


import os

import pytest

from datasets import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
)


snake_case    :   Any	    =					pytest.mark.integration
@pytest.mark.parametrize('''path'''			,  ['''paws''', '''csv''']						)
def     __lowerCamelCase						(			UpperCAmelCase_						:		Optional[int]			,  UpperCAmelCase_						:		Optional[Any]						):




      """simple docstring"""





      inspect_dataset(UpperCAmelCase_			,  UpperCAmelCase_						)
      a						:List[Any]										=	path + '''.py'''
      assert script_name in os.listdir(UpperCAmelCase_						)
      assert "__pycache__" not in os.listdir(UpperCAmelCase_						)
@pytest.mark.filterwarnings('''ignore:inspect_metric is deprecated:FutureWarning'''						)
@pytest.mark.filterwarnings('''ignore:metric_module_factory is deprecated:FutureWarning'''						)
@pytest.mark.parametrize('''path'''			,  ['''accuracy''']						)
def     __lowerCamelCase						(			UpperCAmelCase_						:		List[Any]			,  UpperCAmelCase_						:		Any						):




      """simple docstring"""





      inspect_metric(UpperCAmelCase_			,  UpperCAmelCase_						)
      a						:Dict										=	path + '''.py'''
      assert script_name in os.listdir(UpperCAmelCase_						)
      assert "__pycache__" not in os.listdir(UpperCAmelCase_						)
@pytest.mark.parametrize(
    '''path, config_name, expected_splits'''			,  [
        ('''squad''', '''plain_text''', ['''train''', '''validation''']),
        ('''dalle-mini/wit''', '''dalle-mini--wit''', ['''train''']),
        ('''paws''', '''labeled_final''', ['''train''', '''test''', '''validation''']),
    ]			,  )
def     __lowerCamelCase						(			UpperCAmelCase_						:		Optional[int]			,  UpperCAmelCase_						:		List[Any]			,  UpperCAmelCase_						:		str						):




      """simple docstring"""





      a						:List[str]										=	get_dataset_config_info(UpperCAmelCase_			,  config_name=UpperCAmelCase_						)
      assert info.config_name == config_name
      assert list(info.splits.keys()						) == expected_splits
@pytest.mark.parametrize(
    '''path, config_name, expected_exception'''			,  [
        ('''paws''', None, ValueError),
    ]			,  )
def     __lowerCamelCase						(			UpperCAmelCase_						:		List[Any]			,  UpperCAmelCase_						:		str			,  UpperCAmelCase_						:		Tuple						):




      """simple docstring"""





      with pytest.raises(UpperCAmelCase_						):
            get_dataset_config_info(UpperCAmelCase_			,  config_name=UpperCAmelCase_						)
@pytest.mark.parametrize(
    '''path, expected'''			,  [
        ('''squad''', '''plain_text'''),
        ('''acronym_identification''', '''default'''),
        ('''lhoestq/squad''', '''plain_text'''),
        ('''lhoestq/test''', '''default'''),
        ('''lhoestq/demo1''', '''lhoestq--demo1'''),
        ('''dalle-mini/wit''', '''dalle-mini--wit'''),
    ]			,  )
def     __lowerCamelCase						(			UpperCAmelCase_						:		Tuple			,  UpperCAmelCase_						:		int						):




      """simple docstring"""





      a						:List[str]										=	get_dataset_config_names(UpperCAmelCase_						)
      assert expected in config_names
@pytest.mark.parametrize(
    '''path, expected_configs, expected_splits_in_first_config'''			,  [
        ('''squad''', ['''plain_text'''], ['''train''', '''validation''']),
        ('''dalle-mini/wit''', ['''dalle-mini--wit'''], ['''train''']),
        ('''paws''', ['''labeled_final''', '''labeled_swap''', '''unlabeled_final'''], ['''train''', '''test''', '''validation''']),
    ]			,  )
def     __lowerCamelCase						(			UpperCAmelCase_						:		Tuple			,  UpperCAmelCase_						:		Tuple			,  UpperCAmelCase_						:		Optional[int]						):




      """simple docstring"""





      a						:Optional[int]										=	get_dataset_infos(UpperCAmelCase_						)
      assert list(infos.keys()						) == expected_configs
      a						:Union[str, Any]										=	expected_configs[0]
      assert expected_config in infos
      a						:List[Any]										=	infos[expected_config]
      assert info.config_name == expected_config
      assert list(info.splits.keys()						) == expected_splits_in_first_config
@pytest.mark.parametrize(
    '''path, expected_config, expected_splits'''			,  [
        ('''squad''', '''plain_text''', ['''train''', '''validation''']),
        ('''dalle-mini/wit''', '''dalle-mini--wit''', ['''train''']),
        ('''paws''', '''labeled_final''', ['''train''', '''test''', '''validation''']),
    ]			,  )
def     __lowerCamelCase						(			UpperCAmelCase_						:		Optional[int]			,  UpperCAmelCase_						:		Any			,  UpperCAmelCase_						:		Optional[int]						):




      """simple docstring"""





      a						:Union[str, Any]										=	get_dataset_infos(UpperCAmelCase_						)
      assert expected_config in infos
      a						:int										=	infos[expected_config]
      assert info.config_name == expected_config
      assert list(info.splits.keys()						) == expected_splits






@pytest.mark.parametrize(
    '''path, config_name, expected_exception'''			,  [
        ('''paws''', None, ValueError),
    ]			,  )
def     __lowerCamelCase						(			UpperCAmelCase_						:		Union[str, Any]			,  UpperCAmelCase_						:		Optional[int]			,  UpperCAmelCase_						:		str						):




      """simple docstring"""





      with pytest.raises(UpperCAmelCase_						):
            get_dataset_split_names(UpperCAmelCase_			,  config_name=UpperCAmelCase_						)









# 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 		_snake_case  (				_snake_case							):
 SCREAMING_SNAKE_CASE__				=	'microsoft/speecht5_tts'
 SCREAMING_SNAKE_CASE__				=	(
     '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.'
 )
 SCREAMING_SNAKE_CASE__				=	'text_reader'
 SCREAMING_SNAKE_CASE__				=	SpeechTaProcessor
 SCREAMING_SNAKE_CASE__				=	SpeechTaForTextToSpeech
 SCREAMING_SNAKE_CASE__				=	SpeechTaHifiGan

 SCREAMING_SNAKE_CASE__				=	['text']
 SCREAMING_SNAKE_CASE__				=	['audio']




 def 	SCREAMING_SNAKE_CASE__    (		self   ):
       if self.post_processor is None:
             a						:List[Any]										=	'''microsoft/speecht5_hifigan'''
       super().setup()




 def 	SCREAMING_SNAKE_CASE__    (		self ,  _lowerCamelCase ,  _lowerCamelCase=None   ):
       a						:Tuple										=	self.pre_processor(text=_lowerCamelCase ,  return_tensors='''pt''' ,  truncation=_lowerCamelCase   )

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

             a						:List[Any]										=	load_dataset('''Matthijs/cmu-arctic-xvectors''' ,  split='''validation'''   )
             a						:int										=	torch.tensor(embeddings_dataset[7305]['''xvector''']   ).unsqueeze(0   )

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




 def 	SCREAMING_SNAKE_CASE__    (		self ,  _lowerCamelCase   ):
       with torch.no_grad():
             return self.model.generate_speech(**_lowerCamelCase   )




 def 	SCREAMING_SNAKE_CASE__    (		self ,  _lowerCamelCase   ):
       with torch.no_grad():
             return self.post_processor(_lowerCamelCase   ).cpu().detach()





