
from typing import TYPE_CHECKING

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


lowercase  :					int													=       {
    'configuration_blenderbot': [
        'BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'BlenderbotConfig',
        'BlenderbotOnnxConfig',
    ],
    'tokenization_blenderbot': ['BlenderbotTokenizer'],
}

try:
		if not is_tokenizers_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase  :					Any													=       ['BlenderbotTokenizerFast']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase  :					Tuple													=       [
		    'BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'BlenderbotForCausalLM',
		    'BlenderbotForConditionalGeneration',
		    'BlenderbotModel',
		    'BlenderbotPreTrainedModel',
		]


try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase  :					List[Any]													=       [
		    'TFBlenderbotForConditionalGeneration',
		    'TFBlenderbotModel',
		    'TFBlenderbotPreTrainedModel',
		]


try:
		if not is_flax_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase  :					Tuple													=       [
		    'FlaxBlenderbotForConditionalGeneration',
		    'FlaxBlenderbotModel',
		    'FlaxBlenderbotPreTrainedModel',
		]


if TYPE_CHECKING:
		from .configuration_blenderbot import (
		    BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    BlenderbotConfig,
		    BlenderbotOnnxConfig,
		)
		from .tokenization_blenderbot import BlenderbotTokenizer

		try:
				if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_blenderbot_fast import BlenderbotTokenizerFast

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_blenderbot import (
				    BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    BlenderbotForCausalLM,
				    BlenderbotForConditionalGeneration,
				    BlenderbotModel,
				    BlenderbotPreTrainedModel,
				)

		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_blenderbot import (
				    TFBlenderbotForConditionalGeneration,
				    TFBlenderbotModel,
				    TFBlenderbotPreTrainedModel,
				)

		try:
				if not is_flax_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_flax_blenderbot import (
				    FlaxBlenderbotForConditionalGeneration,
				    FlaxBlenderbotModel,
				    FlaxBlenderbotPreTrainedModel,
				)

else:
		import sys

		lowercase  :					Any													=       _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
from torch import nn





class 		_lowercase						(					nn.Module       ):

 def __init__( self	:							Any   ,      snake_case	:							Dict   ,      snake_case	:							Union[str, Any]			)   ->						Dict:

  """simple docstring"""





  super().__init__()
  UpperCamelCase_					:						List[Any] =					class_size
  UpperCamelCase_					:						List[Any] =					embed_size
  # self.mlp1 = nn.Linear(embed_size, embed_size)
  # self.mlp2 = (nn.Linear(embed_size, class_size))
  UpperCamelCase_					:						int =					nn.Linear(snake_case   ,      snake_case			)


 def 						SCREAMING_SNAKE_CASE__   ( self	:							List[str]   ,      snake_case	:							Any			)   ->						str:

  """simple docstring"""





  UpperCamelCase_					:						Dict =					self.mlp(snake_case			)
  return logits



