






def     a     (		lowerCamelCase_							):






				'''simple docstring'''
				lowercase__  					=     []
				for data in source_data:
								for i, el in enumerate(lowerCamelCase_							):
												if len(lowerCamelCase_							) < i + 1:
																data_lists.append([]							)
												data_lists[i].append(float(lowerCamelCase_							)							)
				return data_lists






def     a     (		lowerCamelCase_						,  lowerCamelCase_							):






				'''simple docstring'''
				lowercase__  					=     []
				for dlist, weight in zip(lowerCamelCase_						,  lowerCamelCase_							):
								lowercase__  					=     min(lowerCamelCase_							)
								lowercase__  					=     max(lowerCamelCase_							)

								lowercase__  					=     []
								# for weight 0 score is 1 - actual score
								if weight == 0:
												for item in dlist:
																try:
																				score.append(1 - ((item - mind) / (maxd - mind))							)
																except ZeroDivisionError:
																				score.append(1							)

								elif weight == 1:
												for item in dlist:
																try:
																				score.append((item - mind) / (maxd - mind)							)
																except ZeroDivisionError:
																				score.append(0							)

        # weight not 0 or 1
								else:
												lowercase__  					=     F"""Invalid weight of {weight:f} provided"""
												raise ValueError(lowerCamelCase_							)

								score_lists.append(lowerCamelCase_							)

				return score_lists






def     a     (		lowerCamelCase_							):






				'''simple docstring'''
				lowercase__  					=     [0 for i in range(len(score_lists[0]							)							)]

				for slist in score_lists:
								for j, ele in enumerate(lowerCamelCase_							):
												lowercase__  					=     final_scores[j] + ele

				return final_scores






def     a     (		lowerCamelCase_						,  lowerCamelCase_							):






				'''simple docstring'''
				lowercase__  					=     get_data(lowerCamelCase_							)
				lowercase__  					=     calculate_each_score(lowerCamelCase_						,  lowerCamelCase_							)
				lowercase__  					=     generate_final_scores(lowerCamelCase_							)

				# append scores to source data
				for i, ele in enumerate(lowerCamelCase_							):
								source_data[i].append(lowerCamelCase_							)

				return source_data












from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


A__      :     Optional[int]       =					{
    'configuration_clap': [
        'CLAP_PRETRAINED_MODEL_ARCHIVE_LIST',
        'ClapAudioConfig',
        'ClapConfig',
        'ClapTextConfig',
    ],
    'processing_clap': ['ClapProcessor'],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							A__      :     str       =					[
							    'CLAP_PRETRAINED_MODEL_ARCHIVE_LIST',
							    'ClapModel',
							    'ClapPreTrainedModel',
							    'ClapTextModel',
							    'ClapTextModelWithProjection',
							    'ClapAudioModel',
							    'ClapAudioModelWithProjection',
							]
							A__      :     List[Any]       =					['ClapFeatureExtractor']

if TYPE_CHECKING:
							from .configuration_clap import (
							    CLAP_PRETRAINED_MODEL_ARCHIVE_LIST,
							    ClapAudioConfig,
							    ClapConfig,
							    ClapTextConfig,
							)
							from .processing_clap import ClapProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .feature_extraction_clap import ClapFeatureExtractor
														from .modeling_clap import (
														    CLAP_PRETRAINED_MODEL_ARCHIVE_LIST,
														    ClapAudioModel,
														    ClapAudioModelWithProjection,
														    ClapModel,
														    ClapPreTrainedModel,
														    ClapTextModel,
														    ClapTextModelWithProjection,
														)


else:
							import sys

							A__      :     int       =					_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




