FM / longformer

/usr/local/lib/python3.6/site-packages/transformers/models/longformer/

/usr/local/lib/python3.6/site-packages/transformers/models/longformer

Name	Size	Mode	Actions
__pycache__/	-	0755	rm
configuration_longformer.py	3407	0644	edit dl rm
convert_longformer_original_pytorch_lightning_to_pytorch.py	3027	0644	edit dl rm
modeling_longformer.py	111780	0644	edit dl rm
modeling_tf_longformer.py	123396	0644	edit dl rm
tokenization_longformer.py	3122	0644	edit dl rm
tokenization_longformer_fast.py	4150	0644	edit dl rm
__init__.py	3566	0644	edit dl rm

Edit: /usr/local/lib/python3.6/site-packages/transformers/models/longformer/__init__.py (3566B)

# 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 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 law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from typing import TYPE_CHECKING

from ...utils import _LazyModule, is_tf_available, is_tokenizers_available, is_torch_available

_import_structure = {
    "configuration_longformer": [
        "LONGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "LongformerConfig",
        "LongformerOnnxConfig",
    ],
    "tokenization_longformer": ["LongformerTokenizer"],
}

if is_tokenizers_available():
    _import_structure["tokenization_longformer_fast"] = ["LongformerTokenizerFast"]

if is_torch_available():
    _import_structure["modeling_longformer"] = [
        "LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
        "LongformerForMaskedLM",
        "LongformerForMultipleChoice",
        "LongformerForQuestionAnswering",
        "LongformerForSequenceClassification",
        "LongformerForTokenClassification",
        "LongformerModel",
        "LongformerPreTrainedModel",
        "LongformerSelfAttention",
    ]

if is_tf_available():
    _import_structure["modeling_tf_longformer"] = [
        "TF_LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
        "TFLongformerForMaskedLM",
        "TFLongformerForMultipleChoice",
        "TFLongformerForQuestionAnswering",
        "TFLongformerForSequenceClassification",
        "TFLongformerForTokenClassification",
        "TFLongformerModel",
        "TFLongformerPreTrainedModel",
        "TFLongformerSelfAttention",
    ]

if TYPE_CHECKING:
    from .configuration_longformer import (
        LONGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
        LongformerConfig,
        LongformerOnnxConfig,
    )
    from .tokenization_longformer import LongformerTokenizer

if is_tokenizers_available():
        from .tokenization_longformer_fast import LongformerTokenizerFast

if is_torch_available():
        from .modeling_longformer import (
            LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
            LongformerForMaskedLM,
            LongformerForMultipleChoice,
            LongformerForQuestionAnswering,
            LongformerForSequenceClassification,
            LongformerForTokenClassification,
            LongformerModel,
            LongformerPreTrainedModel,
            LongformerSelfAttention,
        )

if is_tf_available():
        from .modeling_tf_longformer import (
            TF_LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFLongformerForMaskedLM,
            TFLongformerForMultipleChoice,
            TFLongformerForQuestionAnswering,
            TFLongformerForSequenceClassification,
            TFLongformerForTokenClassification,
            TFLongformerModel,
            TFLongformerPreTrainedModel,
            TFLongformerSelfAttention,
        )

else:
    import sys

sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)

# 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 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 law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from typing import TYPE_CHECKING from ...utils import _LazyModule, is_tf_available, is_tokenizers_available, is_torch_available _import_structure = { "configuration_longformer": [ "LONGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "LongformerConfig", "LongformerOnnxConfig", ], "tokenization_longformer": ["LongformerTokenizer"], } if is_tokenizers_available(): _import_structure["tokenization_longformer_fast"] = ["LongformerTokenizerFast"] if is_torch_available(): _import_structure["modeling_longformer"] = [ "LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST", "LongformerForMaskedLM", "LongformerForMultipleChoice", "LongformerForQuestionAnswering", "LongformerForSequenceClassification", "LongformerForTokenClassification", "LongformerModel", "LongformerPreTrainedModel", "LongformerSelfAttention", ] if is_tf_available(): _import_structure["modeling_tf_longformer"] = [ "TF_LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST", "TFLongformerForMaskedLM", "TFLongformerForMultipleChoice", "TFLongformerForQuestionAnswering", "TFLongformerForSequenceClassification", "TFLongformerForTokenClassification", "TFLongformerModel", "TFLongformerPreTrainedModel", "TFLongformerSelfAttention", ] if TYPE_CHECKING: from .configuration_longformer import ( LONGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, LongformerConfig, LongformerOnnxConfig, ) from .tokenization_longformer import LongformerTokenizer if is_tokenizers_available(): from .tokenization_longformer_fast import LongformerTokenizerFast if is_torch_available(): from .modeling_longformer import ( LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST, LongformerForMaskedLM, LongformerForMultipleChoice, LongformerForQuestionAnswering, LongformerForSequenceClassification, LongformerForTokenClassification, LongformerModel, LongformerPreTrainedModel, LongformerSelfAttention, ) if is_tf_available(): from .modeling_tf_longformer import ( TF_LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST, TFLongformerForMaskedLM, TFLongformerForMultipleChoice, TFLongformerForQuestionAnswering, TFLongformerForSequenceClassification, TFLongformerForTokenClassification, TFLongformerModel, TFLongformerPreTrainedModel, TFLongformerSelfAttention, ) else: import sys sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)