






from typing import TYPE_CHECKING

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


a						:			Tuple     	=					{
    "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:
       a						:			List[Any]     	=					["BlenderbotSmallTokenizerFast"]

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

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

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

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









SCREAMING_SNAKE_CASE_   :      dict[str, float]			=   {
    "joule": 1.0,
    "kilojoule": 1000,
    "megajoule": 100_0000,
    "gigajoule": 10_0000_0000,
    "wattsecond": 1.0,
    "watthour": 3600,
    "kilowatthour": 360_0000,
    "newtonmeter": 1.0,
    "calorie_nutr": 4186.8,
    "kilocalorie_nutr": 418_6800.00,
    "electronvolt": 1.6_0_2_1_7_6_6_3_4e-1_9,
    "britishthermalunit_it": 1055.0_5585,
    "footpound": 1.35_5818,
}



def  SCREAMING_SNAKE_CASE				(      snake_case						,   snake_case						,   snake_case							)		->    float:
		if to_type not in ENERGY_CONVERSION or from_type not in ENERGY_CONVERSION:
				__lowercase											=     (
				    F"Incorrect 'from_type' or 'to_type' value: {from_type!r}, {to_type!r}\n"
				    F"Valid values are: {', '.join(snake_case							)}"
				)
				raise ValueError(snake_case							)
		return value * ENERGY_CONVERSION[from_type] / ENERGY_CONVERSION[to_type]


if __name__ == "__main__":
		import doctest

		doctest.testmod()




