





"""simple docstring"""






from typing import Any

def       __A (     a_  :list				,    a_  :list				,    a_  :dict				,    a_  :dict				,    a_  :dict				,    )						->						list:
				_validation(
				    a_				,    a_				,    a_				,    a_				,    a_				,    )
				# Creates data structures and fill initial step
				__a	:  dict         =					{}
				__a	:  dict         =					{}
				for state in states_space:
								__a	:  int         =					observations_space[0]
								__a	:  List[Any]         =					(
								    initial_probabilities[state] * emission_probabilities[state][observation]
								)
								__a	:  int         =					None

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

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

												__a	:  Optional[int]         =					arg_max

    # The final observation
				__a	:  Optional[int]         =					observations_space[len(a_) - 1]

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

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

				return result

def       __A (     a_  :Any				,    a_  :Any				,    a_  :Any				,    a_  :Any				,    a_  :Any				,    )						->						None:
				_validate_not_empty(
				    a_				,    a_				,    a_				,    a_				,    a_				,    )
				_validate_lists(a_				,    a_)
				_validate_dicts(
				    a_				,    a_				,    a_)

def       __A (     a_  :Any				,    a_  :Any				,    a_  :Any				,    a_  :Any				,    a_  :Any				,    )						->						None:
				if not all(
				    [
				        observations_space,
				        states_space,
				        initial_probabilities,
				        transition_probabilities,
				        emission_probabilities,
				    ]):
								raise ValueError('''There\'s an empty parameter''')

def       __A (     a_  :Any				,    a_  :Any)						->						None:
				_validate_list(a_				,    '''observations_space''')
				_validate_list(a_				,    '''states_space''')

def       __A (     a_  :Any				,    a_  :str)						->						None:
				if not isinstance(_object				,    a_):
								__a	:  Optional[int]         =					F"""{var_name} must be a list"""
								raise ValueError(a_)
				else:
								for x in _object:
												if not isinstance(a_				,    a_):
																__a	:  Any         =					F"""{var_name} must be a list of strings"""
																raise ValueError(a_)

def       __A (     a_  :Any				,    a_  :Any				,    a_  :Any				,    )						->						None:
				_validate_dict(a_				,    '''initial_probabilities'''				,    a_)
				_validate_nested_dict(a_				,    '''transition_probabilities''')
				_validate_nested_dict(a_				,    '''emission_probabilities''')

def       __A (     a_  :Any				,    a_  :str)						->						None:
				_validate_dict(_object				,    a_				,    a_)
				for x in _object.values():
								_validate_dict(a_				,    a_				,    a_				,    a_)

def       __A (     a_  :Any				,    a_  :str				,    a_  :type				,    a_  :bool = False)						->						None:
				if not isinstance(_object				,    a_):
								__a	:  int         =					F"""{var_name} must be a dict"""
								raise ValueError(a_)
				if not all(isinstance(a_				,    a_) for x in _object):
								__a	:  Any         =					F"""{var_name} all keys must be strings"""
								raise ValueError(a_)
				if not all(isinstance(a_				,    a_) for x in _object.values()):
								__a	:  Dict         =					'''nested dictionary ''' if nested else ''''''
								__a	:  Optional[Any]         =					F"""{var_name} {nested_text}all values must be {value_type.__name__}"""
								raise ValueError(a_)


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

		testmod()






"""simple docstring"""






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


A	     =					{
    '''configuration_instructblip''': [
        '''INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''InstructBlipConfig''',
        '''InstructBlipQFormerConfig''',
        '''InstructBlipVisionConfig''',
    ],
    '''processing_instructblip''': ['''InstructBlipProcessor'''],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		A	     =					[
		    '''INSTRUCTBLIP_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''InstructBlipQFormerModel''',
		    '''InstructBlipPreTrainedModel''',
		    '''InstructBlipForConditionalGeneration''',
		    '''InstructBlipVisionModel''',
		]

if TYPE_CHECKING:
		from .configuration_instructblip import (
		    INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    InstructBlipConfig,
		    InstructBlipQFormerConfig,
		    InstructBlipVisionConfig,
		)
		from .processing_instructblip import InstructBlipProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_instructblip import (
				    INSTRUCTBLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
				    InstructBlipForConditionalGeneration,
				    InstructBlipPreTrainedModel,
				    InstructBlipQFormerModel,
				    InstructBlipVisionModel,
				)

else:
		import sys

		A	     =					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)