


'''simple docstring'''

from typing import TYPE_CHECKING

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


_UpperCAmelCase				: Union[str, Any]							    =				{
    'configuration_blenderbot_small': [
        'BLENDERBOT_SMALL_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'BlenderbotSmallConfig',
        'BlenderbotSmallOnnxConfig',
    ],
    'tokenization_blenderbot_small': ['BlenderbotSmallTokenizer'],
}

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_UpperCAmelCase				: Optional[int]							    =				['BlenderbotSmallTokenizerFast']

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_UpperCAmelCase				: List[Any]							    =				[
	    'BLENDERBOT_SMALL_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'BlenderbotSmallForCausalLM',
	    'BlenderbotSmallForConditionalGeneration',
	    'BlenderbotSmallModel',
	    'BlenderbotSmallPreTrainedModel',
	]

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_UpperCAmelCase				: str							    =				[
	    'TFBlenderbotSmallForConditionalGeneration',
	    'TFBlenderbotSmallModel',
	    'TFBlenderbotSmallPreTrainedModel',
	]

try:
	if not is_flax_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_UpperCAmelCase				: Tuple							    =				[
	    'FlaxBlenderbotSmallForConditionalGeneration',
	    'FlaxBlenderbotSmallModel',
	    'FlaxBlenderbotSmallPreTrainedModel',
	]

if TYPE_CHECKING:
	from .configuration_blenderbot_small import (
	    BLENDERBOT_SMALL_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    BlenderbotSmallConfig,
	    BlenderbotSmallOnnxConfig,
	)
	from .tokenization_blenderbot_small import BlenderbotSmallTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_blenderbot_small_fast import BlenderbotSmallTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_blenderbot_small import (
		    BLENDERBOT_SMALL_PRETRAINED_MODEL_ARCHIVE_LIST,
		    BlenderbotSmallForCausalLM,
		    BlenderbotSmallForConditionalGeneration,
		    BlenderbotSmallModel,
		    BlenderbotSmallPreTrainedModel,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_blenderbot_small import (
		    TFBlenderbotSmallForConditionalGeneration,
		    TFBlenderbotSmallModel,
		    TFBlenderbotSmallPreTrainedModel,
		)

	try:
		if not is_flax_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_flax_blenderbot_small import (
		    FlaxBlenderbotSmallForConditionalGeneration,
		    FlaxBlenderbotSmallModel,
		    FlaxBlenderbotSmallPreTrainedModel,
		)

else:
	import sys

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





'''simple docstring'''

from torch import nn

def 							__magic_name__(						lowerCamelCase):
						if act_fn in ["swish", "silu"]:
												return nn.SiLU()
						elif act_fn == "mish":
												return nn.Mish()
						elif act_fn == "gelu":
												return nn.GELU()
						else:
												raise ValueError(F"""Unsupported activation function: {act_fn}""")

