





def 					__SCREAMING_SNAKE_CASE  (							__lowercase:		str):



  '''simple docstring'''






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


if __name__ == "__main__":
      __lowercase													=			input("""Enter the string: """).strip()
      __lowercase													=			find_minimum_partitions(s)
      print(f"""Minimum number of partitions required for the '{s}' is {ans}""")







from typing import TYPE_CHECKING

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


__lowercase													=			{
    """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:
      __lowercase													=			[
          """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

      __lowercase													=			_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
