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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|---|---|---|---|---|---|---|
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes/src/transformers/models/mmbt/__init__.py | # flake8: noqa
# There's no way to ignore "F401 '...' imported but unused" warnings in this
# module, but to preserve other warnings. So, don't check this module at all.
# Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use thi... | 1,773 | 31.254545 | 115 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes/src/transformers/models/marian/modeling_marian.py | # coding=utf-8
# Copyright 2021 The Marian Team Authors and The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licen... | 56,443 | 45.265574 | 239 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes/src/transformers/models/marian/convert_marian_to_pytorch.py | # Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 23,458 | 36.060032 | 119 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes/src/transformers/models/marian/convert_marian_tatoeba_to_pytorch.py | # Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 33,873 | 25.693459 | 175 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes/src/transformers/models/marian/__init__.py | # flake8: noqa
# There's no way to ignore "F401 '...' imported but unused" warnings in this
# module, but to preserve other warnings. So, don't check this module at all.
# Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use thi... | 2,535 | 29.926829 | 115 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes/src/transformers/models/marian/modeling_tf_marian.py | # coding=utf-8
# Copyright 2021 The Marian Team Authors and The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licen... | 61,637 | 45.837386 | 236 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes/src/transformers/models/flaubert/modeling_tf_flaubert.py | # coding=utf-8
# Copyright 2019-present, Facebook, Inc and the HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Un... | 39,450 | 41.058635 | 160 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes/src/transformers/models/flaubert/modeling_flaubert.py | # coding=utf-8
# Copyright 2019-present CNRS, Facebook Inc. and the HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#... | 17,516 | 39.454965 | 120 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes/src/transformers/models/flaubert/__init__.py | # flake8: noqa
# There's no way to ignore "F401 '...' imported but unused" warnings in this
# module, but to preserve other warnings. So, don't check this module at all.
# Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use thi... | 3,337 | 33.412371 | 115 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes/src/transformers/models/mbart/convert_mbart_original_checkpoint_to_pytorch.py | # Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 2,119 | 41.4 | 117 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes/src/transformers/models/mbart/modeling_tf_mbart.py | # coding=utf-8
# Copyright 2021 The Fairseq Authors and The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/... | 61,341 | 46.113671 | 236 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes/src/transformers/models/mbart/modeling_mbart.py | # coding=utf-8
# Copyright 2021, The Facebook AI Research Team and The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.or... | 66,941 | 44.569775 | 239 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes/src/transformers/models/mbart/__init__.py | # flake8: noqa
# There's no way to ignore "F401 '...' imported but unused" warnings in this
# module, but to preserve other warnings. So, don't check this module at all.
# Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use thi... | 2,943 | 31 | 115 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes/src/transformers/commands/add_new_model.py | # Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 9,392 | 40.017467 | 119 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes/src/transformers/commands/convert.py | # Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 7,189 | 40.560694 | 117 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes/src/transformers/commands/train.py | # Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 6,397 | 38.73913 | 117 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes/src/transformers/commands/env.py | # Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 2,604 | 34.684932 | 105 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes/src/transformers/benchmark/benchmark.py | # coding=utf-8
# Copyright 2018 The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.a... | 10,629 | 38.664179 | 181 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes/src/transformers/benchmark/benchmark_utils.py | # This file is adapted from the AllenNLP library at https://github.com/allenai/allennlp
# Copyright 2020 The HuggingFace Team and the AllenNLP authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may o... | 37,341 | 39.85558 | 204 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes/src/transformers/benchmark/benchmark_args.py | # coding=utf-8
# Copyright 2018 The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.a... | 3,777 | 31.568966 | 127 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes/src/transformers/utils/dummy_pt_objects.py | # This file is autogenerated by the command `make fix-copies`, do not edit.
from ..file_utils import requires_pytorch
class PyTorchBenchmark:
def __init__(self, *args, **kwargs):
requires_pytorch(self)
class PyTorchBenchmarkArguments:
def __init__(self, *args, **kwargs):
requires_pytorch(sel... | 52,291 | 20.842941 | 75 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes/src/transformers/utils/dummy_flax_objects.py | # This file is autogenerated by the command `make fix-copies`, do not edit.
from ..file_utils import requires_flax
class FlaxPreTrainedModel:
def __init__(self, *args, **kwargs):
requires_flax(self)
@classmethod
def from_pretrained(self, *args, **kwargs):
requires_flax(self)
FLAX_MODEL_... | 1,088 | 20.352941 | 75 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes/src/transformers/data/data_collator.py | # Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 31,408 | 48.697785 | 181 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes/src/transformers/data/test_generation_utils.py | # Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 3,438 | 33.049505 | 94 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes/src/transformers/data/datasets/glue.py | # Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 6,227 | 36.293413 | 119 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes/src/transformers/data/datasets/squad.py | # Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 9,138 | 39.438053 | 129 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes/src/transformers/data/datasets/language_modeling.py | # Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 22,821 | 42.387833 | 119 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes/src/transformers/data/processors/squad.py | # Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 33,279 | 38.43128 | 125 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes/src/transformers/data/processors/utils.py | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a cop... | 13,911 | 38.410765 | 119 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes/src/transformers/pipelines/base.py | # coding=utf-8
# Copyright 2018 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable... | 23,006 | 35.752396 | 137 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes/src/transformers/pipelines/token_classification.py | from typing import TYPE_CHECKING, List, Optional, Union
import numpy as np
from ..file_utils import add_end_docstrings, is_tf_available, is_torch_available
from ..modelcard import ModelCard
from ..models.bert.tokenization_bert import BasicTokenizer
from ..tokenization_utils import PreTrainedTokenizer
from .base impor... | 12,183 | 39.078947 | 127 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes/src/transformers/pipelines/text_classification.py | import numpy as np
from ..file_utils import add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
from ..models.auto.modeling_tf_auto import TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING
if is_torch_available():
from ..models.auto.modelin... | 3,194 | 38.9375 | 119 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes/src/transformers/pipelines/fill_mask.py | from typing import TYPE_CHECKING, Optional, Union
import numpy as np
from ..file_utils import add_end_docstrings, is_tf_available, is_torch_available
from ..modelcard import ModelCard
from ..tokenization_utils import PreTrainedTokenizer
from ..utils import logging
from .base import PIPELINE_INIT_ARGS, ArgumentHandler... | 8,002 | 40.041026 | 126 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes/src/transformers/pipelines/question_answering.py | from collections.abc import Iterable
from typing import TYPE_CHECKING, Dict, List, Optional, Tuple, Union
import numpy as np
from ..data import SquadExample, SquadFeatures, squad_convert_examples_to_features
from ..file_utils import add_end_docstrings, is_tf_available, is_torch_available
from ..modelcard import Model... | 23,982 | 48.04499 | 128 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes/src/transformers/pipelines/text2text_generation.py | from ..file_utils import add_end_docstrings, is_tf_available, is_torch_available
from ..tokenization_utils import TruncationStrategy
from ..utils import logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
from ..models.auto.modeling_tf_auto import TF_MODEL_FOR... | 12,203 | 44.707865 | 179 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes/src/transformers/pipelines/conversational.py | import uuid
from typing import List, Optional, Union
from ..file_utils import add_end_docstrings, is_tf_available, is_torch_available
from ..tokenization_utils import TruncationStrategy
from ..utils import logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
if is... | 17,335 | 43.337596 | 158 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes/src/transformers/pipelines/table_question_answering.py | import collections
import numpy as np
from ..file_utils import add_end_docstrings, is_torch_available, requires_pandas
from .base import PIPELINE_INIT_ARGS, ArgumentHandler, Pipeline
if is_torch_available():
import torch
from ..models.auto.modeling_auto import MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING
c... | 13,772 | 48.014235 | 150 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes/src/transformers/pipelines/__init__.py | # flake8: noqa
# There's no way to ignore "F401 '...' imported but unused" warnings in this
# module, but to preserve other warnings. So, don't check this module at all.
# coding=utf-8
# Copyright 2018 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this... | 19,326 | 45.126492 | 121 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes/src/transformers/pipelines/text_generation.py | from ..file_utils import add_end_docstrings
from .base import PIPELINE_INIT_ARGS, Pipeline
@add_end_docstrings(PIPELINE_INIT_ARGS)
class TextGenerationPipeline(Pipeline):
"""
Language generation pipeline using any :obj:`ModelWithLMHead`. This pipeline predicts the words that will follow a
specified text p... | 8,329 | 45.277778 | 147 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/interact.py | # coding=utf-8
import json
import datetime
import torch
from torch import Tensor
import numpy as np
import os
import logging
import argparse
import random
from transformers.trainer_utils import set_seed
from utils.building_utils import boolean_string, build_model, deploy_model
from inputters import inputters
from inp... | 5,974 | 30.781915 | 87 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/prepare.py | # coding=utf-8
import argparse
import json
import shutil
import pickle
import os
import logging
import multiprocessing as mp
from os.path import dirname, exists, join
import torch
import tqdm
from inputters import inputters
from utils.building_utils import build_model
parser = argparse.ArgumentParser()
parser.add_ar... | 2,764 | 30.781609 | 111 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/infer.py | # coding=utf-8
import argparse
import json
import logging
import os
import nltk
import numpy as np
import torch
from sklearn.metrics import classification_report, f1_score, confusion_matrix
from torch import Tensor
from transformers.trainer_utils import set_seed
from inputters import inputters
from inputters.inputte... | 16,817 | 42.012788 | 149 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/train.py | # coding=utf-8
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
import argparse
import datetime
import json
import logging
import os
import sys
import time
from os.path import join
import numpy as np
import torch
import tqdm
from torch import Tensor
from torch.distributed import get_rank, get_... | 16,784 | 38.964286 | 129 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/inputters/strat.py | # coding=utf-8
import json
import tqdm
import torch
from typing import List
from transformers.tokenization_utils import PreTrainedTokenizer
import numpy as np
import random
from functools import partial
from torch.utils.data import DataLoader, Sampler, Dataset
from torch.nn.utils.rnn import pad_sequence
from math impo... | 10,191 | 32.860465 | 117 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/inputters/inputter_utils.py | # coding=utf-8
import gzip
import json
import os
import math
import random
import pickle
from functools import partial
from torch.utils.data import DataLoader, Sampler
def _norm(s):
return ' '.join(s.strip().split())
class BucketSampler(Sampler):
"""
this sampler will sort data by sequence length
""... | 3,298 | 33.010309 | 95 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/inputters/vanilla.py | # coding=utf-8
import json
import tqdm
import torch
from typing import List
from transformers.tokenization_utils import PreTrainedTokenizer
import numpy as np
import random
from functools import partial
from torch.utils.data import DataLoader, Sampler, Dataset
from torch.nn.utils.rnn import pad_sequence
from math impo... | 9,378 | 32.859206 | 117 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/models/vanilla_blenderbot_small.py | # coding=utf-8
# copied from bart
import torch
import torch.nn as nn
import torch.nn.functional as F
from models.model_utils import BaseModel
from transformers.generation_utils import top_k_top_p_filtering
from transformers.models.blenderbot_small import (BlenderbotSmallConfig, BlenderbotSmallForConditionalGeneration,... | 4,539 | 35.910569 | 114 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/models/model_utils.py | # coding=utf-8
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Dict, Iterable
import torch
import torch.nn as nn
import torch.nn.functional as F
from transformers import (PreTrainedTokenizer, PreTrainedModel, PretrainedConfig)
class BaseModel(PreTrainedModel):
def __init__(self... | 607 | 26.636364 | 81 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/models/vanilla_dialogpt.py | # coding=utf-8
# copied from gpt2
import torch
import torch.nn as nn
import torch.nn.functional as F
from models.model_utils import BaseModel
from transformers.generation_utils import top_k_top_p_filtering
from transformers.models.gpt2 import (GPT2Config, GPT2LMHeadModel,)
from transformers.modeling_outputs import (Ca... | 5,056 | 38.20155 | 119 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/models/strat_blenderbot_small.py | # coding=utf-8
# copied from bart
import torch
import torch.nn as nn
import torch.nn.functional as F
from models.model_utils import BaseModel
from transformers.generation_utils import top_k_top_p_filtering
from transformers.models.blenderbot_small import (BlenderbotSmallConfig, BlenderbotSmallForConditionalGeneration,... | 6,130 | 36.845679 | 130 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/models/strat_dialogpt.py | # coding=utf-8
# copied from gpt2
import torch
import torch.nn as nn
import torch.nn.functional as F
from models.model_utils import BaseModel
from transformers.generation_utils import top_k_top_p_filtering
from transformers.models.gpt2 import (GPT2Config, GPT2LMHeadModel,)
from transformers.modeling_outputs import (Ca... | 6,636 | 38.041176 | 119 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/__init__.py | # May help avoid undefined symbol errors https://pytorch.org/cppdocs/notes/faq.html#undefined-symbol-errors-from-pytorch-aten
import torch
import warnings
if torch.distributed.is_available():
from . import parallel
from . import amp
from . import fp16_utils
# For optimizers and normalization there is no Python f... | 851 | 39.571429 | 125 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/amp/scaler.py | import torch
from ..multi_tensor_apply import multi_tensor_applier
from ._amp_state import _amp_state, master_params, maybe_print
from itertools import product
def scale_check_overflow_python(model_grad, master_grad, scale, check_overflow=False):
# Exception handling for 18.04 compatibility
if check_overflow:
... | 10,504 | 47.188073 | 110 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/amp/_process_optimizer.py | import types
from ..fp16_utils import master_params_to_model_params
from ..multi_tensor_apply import multi_tensor_applier
from ._amp_state import maybe_print
import torch
from ..optimizers import FusedSGD
class AmpOptimizerState(object):
def __init__(self):
pass
def _master_params_to_model_params(self):... | 20,747 | 41.342857 | 115 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/amp/_amp_state.py | # This is a "header object" that allows different amp modules to communicate.
# I'm a C++ guy, not a python guy. I decided this approach because it seemed most C++-like.
# But apparently it's ok:
# http://effbot.org/pyfaq/how-do-i-share-global-variables-across-modules.htm
import os
import torch
TORCH_MAJOR = int(torc... | 1,987 | 27.811594 | 92 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/amp/utils.py | from . import compat
import functools
import itertools
import torch
def is_cuda_enabled():
return torch.version.cuda is not None
def get_cuda_version():
return tuple(int(x) for x in torch.version.cuda.split('.'))
def is_fp_tensor(x):
if is_nested(x):
# Fast-fail version of all(is_fp_tensor)
... | 7,222 | 33.232227 | 86 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/amp/opt.py | import contextlib
import warnings
from .scaler import LossScaler, master_params
from ._amp_state import maybe_print
import numpy as np
class OptimWrapper(object):
def __init__(self, optimizer, amp_handle, num_loss):
self._optimizer = optimizer
self._amp_handle = amp_handle
self._num_loss ... | 3,446 | 32.144231 | 80 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/amp/amp.py | from . import compat, rnn_compat, utils, wrap
from .handle import AmpHandle, NoOpHandle
from .lists import functional_overrides, torch_overrides, tensor_overrides
from ._amp_state import _amp_state
from .frontend import *
import functools
import itertools
import torch
_DECORATOR_HANDLE = None
_USER_CAST_REGISTRY = ... | 7,266 | 39.825843 | 101 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/amp/compat.py | import torch
# True for post-0.4, when Variables/Tensors merged.
def variable_is_tensor():
v = torch.autograd.Variable()
return isinstance(v, torch.Tensor)
def tensor_is_variable():
x = torch.Tensor()
return type(x) == torch.autograd.Variable
# False for post-0.4
def tensor_is_float_tensor():
x =... | 1,393 | 28.659574 | 77 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/amp/wrap.py | from . import compat
from . import utils
from ._amp_state import _amp_state
from . import rnn_compat
import functools
import torch
def make_cast_wrapper(orig_fn, cast_fn, handle,
try_caching=False):
@functools.wraps(orig_fn)
def wrapper(*args, **kwargs):
if not handle.is_active(... | 11,242 | 39.588448 | 89 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/amp/_initialize.py | import torch
from torch._six import string_classes
import functools
import numpy as np
import sys
from types import MethodType
import warnings
from ._amp_state import _amp_state, warn_or_err, container_abcs
from .handle import disable_casts
from .scaler import LossScaler
from ._process_optimizer import _process_optimiz... | 11,606 | 42.965909 | 111 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/amp/frontend.py | import torch
from ._initialize import _initialize
from ._amp_state import _amp_state, warn_or_err, maybe_print
from collections import OrderedDict
class Properties(object):
"""
This class has two purposes: to establish a set of default properties,
and to route setting of these attributes through __setattr... | 21,267 | 47.009029 | 115 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/amp/rnn_compat.py | from . import utils, wrap
import torch
_VF = torch._C._VariableFunctions
RNN_NAMES = ['rnn_relu', 'rnn_tanh', 'gru', 'lstm']
def _gen_VF_wrapper(name):
def wrapper(*args, **kwargs):
return getattr(_VF, name)(*args, **kwargs)
return wrapper
# Some python magic to generate an object that has the rnn ce... | 1,995 | 35.962963 | 79 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/amp/handle.py | import contextlib
import warnings
import sys
import torch
from . import utils
from .opt import OptimWrapper
from .scaler import LossScaler
from ._amp_state import _amp_state, master_params, maybe_print
if torch.distributed.is_available():
from ..parallel.LARC import LARC
# There's no reason to expose the notion... | 12,066 | 41.79078 | 118 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/amp/lists/functional_overrides.py |
# TODO: think about the following two. They do weird things.
# - torch.nn.utils.clip_grad (but it should always be fp32 anyway)
# - torch.nn.utils.weight_norm
# Notes:
# F.instance_norm uses batch_norm internally. Which correctly handles
# fp16 in/out with fp32 weights. So we shouldn't do anything for
# either of... | 2,248 | 26.765432 | 96 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/amp/lists/tensor_overrides.py | from .. import compat
from . import torch_overrides
import importlib
import torch
# if compat.variable_is_tensor() and not compat.tensor_is_variable():
MODULE = torch.Tensor
# else:
# MODULE = torch.autograd.Variable
FP16_FUNCS = compat.filter_attrs(MODULE, [
'__matmul__',
])
FP32_FUNCS = compat.filter_at... | 1,402 | 20.921875 | 72 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/amp/lists/torch_overrides.py | import torch
from .. import utils
MODULE = torch
FP16_FUNCS = [
# Low level functions wrapped by torch.nn layers.
# The wrapper layers contain the weights which are then passed in as a parameter
# to these functions.
'conv1d',
'conv2d',
'conv3d',
'conv_transpose1d',
'conv_transpose2d'... | 2,082 | 16.956897 | 84 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/normalization/fused_layer_norm.py | import math
import torch
import numbers
from torch.nn.parameter import Parameter
from torch.nn import init
from torch.nn import functional as F
import importlib
global fused_layer_norm_cuda
fused_layer_norm_cuda = None
class FusedLayerNormAffineFunction(torch.autograd.Function):
@staticmethod
def forward(ctx, in... | 6,612 | 38.837349 | 102 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/fp16_utils/fp16_optimizer.py | import torch
from torch import nn
from torch.autograd import Variable
from torch.nn.parameter import Parameter
from torch._utils import _flatten_dense_tensors, _unflatten_dense_tensors
from ..amp._amp_state import _amp_state, maybe_print
from ..amp.scaler import LossScaler
from ..multi_tensor_apply import multi_tensor... | 27,769 | 49.036036 | 425 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/fp16_utils/fp16util.py | import torch
import torch.nn as nn
from torch.autograd import Variable
from torch._utils import _flatten_dense_tensors, _unflatten_dense_tensors
class tofp16(nn.Module):
"""
Utility module that implements::
def forward(self, input):
return input.half()
"""
def __init__(self):
... | 7,141 | 36.989362 | 337 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/fp16_utils/loss_scaler.py | import torch
# item() is a recent addition, so this helps with backward compatibility.
def to_python_float(t):
if hasattr(t, 'item'):
return t.item()
else:
return t[0]
class LossScaler:
"""
Class that manages a static loss scale. This class is intended to interact with
:class:`FP1... | 7,568 | 39.475936 | 326 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/parallel/multiproc.py | import torch
import sys
import subprocess
def docstring_hack():
"""
Multiproc file which will launch a set of processes locally for multi-gpu
usage: python -m apex.parallel.multiproc main.py ...
"""
pass
argslist = list(sys.argv)[1:]
world_size = torch.cuda.device_count()
if '--world-size' in arg... | 884 | 23.583333 | 77 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/parallel/optimized_sync_batchnorm.py | import torch
from torch.nn.modules.batchnorm import _BatchNorm
from torch.nn import functional as F
import syncbn
from .optimized_sync_batchnorm_kernel import SyncBatchnormFunction
class SyncBatchNorm(_BatchNorm):
"""
synchronized batch normalization module extented from `torch.nn.BatchNormNd`
with the a... | 4,364 | 49.755814 | 252 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/parallel/optimized_sync_batchnorm_kernel.py | import torch
from torch.autograd.function import Function
import syncbn
from apex.parallel import ReduceOp
class SyncBatchnormFunction(Function):
@staticmethod
def forward(ctx, input, z, weight, bias, running_mean, running_variance, eps, track_running_stats = True, momentum = 1.0, process_group = None, chann... | 5,559 | 45.333333 | 189 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/parallel/LARC.py | import torch
from torch import nn
from torch.nn.parameter import Parameter
class LARC(object):
"""
:class:`LARC` is a pytorch implementation of both the scaling and clipping variants of LARC,
in which the ratio between gradient and parameter magnitudes is used to calculate an adaptive
local learning r... | 4,018 | 36.212963 | 225 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/parallel/distributed.py | import torch
import torch.distributed as dist
from torch.nn.modules import Module
from torch.autograd import Variable
from collections import OrderedDict
from itertools import chain
import copy
import importlib
from ..multi_tensor_apply import multi_tensor_applier
imported_flatten_impl = False
def import_flatten_impl... | 30,651 | 46.89375 | 496 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/parallel/__init__.py | import torch
if hasattr(torch.distributed, 'ReduceOp'):
ReduceOp = torch.distributed.ReduceOp
elif hasattr(torch.distributed, 'reduce_op'):
ReduceOp = torch.distributed.reduce_op
else:
ReduceOp = torch.distributed.deprecated.reduce_op
from .distributed import DistributedDataParallel, Reducer
# This is tri... | 3,667 | 37.208333 | 162 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/parallel/sync_batchnorm.py | import torch
from torch.nn.modules.batchnorm import _BatchNorm
from torch.nn import functional as F
from .sync_batchnorm_kernel import SyncBatchnormFunction
from apex.parallel import ReduceOp
class SyncBatchNorm(_BatchNorm):
"""
synchronized batch normalization module extented from ``torch.nn.BatchNormNd``
... | 6,532 | 47.392593 | 228 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/parallel/sync_batchnorm_kernel.py | import torch
from torch.autograd.function import Function
from apex.parallel import ReduceOp
class SyncBatchnormFunction(Function):
@staticmethod
def forward(ctx, input, weight, bias, running_mean, running_variance, eps, process_group, world_size):
torch.cuda.nvtx.range_push("sync_BN_fw")
# ... | 3,761 | 41.75 | 106 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/RNN/cells.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from .RNNBackend import RNNCell
from torch.nn._functions.thnn import rnnFusedPointwise as fusedBackend
import math
class mLSTMRNNCell(RNNCell):
"""
mLSTMRNNCell
"""
def __init__(self, input_size, hidden_size, bias = False, output_... | 2,550 | 29.011765 | 156 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/RNN/RNNBackend.py | import torch
import torch.nn as nn
from torch.autograd import Variable
import torch.nn.functional as F
import math
def is_iterable(maybe_iterable):
return isinstance(maybe_iterable, list) or isinstance(maybe_iterable, tuple)
def flatten_list(tens_list):
"""
flatten_list
"""
if not is_iterable(... | 11,578 | 30.636612 | 126 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/RNN/models.py | import torch
from torch.nn._functions.rnn import LSTMCell, RNNReLUCell, RNNTanhCell, GRUCell
from .RNNBackend import bidirectionalRNN, stackedRNN, RNNCell
from .cells import mLSTMRNNCell, mLSTMCell
def toRNNBackend(inputRNN, num_layers, bidirectional=False, dropout = 0):
"""
:class:`toRNNBackend`
"""
... | 2,137 | 37.872727 | 129 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/pyprof/nvtx/nvmarker.py | """
This file intercepts (monkey patches) the following functions and adds NVTX markers.
torch.*
torch.Tensor.*
torch.nn.functional.*
torch.nn.*.forward
The NVTX markers (one or more) contain the following information
call trace (a list of file_name:line_number)
extra_repr() from torch.nn modules
module/class n... | 6,153 | 26.596413 | 636 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/pyprof/examples/operators.py | #!/usr/bin/env python3
"""
This file checks all Python operators.
"""
import sys
import torch
import torch.cuda.profiler as profiler
import operator
import inspect
#Import and initialize pyprof
from apex import pyprof
pyprof.nvtx.init()
X = 1024
Y = 1024
fa = torch.rand(X, Y).cuda()
fb = torch.rand(X, Y).cuda()
fc... | 3,439 | 22.561644 | 158 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/pyprof/examples/simple.py | #!/usr/bin/env python3
"""
This simple file provides an example of how to
- import the pyprof library and initialize it
- use the emit_nvtx context manager
- start and stop the profiler
Only kernels within profiler.start and profiler.stop calls are profiled.
To profile
$ nvprof -f -o simple.sql --profile-from-star... | 791 | 19.307692 | 72 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/pyprof/examples/lenet.py | #!/usr/bin/env python3
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.cuda.profiler as profiler
import torch.optim as optim
from apex import pyprof
pyprof.nvtx.init()
class LeNet5(nn.Module):
def __init__(self):
super(LeNet5, self).__init__()
# 1 input image channel, 6 output ch... | 1,679 | 24.454545 | 70 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/pyprof/examples/imagenet/imagenet.py | #!/usr/bin/env python3
"""
Example to run pyprof with imagenet models.
"""
import sys
import torch
import torch.nn as nn
import torchvision.models as models
import torch.cuda.profiler as profiler
import argparse
from apex import pyprof
from apex.optimizers import FusedAdam
def parseArgs():
parser = argparse.Argume... | 4,109 | 29.220588 | 530 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/pyprof/examples/jit/jit_trace_method.py | #!/usr/bin/env python3
import torch
import torch.cuda.profiler as profiler
from apex import pyprof
class Foo(torch.nn.Module):
def __init__(self, size):
super(Foo, self).__init__()
self.n = torch.nn.Parameter(torch.ones(size))
self.m = torch.nn.Parameter(torch.ones(size))
def forward(... | 817 | 21.108108 | 53 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/pyprof/examples/jit/jit_script_function.py | #!/usr/bin/env python3
import torch
import torch.cuda.profiler as profiler
from apex import pyprof
#The following creates an object "foo" of type ScriptModule
#The new object has a function called "forward"
@torch.jit.script
def foo(x, y):
return torch.sigmoid(x) + y
#Initialize pyprof after the JIT step
pyprof.nv... | 620 | 19.032258 | 59 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/pyprof/examples/jit/jit_trace_function.py | #!/usr/bin/env python3
import torch
import torch.cuda.profiler as profiler
from apex import pyprof
def foo(x, y):
return torch.sigmoid(x) + y
x = torch.zeros(4,4).cuda()
y = torch.ones(4,4).cuda()
#JIT the function using tracing
#This returns an object of type ScriptModule with a forward method.
traced_foo = torch... | 675 | 20.806452 | 67 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/pyprof/examples/jit/jit_script_method.py | #!/usr/bin/env python3
import torch
import torch.cuda.profiler as profiler
from apex import pyprof
class Foo(torch.jit.ScriptModule):
def __init__(self, size):
super(Foo, self).__init__()
self.n = torch.nn.Parameter(torch.ones(size))
self.m = torch.nn.Parameter(torch.ones(size))
@torc... | 689 | 20.5625 | 53 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/pyprof/examples/apex/fused_layer_norm.py | import torch
import fused_layer_norm_cuda
from apex.normalization import FusedLayerNorm
from apex import pyprof
pyprof.nvtx.init()
pyprof.nvtx.wrap(fused_layer_norm_cuda, 'forward')
pyprof.nvtx.wrap(fused_layer_norm_cuda, 'backward')
pyprof.nvtx.wrap(fused_layer_norm_cuda, 'forward_affine')
pyprof.nvtx.wrap(fused_laye... | 790 | 26.275862 | 69 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/pyprof/examples/apex/fused_adam.py | import torch
import fused_adam_cuda
from apex.optimizers import FusedAdam, FP16_Optimizer
from apex import pyprof
pyprof.nvtx.init()
pyprof.nvtx.wrap(fused_adam_cuda, 'adam')
model = torch.nn.Linear(10, 20).cuda().half()
criterion = torch.nn.CrossEntropyLoss().cuda()
optimizer = FusedAdam(model.parameters())
optimize... | 546 | 25.047619 | 61 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/pyprof/examples/custom_func_module/custom_module.py | #!/usr/bin/env python3
import torch
import torch.cuda.profiler as profiler
from apex import pyprof
pyprof.nvtx.init()
class Foo(torch.nn.Module):
def __init__(self, size):
super(Foo, self).__init__()
self.n = torch.nn.Parameter(torch.ones(size))
self.m = torch.nn.Parameter(torch.ones(size)... | 601 | 20.5 | 53 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/pyprof/examples/custom_func_module/custom_function.py | #!/usr/bin/env python3
import torch
import torch.cuda.profiler as profiler
from apex import pyprof
#Initialize pyprof
pyprof.nvtx.init()
class Foo(torch.autograd.Function):
@staticmethod
def forward(ctx, in1, in2):
out = in1 + in2 #This could be a custom C/C++ function.
return out
@staticmethod
def backward... | 762 | 21.441176 | 58 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/pyprof/examples/user_annotation/resnet.py | #!/usr/bin/env python3
"""
An example showing use of nested NVTX markers.
"""
import torch
import torch.nn as nn
import torch.cuda.profiler as profiler
import torch.cuda.nvtx as nvtx
from apex import pyprof
pyprof.nvtx.init()
def conv3x3(in_planes, out_planes, stride=1, groups=1, dilation=1):
"""3x3 convolution wi... | 5,660 | 25.208333 | 90 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/pyprof/parse/nvvp.py | import sys
class NVVP(object):
"""
This class gets kernel information from the SQL (nvvp) database.
"""
driverT = "CUPTI_ACTIVITY_KIND_DRIVER"
runtimeT = "CUPTI_ACTIVITY_KIND_RUNTIME"
kernelT = "CUPTI_ACTIVITY_KIND_CONCURRENT_KERNEL"
markerT = "CUPTI_ACTIVITY_KIND_MARKER"
stringT = "StringTable"
def __init_... | 8,803 | 30.109541 | 192 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/pyprof/parse/parse.py | #!/usr/bin/env python3
"""
Parse the SQL db and print a dictionary for every kernel.
"""
import sys
import argparse
from tqdm import tqdm
from .db import DB
from .kernel import Kernel
from .nvvp import NVVP
def parseArgs():
parser = argparse.ArgumentParser(prog=sys.argv[0], description="Parse SQL (nvvp) db.")
par... | 2,907 | 22.642276 | 156 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/pyprof/parse/kernel.py | import cxxfilt, struct, binascii
#Helper functions
def demangle(name):
"""
Demangle a C++ string
"""
return cxxfilt.demangle(name)
def encode_object_id(pid, tid):
"""
Given process id (pid) and thread id (tid), return the object id.
object id = pid (little endian 4 bytes) + tid (little endian 8 bytes)
"""
o... | 5,286 | 24.056872 | 175 | py |
Emotional-Support-Conversation | Emotional-Support-Conversation-main/codes_zcj/apex/pyprof/prof/embedding.py | from collections import OrderedDict
from .utility import Utility
from .base import OperatorLayerBase
class Embedding(OperatorLayerBase):
def __init__(self, d):
marker = eval(d.argMarker[0])
mod = marker['mod']
op = marker['op']
args = marker['args']
self.marker = marker
self.mod_ = mod
self.op_ = op
... | 1,409 | 18.583333 | 105 | py |
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