



from typing import TYPE_CHECKING

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


_snake_case	=						{
    "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	=						["SpeechT5Tokenizer"]

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_snake_case	=						[
						    "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	=						_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





def        A       (      _lowerCamelCase       ,				_lowerCamelCase       ,				_lowerCamelCase						):





							'''simple docstring'''




							def count_of_possible_combinations(_lowerCamelCase						) -> int:
														if target < 0:
																					return 0
														if target == 0:
																					return 1
														return sum(count_of_possible_combinations(target - item						) for item in array						)

							return count_of_possible_combinations(_lowerCamelCase						)






def        A       (      _lowerCamelCase       ,				_lowerCamelCase       ,				_lowerCamelCase						):





							'''simple docstring'''




							def count_of_possible_combinations_with_dp_array(
							    _lowerCamelCase       ,				_lowerCamelCase						) -> int:
														if target < 0:
																					return 0
														if target == 0:
																					return 1
														if dp_array[target] != -1:
																					return dp_array[target]
														_lowerCAmelCase  :							Optional[int]				     =					sum(
														    count_of_possible_combinations_with_dp_array(target - item       ,				_lowerCamelCase						)
														    for item in array						)
														_lowerCAmelCase  :							Any				     =					answer
														return answer

							_lowerCAmelCase  :							List[Any]				     =					[-1] * (target + 1)
							return count_of_possible_combinations_with_dp_array(_lowerCamelCase       ,				_lowerCamelCase						)






def        A       (      _lowerCamelCase       ,				_lowerCamelCase       ,				_lowerCamelCase						):





							'''simple docstring'''




							_lowerCAmelCase  :							List[Any]				     =					[0] * (target + 1)
							_lowerCAmelCase  :							List[str]				     =					1

							for i in range(1       ,				target + 1						):
														for j in range(_lowerCamelCase						):
																					if i - array[j] >= 0:
																												dp_array[i] += dp_array[i - array[j]]

							return dp_array[target]


if __name__ == "__main__":
						import doctest

						doctest.testmod()
						_snake_case	=						3
						_snake_case	=						5
						_snake_case	=						[1, 2, 5]
						print(combination_sum_iv(n, array, target))
