'''simple docstring'''
from typing import Any


def 	_lowerCAmelCase (						_UpperCamelCase						:					list							,			_UpperCamelCase						:					list							,			_UpperCamelCase						:					dict							,			_UpperCamelCase						:					dict							,			_UpperCamelCase						:					dict							,			)				->      list:
     """simple docstring"""




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

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

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

               _SCREAMING_SNAKE_CASE							   =arg_max

    # The final observation
     _SCREAMING_SNAKE_CASE							   =observations_space[len(_UpperCamelCase    ) - 1]

     # argmax for given final observation
     _SCREAMING_SNAKE_CASE							   =''
     _SCREAMING_SNAKE_CASE							   =-1
     for k_state in states_space:
          _SCREAMING_SNAKE_CASE							   =probabilities[(k_state, final_observation)]
          if probability > max_probability:
               _SCREAMING_SNAKE_CASE							   =probability
               _SCREAMING_SNAKE_CASE							   =k_state
     _SCREAMING_SNAKE_CASE							   =arg_max

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

     return result


def 	_lowerCAmelCase (						_UpperCamelCase						:					Any							,			_UpperCamelCase						:					Any							,			_UpperCamelCase						:					Any							,			_UpperCamelCase						:					Any							,			_UpperCamelCase						:					Any							,			)				->      None:
     """simple docstring"""




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


def 	_lowerCAmelCase (						_UpperCamelCase						:					Any							,			_UpperCamelCase						:					Any							,			_UpperCamelCase						:					Any							,			_UpperCamelCase						:					Any							,			_UpperCamelCase						:					Any							,			)				->      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						:					Any							,			_UpperCamelCase						:					Any    )				->      None:
     """simple docstring"""




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


def 	_lowerCAmelCase (						_UpperCamelCase						:					Any							,			_UpperCamelCase						:					str    )				->      None:
     """simple docstring"""




     if not isinstance(_object							,			_UpperCamelCase    ):
          _SCREAMING_SNAKE_CASE							   =f"{var_name} must be a list"
          raise ValueError(_UpperCamelCase    )
     else:
          for x in _object:
               if not isinstance(_UpperCamelCase							,			_UpperCamelCase    ):
                    _SCREAMING_SNAKE_CASE							   =f"{var_name} must be a list of strings"
                    raise ValueError(_UpperCamelCase    )


def 	_lowerCAmelCase (						_UpperCamelCase						:					Any							,			_UpperCamelCase						:					Any							,			_UpperCamelCase						:					Any							,			)				->      None:
     """simple docstring"""




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


def 	_lowerCAmelCase (						_UpperCamelCase						:					Any							,			_UpperCamelCase						:					str    )				->      None:
     """simple docstring"""




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


def 	_lowerCAmelCase (						_UpperCamelCase						:					Any							,			_UpperCamelCase						:					str							,			_UpperCamelCase						:					type							,			_UpperCamelCase						:					bool = False    )				->      None:
     """simple docstring"""




     if not isinstance(_object							,			_UpperCamelCase    ):
          _SCREAMING_SNAKE_CASE							   =f"{var_name} must be a dict"
          raise ValueError(_UpperCamelCase    )
     if not all(isinstance(_UpperCamelCase							,			_UpperCamelCase    ) for x in _object    ):
          _SCREAMING_SNAKE_CASE							   =f"{var_name} all keys must be strings"
          raise ValueError(_UpperCamelCase    )
     if not all(isinstance(_UpperCamelCase							,			_UpperCamelCase    ) for x in _object.values()    ):
          _SCREAMING_SNAKE_CASE							   ='nested dictionary ' if nested else ''
          _SCREAMING_SNAKE_CASE							   =f"{var_name} {nested_text}all values must be {value_type.__name__}"
          raise ValueError(_UpperCamelCase    )


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

     testmod()



'''simple docstring'''
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


lowerCamelCase			:				Optional[int] 			=					{
    "configuration_efficientnet": [
        "EFFICIENTNET_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "EfficientNetConfig",
        "EfficientNetOnnxConfig",
    ]
}

try:
     if not is_vision_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCamelCase			:				str 			=					["EfficientNetImageProcessor"]

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCamelCase			:				Tuple 			=					[
         "EFFICIENTNET_PRETRAINED_MODEL_ARCHIVE_LIST",
         "EfficientNetForImageClassification",
         "EfficientNetModel",
         "EfficientNetPreTrainedModel",
     ]

if TYPE_CHECKING:
     from .configuration_efficientnet import (
         EFFICIENTNET_PRETRAINED_CONFIG_ARCHIVE_MAP,
         EfficientNetConfig,
         EfficientNetOnnxConfig,
     )

     try:
          if not is_vision_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .image_processing_efficientnet import EfficientNetImageProcessor

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_efficientnet import (
              EFFICIENTNET_PRETRAINED_MODEL_ARCHIVE_LIST,
              EfficientNetForImageClassification,
              EfficientNetModel,
              EfficientNetPreTrainedModel,
          )

else:
     import sys

     lowerCamelCase			:				int 			=					_LazyModule(__name__, globals()["__file__"], _import_structure)
