FM / rag

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

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

Name	Size	Mode	Actions
__pycache__/	-	0755	rm
configuration_rag.py	8804	0644	edit dl rm
modeling_rag.py	91005	0644	edit dl rm
modeling_tf_rag.py	89657	0644	edit dl rm
retrieval_rag.py	28664	0644	edit dl rm
tokenization_rag.py	4898	0644	edit dl rm
__init__.py	2069	0644	edit dl rm

Edit: /usr/local/lib/python3.6/site-packages/transformers/models/rag/__init__.py (2069B)

# 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_rag": ["RagConfig"],
    "retrieval_rag": ["RagRetriever"],
    "tokenization_rag": ["RagTokenizer"],
}

if is_torch_available():
    _import_structure["modeling_rag"] = [
        "RagModel",
        "RagPreTrainedModel",
        "RagSequenceForGeneration",
        "RagTokenForGeneration",
    ]

if is_tf_available():
    _import_structure["modeling_tf_rag"] = [
        "TFRagModel",
        "TFRagPreTrainedModel",
        "TFRagSequenceForGeneration",
        "TFRagTokenForGeneration",
    ]

if TYPE_CHECKING:
    from .configuration_rag import RagConfig
    from .retrieval_rag import RagRetriever
    from .tokenization_rag import RagTokenizer

if is_torch_available():
        from .modeling_rag import RagModel, RagPreTrainedModel, RagSequenceForGeneration, RagTokenForGeneration

if is_tf_available():
        from .modeling_tf_rag import (
            TFRagModel,
            TFRagPreTrainedModel,
            TFRagSequenceForGeneration,
            TFRagTokenForGeneration,
        )

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_rag": ["RagConfig"], "retrieval_rag": ["RagRetriever"], "tokenization_rag": ["RagTokenizer"], } if is_torch_available(): _import_structure["modeling_rag"] = [ "RagModel", "RagPreTrainedModel", "RagSequenceForGeneration", "RagTokenForGeneration", ] if is_tf_available(): _import_structure["modeling_tf_rag"] = [ "TFRagModel", "TFRagPreTrainedModel", "TFRagSequenceForGeneration", "TFRagTokenForGeneration", ] if TYPE_CHECKING: from .configuration_rag import RagConfig from .retrieval_rag import RagRetriever from .tokenization_rag import RagTokenizer if is_torch_available(): from .modeling_rag import RagModel, RagPreTrainedModel, RagSequenceForGeneration, RagTokenForGeneration if is_tf_available(): from .modeling_tf_rag import ( TFRagModel, TFRagPreTrainedModel, TFRagSequenceForGeneration, TFRagTokenForGeneration, ) else: import sys sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)