


"""simple docstring"""






from typing import Any


def __lowercase     (      lowerCamelCase_  :      list						,					lowerCamelCase_  :      list						,					lowerCamelCase_  :      dict						,					lowerCamelCase_  :      dict						,					lowerCamelCase_  :      dict						,					):
				_validation(
				    lowerCamelCase_						,					lowerCamelCase_						,					lowerCamelCase_						,					lowerCamelCase_						,					lowerCamelCase_						,					)
				# 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(lowerCamelCase_  )  ):
								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(lowerCamelCase_  ) - 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(lowerCamelCase_  ) - 1						,					-1						,					-1  ):
								result.append(lowerCamelCase_  )
								SCREAMING_SNAKE_CASE__     							=				pointers[previous, observations_space[o]]
				result.reverse()

				return result


def __lowercase     (      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 __lowercase     (      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 __lowercase     (      lowerCamelCase_  :      Any						,					lowerCamelCase_  :      Any  ):
				_validate_list(lowerCamelCase_						,					"observations_space"  )
				_validate_list(lowerCamelCase_						,					"states_space"  )


def __lowercase     (      lowerCamelCase_  :      Any						,					lowerCamelCase_  :      str  ):
				if not isinstance(_object						,					lowerCamelCase_  ):
								SCREAMING_SNAKE_CASE__     							=				F'''{var_name} must be a list'''
								raise ValueError(lowerCamelCase_  )
				else:
								for x in _object:
												if not isinstance(lowerCamelCase_						,					lowerCamelCase_  ):
																SCREAMING_SNAKE_CASE__     							=				F'''{var_name} must be a list of strings'''
																raise ValueError(lowerCamelCase_  )


def __lowercase     (      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 __lowercase     (      lowerCamelCase_  :      Any						,					lowerCamelCase_  :      str  ):
				_validate_dict(_object						,					lowerCamelCase_						,					lowerCamelCase_  )
				for x in _object.values():
								_validate_dict(lowerCamelCase_						,					lowerCamelCase_						,					lowerCamelCase_						,					lowerCamelCase_  )


def __lowercase     (      lowerCamelCase_  :      Any						,					lowerCamelCase_  :      str						,					lowerCamelCase_  :      type						,					lowerCamelCase_  :      bool = False  ):
				if not isinstance(_object						,					lowerCamelCase_  ):
								SCREAMING_SNAKE_CASE__     							=				F'''{var_name} must be a dict'''
								raise ValueError(lowerCamelCase_  )
				if not all(isinstance(lowerCamelCase_						,					lowerCamelCase_  ) for x in _object  ):
								SCREAMING_SNAKE_CASE__     							=				F'''{var_name} all keys must be strings'''
								raise ValueError(lowerCamelCase_  )
				if not all(isinstance(lowerCamelCase_						,					lowerCamelCase_  ) 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(lowerCamelCase_  )


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

	testmod()








"""simple docstring"""






import numpy as np
import torch
from imwatermark import WatermarkEncoder


# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
_lowerCamelCase     =  0b1011_0011_1110_1100_1001_0000_0111_1011_1011_0001_1001_1110
# bin(x)[2:] gives bits of x as str, use int to convert them to 0/1
_lowerCamelCase     =  [int(bit) for bit in bin(WATERMARK_MESSAGE)[2:]]


class 			lowerCamelCase_		:





				"""simple docstring"""







				def __init__(						self     ):
								SCREAMING_SNAKE_CASE__     							=				WATERMARK_BITS
								SCREAMING_SNAKE_CASE__     							=				WatermarkEncoder()

								self.encoder.set_watermark("bits"       ,		self.watermark     )






				def   lowerCAmelCase__		(						self       ,		UpperCAmelCase__     ):
								# can't encode images that are smaller than 256
								if images.shape[-1] < 256:
												return images

								SCREAMING_SNAKE_CASE__     							=				(255 * (images / 2 + 0.5)).cpu().permute(0       ,		2       ,		3       ,		1     ).float().numpy()

								SCREAMING_SNAKE_CASE__     							=				[self.encoder.encode(UpperCAmelCase__       ,		"dwtDct"     ) for image in images]

								SCREAMING_SNAKE_CASE__     							=				torch.from_numpy(np.array(UpperCAmelCase__     )     ).permute(0       ,		3       ,		1       ,		2     )

								SCREAMING_SNAKE_CASE__     							=				torch.clamp(2 * (images / 255 - 0.5)       ,		min=-1.0       ,		max=1.0     )
								return images
