
from ...processing_utils import ProcessorMixin





class     lowerCamelCase      (       __lowerCamelCase					):
	UpperCamelCase_  :					Any    		=	'SpeechT5FeatureExtractor'
	UpperCamelCase_  :					Any    		=	'SpeechT5Tokenizer'







	def __init__(     self      :int   ,     lowercase      :Union[str, Any]   ,     lowercase      :Tuple			)		->      Optional[Any]:







				"""simple docstring"""






				super().__init__(lowercase   ,     lowercase			)







	def __call__(     self      :int   ,     *lowercase      :Tuple   ,     **lowercase      :List[Any]			)		->      Any:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE     						= kwargs.pop('''audio'''   ,     lowercase			)
				SCREAMING_SNAKE_CASE     						= kwargs.pop('''text'''   ,     lowercase			)
				SCREAMING_SNAKE_CASE     						= kwargs.pop('''text_target'''   ,     lowercase			)
				SCREAMING_SNAKE_CASE     						= kwargs.pop('''audio_target'''   ,     lowercase			)
				SCREAMING_SNAKE_CASE     						= kwargs.pop('''sampling_rate'''   ,     lowercase			)

				if audio is not None and text is not None:
							raise ValueError(
							    '''Cannot process both `audio` and `text` inputs. Did you mean `audio_target` or `text_target`?'''			)
				if audio_target is not None and text_target is not None:
							raise ValueError(
							    '''Cannot process both `audio_target` and `text_target` inputs. Did you mean `audio` or `text`?'''			)
				if audio is None and audio_target is None and text is None and text_target is None:
							raise ValueError(
							    '''You need to specify either an `audio`, `audio_target`, `text`, or `text_target` input to process.'''			)

				if audio is not None:
							SCREAMING_SNAKE_CASE     						= self.feature_extractor(lowercase   ,     *lowercase   ,     sampling_rate=lowercase   ,     **lowercase			)
				elif text is not None:
							SCREAMING_SNAKE_CASE     						= self.tokenizer(lowercase   ,     **lowercase			)
				else:
							SCREAMING_SNAKE_CASE     						= None

				if audio_target is not None:
							SCREAMING_SNAKE_CASE     						= self.feature_extractor(audio_target=lowercase   ,     *lowercase   ,     sampling_rate=lowercase   ,     **lowercase			)
							SCREAMING_SNAKE_CASE     						= targets['''input_values''']
				elif text_target is not None:
							SCREAMING_SNAKE_CASE     						= self.tokenizer(lowercase   ,     **lowercase			)
							SCREAMING_SNAKE_CASE     						= targets['''input_ids''']
				else:
							SCREAMING_SNAKE_CASE     						= None

				if inputs is None:
							return targets

				if targets is not None:
							SCREAMING_SNAKE_CASE     						= labels

							SCREAMING_SNAKE_CASE     						= targets.get('''attention_mask'''			)
							if decoder_attention_mask is not None:
										SCREAMING_SNAKE_CASE     						= decoder_attention_mask

				return inputs







	def  snake_case__     (     self      :int   ,     *lowercase      :Any   ,     **lowercase      :str			)		->      str:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE     						= kwargs.pop('''input_values'''   ,     lowercase			)
				SCREAMING_SNAKE_CASE     						= kwargs.pop('''input_ids'''   ,     lowercase			)
				SCREAMING_SNAKE_CASE     						= kwargs.pop('''labels'''   ,     lowercase			)

				if input_values is not None and input_ids is not None:
							raise ValueError('''Cannot process both `input_values` and `input_ids` inputs.'''			)
				if input_values is None and input_ids is None and labels is None:
							raise ValueError(
							    '''You need to specify either an `input_values`, `input_ids`, or `labels` input to be padded.'''			)

				if input_values is not None:
							SCREAMING_SNAKE_CASE     						= self.feature_extractor.pad(lowercase   ,     *lowercase   ,     **lowercase			)
				elif input_ids is not None:
							SCREAMING_SNAKE_CASE     						= self.tokenizer.pad(lowercase   ,     **lowercase			)
				else:
							SCREAMING_SNAKE_CASE     						= None

				if labels is not None:
							if "input_ids" in labels or (isinstance(lowercase   ,     lowercase			) and "input_ids" in labels[0]):
										SCREAMING_SNAKE_CASE     						= self.tokenizer.pad(lowercase   ,     **lowercase			)
										SCREAMING_SNAKE_CASE     						= targets['''input_ids''']
							else:
										SCREAMING_SNAKE_CASE     						= self.feature_extractor.feature_size
										SCREAMING_SNAKE_CASE     						= self.feature_extractor.num_mel_bins
										SCREAMING_SNAKE_CASE     						= self.feature_extractor.pad(lowercase   ,     *lowercase   ,     **lowercase			)
										SCREAMING_SNAKE_CASE     						= feature_size_hack
										SCREAMING_SNAKE_CASE     						= targets['''input_values''']
				else:
							SCREAMING_SNAKE_CASE     						= None

				if inputs is None:
							return targets

				if targets is not None:
							SCREAMING_SNAKE_CASE     						= labels

							SCREAMING_SNAKE_CASE     						= targets.get('''attention_mask'''			)
							if decoder_attention_mask is not None:
										SCREAMING_SNAKE_CASE     						= decoder_attention_mask

				return inputs







	def  snake_case__     (     self      :str   ,     *lowercase      :Tuple   ,     **lowercase      :List[str]			)		->      List[Any]:







				"""simple docstring"""






				return self.tokenizer.batch_decode(*lowercase   ,     **lowercase			)







	def  snake_case__     (     self      :Any   ,     *lowercase      :Tuple   ,     **lowercase      :str			)		->      Tuple:







				"""simple docstring"""






				return self.tokenizer.decode(*lowercase   ,     **lowercase			)

import os


def    a      ( a = "matrix.txt"	)     ->int:




			'''simple docstring'''


			with open(os.path.join(os.path.dirname(a	)		,						a	)	) as in_file:
						SCREAMING_SNAKE_CASE     						= in_file.read()

			SCREAMING_SNAKE_CASE     						= [[int(a	) for cell in row.split(''','''	)] for row in data.strip().splitlines()]
			SCREAMING_SNAKE_CASE     						= [[0 for cell in row] for row in grid]
			SCREAMING_SNAKE_CASE     						= len(grid[0]	)

			SCREAMING_SNAKE_CASE     						= [[0 for i in range(a	)] for j in range(a	)]
			SCREAMING_SNAKE_CASE     						= grid[0][0]
			for i in range(1		,						a	):
						SCREAMING_SNAKE_CASE     						= grid[0][i] + dp[0][i - 1]
			for i in range(1		,						a	):
						SCREAMING_SNAKE_CASE     						= grid[i][0] + dp[i - 1][0]

			for i in range(1		,						a	):
						for j in range(1		,						a	):
									SCREAMING_SNAKE_CASE     						= grid[i][j] + min(dp[i - 1][j]		,						dp[i][j - 1]	)

			return dp[-1][-1]


if __name__ == "__main__":
							print(F'''{solution() = }''')