2020 the huggingface team 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 orglicenseslicense2 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 2020 the huggingface team 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_flax_available,
    is_keras_nlp_available,
    is_tensorflow_text_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


_import_structure = {
    "configuration_gpt2": ["GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPT2Config", "GPT2OnnxConfig"],
    "tokenization_gpt2": ["GPT2Tokenizer"],
}

try:
    if not is_tokenizers_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _import_structure["tokenization_gpt2_fast"] = ["GPT2TokenizerFast"]

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _import_structure["modeling_gpt2"] = [
        "GPT2_PRETRAINED_MODEL_ARCHIVE_LIST",
        "GPT2DoubleHeadsModel",
        "GPT2ForQuestionAnswering",
        "GPT2ForSequenceClassification",
        "GPT2ForTokenClassification",
        "GPT2LMHeadModel",
        "GPT2Model",
        "GPT2PreTrainedModel",
        "load_tf_weights_in_gpt2",
    ]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _import_structure["modeling_tf_gpt2"] = [
        "TF_GPT2_PRETRAINED_MODEL_ARCHIVE_LIST",
        "TFGPT2DoubleHeadsModel",
        "TFGPT2ForSequenceClassification",
        "TFGPT2LMHeadModel",
        "TFGPT2MainLayer",
        "TFGPT2Model",
        "TFGPT2PreTrainedModel",
    ]

try:
    if not is_keras_nlp_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _import_structure["tokenization_gpt2_tf"] = ["TFGPT2Tokenizer"]

try:
    if not is_flax_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _import_structure["modeling_flax_gpt2"] = ["FlaxGPT2LMHeadModel", "FlaxGPT2Model", "FlaxGPT2PreTrainedModel"]

if TYPE_CHECKING:
    from .configuration_gpt2 import GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP, GPT2Config, GPT2OnnxConfig
    from .tokenization_gpt2 import GPT2Tokenizer

    try:
        if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_gpt2_fast import GPT2TokenizerFast

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_gpt2 import (
            GPT2_PRETRAINED_MODEL_ARCHIVE_LIST,
            GPT2DoubleHeadsModel,
            GPT2ForQuestionAnswering,
            GPT2ForSequenceClassification,
            GPT2ForTokenClassification,
            GPT2LMHeadModel,
            GPT2Model,
            GPT2PreTrainedModel,
            load_tf_weights_in_gpt2,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_gpt2 import (
            TF_GPT2_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFGPT2DoubleHeadsModel,
            TFGPT2ForSequenceClassification,
            TFGPT2LMHeadModel,
            TFGPT2MainLayer,
            TFGPT2Model,
            TFGPT2PreTrainedModel,
        )

    try:
        if not is_keras_nlp_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_gpt2_tf import TFGPT2Tokenizer

    try:
        if not is_flax_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_flax_gpt2 import FlaxGPT2LMHeadModel, FlaxGPT2Model, FlaxGPT2PreTrainedModel

else:
    import sys

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