




from typing import TYPE_CHECKING

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


lowercase__    :					Dict					=						{"configuration_gptj": ["GPTJ_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTJConfig", "GPTJOnnxConfig"]}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase__    :					Any					=						[
		    "GPTJ_PRETRAINED_MODEL_ARCHIVE_LIST",
		    "GPTJForCausalLM",
		    "GPTJForQuestionAnswering",
		    "GPTJForSequenceClassification",
		    "GPTJModel",
		    "GPTJPreTrainedModel",
		]

try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase__    :					Any					=						[
		    "TFGPTJForCausalLM",
		    "TFGPTJForQuestionAnswering",
		    "TFGPTJForSequenceClassification",
		    "TFGPTJModel",
		    "TFGPTJPreTrainedModel",
		]

try:
		if not is_flax_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase__    :					Optional[int]					=						[
		    "FlaxGPTJForCausalLM",
		    "FlaxGPTJModel",
		    "FlaxGPTJPreTrainedModel",
		]


if TYPE_CHECKING:
		from .configuration_gptj import GPTJ_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTJConfig, GPTJOnnxConfig

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_gptj import (
				    GPTJ_PRETRAINED_MODEL_ARCHIVE_LIST,
				    GPTJForCausalLM,
				    GPTJForQuestionAnswering,
				    GPTJForSequenceClassification,
				    GPTJModel,
				    GPTJPreTrainedModel,
				)

		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_gptj import (
				    TFGPTJForCausalLM,
				    TFGPTJForQuestionAnswering,
				    TFGPTJForSequenceClassification,
				    TFGPTJModel,
				    TFGPTJPreTrainedModel,
				)

		try:
				if not is_flax_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_flax_gptj import FlaxGPTJForCausalLM, FlaxGPTJModel, FlaxGPTJPreTrainedModel

else:
		import sys

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






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_torch_available


lowercase__    :					List[str]					=						{
    "configuration_xlm_prophetnet": ["XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "XLMProphetNetConfig"],
}

try:
		if not is_sentencepiece_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase__    :					Optional[Any]					=						["XLMProphetNetTokenizer"]

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase__    :					List[Any]					=						[
		    "XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST",
		    "XLMProphetNetDecoder",
		    "XLMProphetNetEncoder",
		    "XLMProphetNetForCausalLM",
		    "XLMProphetNetForConditionalGeneration",
		    "XLMProphetNetModel",
		    "XLMProphetNetPreTrainedModel",
		]


if TYPE_CHECKING:
		from .configuration_xlm_prophetnet import XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP, XLMProphetNetConfig

		try:
				if not is_sentencepiece_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_xlm_prophetnet import XLMProphetNetTokenizer

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_xlm_prophetnet import (
				    XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST,
				    XLMProphetNetDecoder,
				    XLMProphetNetEncoder,
				    XLMProphetNetForCausalLM,
				    XLMProphetNetForConditionalGeneration,
				    XLMProphetNetModel,
				    XLMProphetNetPreTrainedModel,
				)

else:
		import sys

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