Lightstar/venv/Lib/site-packages/transformers/models/dpr/__init__.py

# 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 (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


_import_structure = {
    "configuration_dpr": ["DPRConfig"],
    "tokenization_dpr": [
        "DPRContextEncoderTokenizer",
        "DPRQuestionEncoderTokenizer",
        "DPRReaderOutput",
        "DPRReaderTokenizer",
    ],
}


try:
    if not is_tokenizers_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _import_structure["tokenization_dpr_fast"] = [
        "DPRContextEncoderTokenizerFast",
        "DPRQuestionEncoderTokenizerFast",
        "DPRReaderTokenizerFast",
    ]

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _import_structure["modeling_dpr"] = [
        "DPRContextEncoder",
        "DPRPretrainedContextEncoder",
        "DPRPreTrainedModel",
        "DPRPretrainedQuestionEncoder",
        "DPRPretrainedReader",
        "DPRQuestionEncoder",
        "DPRReader",
    ]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _import_structure["modeling_tf_dpr"] = [
        "TFDPRContextEncoder",
        "TFDPRPretrainedContextEncoder",
        "TFDPRPretrainedQuestionEncoder",
        "TFDPRPretrainedReader",
        "TFDPRQuestionEncoder",
        "TFDPRReader",
    ]


if TYPE_CHECKING:
    from .configuration_dpr import DPRConfig
    from .tokenization_dpr import (
        DPRContextEncoderTokenizer,
        DPRQuestionEncoderTokenizer,
        DPRReaderOutput,
        DPRReaderTokenizer,
    )

    try:
        if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_dpr_fast import (
            DPRContextEncoderTokenizerFast,
            DPRQuestionEncoderTokenizerFast,
            DPRReaderTokenizerFast,
        )

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_dpr import (
            DPRContextEncoder,
            DPRPretrainedContextEncoder,
            DPRPreTrainedModel,
            DPRPretrainedQuestionEncoder,
            DPRPretrainedReader,
            DPRQuestionEncoder,
            DPRReader,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_dpr import (
            TFDPRContextEncoder,
            TFDPRPretrainedContextEncoder,
            TFDPRPretrainedQuestionEncoder,
            TFDPRPretrainedReader,
            TFDPRQuestionEncoder,
            TFDPRReader,
        )

else:
    import sys

    sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)