
from typing import Any


def 							SCREAMING_SNAKE_CASE_      (			UpperCamelCase__ ,		UpperCamelCase__ ,		UpperCamelCase__ ,		UpperCamelCase__ ,		UpperCamelCase__ ,		):
      _validation(
          UpperCamelCase__ ,		UpperCamelCase__ ,		UpperCamelCase__ ,		UpperCamelCase__ ,		UpperCamelCase__ ,		)
      # Creates data structures and fill initial step
      UpperCamelCase__    :   dict					=				{}
      UpperCamelCase__    :   dict					=				{}
      for state in states_space:
            UpperCamelCase__    :   Dict					=				observations_space[0]
            UpperCamelCase__    :   List[str]					=				(
                initial_probabilities[state] * emission_probabilities[state][observation]
            )
            UpperCamelCase__    :   Union[str, Any]					=				None

      # Fills the data structure with the probabilities of
      # different transitions and pointers to previous states
      for o in range(1 ,		len(UpperCamelCase__		)		):
            UpperCamelCase__    :   Dict					=				observations_space[o]
            UpperCamelCase__    :   Optional[int]					=				observations_space[o - 1]
            for state in states_space:
                  # Calculates the argmax for probability function
                  UpperCamelCase__    :   str					=				''''''
                  UpperCamelCase__    :   List[Any]					=				-1
                  for k_state in states_space:
                        UpperCamelCase__    :   Optional[int]					=				(
                            probabilities[(k_state, prior_observation)]
                            * transition_probabilities[k_state][state]
                            * emission_probabilities[state][observation]
                        )
                        if probability > max_probability:
                              UpperCamelCase__    :   Dict					=				probability
                              UpperCamelCase__    :   List[Any]					=				k_state

            # Update probabilities and pointers dicts
                  UpperCamelCase__    :   int					=				(
                      probabilities[(arg_max, prior_observation)]
                      * transition_probabilities[arg_max][state]
                      * emission_probabilities[state][observation]
                  )

                  UpperCamelCase__    :   Any					=				arg_max

    # The final observation
      UpperCamelCase__    :   Optional[Any]					=				observations_space[len(UpperCamelCase__		) - 1]

      # argmax for given final observation
      UpperCamelCase__    :   Union[str, Any]					=				''''''
      UpperCamelCase__    :   str					=				-1
      for k_state in states_space:
            UpperCamelCase__    :   Tuple					=				probabilities[(k_state, final_observation)]
            if probability > max_probability:
                  UpperCamelCase__    :   Union[str, Any]					=				probability
                  UpperCamelCase__    :   Optional[Any]					=				k_state
      UpperCamelCase__    :   List[str]					=				arg_max

      # Process pointers backwards
      UpperCamelCase__    :   str					=				last_state
      UpperCamelCase__    :   List[str]					=				[]
      for o in range(len(UpperCamelCase__		) - 1 ,		-1 ,		-1		):
            result.append(UpperCamelCase__		)
            UpperCamelCase__    :   List[str]					=				pointers[previous, observations_space[o]]
      result.reverse()

      return result


def 							SCREAMING_SNAKE_CASE_      (			UpperCamelCase__ ,		UpperCamelCase__ ,		UpperCamelCase__ ,		UpperCamelCase__ ,		UpperCamelCase__ ,		):
      _validate_not_empty(
          UpperCamelCase__ ,		UpperCamelCase__ ,		UpperCamelCase__ ,		UpperCamelCase__ ,		UpperCamelCase__ ,		)
      _validate_lists(UpperCamelCase__ ,		UpperCamelCase__		)
      _validate_dicts(
          UpperCamelCase__ ,		UpperCamelCase__ ,		UpperCamelCase__		)


def 							SCREAMING_SNAKE_CASE_      (			UpperCamelCase__ ,		UpperCamelCase__ ,		UpperCamelCase__ ,		UpperCamelCase__ ,		UpperCamelCase__ ,		):
      if not all(
          [
              observations_space,
              states_space,
              initial_probabilities,
              transition_probabilities,
              emission_probabilities,
          ]		):
            raise ValueError('''There\'s an empty parameter'''		)


def 							SCREAMING_SNAKE_CASE_      (			UpperCamelCase__ ,		UpperCamelCase__		):
      _validate_list(UpperCamelCase__ ,		'''observations_space'''		)
      _validate_list(UpperCamelCase__ ,		'''states_space'''		)


def 							SCREAMING_SNAKE_CASE_      (			UpperCamelCase__ ,		UpperCamelCase__		):
      if not isinstance(_object ,		UpperCamelCase__		):
            UpperCamelCase__    :   List[str]					=				f'''{var_name} must be a list'''
            raise ValueError(UpperCamelCase__		)
      else:
            for x in _object:
                  if not isinstance(UpperCamelCase__ ,		UpperCamelCase__		):
                        UpperCamelCase__    :   Optional[Any]					=				f'''{var_name} must be a list of strings'''
                        raise ValueError(UpperCamelCase__		)


def 							SCREAMING_SNAKE_CASE_      (			UpperCamelCase__ ,		UpperCamelCase__ ,		UpperCamelCase__ ,		):
      _validate_dict(UpperCamelCase__ ,		'''initial_probabilities''' ,		UpperCamelCase__		)
      _validate_nested_dict(UpperCamelCase__ ,		'''transition_probabilities'''		)
      _validate_nested_dict(UpperCamelCase__ ,		'''emission_probabilities'''		)


def 							SCREAMING_SNAKE_CASE_      (			UpperCamelCase__ ,		UpperCamelCase__		):
      _validate_dict(_object ,		UpperCamelCase__ ,		UpperCamelCase__		)
      for x in _object.values():
            _validate_dict(UpperCamelCase__ ,		UpperCamelCase__ ,		UpperCamelCase__ ,		UpperCamelCase__		)


def 							SCREAMING_SNAKE_CASE_      (			UpperCamelCase__ ,		UpperCamelCase__ ,		UpperCamelCase__ ,		UpperCamelCase__ = False		):
      if not isinstance(_object ,		UpperCamelCase__		):
            UpperCamelCase__    :   List[str]					=				f'''{var_name} must be a dict'''
            raise ValueError(UpperCamelCase__		)
      if not all(isinstance(UpperCamelCase__ ,		UpperCamelCase__		) for x in _object		):
            UpperCamelCase__    :   Tuple					=				f'''{var_name} all keys must be strings'''
            raise ValueError(UpperCamelCase__		)
      if not all(isinstance(UpperCamelCase__ ,		UpperCamelCase__		) for x in _object.values()		):
            UpperCamelCase__    :   Optional[Any]					=				'''nested dictionary ''' if nested else ''''''
            UpperCamelCase__    :   Optional[Any]					=				f'''{var_name} {nested_text}all values must be {value_type.__name__}'''
            raise ValueError(UpperCamelCase__		)


if __name__ == "__main__":
    from doctest import testmod

    testmod()




from typing import TYPE_CHECKING

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


lowerCamelCase      ={
    "configuration_blenderbot": [
        "BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "BlenderbotConfig",
        "BlenderbotOnnxConfig",
    ],
    "tokenization_blenderbot": ["BlenderbotTokenizer"],
}

try:
    if not is_tokenizers_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCamelCase      =["BlenderbotTokenizerFast"]

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


try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCamelCase      =[
        "TFBlenderbotForConditionalGeneration",
        "TFBlenderbotModel",
        "TFBlenderbotPreTrainedModel",
    ]


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

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


