





from typing import Any






def 					lowerCamelCase_						(    _UpperCamelCase			,    _UpperCamelCase			,    _UpperCamelCase			,    _UpperCamelCase			,    _UpperCamelCase			,    )		->						list:






				"""simple docstring"""


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

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

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

												snake_case_						:   List[Any]           =  arg_max

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

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

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

				return result






def 					lowerCamelCase_						(    _UpperCamelCase			,    _UpperCamelCase			,    _UpperCamelCase			,    _UpperCamelCase			,    _UpperCamelCase			,    )		->						None:






				"""simple docstring"""


				_validate_not_empty(
				    _UpperCamelCase			,    _UpperCamelCase			,    _UpperCamelCase			,    _UpperCamelCase			,    _UpperCamelCase			,    )
				_validate_lists(_UpperCamelCase			,    _UpperCamelCase			)
				_validate_dicts(
				    _UpperCamelCase			,    _UpperCamelCase			,    _UpperCamelCase			)






def 					lowerCamelCase_						(    _UpperCamelCase			,    _UpperCamelCase			,    _UpperCamelCase			,    _UpperCamelCase			,    _UpperCamelCase			,    )		->						None:






				"""simple docstring"""


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






def 					lowerCamelCase_						(    _UpperCamelCase			,    _UpperCamelCase			)		->						None:






				"""simple docstring"""


				_validate_list(_UpperCamelCase			,    '''observations_space'''			)
				_validate_list(_UpperCamelCase			,    '''states_space'''			)






def 					lowerCamelCase_						(    _UpperCamelCase			,    _UpperCamelCase			)		->						None:






				"""simple docstring"""


				if not isinstance(_object			,    _UpperCamelCase			):
								snake_case_						:   str           =  f'''{var_name} must be a list'''
								raise ValueError(_UpperCamelCase			)
				else:
								for x in _object:
												if not isinstance(_UpperCamelCase			,    _UpperCamelCase			):
																snake_case_						:   Union[str, Any]           =  f'''{var_name} must be a list of strings'''
																raise ValueError(_UpperCamelCase			)






def 					lowerCamelCase_						(    _UpperCamelCase			,    _UpperCamelCase			,    _UpperCamelCase			,    )		->						None:






				"""simple docstring"""


				_validate_dict(_UpperCamelCase			,    '''initial_probabilities'''			,    _UpperCamelCase			)
				_validate_nested_dict(_UpperCamelCase			,    '''transition_probabilities'''			)
				_validate_nested_dict(_UpperCamelCase			,    '''emission_probabilities'''			)






def 					lowerCamelCase_						(    _UpperCamelCase			,    _UpperCamelCase			)		->						None:






				"""simple docstring"""


				_validate_dict(_object			,    _UpperCamelCase			,    _UpperCamelCase			)
				for x in _object.values():
								_validate_dict(_UpperCamelCase			,    _UpperCamelCase			,    _UpperCamelCase			,    _UpperCamelCase			)






def 					lowerCamelCase_						(    _UpperCamelCase			,    _UpperCamelCase			,    _UpperCamelCase			,    _UpperCamelCase = False			)		->						None:






				"""simple docstring"""


				if not isinstance(_object			,    _UpperCamelCase			):
								snake_case_						:   List[Any]           =  f'''{var_name} must be a dict'''
								raise ValueError(_UpperCamelCase			)
				if not all(isinstance(_UpperCamelCase			,    _UpperCamelCase			) for x in _object			):
								snake_case_						:   str           =  f'''{var_name} all keys must be strings'''
								raise ValueError(_UpperCamelCase			)
				if not all(isinstance(_UpperCamelCase			,    _UpperCamelCase			) for x in _object.values()			):
								snake_case_						:   List[str]           =  '''nested dictionary ''' if nested else ''''''
								snake_case_						:   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_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


lowerCAmelCase_    =    {'''configuration_xglm''': ['''XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XGLMConfig''']}

try:
	if not is_sentencepiece_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase_    =    ['''XGLMTokenizer''']

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase_    =    ['''XGLMTokenizerFast''']

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase_    =    [
	    '''XGLM_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''XGLMForCausalLM''',
	    '''XGLMModel''',
	    '''XGLMPreTrainedModel''',
	]


try:
	if not is_flax_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase_    =    [
	    '''FlaxXGLMForCausalLM''',
	    '''FlaxXGLMModel''',
	    '''FlaxXGLMPreTrainedModel''',
	]


try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase_    =    [
	    '''TF_XGLM_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''TFXGLMForCausalLM''',
	    '''TFXGLMModel''',
	    '''TFXGLMPreTrainedModel''',
	]


if TYPE_CHECKING:
	from .configuration_xglm import XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP, XGLMConfig

	try:
		if not is_sentencepiece_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_xglm import XGLMTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_xglm_fast import XGLMTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_xglm import XGLM_PRETRAINED_MODEL_ARCHIVE_LIST, XGLMForCausalLM, XGLMModel, XGLMPreTrainedModel

	try:
		if not is_flax_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_flax_xglm import FlaxXGLMForCausalLM, FlaxXGLMModel, FlaxXGLMPreTrainedModel

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_xglm import (
		    TF_XGLM_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TFXGLMForCausalLM,
		    TFXGLMModel,
		    TFXGLMPreTrainedModel,
		)


else:
	import sys

	lowerCAmelCase_    =    _LazyModule(__name__, globals()['''__file__'''], _import_structure)
