
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_torch_available,
)


_snake_case      :							Tuple     	=    {
    "configuration_speecht5": [
        "SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "SPEECHT5_PRETRAINED_HIFIGAN_CONFIG_ARCHIVE_MAP",
        "SpeechT5Config",
        "SpeechT5HifiGanConfig",
    ],
    "feature_extraction_speecht5": ["SpeechT5FeatureExtractor"],
    "processing_speecht5": ["SpeechT5Processor"],
}

try:
						if not is_sentencepiece_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_snake_case      :							int     	=    ["SpeechT5Tokenizer"]

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_snake_case      :							List[str]     	=    [
						    "SPEECHT5_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "SpeechT5ForSpeechToText",
						    "SpeechT5ForSpeechToSpeech",
						    "SpeechT5ForTextToSpeech",
						    "SpeechT5Model",
						    "SpeechT5PreTrainedModel",
						    "SpeechT5HifiGan",
						]

if TYPE_CHECKING:
						from .configuration_speechta import (
						    SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP,
						    SPEECHT5_PRETRAINED_HIFIGAN_CONFIG_ARCHIVE_MAP,
						    SpeechTaConfig,
						    SpeechTaHifiGanConfig,
						)
						from .feature_extraction_speechta import SpeechTaFeatureExtractor
						from .processing_speechta import SpeechTaProcessor

						try:
												if not is_sentencepiece_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_speechta import SpeechTaTokenizer

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_speechta import (
												    SPEECHT5_PRETRAINED_MODEL_ARCHIVE_LIST,
												    SpeechTaForSpeechToSpeech,
												    SpeechTaForSpeechToText,
												    SpeechTaForTextToSpeech,
												    SpeechTaHifiGan,
												    SpeechTaModel,
												    SpeechTaPreTrainedModel,
												)

else:
						import sys

						_snake_case      :							List[str]     	=    _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)


import numpy as np





class   UpperCamelCase_      :







						'''simple docstring'''



						def __init__(			self							:List[Any]     )  ->Any:
										lowercase         =      (0, 0)
										lowercase         =      None
										lowercase         =      0
										lowercase         =      0
										lowercase         =      0





						def __eq__(			self							:Optional[int]		,    lowerCAmelCase__							:Any     )  ->Optional[int]:
										return self.position == cell.position





						def        SCREAMING_SNAKE_CASE(			self							:Optional[Any]     )  ->Optional[Any]:
										print(self.position     )





class   UpperCamelCase_      :







						'''simple docstring'''



						def __init__(			self							:Optional[Any]		,    lowerCAmelCase__							:Tuple=(5, 5)     )  ->str:
										lowercase         =      np.zeros(lowerCAmelCase__     )
										lowercase         =      world_size[0]
										lowercase         =      world_size[1]





						def        SCREAMING_SNAKE_CASE(			self							:List[Any]     )  ->Optional[int]:
										print(self.w     )





						def        SCREAMING_SNAKE_CASE(			self							:Optional[int]		,    lowerCAmelCase__							:Optional[Any]     )  ->Optional[Any]:
										lowercase         =      [
										    (-1, -1),
										    (-1, 0),
										    (-1, 1),
										    (0, -1),
										    (0, 1),
										    (1, -1),
										    (1, 0),
										    (1, 1),
										]
										lowercase         =      cell.position[0]
										lowercase         =      cell.position[1]
										lowercase         =      []
										for n in neughbour_cord:
														lowercase         =      current_x + n[0]
														lowercase         =      current_y + n[1]
														if 0 <= x < self.world_x_limit and 0 <= y < self.world_y_limit:
																		lowercase         =      Cell()
																		lowercase         =      (x, y)
																		lowercase         =      cell
																		neighbours.append(lowerCAmelCase__     )
										return neighbours




def  __snake_case							(	__magic_name__		,    __magic_name__		,    __magic_name__						):







				'''simple docstring'''


				lowercase         =      []
				lowercase         =      []
				_open.append(__magic_name__						)

				while _open:
								lowercase         =      np.argmin([n.f for n in _open]						)
								lowercase         =      _open[min_f]
								_closed.append(_open.pop(__magic_name__						)						)
								if current == goal:
												break
								for n in world.get_neigbours(__magic_name__						):
												for c in _closed:
																if c == n:
																				continue
												lowercase         =      current.g + 1
												lowercase     ,	lowercase         =      n.position
												lowercase     ,	lowercase         =      goal.position
												lowercase         =      (ya - ya) ** 2 + (xa - xa) ** 2
												lowercase         =      n.h + n.g

												for c in _open:
																if c == n and c.f < n.f:
																				continue
												_open.append(__magic_name__						)
				lowercase         =      []
				while current.parent is not None:
								path.append(current.position						)
								lowercase         =      current.parent
				path.append(current.position						)
				return path[::-1]


if __name__ == "__main__":
						_snake_case      :							Optional[int]     	=    Gridworld()
						# Start position and goal
						_snake_case      :							Dict     	=    Cell()
						_snake_case      :							List[str]     	=    (0, 0)
						_snake_case      :							Union[str, Any]     	=    Cell()
						_snake_case      :							List[Any]     	=    (4, 4)
						print(F"path from {start.position} to {goal.position}")
						_snake_case      :							str     	=    astar(world, start, goal)
						#   Just for visual reasons.
						for i in s:
												_snake_case      :							List[Any]     	=    1
						print(world.w)
