FM / canine

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

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

Name	Size	Mode	Actions
__pycache__/	-	0755	rm
configuration_canine.py	6548	0644	edit dl rm
convert_canine_original_tf_checkpoint_to_pytorch.py	2118	0644	edit dl rm
modeling_canine.py	70012	0644	edit dl rm
tokenization_canine.py	9275	0644	edit dl rm
__init__.py	2163	0644	edit dl rm

Edit: /usr/local/lib/python3.6/site-packages/transformers/models/canine/__init__.py (2163B)

# 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_tokenizers_available, is_torch_available

_import_structure = {
    "configuration_canine": ["CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP", "CanineConfig"],
    "tokenization_canine": ["CanineTokenizer"],
}

if is_torch_available():
    _import_structure["modeling_canine"] = [
        "CANINE_PRETRAINED_MODEL_ARCHIVE_LIST",
        "CanineForMultipleChoice",
        "CanineForQuestionAnswering",
        "CanineForSequenceClassification",
        "CanineForTokenClassification",
        "CanineLayer",
        "CanineModel",
        "CaninePreTrainedModel",
        "load_tf_weights_in_canine",
    ]

if TYPE_CHECKING:
    from .configuration_canine import CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP, CanineConfig
    from .tokenization_canine import CanineTokenizer

if is_torch_available():
        from .modeling_canine import (
            CANINE_PRETRAINED_MODEL_ARCHIVE_LIST,
            CanineForMultipleChoice,
            CanineForQuestionAnswering,
            CanineForSequenceClassification,
            CanineForTokenClassification,
            CanineLayer,
            CanineModel,
            CaninePreTrainedModel,
            load_tf_weights_in_canine,
        )

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_tokenizers_available, is_torch_available _import_structure = { "configuration_canine": ["CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP", "CanineConfig"], "tokenization_canine": ["CanineTokenizer"], } if is_torch_available(): _import_structure["modeling_canine"] = [ "CANINE_PRETRAINED_MODEL_ARCHIVE_LIST", "CanineForMultipleChoice", "CanineForQuestionAnswering", "CanineForSequenceClassification", "CanineForTokenClassification", "CanineLayer", "CanineModel", "CaninePreTrainedModel", "load_tf_weights_in_canine", ] if TYPE_CHECKING: from .configuration_canine import CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP, CanineConfig from .tokenization_canine import CanineTokenizer if is_torch_available(): from .modeling_canine import ( CANINE_PRETRAINED_MODEL_ARCHIVE_LIST, CanineForMultipleChoice, CanineForQuestionAnswering, CanineForSequenceClassification, CanineForTokenClassification, CanineLayer, CanineModel, CaninePreTrainedModel, load_tf_weights_in_canine, ) else: import sys sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)