FM / t5

/usr/local/lib/python3.6/site-packages/transformers/models/t5/

/usr/local/lib/python3.6/site-packages/transformers/models/t5

Name	Size	Mode	Actions
__pycache__/	-	0755	rm
configuration_t5.py	6766	0644	edit dl rm
convert_t5_original_tf_checkpoint_to_pytorch.py	2107	0644	edit dl rm
modeling_flax_t5.py	68620	0644	edit dl rm
modeling_t5.py	82840	0644	edit dl rm
modeling_tf_t5.py	77705	0644	edit dl rm
tokenization_t5.py	13200	0644	edit dl rm
tokenization_t5_fast.py	8796	0644	edit dl rm
__init__.py	3059	0644	edit dl rm

Edit: /usr/local/lib/python3.6/site-packages/transformers/models/t5/__init__.py (3059B)

# 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_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)

_import_structure = {
    "configuration_t5": ["T5_PRETRAINED_CONFIG_ARCHIVE_MAP", "T5Config", "T5OnnxConfig"],
}

if is_sentencepiece_available():
    _import_structure["tokenization_t5"] = ["T5Tokenizer"]

if is_tokenizers_available():
    _import_structure["tokenization_t5_fast"] = ["T5TokenizerFast"]

if is_torch_available():
    _import_structure["modeling_t5"] = [
        "T5_PRETRAINED_MODEL_ARCHIVE_LIST",
        "T5EncoderModel",
        "T5ForConditionalGeneration",
        "T5Model",
        "T5PreTrainedModel",
        "load_tf_weights_in_t5",
    ]

if is_tf_available():
    _import_structure["modeling_tf_t5"] = [
        "TF_T5_PRETRAINED_MODEL_ARCHIVE_LIST",
        "TFT5EncoderModel",
        "TFT5ForConditionalGeneration",
        "TFT5Model",
        "TFT5PreTrainedModel",
    ]

if is_flax_available():
    _import_structure["modeling_flax_t5"] = [
        "FlaxT5ForConditionalGeneration",
        "FlaxT5Model",
        "FlaxT5PreTrainedModel",
    ]

if TYPE_CHECKING:
    from .configuration_t5 import T5_PRETRAINED_CONFIG_ARCHIVE_MAP, T5Config, T5OnnxConfig

if is_sentencepiece_available():
        from .tokenization_t5 import T5Tokenizer

if is_tokenizers_available():
        from .tokenization_t5_fast import T5TokenizerFast

if is_torch_available():
        from .modeling_t5 import (
            T5_PRETRAINED_MODEL_ARCHIVE_LIST,
            T5EncoderModel,
            T5ForConditionalGeneration,
            T5Model,
            T5PreTrainedModel,
            load_tf_weights_in_t5,
        )

if is_tf_available():
        from .modeling_tf_t5 import (
            TF_T5_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFT5EncoderModel,
            TFT5ForConditionalGeneration,
            TFT5Model,
            TFT5PreTrainedModel,
        )

if is_flax_available():
        from .modeling_flax_t5 import FlaxT5ForConditionalGeneration, FlaxT5Model, FlaxT5PreTrainedModel

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_flax_available, is_sentencepiece_available, is_tf_available, is_tokenizers_available, is_torch_available, ) _import_structure = { "configuration_t5": ["T5_PRETRAINED_CONFIG_ARCHIVE_MAP", "T5Config", "T5OnnxConfig"], } if is_sentencepiece_available(): _import_structure["tokenization_t5"] = ["T5Tokenizer"] if is_tokenizers_available(): _import_structure["tokenization_t5_fast"] = ["T5TokenizerFast"] if is_torch_available(): _import_structure["modeling_t5"] = [ "T5_PRETRAINED_MODEL_ARCHIVE_LIST", "T5EncoderModel", "T5ForConditionalGeneration", "T5Model", "T5PreTrainedModel", "load_tf_weights_in_t5", ] if is_tf_available(): _import_structure["modeling_tf_t5"] = [ "TF_T5_PRETRAINED_MODEL_ARCHIVE_LIST", "TFT5EncoderModel", "TFT5ForConditionalGeneration", "TFT5Model", "TFT5PreTrainedModel", ] if is_flax_available(): _import_structure["modeling_flax_t5"] = [ "FlaxT5ForConditionalGeneration", "FlaxT5Model", "FlaxT5PreTrainedModel", ] if TYPE_CHECKING: from .configuration_t5 import T5_PRETRAINED_CONFIG_ARCHIVE_MAP, T5Config, T5OnnxConfig if is_sentencepiece_available(): from .tokenization_t5 import T5Tokenizer if is_tokenizers_available(): from .tokenization_t5_fast import T5TokenizerFast if is_torch_available(): from .modeling_t5 import ( T5_PRETRAINED_MODEL_ARCHIVE_LIST, T5EncoderModel, T5ForConditionalGeneration, T5Model, T5PreTrainedModel, load_tf_weights_in_t5, ) if is_tf_available(): from .modeling_tf_t5 import ( TF_T5_PRETRAINED_MODEL_ARCHIVE_LIST, TFT5EncoderModel, TFT5ForConditionalGeneration, TFT5Model, TFT5PreTrainedModel, ) if is_flax_available(): from .modeling_flax_t5 import FlaxT5ForConditionalGeneration, FlaxT5Model, FlaxT5PreTrainedModel else: import sys sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)