FM / splinter

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

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

Name	Size	Mode	Actions
__pycache__/	-	0755	rm
configuration_splinter.py	6119	0644	edit dl rm
modeling_splinter.py	44759	0644	edit dl rm
tokenization_splinter.py	22015	0644	edit dl rm
tokenization_splinter_fast.py	9658	0644	edit dl rm
__init__.py	2105	0644	edit dl rm

Edit: /usr/local/lib/python3.6/site-packages/transformers/models/splinter/__init__.py (2105B)

# 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 2021 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_tokenizers_available, is_torch_available

_import_structure = {
    "configuration_splinter": ["SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP", "SplinterConfig"],
    "tokenization_splinter": ["SplinterTokenizer"],
}

if is_tokenizers_available():
    _import_structure["tokenization_splinter_fast"] = ["SplinterTokenizerFast"]

if is_torch_available():
    _import_structure["modeling_splinter"] = [
        "SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST",
        "SplinterForQuestionAnswering",
        "SplinterLayer",
        "SplinterModel",
        "SplinterPreTrainedModel",
    ]

if TYPE_CHECKING:
    from .configuration_splinter import SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP, SplinterConfig
    from .tokenization_splinter import SplinterTokenizer

if is_tokenizers_available():
        from .tokenization_splinter_fast import SplinterTokenizerFast

if is_torch_available():
        from .modeling_splinter import (
            SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST,
            SplinterForQuestionAnswering,
            SplinterLayer,
            SplinterModel,
            SplinterPreTrainedModel,
        )

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 2021 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_tokenizers_available, is_torch_available _import_structure = { "configuration_splinter": ["SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP", "SplinterConfig"], "tokenization_splinter": ["SplinterTokenizer"], } if is_tokenizers_available(): _import_structure["tokenization_splinter_fast"] = ["SplinterTokenizerFast"] if is_torch_available(): _import_structure["modeling_splinter"] = [ "SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST", "SplinterForQuestionAnswering", "SplinterLayer", "SplinterModel", "SplinterPreTrainedModel", ] if TYPE_CHECKING: from .configuration_splinter import SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP, SplinterConfig from .tokenization_splinter import SplinterTokenizer if is_tokenizers_available(): from .tokenization_splinter_fast import SplinterTokenizerFast if is_torch_available(): from .modeling_splinter import ( SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST, SplinterForQuestionAnswering, SplinterLayer, SplinterModel, SplinterPreTrainedModel, ) else: import sys sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)