FM / fnet

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

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

Name	Size	Mode	Actions
__pycache__/	-	0755	rm
configuration_fnet.py	5809	0644	edit dl rm
convert_fnet_original_flax_checkpoint_to_pytorch.py	6884	0644	edit dl rm
modeling_fnet.py	49471	0644	edit dl rm
tokenization_fnet.py	13234	0644	edit dl rm
tokenization_fnet_fast.py	8557	0644	edit dl rm
__init__.py	2433	0644	edit dl rm

Edit: /usr/local/lib/python3.6/site-packages/transformers/models/fnet/__init__.py (2433B)

# 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_fnet": ["FNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "FNetConfig"],
    "tokenization_fnet": ["FNetTokenizer"],
}

if is_tokenizers_available():
    _import_structure["tokenization_fnet_fast"] = ["FNetTokenizerFast"]

if is_torch_available():
    _import_structure["modeling_fnet"] = [
        "FNET_PRETRAINED_MODEL_ARCHIVE_LIST",
        "FNetForMaskedLM",
        "FNetForMultipleChoice",
        "FNetForNextSentencePrediction",
        "FNetForPreTraining",
        "FNetForQuestionAnswering",
        "FNetForSequenceClassification",
        "FNetForTokenClassification",
        "FNetLayer",
        "FNetModel",
        "FNetPreTrainedModel",
    ]

if TYPE_CHECKING:
    from .configuration_fnet import FNET_PRETRAINED_CONFIG_ARCHIVE_MAP, FNetConfig
    from .tokenization_fnet import FNetTokenizer

if is_tokenizers_available():
        from .tokenization_fnet_fast import FNetTokenizerFast

if is_torch_available():
        from .modeling_fnet import (
            FNET_PRETRAINED_MODEL_ARCHIVE_LIST,
            FNetForMaskedLM,
            FNetForMultipleChoice,
            FNetForNextSentencePrediction,
            FNetForPreTraining,
            FNetForQuestionAnswering,
            FNetForSequenceClassification,
            FNetForTokenClassification,
            FNetLayer,
            FNetModel,
            FNetPreTrainedModel,
        )

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_fnet": ["FNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "FNetConfig"], "tokenization_fnet": ["FNetTokenizer"], } if is_tokenizers_available(): _import_structure["tokenization_fnet_fast"] = ["FNetTokenizerFast"] if is_torch_available(): _import_structure["modeling_fnet"] = [ "FNET_PRETRAINED_MODEL_ARCHIVE_LIST", "FNetForMaskedLM", "FNetForMultipleChoice", "FNetForNextSentencePrediction", "FNetForPreTraining", "FNetForQuestionAnswering", "FNetForSequenceClassification", "FNetForTokenClassification", "FNetLayer", "FNetModel", "FNetPreTrainedModel", ] if TYPE_CHECKING: from .configuration_fnet import FNET_PRETRAINED_CONFIG_ARCHIVE_MAP, FNetConfig from .tokenization_fnet import FNetTokenizer if is_tokenizers_available(): from .tokenization_fnet_fast import FNetTokenizerFast if is_torch_available(): from .modeling_fnet import ( FNET_PRETRAINED_MODEL_ARCHIVE_LIST, FNetForMaskedLM, FNetForMultipleChoice, FNetForNextSentencePrediction, FNetForPreTraining, FNetForQuestionAnswering, FNetForSequenceClassification, FNetForTokenClassification, FNetLayer, FNetModel, FNetPreTrainedModel, ) else: import sys sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)