



"""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_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:
	lowercase__			   =  ["BlenderbotSmallTokenizerFast"]

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowercase__			   =  [
	    "BLENDERBOT_SMALL_PRETRAINED_MODEL_ARCHIVE_LIST",
	    "BlenderbotSmallForCausalLM",
	    "BlenderbotSmallForConditionalGeneration",
	    "BlenderbotSmallModel",
	    "BlenderbotSmallPreTrainedModel",
	]

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowercase__			   =  [
	    "TFBlenderbotSmallForConditionalGeneration",
	    "TFBlenderbotSmallModel",
	    "TFBlenderbotSmallPreTrainedModel",
	]

try:
	if not is_flax_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowercase__			   =  [
	    "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

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






"""simple docstring"""

from typing import Callable, Dict, Optional, Tuple

import torch
from torch import nn
from torch.distributions import (
    AffineTransform,
    Distribution,
    Independent,
    NegativeBinomial,
    Normal,
    StudentT,
    TransformedDistribution,
)




class SCREAMING_SNAKE_CASE__					(		__snake_case      ):



						def __init__(self						,     _lowercase						,     _lowercase=None						,     _lowercase=None						,     _lowercase=0							):





													'''simple docstring'''

													__a		:		Any									=       1.0 if scale is None else scale
													__a		:		str									=       0.0 if loc is None else loc

													super().__init__(_lowercase						,     [AffineTransform(loc=self.loc						,     scale=self.scale						,     event_dim=_lowercase							)]							)



						@property
						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													return self.base_dist.mean * self.scale + self.loc



						@property
						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													return self.base_dist.variance * self.scale**2





						@property
						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													return self.variance.sqrt()







class SCREAMING_SNAKE_CASE__					(		nn.Module      ):



						def __init__(self						,     _lowercase						,     _lowercase						,     _lowercase						,     **_lowercase							):





													'''simple docstring'''

													super().__init__(**_lowercase							)
													__a		:		str									=       args_dim
													__a		:		List[Any]									=       nn.ModuleList([nn.Linear(_lowercase						,     _lowercase							) for dim in args_dim.values()]							)
													__a		:		Dict									=       domain_map





						def     lowerCAmelCase__(self						,     _lowercase							):





													'''simple docstring'''

													__a		:		List[Any]									=       [proj(_lowercase							) for proj in self.proj]

													return self.domain_map(*_lowercase							)







class SCREAMING_SNAKE_CASE__					(		nn.Module      ):



						def __init__(self						,     _lowercase							):





													'''simple docstring'''

													super().__init__()
													__a		:		Optional[int]									=       function





						def     lowerCAmelCase__(self						,     _lowercase						,     *_lowercase							):





													'''simple docstring'''

													return self.function(_lowercase						,     *_lowercase							)







class SCREAMING_SNAKE_CASE__					:
						_lowerCAmelCase							=					42
						_lowerCAmelCase							=					42
						_lowerCAmelCase							=					42



						def __init__(self						,     _lowercase = 1							):





													'''simple docstring'''

													__a		:		Optional[int]									=       dim
													__a		:		str									=       {k: dim * self.args_dim[k] for k in self.args_dim}



						def     lowerCAmelCase__(self						,     _lowercase							):





													'''simple docstring'''

													if self.dim == 1:
																				return self.distribution_class(*_lowercase							)
													else:
																				return Independent(self.distribution_class(*_lowercase							)						,     1							)



						def     lowerCAmelCase__(self						,     _lowercase						,     _lowercase = None						,     _lowercase = None						,     ):





													'''simple docstring'''

													__a		:		Tuple									=       self._base_distribution(_lowercase							)
													if loc is None and scale is None:
																				return distr
													else:
																				return AffineTransformed(_lowercase						,     loc=_lowercase						,     scale=_lowercase						,     event_dim=self.event_dim							)



						@property
						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													return () if self.dim == 1 else (self.dim,)



						@property
						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													return len(self.event_shape							)



						@property
						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													return 0.0



						def     lowerCAmelCase__(self						,     _lowercase							):





													'''simple docstring'''

													return ParameterProjection(
													    in_features=_lowercase						,     args_dim=self.args_dim						,     domain_map=LambdaLayer(self.domain_map							)						,     )



						def     lowerCAmelCase__(self						,     *_lowercase							):





													'''simple docstring'''

													raise NotImplementedError()





						@staticmethod
						def     lowerCAmelCase__(_lowercase							):





													'''simple docstring'''

													return (x + torch.sqrt(torch.square(_lowercase							) + 4.0							)) / 2.0







class SCREAMING_SNAKE_CASE__					(		__snake_case      ):
						_lowerCAmelCase							=					{"df": 1, "loc": 1, "scale": 1}
						_lowerCAmelCase							=					StudentT



						@classmethod
						def     lowerCAmelCase__(cls						,     _lowercase						,     _lowercase						,     _lowercase							):





													'''simple docstring'''

													__a		:		int									=       cls.squareplus(_lowercase							).clamp_min(torch.finfo(scale.dtype							).eps							)
													__a		:		Optional[Any]									=       2.0 + cls.squareplus(_lowercase							)
													return df.squeeze(-1							), loc.squeeze(-1							), scale.squeeze(-1							)







class SCREAMING_SNAKE_CASE__					(		__snake_case      ):
						_lowerCAmelCase							=					{"loc": 1, "scale": 1}
						_lowerCAmelCase							=					Normal



						@classmethod
						def     lowerCAmelCase__(cls						,     _lowercase						,     _lowercase							):





													'''simple docstring'''

													__a		:		str									=       cls.squareplus(_lowercase							).clamp_min(torch.finfo(scale.dtype							).eps							)
													return loc.squeeze(-1							), scale.squeeze(-1							)







class SCREAMING_SNAKE_CASE__					(		__snake_case      ):
						_lowerCAmelCase							=					{"total_count": 1, "logits": 1}
						_lowerCAmelCase							=					NegativeBinomial



						@classmethod
						def     lowerCAmelCase__(cls						,     _lowercase						,     _lowercase							):





													'''simple docstring'''

													__a		:		Union[str, Any]									=       cls.squareplus(_lowercase							)
													return total_count.squeeze(-1							), logits.squeeze(-1							)



						def     lowerCAmelCase__(self						,     _lowercase							):





													'''simple docstring'''

													__a							,     __a		:		Optional[Any]									=       distr_args
													if self.dim == 1:
																				return self.distribution_class(total_count=_lowercase						,     logits=_lowercase							)
													else:
																				return Independent(self.distribution_class(total_count=_lowercase						,     logits=_lowercase							)						,     1							)





						def     lowerCAmelCase__(self						,     _lowercase						,     _lowercase = None						,     _lowercase = None							):





													'''simple docstring'''

													__a							,     __a		:		List[Any]									=       distr_args

													if scale is not None:
																				# See scaling property of Gamma.
																				logits += scale.log()

													return self._base_distribution((total_count, logits)							)

