



"""simple docstring"""







# 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


lowerCAmelCase_   						=   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)

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

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



def      __UpperCAmelCase      (    __lowerCamelCase						,     __lowerCamelCase						,     __lowerCamelCase	)							->      Union[str, Any]:
		# customize the test name generator function as we want both params to appear in the sub-test
		# name, as by default it shows only the first param
		lowercase__   :    Optional[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
lowerCAmelCase_   						=   list(itertools.product(stages, models.keys()))





@slow
@require_deepspeed
@require_torch_gpu
class        __A       (	A_    ):







		'''simple docstring'''





		@parameterized.expand(_snake_case			,name_func=_snake_case						)
		def 					UpperCAmelCase    (	self						:  str			,_snake_case						:  Tuple			,_snake_case						:  str						)					->		Union[str, Any]:






				"""simple docstring"""



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







		@require_torch_multi_gpu
		@parameterized.expand(_snake_case			,name_func=_snake_case						)
		def 					UpperCAmelCase    (	self						:  int			,_snake_case						:  Optional[int]			,_snake_case						:  Dict						)					->		List[str]:






				"""simple docstring"""



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







		@parameterized.expand(_snake_case			,name_func=_snake_case						)
		def 					UpperCAmelCase    (	self						:  int			,_snake_case						:  str			,_snake_case						:  List[Any]						)					->		Union[str, Any]:






				"""simple docstring"""



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







		@require_torch_multi_gpu
		@parameterized.expand(_snake_case			,name_func=_snake_case						)
		def 					UpperCAmelCase    (	self						:  List[str]			,_snake_case						:  str			,_snake_case						:  str						)					->		Optional[Any]:






				"""simple docstring"""



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







		def 					UpperCAmelCase    (	self						:  List[Any]			,_snake_case						:  Any						)					->		Any:






				"""simple docstring"""



				pass







		def 					UpperCAmelCase    (	self						:  Tuple			,_snake_case						:  str			,_snake_case						:  str			,_snake_case						:  int = 10			,_snake_case						:  bool = True			,_snake_case						:  bool = True			,_snake_case						:  bool = True			,)					->		Any:






				"""simple docstring"""



				lowercase__   :    Optional[int]				=			models[model]

				lowercase__   :    Optional[int]				=			self.run_trainer(
				    stage=_snake_case			,model_name=_snake_case			,eval_steps=_snake_case			,num_train_epochs=1			,distributed=_snake_case			,fpaa=_snake_case			,)

				self.do_checks(_snake_case						)

				return output_dir







		def 					UpperCAmelCase    (	self						:  Any			,_snake_case						:  str			,_snake_case						:  str			,_snake_case						:  int = 10			,_snake_case						:  int = 1			,_snake_case						:  bool = True			,_snake_case						:  bool = True			,)					->		List[str]:






				"""simple docstring"""



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

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

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

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

				return output_dir







		def 					UpperCAmelCase    (	self						:  Optional[Any]			,_snake_case						:  List[str]=False						)					->		Any:






				"""simple docstring"""



				lowercase__   :    Optional[int]				=			min(2			,get_gpu_count()						) if distributed else 1
				return f"""deepspeed --num_nodes 1 --num_gpus {num_gpus}""".split()





"""simple docstring"""







import unittest

from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class        __A       (	unittest.TestCase    ):







		'''simple docstring'''





		def 					UpperCAmelCase    (	self						:  Optional[int]						)					->		str:






				"""simple docstring"""



				debug_launcher(test_script.main						)







		def 					UpperCAmelCase    (	self						:  Dict						)					->		Tuple:






				"""simple docstring"""



				debug_launcher(test_ops.main						)
