





"""simple docstring"""





# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import torch

from ..models.speechta import SpeechTaForTextToSpeech, SpeechTaHifiGan, SpeechTaProcessor
from ..utils import is_datasets_available
from .base import PipelineTool


if is_datasets_available():
							from datasets import load_dataset
class 		SCREAMING_SNAKE_CASE_				(     snake_case__ ):
				"""simple docstring"""
				__snake_case :							Dict									=		"""microsoft/speecht5_tts"""
				__snake_case :							Any									=		(
				    """This is a tool that reads an English text out loud. It takes an input named `text` which should contain the """
				    """text to read (in English) and returns a waveform object containing the sound."""
				)
				__snake_case :							Union[str, Any]									=		"""text_reader"""
				__snake_case :							str									=		SpeechTaProcessor
				__snake_case :							List[str]									=		SpeechTaForTextToSpeech
				__snake_case :							Optional[int]									=		SpeechTaHifiGan

				__snake_case :							Optional[Any]									=		["""text"""]
				__snake_case :							Union[str, Any]									=		["""audio"""]




				def        __lowercase	(  self	:str      ):
											if self.post_processor is None:
																		__lowerCamelCase   :   Union[str, Any]       ='''microsoft/speecht5_hifigan'''
											super().setup()




				def        __lowercase	(  self	:int    ,     __lowercase	:int    ,     __lowercase	:Union[str, Any]=None      ):
											__lowerCamelCase   :   str       =self.pre_processor(text=__lowercase    ,     return_tensors='''pt'''    ,     truncation=__lowercase      )

											if speaker_embeddings is None:
																		if not is_datasets_available():
																									raise ImportError('''Datasets needs to be installed if not passing speaker embeddings.'''      )

																		__lowerCamelCase   :   str       =load_dataset('''Matthijs/cmu-arctic-xvectors'''    ,     split='''validation'''      )
																		__lowerCamelCase   :   Tuple       =torch.tensor(embeddings_dataset[7305]['''xvector''']      ).unsqueeze(0      )

											return {"input_ids": inputs["input_ids"], "speaker_embeddings": speaker_embeddings}




				def        __lowercase	(  self	:str    ,     __lowercase	:Optional[Any]      ):
											with torch.no_grad():
																		return self.model.generate_speech(**__lowercase      )




				def        __lowercase	(  self	:Union[str, Any]    ,     __lowercase	:List[Any]      ):
											with torch.no_grad():
																		return self.post_processor(__lowercase      ).cpu().detach()











"""simple docstring"""





# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from ..models.auto import AutoModelForSeqaSeqLM, AutoTokenizer
from .base import PipelineTool
class 		SCREAMING_SNAKE_CASE_				(     snake_case__ ):
				"""simple docstring"""
				__snake_case :							int									=		"""philschmid/bart-large-cnn-samsum"""
				__snake_case :							Optional[int]									=		(
				    """This is a tool that summarizes an English text. It takes an input `text` containing the text to summarize, """
				    """and returns a summary of the text."""
				)
				__snake_case :							Dict									=		"""summarizer"""
				__snake_case :							str									=		AutoTokenizer
				__snake_case :							List[str]									=		AutoModelForSeqaSeqLM

				__snake_case :							List[Any]									=		["""text"""]
				__snake_case :							Dict									=		["""text"""]




				def        __lowercase	(  self	:int    ,     __lowercase	:List[Any]      ):
											return self.pre_processor(__lowercase    ,     return_tensors='''pt'''    ,     truncation=__lowercase      )




				def        __lowercase	(  self	:Optional[int]    ,     __lowercase	:Optional[int]      ):
											return self.model.generate(**__lowercase      )[0]




				def        __lowercase	(  self	:List[Any]    ,     __lowercase	:str      ):
											return self.pre_processor.decode(__lowercase    ,     skip_special_tokens=__lowercase    ,     clean_up_tokenization_spaces=__lowercase      )




