FM / xlm

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

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

Name	Size	Mode	Actions
__pycache__/	-	0755	rm
configuration_xlm.py	11288	0644	edit dl rm
convert_xlm_original_pytorch_checkpoint_to_pytorch.py	2946	0644	edit dl rm
modeling_tf_xlm.py	52294	0644	edit dl rm
modeling_xlm.py	55158	0644	edit dl rm
tokenization_xlm.py	34158	0644	edit dl rm
__init__.py	2903	0644	edit dl rm

Edit: /usr/local/lib/python3.6/site-packages/transformers/models/xlm/__init__.py (2903B)

# 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_torch_available

_import_structure = {
    "configuration_xlm": ["XLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "XLMConfig"],
    "tokenization_xlm": ["XLMTokenizer"],
}

if is_torch_available():
    _import_structure["modeling_xlm"] = [
        "XLM_PRETRAINED_MODEL_ARCHIVE_LIST",
        "XLMForMultipleChoice",
        "XLMForQuestionAnswering",
        "XLMForQuestionAnsweringSimple",
        "XLMForSequenceClassification",
        "XLMForTokenClassification",
        "XLMModel",
        "XLMPreTrainedModel",
        "XLMWithLMHeadModel",
    ]

if is_tf_available():
    _import_structure["modeling_tf_xlm"] = [
        "TF_XLM_PRETRAINED_MODEL_ARCHIVE_LIST",
        "TFXLMForMultipleChoice",
        "TFXLMForQuestionAnsweringSimple",
        "TFXLMForSequenceClassification",
        "TFXLMForTokenClassification",
        "TFXLMMainLayer",
        "TFXLMModel",
        "TFXLMPreTrainedModel",
        "TFXLMWithLMHeadModel",
    ]

if TYPE_CHECKING:
    from .configuration_xlm import XLM_PRETRAINED_CONFIG_ARCHIVE_MAP, XLMConfig
    from .tokenization_xlm import XLMTokenizer

if is_torch_available():
        from .modeling_xlm import (
            XLM_PRETRAINED_MODEL_ARCHIVE_LIST,
            XLMForMultipleChoice,
            XLMForQuestionAnswering,
            XLMForQuestionAnsweringSimple,
            XLMForSequenceClassification,
            XLMForTokenClassification,
            XLMModel,
            XLMPreTrainedModel,
            XLMWithLMHeadModel,
        )

if is_tf_available():
        from .modeling_tf_xlm import (
            TF_XLM_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFXLMForMultipleChoice,
            TFXLMForQuestionAnsweringSimple,
            TFXLMForSequenceClassification,
            TFXLMForTokenClassification,
            TFXLMMainLayer,
            TFXLMModel,
            TFXLMPreTrainedModel,
            TFXLMWithLMHeadModel,
        )

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_torch_available _import_structure = { "configuration_xlm": ["XLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "XLMConfig"], "tokenization_xlm": ["XLMTokenizer"], } if is_torch_available(): _import_structure["modeling_xlm"] = [ "XLM_PRETRAINED_MODEL_ARCHIVE_LIST", "XLMForMultipleChoice", "XLMForQuestionAnswering", "XLMForQuestionAnsweringSimple", "XLMForSequenceClassification", "XLMForTokenClassification", "XLMModel", "XLMPreTrainedModel", "XLMWithLMHeadModel", ] if is_tf_available(): _import_structure["modeling_tf_xlm"] = [ "TF_XLM_PRETRAINED_MODEL_ARCHIVE_LIST", "TFXLMForMultipleChoice", "TFXLMForQuestionAnsweringSimple", "TFXLMForSequenceClassification", "TFXLMForTokenClassification", "TFXLMMainLayer", "TFXLMModel", "TFXLMPreTrainedModel", "TFXLMWithLMHeadModel", ] if TYPE_CHECKING: from .configuration_xlm import XLM_PRETRAINED_CONFIG_ARCHIVE_MAP, XLMConfig from .tokenization_xlm import XLMTokenizer if is_torch_available(): from .modeling_xlm import ( XLM_PRETRAINED_MODEL_ARCHIVE_LIST, XLMForMultipleChoice, XLMForQuestionAnswering, XLMForQuestionAnsweringSimple, XLMForSequenceClassification, XLMForTokenClassification, XLMModel, XLMPreTrainedModel, XLMWithLMHeadModel, ) if is_tf_available(): from .modeling_tf_xlm import ( TF_XLM_PRETRAINED_MODEL_ARCHIVE_LIST, TFXLMForMultipleChoice, TFXLMForQuestionAnsweringSimple, TFXLMForSequenceClassification, TFXLMForTokenClassification, TFXLMMainLayer, TFXLMModel, TFXLMPreTrainedModel, TFXLMWithLMHeadModel, ) else: import sys sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)