# 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.whisper import WhisperForConditionalGeneration, WhisperProcessor
from .base import PipelineTool







class __snake_case				(						lowerCamelCase_		):
   lowerCAmelCase_														=							"openai/whisper-base"
   lowerCAmelCase_														=							(
       "This is a tool that transcribes an audio into text. It takes an input named `audio` and returns the "
       "transcribed text."
   )
   lowerCAmelCase_														=							"transcriber"
   lowerCAmelCase_														=							WhisperProcessor
   lowerCAmelCase_														=							WhisperForConditionalGeneration

   lowerCAmelCase_														=							["audio"]
   lowerCAmelCase_														=							["text"]




   def 	__a						(    self			:				Any       ,	_lowercase			:				List[str]      ):



     """simple docstring"""






     return self.pre_processor(_lowercase       ,	return_tensors="""pt"""      ).input_features




   def 	__a						(    self			:				Union[str, Any]       ,	_lowercase			:				Any      ):



     """simple docstring"""






     return self.model.generate(inputs=_lowercase      )




   def 	__a						(    self			:				str       ,	_lowercase			:				Optional[int]      ):



     """simple docstring"""






     return self.pre_processor.batch_decode(_lowercase       ,	skip_special_tokens=_lowercase      )[0]

import unittest
from dataclasses import dataclass

import pytest

from accelerate.commands.config.config_args import SageMakerConfig
from accelerate.utils import ComputeEnvironment
from accelerate.utils.launch import _convert_nargs_to_dict







@dataclass
class __snake_case				(						lowerCamelCase_		):
   lowerCAmelCase_														=							ComputeEnvironment.AMAZON_SAGEMAKER
   lowerCAmelCase_														=							True
   lowerCAmelCase_														=							"ml.p3.2xlarge"
   lowerCAmelCase_														=							"accelerate_sagemaker_execution_role"
   lowerCAmelCase_														=							"hf-sm"
   lowerCAmelCase_														=							"us-east-1"
   lowerCAmelCase_														=							1
   lowerCAmelCase_														=							"accelerate-sagemaker-1"
   lowerCAmelCase_														=							"1.6"
   lowerCAmelCase_														=							"4.4"
   lowerCAmelCase_														=							"train.py"
   lowerCAmelCase_														=							[
       "--model_name_or_path",
       "bert",
       "--do_train",
       "False",
       "--epochs",
       "3",
       "--learning_rate",
       "5e-5",
       "--max_steps",
       "50.5",
   ]
   lowerCAmelCase_														=							[
       "--model_name_or_path",
       "bert",
       "--do_train",
       "--do_test",
       "False",
       "--do_predict",
       "--epochs",
       "3",
       "--learning_rate",
       "5e-5",
       "--max_steps",
       "50.5",
   ]







class __snake_case				(						unittest.TestCase		):




   def 	__a						(    self			:				List[Any]      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      _convert_nargs_to_dict(MockLaunchConfig.success_training_script_args      )
     assert isinstance(converted_args["""model_name_or_path"""]       ,	_lowercase      )
     assert isinstance(converted_args["""do_train"""]       ,	_lowercase      )
     assert isinstance(converted_args["""epochs"""]       ,	_lowercase      )
     assert isinstance(converted_args["""learning_rate"""]       ,	_lowercase      )
     assert isinstance(converted_args["""max_steps"""]       ,	_lowercase      )

     with pytest.raises(_lowercase      ):
       _convert_nargs_to_dict(MockLaunchConfig.fail_training_script_args      )
