


from ...processing_utils import ProcessorMixin







class 	__lowercase    (__SCREAMING_SNAKE_CASE  ):





							"""simple docstring"""







							_UpperCAmelCase      =						"""WhisperFeatureExtractor"""
							_UpperCAmelCase      =						"""WhisperTokenizer"""






							def __init__(      self			,						lowerCAmelCase__			,						lowerCAmelCase__       ):





										"""simple docstring"""




										super().__init__(lowerCAmelCase__			,						lowerCAmelCase__       )
										SCREAMING_SNAKE_CASE_		:     Union[str, Any]					=					self.feature_extractor
										SCREAMING_SNAKE_CASE_		:     List[Any]					=					False






							def 					UpperCamelCase__     (      self			,						lowerCAmelCase__=None			,						lowerCAmelCase__=None			,						lowerCAmelCase__=True       ):





										"""simple docstring"""




										return self.tokenizer.get_decoder_prompt_ids(task=lowerCAmelCase__			,						language=lowerCAmelCase__			,						no_timestamps=lowerCAmelCase__       )






							def __call__(      self			,						*lowerCAmelCase__			,						**lowerCAmelCase__       ):





										"""simple docstring"""




										if self._in_target_context_manager:
													return self.current_processor(*lowerCAmelCase__			,						**lowerCAmelCase__       )

										SCREAMING_SNAKE_CASE_		:     Tuple					=					kwargs.pop('audio'			,						lowerCAmelCase__       )
										SCREAMING_SNAKE_CASE_		:     str					=					kwargs.pop('sampling_rate'			,						lowerCAmelCase__       )
										SCREAMING_SNAKE_CASE_		:     Optional[Any]					=					kwargs.pop('text'			,						lowerCAmelCase__       )
										if len(lowerCAmelCase__       ) > 0:
													SCREAMING_SNAKE_CASE_		:     List[Any]					=					args[0]
													SCREAMING_SNAKE_CASE_		:     List[Any]					=					args[1:]

										if audio is None and text is None:
													raise ValueError('You need to specify either an `audio` or `text` input to process.'       )

										if audio is not None:
													SCREAMING_SNAKE_CASE_		:     List[Any]					=					self.feature_extractor(lowerCAmelCase__			,						*lowerCAmelCase__			,						sampling_rate=lowerCAmelCase__			,						**lowerCAmelCase__       )
										if text is not None:
													SCREAMING_SNAKE_CASE_		:     Optional[int]					=					self.tokenizer(lowerCAmelCase__			,						**lowerCAmelCase__       )

										if text is None:
													return inputs

										elif audio is None:
													return encodings
										else:
													SCREAMING_SNAKE_CASE_		:     Optional[int]					=					encodings['input_ids']
													return inputs






							def 					UpperCamelCase__     (      self			,						*lowerCAmelCase__			,						**lowerCAmelCase__       ):





										"""simple docstring"""




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






							def 					UpperCamelCase__     (      self			,						*lowerCAmelCase__			,						**lowerCAmelCase__       ):





										"""simple docstring"""




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






							def 					UpperCamelCase__     (      self			,						lowerCAmelCase__			,						lowerCAmelCase__="np"       ):





										"""simple docstring"""




										return self.tokenizer.get_prompt_ids(lowerCAmelCase__			,						return_tensors=lowerCAmelCase__       )










from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


_lowerCAmelCase	:   Any    =   {
    "configuration_chinese_clip": [
        "CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "ChineseCLIPConfig",
        "ChineseCLIPOnnxConfig",
        "ChineseCLIPTextConfig",
        "ChineseCLIPVisionConfig",
    ],
    "processing_chinese_clip": ["ChineseCLIPProcessor"],
}

try:
	if not is_vision_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_lowerCAmelCase	:   str    =   ["ChineseCLIPFeatureExtractor"]
	_lowerCAmelCase	:   Any    =   ["ChineseCLIPImageProcessor"]

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_lowerCAmelCase	:   Optional[int]    =   [
	    "CHINESE_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST",
	    "ChineseCLIPModel",
	    "ChineseCLIPPreTrainedModel",
	    "ChineseCLIPTextModel",
	    "ChineseCLIPVisionModel",
	]

if TYPE_CHECKING:
	from .configuration_chinese_clip import (
	    CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    ChineseCLIPConfig,
	    ChineseCLIPOnnxConfig,
	    ChineseCLIPTextConfig,
	    ChineseCLIPVisionConfig,
	)
	from .processing_chinese_clip import ChineseCLIPProcessor

	try:
		if not is_vision_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .feature_extraction_chinese_clip import ChineseCLIPFeatureExtractor, ChineseCLIPImageProcessor

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_chinese_clip import (
		    CHINESE_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
		    ChineseCLIPModel,
		    ChineseCLIPPreTrainedModel,
		    ChineseCLIPTextModel,
		    ChineseCLIPVisionModel,
		)

else:
	import sys

	_lowerCAmelCase	:   Any    =   _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
