FM / reformer

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

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

Name	Size	Mode	Actions
__pycache__/	-	0755	rm
configuration_reformer.py	13195	0644	edit dl rm
convert_reformer_trax_checkpoint_to_pytorch.py	7790	0644	edit dl rm
modeling_reformer.py	112050	0644	edit dl rm
tokenization_reformer.py	6870	0644	edit dl rm
tokenization_reformer_fast.py	4776	0644	edit dl rm
__init__.py	2516	0644	edit dl rm

Edit: /usr/local/lib/python3.6/site-packages/transformers/models/reformer/__init__.py (2516B)

# 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_sentencepiece_available, is_tokenizers_available, is_torch_available

_import_structure = {
    "configuration_reformer": ["REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "ReformerConfig"],
}

if is_sentencepiece_available():
    _import_structure["tokenization_reformer"] = ["ReformerTokenizer"]

if is_tokenizers_available():
    _import_structure["tokenization_reformer_fast"] = ["ReformerTokenizerFast"]

if is_torch_available():
    _import_structure["modeling_reformer"] = [
        "REFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
        "ReformerAttention",
        "ReformerForMaskedLM",
        "ReformerForQuestionAnswering",
        "ReformerForSequenceClassification",
        "ReformerLayer",
        "ReformerModel",
        "ReformerModelWithLMHead",
        "ReformerPreTrainedModel",
    ]

if TYPE_CHECKING:
    from .configuration_reformer import REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, ReformerConfig

if is_sentencepiece_available():
        from .tokenization_reformer import ReformerTokenizer

if is_tokenizers_available():
        from .tokenization_reformer_fast import ReformerTokenizerFast

if is_torch_available():
        from .modeling_reformer import (
            REFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
            ReformerAttention,
            ReformerForMaskedLM,
            ReformerForQuestionAnswering,
            ReformerForSequenceClassification,
            ReformerLayer,
            ReformerModel,
            ReformerModelWithLMHead,
            ReformerPreTrainedModel,
        )

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_sentencepiece_available, is_tokenizers_available, is_torch_available _import_structure = { "configuration_reformer": ["REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "ReformerConfig"], } if is_sentencepiece_available(): _import_structure["tokenization_reformer"] = ["ReformerTokenizer"] if is_tokenizers_available(): _import_structure["tokenization_reformer_fast"] = ["ReformerTokenizerFast"] if is_torch_available(): _import_structure["modeling_reformer"] = [ "REFORMER_PRETRAINED_MODEL_ARCHIVE_LIST", "ReformerAttention", "ReformerForMaskedLM", "ReformerForQuestionAnswering", "ReformerForSequenceClassification", "ReformerLayer", "ReformerModel", "ReformerModelWithLMHead", "ReformerPreTrainedModel", ] if TYPE_CHECKING: from .configuration_reformer import REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, ReformerConfig if is_sentencepiece_available(): from .tokenization_reformer import ReformerTokenizer if is_tokenizers_available(): from .tokenization_reformer_fast import ReformerTokenizerFast if is_torch_available(): from .modeling_reformer import ( REFORMER_PRETRAINED_MODEL_ARCHIVE_LIST, ReformerAttention, ReformerForMaskedLM, ReformerForQuestionAnswering, ReformerForSequenceClassification, ReformerLayer, ReformerModel, ReformerModelWithLMHead, ReformerPreTrainedModel, ) else: import sys sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)