"""simple docstring"""






import copy
from typing import Dict

from ...generation.configuration_utils import GenerationConfig
from ...utils import logging


lowerCAmelCase__  :  Dict											=     logging.get_logger(__name__)
class     snake_case	(			__UpperCAmelCase    ):




     """simple docstring"""

     snake_case__       =			"semantic"







     def __init__(    self       :     Optional[int]   ,lowerCamelCase__       :     Tuple=10_000   ,lowerCamelCase__       :     Tuple=True   ,lowerCamelCase__       :     Union[str, Any]=768   ,lowerCamelCase__       :     Dict=False   ,lowerCamelCase__       :     Optional[int]=False   ,lowerCamelCase__       :     Any=False   ,lowerCamelCase__       :     str=False   ,lowerCamelCase__       :     List[Any]=0.7   ,lowerCamelCase__       :     Union[str, Any]=True   ,lowerCamelCase__       :     Dict=10_048   ,lowerCamelCase__       :     List[str]=129_595   ,lowerCamelCase__       :     List[str]=129_599   ,lowerCamelCase__       :     Any=10_000   ,lowerCamelCase__       :     int=256   ,lowerCamelCase__       :     List[str]=49.9   ,**lowerCamelCase__       :     str   ,):
         super().__init__(
             temperature=lowerCamelCase__   ,do_sample=lowerCamelCase__   ,eos_token_id=lowerCamelCase__   ,renormalize_logits=lowerCamelCase__   ,max_new_tokens=lowerCamelCase__   ,output_scores=lowerCamelCase__   ,return_dict_in_generate=lowerCamelCase__   ,output_hidden_states=lowerCamelCase__   ,output_attentions=lowerCamelCase__   ,**lowerCamelCase__   ,)

         UpperCAmelCase__					=							text_encoding_offset
         UpperCAmelCase__					=							text_pad_token
         UpperCAmelCase__					=							eos_token_id
         UpperCAmelCase__					=							semantic_infer_token
         UpperCAmelCase__					=							semantic_vocab_size
         UpperCAmelCase__					=							max_input_semantic_length
         UpperCAmelCase__					=							semantic_rate_hz






class     snake_case	(			__UpperCAmelCase    ):




     """simple docstring"""

     snake_case__       =			"coarse_acoustics"







     def __init__(    self       :     Optional[Any]   ,lowerCamelCase__       :     int=True   ,lowerCamelCase__       :     List[str]=False   ,lowerCamelCase__       :     Union[str, Any]=False   ,lowerCamelCase__       :     Any=False   ,lowerCamelCase__       :     Dict=False   ,lowerCamelCase__       :     Optional[Any]=0.7   ,lowerCamelCase__       :     List[str]=True   ,lowerCamelCase__       :     Tuple=12_048   ,lowerCamelCase__       :     Optional[Any]=75   ,lowerCamelCase__       :     List[Any]=2   ,lowerCamelCase__       :     List[str]=12_050   ,lowerCamelCase__       :     Optional[int]=256   ,lowerCamelCase__       :     int = 630   ,lowerCamelCase__       :     int = 60   ,**lowerCamelCase__       :     Dict   ,):
         super().__init__(
             temperature=lowerCamelCase__   ,do_sample=lowerCamelCase__   ,renormalize_logits=lowerCamelCase__   ,output_scores=lowerCamelCase__   ,return_dict_in_generate=lowerCamelCase__   ,output_hidden_states=lowerCamelCase__   ,output_attentions=lowerCamelCase__   ,**lowerCamelCase__   ,)

         UpperCAmelCase__					=							coarse_semantic_pad_token
         UpperCAmelCase__					=							coarse_rate_hz
         UpperCAmelCase__					=							n_coarse_codebooks
         UpperCAmelCase__					=							coarse_infer_token
         UpperCAmelCase__					=							max_coarse_input_length
         UpperCAmelCase__					=							max_coarse_history
         UpperCAmelCase__					=							sliding_window_len






class     snake_case	(			__UpperCAmelCase    ):




     """simple docstring"""

     snake_case__       =			"fine_acoustics"







     def __init__(    self       :     Union[str, Any]   ,lowerCamelCase__       :     Any=0.5   ,lowerCamelCase__       :     List[Any]=512   ,lowerCamelCase__       :     Optional[Any]=1_024   ,lowerCamelCase__       :     List[Any]=8   ,**lowerCamelCase__       :     int   ,):
         super().__init__(temperature=lowerCamelCase__      )

         UpperCAmelCase__					=							max_fine_history_length
         UpperCAmelCase__					=							max_fine_input_length
         UpperCAmelCase__					=							n_fine_codebooks






class     snake_case	(			__UpperCAmelCase    ):




     """simple docstring"""

     snake_case__       =			"bark"
     snake_case__       =			True







     def __init__(    self       :     str   ,lowerCamelCase__       :     Dict = None   ,lowerCamelCase__       :     Dict = None   ,lowerCamelCase__       :     Dict = None   ,lowerCamelCase__       :     Union[str, Any]=24_000   ,lowerCamelCase__       :     Optional[int]=1_024   ,**lowerCamelCase__       :     Optional[Any]   ,):
         if semantic_config is None:
             UpperCAmelCase__					=							{}
             logger.info('semantic_config is None. initializing the semantic model with default values.'      )

         if coarse_acoustics_config is None:
             UpperCAmelCase__					=							{}
             logger.info('coarse_acoustics_config is None. initializing the coarse model with default values.'      )

         if fine_acoustics_config is None:
             UpperCAmelCase__					=							{}
             logger.info('fine_acoustics_config is None. initializing the fine model with default values.'      )

         UpperCAmelCase__					=							BarkSemanticGenerationConfig(**lowerCamelCase__      )
         UpperCAmelCase__					=							BarkCoarseGenerationConfig(**lowerCamelCase__      )
         UpperCAmelCase__					=							BarkFineGenerationConfig(**lowerCamelCase__      )

         UpperCAmelCase__					=							sample_rate
         UpperCAmelCase__					=							codebook_size







     @classmethod
     def 		__lowerCAmelCase						(    cls       :     int   ,lowerCamelCase__       :     BarkSemanticGenerationConfig   ,lowerCamelCase__       :     BarkCoarseGenerationConfig   ,lowerCamelCase__       :     BarkFineGenerationConfig   ,**lowerCamelCase__       :     Any   ,):
         return cls(
             semantic_config=semantic_config.to_dict()   ,coarse_acoustics_config=coarse_acoustics_config.to_dict()   ,fine_acoustics_config=fine_acoustics_config.to_dict()   ,**lowerCamelCase__   ,)







     def 		__lowerCAmelCase						(    self       :     Dict      ):
         UpperCAmelCase__					=							copy.deepcopy(self.__dict__      )

         UpperCAmelCase__					=							self.semantic_config.to_dict()
         UpperCAmelCase__					=							self.coarse_acoustics_config.to_dict()
         UpperCAmelCase__					=							self.fine_acoustics_config.to_dict()

         UpperCAmelCase__					=							self.__class__.model_type
         return output




"""simple docstring"""






from typing import SupportsIndex

import numpy as np
from scipy.ndimage import convolve



def   a_						( lowerCamelCase ,      lowerCamelCase ,      lowerCamelCase	):
				UpperCAmelCase__					=							np.stack((horizontal_flow, vertical_flow) ,      2	)

				# Create a grid of all pixel coordinates and subtract the flow to get the
				# target pixels coordinates
				UpperCAmelCase__					=							np.stack(
				    np.meshgrid(np.arange(0 ,      image.shape[1]	) ,      np.arange(0 ,      image.shape[0]	)	) ,      2	)
				UpperCAmelCase__					=							np.round(grid - flow	).astype(np.intaa	)

				# Find the locations outside of the original image
				UpperCAmelCase__					=							(grid < 0) | (grid >= np.array([image.shape[1], image.shape[0]]	))
				UpperCAmelCase__					=							0

				UpperCAmelCase__					=							image[grid[:, :, 1], grid[:, :, 0]]

				# Set pixels at invalid locations to 0
				UpperCAmelCase__					=							0

				return warped



def   a_						( lowerCamelCase ,      lowerCamelCase ,      lowerCamelCase ,      lowerCamelCase = None ,      ):
				if alpha is None:
								UpperCAmelCase__					=							0.1

				# Initialize flow
				UpperCAmelCase__					=							np.zeros_like(lowerCamelCase	)
				UpperCAmelCase__					=							np.zeros_like(lowerCamelCase	)

				# Prepare kernels for the calculation of the derivatives and the average velocity
				UpperCAmelCase__					=							np.array([[-1, 1], [-1, 1]]	) * 0.25
				UpperCAmelCase__					=							np.array([[-1, -1], [1, 1]]	) * 0.25
				UpperCAmelCase__					=							np.array([[1, 1], [1, 1]]	) * 0.25
				UpperCAmelCase__					=							np.array(
				    [[1 / 1_2, 1 / 6, 1 / 1_2], [1 / 6, 0, 1 / 6], [1 / 1_2, 1 / 6, 1 / 1_2]]	)

				# Iteratively refine the flow
				for _ in range(lowerCamelCase	):
								UpperCAmelCase__					=							warp(lowerCamelCase ,      lowerCamelCase ,      lowerCamelCase	)
								UpperCAmelCase__					=							convolve(lowerCamelCase ,      lowerCamelCase	) + convolve(lowerCamelCase ,      lowerCamelCase	)
								UpperCAmelCase__					=							convolve(lowerCamelCase ,      lowerCamelCase	) + convolve(lowerCamelCase ,      lowerCamelCase	)
								UpperCAmelCase__					=							convolve(lowerCamelCase ,      lowerCamelCase	) + convolve(lowerCamelCase ,      -kernel_t	)

								UpperCAmelCase__					=							convolve(lowerCamelCase ,      lowerCamelCase	)
								UpperCAmelCase__					=							convolve(lowerCamelCase ,      lowerCamelCase	)

								# This updates the flow as proposed in the paper (Step 12)
								UpperCAmelCase__					=							(
								    derivative_x * avg_horizontal_velocity
								    + derivative_y * avg_vertical_velocity
								    + derivative_t
								)
								UpperCAmelCase__					=							update / (alpha**2 + derivative_x**2 + derivative_y**2)

								UpperCAmelCase__					=							avg_horizontal_velocity - derivative_x * update
								UpperCAmelCase__					=							avg_vertical_velocity - derivative_y * update

				return horizontal_flow, vertical_flow


if __name__ == "__main__":
						import doctest

						doctest.testmod()



