




"""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 math import pow, sqrt







def   _snake_case    (       *lowercase__	):
				_lowerCamelCase  :    Dict					=					len(lowercase__	) > 0 and all(value > 0.0 for value in values	)
				return result







def   _snake_case    (       lowercase__							,					lowercase__	):
				return (
				    round(sqrt(molar_mass_a / molar_mass_a	)							,					6	)
				    if validate(lowercase__							,					lowercase__	)
				    else ValueError('Input Error: Molar mass values must greater than 0.'	)
				)







def   _snake_case    (       lowercase__							,					lowercase__							,					lowercase__	):
				return (
				    round(effusion_rate * sqrt(molar_mass_a / molar_mass_a	)							,					6	)
				    if validate(lowercase__							,					lowercase__							,					lowercase__	)
				    else ValueError(
				        'Input Error: Molar mass and effusion rate values must greater than 0.'	)
				)







def   _snake_case    (       lowercase__							,					lowercase__							,					lowercase__	):
				return (
				    round(effusion_rate / sqrt(molar_mass_a / molar_mass_a	)							,					6	)
				    if validate(lowercase__							,					lowercase__							,					lowercase__	)
				    else ValueError(
				        'Input Error: Molar mass and effusion rate values must greater than 0.'	)
				)







def   _snake_case    (       lowercase__							,					lowercase__							,					lowercase__	):
				return (
				    round(molar_mass / pow(effusion_rate_a / effusion_rate_a							,					2	)							,					6	)
				    if validate(lowercase__							,					lowercase__							,					lowercase__	)
				    else ValueError(
				        'Input Error: Molar mass and effusion rate values must greater than 0.'	)
				)







def   _snake_case    (       lowercase__							,					lowercase__							,					lowercase__	):
				return (
				    round(pow(effusion_rate_a / effusion_rate_a							,					2	) / molar_mass							,					6	)
				    if validate(lowercase__							,					lowercase__							,					lowercase__	)
				    else ValueError(
				        'Input Error: Molar mass and effusion rate values must greater than 0.'	)
				)