


'''simple docstring'''


import sys
from pathlib import Path


__magic_name__			=      Path(__file__).resolve().parents[3] / 'src'
sys.path.insert(1, str(git_repo_path))

import dataclasses  # noqa
import io  # noqa
import itertools  # noqa
import json  # noqa
import os  # noqa
import unittest  # noqa
from copy import deepcopy  # noqa

from parameterized import parameterized  # noqa
from transformers import TrainingArguments, is_torch_available  # noqa
from transformers.deepspeed import is_deepspeed_available  # noqa
from transformers.file_utils import WEIGHTS_NAME  # noqa
from transformers.testing_utils import (  # noqa
    CaptureLogger,
    ExtendSysPath,
    TestCasePlus,
    execute_subprocess_async,
    get_gpu_count,
    mockenv_context,
    require_deepspeed,
    require_torch_gpu,
    require_torch_multi_gpu,
    slow,
)
from transformers.trainer_utils import set_seed  # noqa


set_seed(42)

__magic_name__			=      {'base': 'patrickvonplaten/wav2vec2_tiny_random', 'robust': 'patrickvonplaten/wav2vec2_tiny_random_robust'}

__magic_name__			=      'zero2'
__magic_name__			=      'zero3'
__magic_name__			=      [ZEROa, ZEROa]




def      lowerCamelCase					(      lowerCamelCase  :      List[Any]							,						lowerCamelCase  :      Tuple							,						lowerCamelCase  :      str):
      A_						:  Any          =				parameterized.to_safe_name("""_""".join(str(lowerCAmelCase_) for x in param.args))
      return F'{func.__name__}_{param_based_name}'


# Cartesian-product of zero stages with models to test
__magic_name__			=      list(itertools.product(stages, models.keys()))






@slow
@require_deepspeed
@require_torch_gpu
class 	__lowerCAmelCase		(							a__    ):


  '''simple docstring'''







  @parameterized.expand(lowercase__	,name_func=lowercase__ )
  def        _a							(							self :       str	,_a :       Optional[Any]	,_a :       str ):

        '''simple docstring'''




        self.run_and_check(
            stage=lowercase__	,model=lowercase__	,distributed=lowercase__	,fpaa=lowercase__	,)






  @require_torch_multi_gpu
  @parameterized.expand(lowercase__	,name_func=lowercase__ )
  def        _a							(							self :       Tuple	,_a :       Optional[int]	,_a :       str ):

        '''simple docstring'''




        self.run_and_check(
            stage=lowercase__	,model=lowercase__	,distributed=lowercase__	,fpaa=lowercase__	,)






  @parameterized.expand(lowercase__	,name_func=lowercase__ )
  def        _a							(							self :       Union[str, Any]	,_a :       str	,_a :       str ):

        '''simple docstring'''




        self.run_and_check(
            stage=lowercase__	,model=lowercase__	,distributed=lowercase__	,fpaa=lowercase__	,)






  @require_torch_multi_gpu
  @parameterized.expand(lowercase__	,name_func=lowercase__ )
  def        _a							(							self :       Optional[Any]	,_a :       Tuple	,_a :       Union[str, Any] ):

        '''simple docstring'''




        self.run_and_check(
            stage=lowercase__	,model=lowercase__	,distributed=lowercase__	,fpaa=lowercase__	,)






  def        _a							(							self :       Dict	,_a :       str ):

        '''simple docstring'''




        pass






  def        _a							(							self :       str	,_a :       Union[str, Any]	,_a :       str	,_a :       Optional[int] = 10	,_a :       Union[str, Any] = True	,_a :       Tuple = True	,_a :       List[str] = True	,):

        '''simple docstring'''




        A_						:  Dict          =				models[model]

        A_						:  int          =				self.run_trainer(
            stage=lowercase__	,model_name=lowercase__	,eval_steps=lowercase__	,num_train_epochs=1	,distributed=lowercase__	,fpaa=lowercase__	,)

        self.do_checks(lowercase__ )

        return output_dir






  def        _a							(							self :       int	,_a :       List[Any]	,_a :       Union[str, Any]	,_a :       Optional[int] = 10	,_a :       Dict = 1	,_a :       List[Any] = True	,_a :       Union[str, Any] = True	,):

        '''simple docstring'''




        A_						:  Any          =				self.get_auto_remove_tmp_dir("""./xxx"""	,after=lowercase__ )
        A_						:  str          =				f'\n            --model_name_or_path {model_name}\n            --dataset_name hf-internal-testing/librispeech_asr_dummy\n            --dataset_config_name clean\n            --train_split_name validation\n            --validation_split_name validation\n            --output_dir {output_dir}\n            --num_train_epochs {str(lowercase__ )}\n            --per_device_train_batch_size 2\n            --per_device_eval_batch_size 2\n            --evaluation_strategy steps\n            --learning_rate 5e-4\n            --warmup_steps 8\n            --orthography timit\n            --preprocessing_num_workers 1\n            --group_by_length\n            --freeze_feature_extractor\n            --report_to none\n            --save_steps 0\n            --eval_steps {eval_steps}\n            --report_to none\n        '.split()

        if fpaa:
              args.extend(["""--fp16"""] )

        # currently ds_config_wav2vec2_zero.json requires "zero_optimization.find_unused_parameters": true,
        # hence the separate config files
        A_						:  Dict          =				f'--deepspeed {self.test_file_dir_str}/ds_config_wav2vec2_{stage}.json'.split()
        A_						:  Any          =				[f'{self.examples_dir_str}/research_projects/wav2vec2/run_asr.py']
        A_						:  Tuple          =				self.get_launcher(lowercase__ )

        A_						:  List[Any]          =				launcher + script + args + ds_args
        # keep for quick debug
        # print(" ".join([f"\nPYTHONPATH={self.src_dir_str}"] +cmd)); die
        execute_subprocess_async(lowercase__	,env=self.get_env() )

        return output_dir






  def        _a							(							self :       Any	,_a :       Dict=False ):

        '''simple docstring'''




        A_						:  Tuple          =				min(2	,get_gpu_count() ) if distributed else 1
        return f'deepspeed --num_nodes 1 --num_gpus {num_gpus}'.split()




'''simple docstring'''


from ..utils import DummyObject, requires_backends



class 	__lowerCAmelCase		(							metaclass=__SCREAMING_SNAKE_CASE    ):


  '''simple docstring'''







  a_  					=							["""torch""", """torchsde"""]






  def __init__(							self :       Any	,*_a :       Union[str, Any]	,**_a :       Optional[int] ):

        '''simple docstring'''




        requires_backends(self	,["""torch""", """torchsde"""] )






  @classmethod
  def        _a							(							cls :       Optional[int]	,*_a :       List[Any]	,**_a :       Any ):

        '''simple docstring'''




        requires_backends(cls	,["""torch""", """torchsde"""] )






  @classmethod
  def        _a							(							cls :       List[Any]	,*_a :       Tuple	,**_a :       Union[str, Any] ):

        '''simple docstring'''




        requires_backends(cls	,["""torch""", """torchsde"""] )
