






# XXX: we want transformers master here - in the absense of conftest manipulating sys.path:
# hack it in for now:
import sys
from pathlib import Path


UpperCAmelCase__							  =						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)

UpperCAmelCase__							  =						{"base": "patrickvonplaten/wav2vec2_tiny_random", "robust": "patrickvonplaten/wav2vec2_tiny_random_robust"}

UpperCAmelCase__							  =						"zero2"
UpperCAmelCase__							  =						"zero3"
UpperCAmelCase__							  =						[ZEROa, ZEROa]
def 		_a       ( a					:str      ,				a					:Tuple      ,				a					:Union[str, Any]					)				->     Optional[int]:
 a						    = parameterized.to_safe_name('''_'''.join(str(_A					) for x in param.args					)					)
 return F"""{func.__name__}_{param_based_name}"""


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






@slow
@require_deepspeed
@require_torch_gpu
class 						lowercase_   (      UpperCAmelCase__  ):






      '''simple docstring'''




      @parameterized.expand(__lowercase					,   name_func=__lowercase    )
      def  __lowerCAmelCase   ( self :		List[str]					,   __UpperCAmelCase :		Union[str, Any]					,   __UpperCAmelCase :		Union[str, Any]    )       ->List[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  __lowerCAmelCase   ( self :		List[str]					,   __UpperCAmelCase :		List[Any]					,   __UpperCAmelCase :		List[str]    )       ->List[str]:




       """simple docstring"""


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







      @parameterized.expand(__lowercase					,   name_func=__lowercase    )
      def  __lowerCAmelCase   ( self :		str					,   __UpperCAmelCase :		Optional[Any]					,   __UpperCAmelCase :		Union[str, Any]    )       ->List[Any]:




       """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  __lowerCAmelCase   ( self :		str					,   __UpperCAmelCase :		Optional[int]					,   __UpperCAmelCase :		str    )       ->Tuple:




       """simple docstring"""


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







      def  __lowerCAmelCase   ( self :		Tuple					,   __UpperCAmelCase :		Any    )       ->int:




       """simple docstring"""


       pass







      def  __lowerCAmelCase   ( self :		Optional[Any]					,   __UpperCAmelCase :		str					,   __UpperCAmelCase :		str					,   __UpperCAmelCase :		int = 10					,   __UpperCAmelCase :		bool = True					,   __UpperCAmelCase :		bool = True					,   __UpperCAmelCase :		bool = True					,   )       ->Any:




       """simple docstring"""


       a						    = models[model]

       a						    = 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  __lowerCAmelCase   ( self :		Tuple					,   __UpperCAmelCase :		str					,   __UpperCAmelCase :		str					,   __UpperCAmelCase :		int = 10					,   __UpperCAmelCase :		int = 1					,   __UpperCAmelCase :		bool = True					,   __UpperCAmelCase :		bool = True					,   )       ->int:




       """simple docstring"""


       a						    = self.get_auto_remove_tmp_dir('''./xxx'''					,   after=__lowercase    )
       a						    = 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						    = F"""--deepspeed {self.test_file_dir_str}/ds_config_wav2vec2_{stage}.json""".split()
       a						    = [F"""{self.examples_dir_str}/research_projects/wav2vec2/run_asr.py"""]
       a						    = self.get_launcher(__lowercase    )

       a						    = 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  __lowerCAmelCase   ( self :		Dict					,   __UpperCAmelCase :		Dict=False    )       ->str:




       """simple docstring"""


       a						    = min(2					,   get_gpu_count()    ) if distributed else 1
       return F"""deepspeed --num_nodes 1 --num_gpus {num_gpus}""".split()








from abc import ABC, abstractmethod
from argparse import ArgumentParser
class 						UpperCAmelCase  (							UpperCAmelCase__     ):







						'''simple docstring'''





						@staticmethod
						@abstractmethod
						def 			snake_case__		(		__lowercase				:	ArgumentParser		):






							"""simple docstring"""






							raise NotImplementedError()






						@abstractmethod
						def 			snake_case__		(		self				:	Optional[Any]		):






							"""simple docstring"""






							raise NotImplementedError()
