






from typing import Any






def 							lowerCamelCase__ (       __lowerCamelCase     :	list    ,						__lowerCamelCase     :	list    ,						__lowerCamelCase     :	dict    ,						__lowerCamelCase     :	dict    ,						__lowerCamelCase     :	dict    ,						):
  _validation(
      __lowerCamelCase    ,						__lowerCamelCase    ,						__lowerCamelCase    ,						__lowerCamelCase    ,						__lowerCamelCase    ,						)
  # Creates data structures and fill initial step
  __UpperCAmelCase				:      dict	 =    {}
  __UpperCAmelCase				:      dict	 =    {}
  for state in states_space:
    __UpperCAmelCase				:      List[str]	 =    observations_space[0]
    __UpperCAmelCase				:      Union[str, Any]	 =    (
        initial_probabilities[state] * emission_probabilities[state][observation]
    )
    __UpperCAmelCase				:      Optional[int]	 =    None

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

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

      __UpperCAmelCase				:      Tuple	 =    arg_max

    # The final observation
  __UpperCAmelCase				:      int	 =    observations_space[len(__lowerCamelCase						) - 1]

  # argmax for given final observation
  __UpperCAmelCase				:      Tuple	 =    """"""
  __UpperCAmelCase				:      List[str]	 =    -1
  for k_state in states_space:
    __UpperCAmelCase				:      Dict	 =    probabilities[(k_state, final_observation)]
    if probability > max_probability:
      __UpperCAmelCase				:      Dict	 =    probability
      __UpperCAmelCase				:      Tuple	 =    k_state
  __UpperCAmelCase				:      Tuple	 =    arg_max

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

  return result






def 							lowerCamelCase__ (       __lowerCamelCase     :	Any    ,						__lowerCamelCase     :	Any    ,						__lowerCamelCase     :	Any    ,						__lowerCamelCase     :	Any    ,						__lowerCamelCase     :	Any    ,						):
  _validate_not_empty(
      __lowerCamelCase    ,						__lowerCamelCase    ,						__lowerCamelCase    ,						__lowerCamelCase    ,						__lowerCamelCase    ,						)
  _validate_lists(__lowerCamelCase    ,						__lowerCamelCase						)
  _validate_dicts(
      __lowerCamelCase    ,						__lowerCamelCase    ,						__lowerCamelCase						)






def 							lowerCamelCase__ (       __lowerCamelCase     :	Any    ,						__lowerCamelCase     :	Any    ,						__lowerCamelCase     :	Any    ,						__lowerCamelCase     :	Any    ,						__lowerCamelCase     :	Any    ,						):
  if not all(
      [
          observations_space,
          states_space,
          initial_probabilities,
          transition_probabilities,
          emission_probabilities,
      ]						):
    raise ValueError("""There's an empty parameter"""						)






def 							lowerCamelCase__ (       __lowerCamelCase     :	Any    ,						__lowerCamelCase     :	Any						):
  _validate_list(__lowerCamelCase    ,						"""observations_space"""						)
  _validate_list(__lowerCamelCase    ,						"""states_space"""						)






def 							lowerCamelCase__ (       __lowerCamelCase     :	Any    ,						__lowerCamelCase     :	str						):
  if not isinstance(_object    ,						__lowerCamelCase						):
    __UpperCAmelCase				:      List[str]	 =    f"""{var_name} must be a list"""
    raise ValueError(__lowerCamelCase						)
  else:
    for x in _object:
      if not isinstance(__lowerCamelCase    ,						__lowerCamelCase						):
        __UpperCAmelCase				:      Dict	 =    f"""{var_name} must be a list of strings"""
        raise ValueError(__lowerCamelCase						)






def 							lowerCamelCase__ (       __lowerCamelCase     :	Any    ,						__lowerCamelCase     :	Any    ,						__lowerCamelCase     :	Any    ,						):
  _validate_dict(__lowerCamelCase    ,						"""initial_probabilities"""    ,						__lowerCamelCase						)
  _validate_nested_dict(__lowerCamelCase    ,						"""transition_probabilities"""						)
  _validate_nested_dict(__lowerCamelCase    ,						"""emission_probabilities"""						)






def 							lowerCamelCase__ (       __lowerCamelCase     :	Any    ,						__lowerCamelCase     :	str						):
  _validate_dict(_object    ,						__lowerCamelCase    ,						__lowerCamelCase						)
  for x in _object.values():
    _validate_dict(__lowerCamelCase    ,						__lowerCamelCase    ,						__lowerCamelCase    ,						__lowerCamelCase						)






def 							lowerCamelCase__ (       __lowerCamelCase     :	Any    ,						__lowerCamelCase     :	str    ,						__lowerCamelCase     :	type    ,						__lowerCamelCase     :	bool = False						):
  if not isinstance(_object    ,						__lowerCamelCase						):
    __UpperCAmelCase				:      Any	 =    f"""{var_name} must be a dict"""
    raise ValueError(__lowerCamelCase						)
  if not all(isinstance(__lowerCamelCase    ,						__lowerCamelCase						) for x in _object						):
    __UpperCAmelCase				:      Union[str, Any]	 =    f"""{var_name} all keys must be strings"""
    raise ValueError(__lowerCamelCase						)
  if not all(isinstance(__lowerCamelCase    ,						__lowerCamelCase						) for x in _object.values()						):
    __UpperCAmelCase				:      int	 =    """nested dictionary """ if nested else """"""
    __UpperCAmelCase				:      Optional[Any]	 =    f"""{var_name} {nested_text}all values must be {value_type.__name__}"""
    raise ValueError(__lowerCamelCase						)


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

       testmod()









import copy
import random

from transformers import CLIPTokenizer







class       __A							(   lowerCamelCase__	):




      """simple docstring"""







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



             """simple docstring"""





             super().__init__(*a__   ,				**a__)
             _lowerCamelCase				:  Optional[Any]						=		{}


      def 					__snake_case      (		self   ,				a__   ,				*a__   ,				**a__):



             """simple docstring"""





             _lowerCamelCase				:  Optional[int]						=		super().add_tokens(a__   ,				*a__   ,				**a__)
             if num_added_tokens == 0:
                    raise ValueError(
                        F"""The tokenizer already contains the token {placeholder_token}. Please pass a different"""
                        ''' `placeholder_token` that is not already in the tokenizer.''')


      def 					__snake_case      (		self   ,				a__   ,				*a__   ,				a__=1   ,				**a__):



             """simple docstring"""





             _lowerCamelCase				:  Tuple						=		[]
             if num_vec_per_token == 1:
                    self.try_adding_tokens(a__   ,				*a__   ,				**a__)
                    output.append(a__)
             else:
                    _lowerCamelCase				:  Dict						=		[]
                    for i in range(a__):
                           _lowerCamelCase				:  Optional[Any]						=		placeholder_token + F"""_{i}"""
                           self.try_adding_tokens(a__   ,				*a__   ,				**a__)
                           output.append(a__)
        # handle cases where there is a new placeholder token that contains the current placeholder token but is larger
             for token in self.token_map:
                    if token in placeholder_token:
                           raise ValueError(
                               F"""The tokenizer already has placeholder token {token} that can get confused with"""
                               F""" {placeholder_token}keep placeholder tokens independent""")
             _lowerCamelCase				:  int						=		output


      def 					__snake_case      (		self   ,				a__   ,				a__=False   ,				a__=1.0):



             """simple docstring"""





             if isinstance(a__   ,				a__):
                    _lowerCamelCase				:  Tuple						=		[]
                    for i in range(len(a__)):
                           output.append(self.replace_placeholder_tokens_in_text(text[i]   ,				vector_shuffle=a__))
                    return output
             for placeholder_token in self.token_map:
                    if placeholder_token in text:
                           _lowerCamelCase				:  Union[str, Any]						=		self.token_map[placeholder_token]
                           _lowerCamelCase				:  Optional[Any]						=		tokens[: 1 + int(len(a__) * prop_tokens_to_load)]
                           if vector_shuffle:
                                  _lowerCamelCase				:  int						=		copy.copy(a__)
                                  random.shuffle(a__)
                           _lowerCamelCase				:  List[str]						=		text.replace(a__   ,				''' '''.join(a__))
             return text


      def __call__(		self   ,				a__   ,				*a__   ,				a__=False   ,				a__=1.0   ,				**a__):



             """simple docstring"""





             return super().__call__(
                 self.replace_placeholder_tokens_in_text(
                     a__   ,				vector_shuffle=a__   ,				prop_tokens_to_load=a__)   ,				*a__   ,				**a__   ,				)



      def 					__snake_case      (		self   ,				a__   ,				*a__   ,				a__=False   ,				a__=1.0   ,				**a__):



             """simple docstring"""





             return super().encode(
                 self.replace_placeholder_tokens_in_text(
                     a__   ,				vector_shuffle=a__   ,				prop_tokens_to_load=a__)   ,				*a__   ,				**a__   ,				)

