
"""simple docstring"""
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


_a      :			List[Any]					=							{"""configuration_xlnet""": ["""XLNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """XLNetConfig"""]}

try:
    if not is_sentencepiece_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _a      :			List[str]					=							["""XLNetTokenizer"""]

try:
    if not is_tokenizers_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _a      :			Optional[Any]					=							["""XLNetTokenizerFast"""]

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _a      :			Optional[int]					=							[
        """XLNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
        """XLNetForMultipleChoice""",
        """XLNetForQuestionAnswering""",
        """XLNetForQuestionAnsweringSimple""",
        """XLNetForSequenceClassification""",
        """XLNetForTokenClassification""",
        """XLNetLMHeadModel""",
        """XLNetModel""",
        """XLNetPreTrainedModel""",
        """load_tf_weights_in_xlnet""",
    ]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _a      :			Union[str, Any]					=							[
        """TF_XLNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
        """TFXLNetForMultipleChoice""",
        """TFXLNetForQuestionAnsweringSimple""",
        """TFXLNetForSequenceClassification""",
        """TFXLNetForTokenClassification""",
        """TFXLNetLMHeadModel""",
        """TFXLNetMainLayer""",
        """TFXLNetModel""",
        """TFXLNetPreTrainedModel""",
    ]


if TYPE_CHECKING:
    from .configuration_xlnet import XLNET_PRETRAINED_CONFIG_ARCHIVE_MAP, XLNetConfig

    try:
        if not is_sentencepiece_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_xlnet import XLNetTokenizer

    try:
        if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_xlnet_fast import XLNetTokenizerFast

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_xlnet import (
            XLNET_PRETRAINED_MODEL_ARCHIVE_LIST,
            XLNetForMultipleChoice,
            XLNetForQuestionAnswering,
            XLNetForQuestionAnsweringSimple,
            XLNetForSequenceClassification,
            XLNetForTokenClassification,
            XLNetLMHeadModel,
            XLNetModel,
            XLNetPreTrainedModel,
            load_tf_weights_in_xlnet,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_xlnet import (
            TF_XLNET_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFXLNetForMultipleChoice,
            TFXLNetForQuestionAnsweringSimple,
            TFXLNetForSequenceClassification,
            TFXLNetForTokenClassification,
            TFXLNetLMHeadModel,
            TFXLNetMainLayer,
            TFXLNetModel,
            TFXLNetPreTrainedModel,
        )

else:
    import sys

    _a      :			Union[str, Any]					=							_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)








"""simple docstring"""
from ...utils import (
    OptionalDependencyNotAvailable,
    is_torch_available,
    is_transformers_available,
    is_transformers_version,
)


try:
    if not (is_transformers_available() and is_torch_available() and is_transformers_version(""">=""", """4.25.0""")):
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    from ...utils.dummy_torch_and_transformers_objects import UnCLIPImageVariationPipeline, UnCLIPPipeline
else:
    from .pipeline_unclip import UnCLIPPipeline
    from .pipeline_unclip_image_variation import UnCLIPImageVariationPipeline
    from .text_proj import UnCLIPTextProjModel

