.utils.checkpoint as checkpoint
from fairseq impor... | EXA-1-master | exa/models/unilm-master/edgelm/fairseq/modules/checkpoint_activations.py |
# Copyright (c) Facebook, Inc. and 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
... | EXA-1-master | exa/models/unilm-master/edgelm/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 functools
import operator
import torch
import torch.nn.functional as F
from fairseq.modules.fairseq_dropout import FairseqDropout
from... | EXA-1-master | exa/models/unilm-master/edgelm/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 import nn
from torch.nn.modules.utils import _single
from torch import Tensor
class ConvTBC(torch.nn.Module):
""... | EXA-1-master | exa/models/unilm-master/edgelm/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... | EXA-1-master | exa/models/unilm-master/edgelm/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.
import torch.nn as nn
import torch
import sys
from fairseq import utils
from fairseq.distributed import utils as distributed_utils
from fairse... | EXA-1-master | exa/models/unilm-master/edgelm/fairseq/modules/base_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.
"""
This file is to re-implemented the low-rank and beam approximation of CRF layer
Proposed by:
Sun, Zhiqing, et al.
Fast Structured Decodin... | EXA-1-master | exa/models/unilm-master/edgelm/fairseq/modules/dynamic_crf_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.
"""
See "Gaussian Error Linear Units (GELUs)" by Dan Hendrycks and Kevin Gimpel with
the corresponding GitHub repo: https://github.com/hendryck... | EXA-1-master | exa/models/unilm-master/edgelm/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.
"""
LayerDrop as described in https://arxiv.org/abs/1909.11556.
"""
import torch
import torch.nn as nn
class LayerDropModuleList(nn.ModuleLi... | EXA-1-master | exa/models/unilm-master/edgelm/fairseq/modules/layer_drop.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from typing import Optional, Tuple
import torch
import torch.nn as nn
from fairseq.modules import (
FairseqDropout,
LayerDropModuleLi... | EXA-1-master | exa/models/unilm-master/edgelm/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.
"""isort:skip_file"""
from .adaptive_input import AdaptiveInput
from .adaptive_softmax import AdaptiveSoftmax
from .base_layer import BaseLaye... | EXA-1-master | exa/models/unilm-master/edgelm/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... | EXA-1-master | exa/models/unilm-master/edgelm/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 fairseq.incremental_decoding_utils import with_incremental_state
... | EXA-1-master | exa/models/unilm-master/edgelm/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.
from typing import Dict, List, Optional
import torch
import torch.nn as nn
from fairseq import utils
from fairseq.modules import LayerNorm, M... | EXA-1-master | exa/models/unilm-master/edgelm/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.
from typing import Callable, Optional
import torch
import torch.nn as nn
from fairseq import utils
from fairseq.modules import LayerNorm, Mul... | EXA-1-master | exa/models/unilm-master/edgelm/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
import torch.nn as nn
def quant_noise(module, p, block_size):
"""
Wraps modules and applies quantization noise to the w... | EXA-1-master | exa/models/unilm-master/edgelm/fairseq/modules/quant_noise.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch.nn as nn
import torch
import torch.nn.functional as F
class LocationAttention(nn.Module):
"""
Attention-Based Models fo... | EXA-1-master | exa/models/unilm-master/edgelm/fairseq/modules/location_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.
"""
Layer norm done in fp32 (for fp16 training)
"""
import torch.nn as nn
import torch.nn.functional as F
class Fp32GroupNorm(nn.GroupNorm):... | EXA-1-master | exa/models/unilm-master/edgelm/fairseq/modules/fp32_group_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.
import torch
import torch.nn as nn
import torch.nn.functional as F
from fairseq import utils
from fairseq.incremental_decoding_utils import wi... | EXA-1-master | exa/models/unilm-master/edgelm/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 logging
from typing import List, Optional
import torch.nn as nn
import torch.nn.functional as F
logger = logging.getLogger(__name__)... | EXA-1-master | exa/models/unilm-master/edgelm/fairseq/modules/fairseq_dropout.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
import torch.nn as nn
import torch.nn.functional as F
class GumbelVectorQuantizer(nn.Module):
def __init__(
self,
... | EXA-1-master | exa/models/unilm-master/edgelm/fairseq/modules/gumbel_vector_quantizer.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
import torch.nn as nn
from fairseq.modules import Fp32GroupNorm
class KmeansVectorQuantizer(nn.Module):
def __init__(
... | EXA-1-master | exa/models/unilm-master/edgelm/fairseq/modules/kmeans_vector_quantizer.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch.nn as nn
class LSTMCellWithZoneOut(nn.Module):
"""
Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations... | EXA-1-master | exa/models/unilm-master/edgelm/fairseq/modules/lstm_cell_with_zoneout.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from typing import List
import torch
from fairseq.modules.quant_noise import quant_noise
from torch import nn
class AdaptiveInput(nn.Modul... | EXA-1-master | exa/models/unilm-master/edgelm/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.incremental_decoding_utils import wi... | EXA-1-master | exa/models/unilm-master/edgelm/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
... | EXA-1-master | exa/models/unilm-master/edgelm/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.nn as nn
from .learned_positional_embedding import LearnedPositionalEmbedding
from .sinusoidal_positional_embedding import Sinus... | EXA-1-master | exa/models/unilm-master/edgelm/fairseq/modules/positional_embedding.py |
import torch.nn as nn
from .fairseq_dropout import FairseqDropout
class Lora(nn.Module):
def __init__(self, u_dim, r, v_dim, shared_u=None, shared_v=None, dropout=0.0):
super().__init__()
self.u_dim = u_dim
self.d_dim = r
self.v_dim = v_dim
self.dropout_module = FairseqDropo... | EXA-1-master | exa/models/unilm-master/edgelm/fairseq/modules/lora.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import math
import torch
from .multihead_attention import MultiheadAttention
class SparseMultiheadAttention(MultiheadAttention):
"""Sp... | EXA-1-master | exa/models/unilm-master/edgelm/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.
"""
transpose last 2 dimensions of the input
"""
import torch.nn as nn
class TransposeLast(nn.Module):
def __init__(self, deconstruct_id... | EXA-1-master | exa/models/unilm-master/edgelm/fairseq/modules/transpose_last.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import math
from typing import Any, Optional
import torch
import torch.onnx.operators
from fairseq import utils
from torch import Tensor, nn
... | EXA-1-master | exa/models/unilm-master/edgelm/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
import torch.nn as nn
import torch.nn.functional as F
try:
from apex.normalization import FusedLayerNorm as _FusedLayerNorm... | EXA-1-master | exa/models/unilm-master/edgelm/fairseq/modules/layer_norm.py |
import torch
import torch.nn as nn
import torch.nn.functional as F
import math
from inspect import isfunction
from operator import mul
from functools import reduce, wraps
from aml.multimodal_video.utils.einops.lib import rearrange, repeat
from aml.multimodal_video.utils.einops.lib.layers.torch import Rearrange
from f... | EXA-1-master | exa/models/unilm-master/edgelm/fairseq/modules/kmeans_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 torch import nn
class SamePad(nn.Module):
def __init__(self, kernel_size, causal=False):
super().__init__()
if cau... | EXA-1-master | exa/models/unilm-master/edgelm/fairseq/modules/same_pad.py |
EXA-1-master | exa/models/unilm-master/edgelm/fairseq/modules/quantization/__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.
def parse_config_yaml(yaml_data):
# Initialize to default options.
quantization_options = {
"n_centroids": {
"Lin... | EXA-1-master | exa/models/unilm-master/edgelm/fairseq/modules/quantization/quantization_options.py |
# Copyright (c) Facebook, Inc. and 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 .utils import SizeTracker, get_param, attrsetter, quantize_model_ # NOQA
| EXA-1-master | exa/models/unilm-master/edgelm/fairseq/modules/quantization/pq/__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 .em import EM, EmptyClusterResolveError
class PQ(EM):
"""
Quantizes the layer weights W with the standard Product Quantization
... | EXA-1-master | exa/models/unilm-master/edgelm/fairseq/modules/quantization/pq/pq.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import logging
import os
import random
from collections import Counter
import torch
class EM:
"""
EM algorithm used to quantize the... | EXA-1-master | exa/models/unilm-master/edgelm/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 logging
import re
from operator import attrgetter, itemgetter
import torch
import numpy as np
import torch.distributed as dist
import t... | EXA-1-master | exa/models/unilm-master/edgelm/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 torch
import torch.nn as nn
import torch.nn.functional as F
class PQLinear(nn.Module):
"""
Quantized counterpart of nn.Linear... | EXA-1-master | exa/models/unilm-master/edgelm/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 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... | EXA-1-master | exa/models/unilm-master/edgelm/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.
from .qconv import PQConv2d # NOQA
from .qemb import PQEmbedding # NOQA
from .qlinear import PQLinear # NOQA
| EXA-1-master | exa/models/unilm-master/edgelm/fairseq/modules/quantization/pq/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
import torch.nn as nn
import torch.nn.functional as F
class PQEmbedding(nn.Module):
"""
Quantized counterpart of nn.Emb... | EXA-1-master | exa/models/unilm-master/edgelm/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.
from .utils import quantize_model_ # NOQA
| EXA-1-master | exa/models/unilm-master/edgelm/fairseq/modules/quantization/scalar/__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
def emulate_int(w, bits, method, scale=None, zero_point=None):
q = globals()[f"emulate_int8_{method}"]
return q(w, scal... | EXA-1-master | exa/models/unilm-master/edgelm/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 logging
from operator import attrgetter
import torch.distributed as dist
import torch.nn as nn
from ..pq.utils import attrsetter, get... | EXA-1-master | exa/models/unilm-master/edgelm/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 torch
import torch.nn as nn
import torch.nn.functional as F
from ..ops import emulate_int
class IntLinear(nn.Module):
"""
Qu... | EXA-1-master | exa/models/unilm-master/edgelm/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.functional as F
from torch.nn.modules.conv import _ConvNd
from torch.nn.modules.utils import _pair
from ..ops im... | EXA-1-master | exa/models/unilm-master/edgelm/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.
from .qact import ActivationQuantizer # NOQA
from .qconv import IntConv2d # NOQA
from .qemb import IntEmbedding # NOQA
from .qlinear import... | EXA-1-master | exa/models/unilm-master/edgelm/fairseq/modules/quantization/scalar/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
import torch.nn as nn
import torch.nn.functional as F
from ..ops import emulate_int
class IntEmbedding(nn.Module):
"""
... | EXA-1-master | exa/models/unilm-master/edgelm/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
from ..ops import emulate_int
class ActivationQuantizer:
"""
Fake scalar quantization of the activations using a forwa... | EXA-1-master | exa/models/unilm-master/edgelm/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.
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,... | EXA-1-master | exa/models/unilm-master/edgelm/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
| EXA-1-master | exa/models/unilm-master/edgelm/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 lightconv_cuda
import torch
import torch.nn.functional as F
from fairseq import utils
from fairseq.incremental_decoding_utils import wi... | EXA-1-master | exa/models/unilm-master/edgelm/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 BuildExtension, CUDAExtension
setup(
name="lig... | EXA-1-master | exa/models/unilm-master/edgelm/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... | EXA-1-master | exa/models/unilm-master/edgelm/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
| EXA-1-master | exa/models/unilm-master/edgelm/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 dynamicconv_cuda
import torch
import torch.nn.functional as F
from fairseq import utils
from fairseq.incremental_decoding_utils import ... | EXA-1-master | exa/models/unilm-master/edgelm/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 BuildExtension, CUDAExtension
setup(
name="dyn... | EXA-1-master | exa/models/unilm-master/edgelm/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().__i... | EXA-1-master | exa/models/unilm-master/edgelm/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 ... | EXA-1-master | exa/models/unilm-master/edgelm/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 logging
import time
from collections import OrderedDict
from typing import Dict, List, Optional
import numpy as np
from fairseq.data i... | EXA-1-master | exa/models/unilm-master/edgelm/fairseq/data/multi_corpus_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(... | EXA-1-master | exa/models/unilm-master/edgelm/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... | EXA-1-master | exa/models/unilm-master/edgelm/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):... | EXA-1-master | exa/models/unilm-master/edgelm/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 ... | EXA-1-master | exa/models/unilm-master/edgelm/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, ... | EXA-1-master | exa/models/unilm-master/edgelm/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... | EXA-1-master | exa/models/unilm-master/edgelm/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__(se... | EXA-1-master | exa/models/unilm-master/edgelm/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 numpy as np
import torch
from fairseq.data import data_utils
class WordNoising(object):
"""Generate a noisy version of a sentence... | EXA-1-master | exa/models/unilm-master/edgelm/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 fairseq.data import data_utils
from . import BaseWrapperDataset
class TruncateDataset(BaseWrapperDataset):
"""T... | EXA-1-master | exa/models/unilm-master/edgelm/fairseq/data/shorten_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... | EXA-1-master | exa/models/unilm-master/edgelm/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):
... | EXA-1-master | exa/models/unilm-master/edgelm/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.
from enum import Enum
class TextCompressionLevel(Enum):
none = 0
low = 1
high = 2
class TextCompressor(object):
def __init... | EXA-1-master | exa/models/unilm-master/edgelm/fairseq/data/text_compressor.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import numpy as np
import torch
from . import FairseqDataset, data_utils
def collate(samples, pad_idx, eos_idx, fixed_pad_length=None, pad_... | EXA-1-master | exa/models/unilm-master/edgelm/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 os
import subprocess
import threading
from pathlib import Path
import numpy as np
import torch
def fasta_file_path(prefix_path):
... | EXA-1-master | exa/models/unilm-master/edgelm/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.
from torch.utils.data.dataloader import default_collate
from . import FairseqDataset
class BaseWrapperDataset(FairseqDataset):
def __in... | EXA-1-master | exa/models/unilm-master/edgelm/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, re... | EXA-1-master | exa/models/unilm-master/edgelm/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.
"""isort:skip_file"""
from .dictionary import Dictionary, TruncatedDictionary
from .fairseq_dataset import FairseqDataset, FairseqIterableDat... | EXA-1-master | exa/models/unilm-master/edgelm/fairseq/data/__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 . import FairseqDataset
class ConcatSentencesDataset(FairseqDataset):
def __init__(self, *datasets):
super().... | EXA-1-master | exa/models/unilm-master/edgelm/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.
from functools import lru_cache
import numpy as np
import torch
from fairseq.data import Dictionary, data_utils
from . import BaseWrapperDat... | EXA-1-master | exa/models/unilm-master/edgelm/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
from . import BaseWrapperDataset
class LRUCacheDataset(BaseWrapperDataset):
def __init__(self, dataset,... | EXA-1-master | exa/models/unilm-master/edgelm/fairseq/data/lru_cache_dataset.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import math
import numpy as np
import torch
from . import FairseqDataset, data_utils
def collate(
samples,
pad_idx,
eos_idx,
... | EXA-1-master | exa/models/unilm-master/edgelm/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.
from . import BaseWrapperDataset
class StripTokenDataset(BaseWrapperDataset):
def __init__(self, dataset, id_to_strip):
super().... | EXA-1-master | exa/models/unilm-master/edgelm/fairseq/data/strip_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.
try:
from collections.abc import Iterable
except ImportError:
from collections import Iterable
import contextlib
import itertools
impo... | EXA-1-master | exa/models/unilm-master/edgelm/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.
import numpy as np
import torch
from . import BaseWrapperDataset
class PrependTokenDataset(BaseWrapperDataset):
def __init__(self, data... | EXA-1-master | exa/models/unilm-master/edgelm/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 torch
from . import FairseqDataset
class TransformEosDataset(FairseqDataset):
"""A :class:`~fairseq.data.FairseqDataset` wrapper... | EXA-1-master | exa/models/unilm-master/edgelm/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 BaseWrapperDataset
class ColorizeDataset(BaseWrapperDataset):
""" Adds 'colors' property to net input that i... | EXA-1-master | exa/models/unilm-master/edgelm/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 FairseqDataset
class RawLabelDataset(FairseqDataset):
def __init__(self, labels):
super().__init__()... | EXA-1-master | exa/models/unilm-master/edgelm/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.
from . import BaseWrapperDataset
class ListDataset(BaseWrapperDataset):
def __init__(self, dataset, sizes=None):
super().__init_... | EXA-1-master | exa/models/unilm-master/edgelm/fairseq/data/list_dataset.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import logging
from collections import OrderedDict
from typing import Dict, Sequence
import numpy as np
from . import FairseqDataset, Langua... | EXA-1-master | exa/models/unilm-master/edgelm/fairseq/data/round_robin_zip_datasets.py |
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