






"""simple docstring"""

from typing import TYPE_CHECKING

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


lowercase__          = {
    """configuration_distilbert""": [
        """DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """DistilBertConfig""",
        """DistilBertOnnxConfig""",
    ],
    """tokenization_distilbert""": ["""DistilBertTokenizer"""],
}

try:
					if not is_tokenizers_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowercase__          = ["""DistilBertTokenizerFast"""]

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowercase__          = [
					    """DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """DistilBertForMaskedLM""",
					    """DistilBertForMultipleChoice""",
					    """DistilBertForQuestionAnswering""",
					    """DistilBertForSequenceClassification""",
					    """DistilBertForTokenClassification""",
					    """DistilBertModel""",
					    """DistilBertPreTrainedModel""",
					]

try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowercase__          = [
					    """TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """TFDistilBertForMaskedLM""",
					    """TFDistilBertForMultipleChoice""",
					    """TFDistilBertForQuestionAnswering""",
					    """TFDistilBertForSequenceClassification""",
					    """TFDistilBertForTokenClassification""",
					    """TFDistilBertMainLayer""",
					    """TFDistilBertModel""",
					    """TFDistilBertPreTrainedModel""",
					]

try:
					if not is_flax_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowercase__          = [
					    """FlaxDistilBertForMaskedLM""",
					    """FlaxDistilBertForMultipleChoice""",
					    """FlaxDistilBertForQuestionAnswering""",
					    """FlaxDistilBertForSequenceClassification""",
					    """FlaxDistilBertForTokenClassification""",
					    """FlaxDistilBertModel""",
					    """FlaxDistilBertPreTrainedModel""",
					]


if TYPE_CHECKING:
					from .configuration_distilbert import (
					    DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
					    DistilBertConfig,
					    DistilBertOnnxConfig,
					)
					from .tokenization_distilbert import DistilBertTokenizer

					try:
										if not is_tokenizers_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_distilbert_fast import DistilBertTokenizerFast

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_distilbert import (
										    DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
										    DistilBertForMaskedLM,
										    DistilBertForMultipleChoice,
										    DistilBertForQuestionAnswering,
										    DistilBertForSequenceClassification,
										    DistilBertForTokenClassification,
										    DistilBertModel,
										    DistilBertPreTrainedModel,
										)

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_distilbert import (
										    TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
										    TFDistilBertForMaskedLM,
										    TFDistilBertForMultipleChoice,
										    TFDistilBertForQuestionAnswering,
										    TFDistilBertForSequenceClassification,
										    TFDistilBertForTokenClassification,
										    TFDistilBertMainLayer,
										    TFDistilBertModel,
										    TFDistilBertPreTrainedModel,
										)

					try:
										if not is_flax_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_flax_distilbert import (
										    FlaxDistilBertForMaskedLM,
										    FlaxDistilBertForMultipleChoice,
										    FlaxDistilBertForQuestionAnswering,
										    FlaxDistilBertForSequenceClassification,
										    FlaxDistilBertForTokenClassification,
										    FlaxDistilBertModel,
										    FlaxDistilBertPreTrainedModel,
										)

else:
					import sys

					lowercase__          = _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)








from typing import TYPE_CHECKING

from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable


lowercase  							=					{"configuration_gpt_neox": ["GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTNeoXConfig"]}

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowercase  							=					["GPTNeoXTokenizerFast"]

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowercase  							=					[
	    "GPT_NEOX_PRETRAINED_MODEL_ARCHIVE_LIST",
	    "GPTNeoXForCausalLM",
	    "GPTNeoXForQuestionAnswering",
	    "GPTNeoXForSequenceClassification",
	    "GPTNeoXForTokenClassification",
	    "GPTNeoXLayer",
	    "GPTNeoXModel",
	    "GPTNeoXPreTrainedModel",
	]


if TYPE_CHECKING:
	from .configuration_gpt_neox import GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoXConfig

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_gpt_neox_fast import GPTNeoXTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_gpt_neox import (
		    GPT_NEOX_PRETRAINED_MODEL_ARCHIVE_LIST,
		    GPTNeoXForCausalLM,
		    GPTNeoXForQuestionAnswering,
		    GPTNeoXForSequenceClassification,
		    GPTNeoXForTokenClassification,
		    GPTNeoXLayer,
		    GPTNeoXModel,
		    GPTNeoXPreTrainedModel,
		)


else:
	import sys

	lowercase  							=					_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





