




from typing import TYPE_CHECKING

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


__A    :				Optional[Any]    						=	{
    """configuration_speech_to_text_2""": ["""SPEECH_TO_TEXT_2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Speech2Text2Config"""],
    """processing_speech_to_text_2""": ["""Speech2Text2Processor"""],
    """tokenization_speech_to_text_2""": ["""Speech2Text2Tokenizer"""],
}


try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__A    :				Optional[Any]    						=	[
		    """SPEECH_TO_TEXT_2_PRETRAINED_MODEL_ARCHIVE_LIST""",
		    """Speech2Text2ForCausalLM""",
		    """Speech2Text2PreTrainedModel""",
		]


if TYPE_CHECKING:
		from .configuration_speech_to_text_a import SPEECH_TO_TEXT_2_PRETRAINED_CONFIG_ARCHIVE_MAP, SpeechaTextaConfig
		from .processing_speech_to_text_a import SpeechaTextaProcessor
		from .tokenization_speech_to_text_a import SpeechaTextaTokenizer

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_speech_to_text_a import (
				    SPEECH_TO_TEXT_2_PRETRAINED_MODEL_ARCHIVE_LIST,
				    SpeechaTextaForCausalLM,
				    SpeechaTextaPreTrainedModel,
				)

else:
		import sys

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












def        lowerCamelCase_     (     SCREAMING_SNAKE_CASE ):
			'''simple docstring'''
			SCREAMING_SNAKE_CASE     =       len(SCREAMING_SNAKE_CASE )
			SCREAMING_SNAKE_CASE     =       [0] * length
			SCREAMING_SNAKE_CASE     =       [[False for i in range(SCREAMING_SNAKE_CASE )] for j in range(SCREAMING_SNAKE_CASE )]
			for i, c in enumerate(SCREAMING_SNAKE_CASE ):
						SCREAMING_SNAKE_CASE     =       i
						for j in range(i + 1 ):
									if c == string[j] and (i - j < 2 or is_palindromic[j + 1][i - 1]):
												SCREAMING_SNAKE_CASE     =       True
												SCREAMING_SNAKE_CASE     =       min(SCREAMING_SNAKE_CASE       ,						0 if j == 0 else (cut[j - 1] + 1) )
						SCREAMING_SNAKE_CASE     =       mincut
			return cut[length - 1]


if __name__ == "__main__":
		__A    :				Optional[int]    						=	input("""Enter the string: """).strip()
		__A    :				List[Any]    						=	find_minimum_partitions(s)
		print(f'''Minimum number of partitions required for the \'{s}\' is {ans}''')






