


from typing import Any





def __UpperCAmelCase       (		__A ,						__A ,						__A ,						__A ,						__A ,						)						->					list:



       '''simple docstring'''





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

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

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

                     UpperCAmelCase__										=     arg_max

    # The final observation
       UpperCAmelCase__										=     observations_space[len(__A			) - 1]

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

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

       return result





def __UpperCAmelCase       (		__A ,						__A ,						__A ,						__A ,						__A ,						)						->					None:



       '''simple docstring'''





       _validate_not_empty(
           __A ,						__A ,						__A ,						__A ,						__A ,						)
       _validate_lists(__A ,						__A			)
       _validate_dicts(
           __A ,						__A ,						__A			)





def __UpperCAmelCase       (		__A ,						__A ,						__A ,						__A ,						__A ,						)						->					None:



       '''simple docstring'''





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





def __UpperCAmelCase       (		__A ,						__A			)						->					None:



       '''simple docstring'''





       _validate_list(__A ,						"observations_space"			)
       _validate_list(__A ,						"states_space"			)





def __UpperCAmelCase       (		__A ,						__A			)						->					None:



       '''simple docstring'''





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





def __UpperCAmelCase       (		__A ,						__A ,						__A ,						)						->					None:



       '''simple docstring'''





       _validate_dict(__A ,						"initial_probabilities" ,						__A			)
       _validate_nested_dict(__A ,						"transition_probabilities"			)
       _validate_nested_dict(__A ,						"emission_probabilities"			)





def __UpperCAmelCase       (		__A ,						__A			)						->					None:



       '''simple docstring'''





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





def __UpperCAmelCase       (		__A ,						__A ,						__A ,						__A = False			)						->					None:



       '''simple docstring'''





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


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

    testmod()









import unittest

import numpy as np

from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
    is_onnx_available,
    load_image,
    load_numpy,
    nightly,
    require_onnxruntime,
    require_torch_gpu,
)


if is_onnx_available():
    import onnxruntime as ort


@nightly
@require_onnxruntime
@require_torch_gpu
class     lowercase__  (					unittest.TestCase		):






  @property
  def 			_UpperCAmelCase  (					self      :					Union[str, Any] ):




         """simple docstring"""







         return (
             "CUDAExecutionProvider",
             {
                 "gpu_mem_limit": "15000000000",  # 15GB
                 "arena_extend_strategy": "kSameAsRequested",
             },
         )






  @property
  def 			_UpperCAmelCase  (					self      :					Optional[Any] ):




         """simple docstring"""







         UpperCAmelCase__										=     ort.SessionOptions()
         UpperCAmelCase__										=     False
         return options






  def 			_UpperCAmelCase  (					self      :					Dict ):




         """simple docstring"""







         UpperCAmelCase__										=     load_image(
             "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main"
             "/in_paint/overture-creations-5sI6fQgYIuo.png" )
         UpperCAmelCase__										=     load_image(
             "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main"
             "/in_paint/overture-creations-5sI6fQgYIuo_mask.png" )
         UpperCAmelCase__										=     load_numpy(
             "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main"
             "/in_paint/red_cat_sitting_on_a_park_bench_onnx.npy" )

         # using the PNDM scheduler by default
         UpperCAmelCase__										=     OnnxStableDiffusionInpaintPipelineLegacy.from_pretrained(
             "CompVis/stable-diffusion-v1-4"		,						revision="onnx"		,						safety_checker=_lowercase		,						feature_extractor=_lowercase		,						provider=self.gpu_provider		,						sess_options=self.gpu_options		,						)
         pipe.set_progress_bar_config(disable=_lowercase )

         UpperCAmelCase__										=     "A red cat sitting on a park bench"

         UpperCAmelCase__										=     np.random.RandomState(0 )
         UpperCAmelCase__										=     pipe(
             prompt=_lowercase		,						image=_lowercase		,						mask_image=_lowercase		,						strength=0.7_5		,						guidance_scale=7.5		,						num_inference_steps=15		,						generator=_lowercase		,						output_type="np"		,						)

         UpperCAmelCase__										=     output.images[0]

         assert image.shape == (5_12, 5_12, 3)
         assert np.abs(expected_image - image ).max() < 1E-2





