"""simple docstring"""
import sys
from pathlib import Path


SCREAMING_SNAKE_CASE__					  =     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)

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

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





def       lowerCAmelCase__			(	_UpperCamelCase				: Optional[int]       ,	_UpperCamelCase				: Optional[Any]       ,	_UpperCamelCase				: Optional[int]    )    -> Optional[int]:





						"""simple docstring"""






						snake_case	    =	parameterized.to_safe_name('_'.join(str(snake_case_    ) for x in param.args    )    )
						return f"""{func.__name__}_{param_based_name}"""


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



@slow
@require_deepspeed
@require_torch_gpu
class      lowerCAmelCase_			(	UpperCamelCase__    ):



				"""simple docstring"""

				@parameterized.expand(__a						,			name_func=__a			)
				def 						snake_case       ( self						,			lowerCAmelCase						,			lowerCAmelCase			):






										"""simple docstring"""

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

				@require_torch_multi_gpu
				@parameterized.expand(__a						,			name_func=__a			)
				def 						snake_case       ( self						,			lowerCAmelCase						,			lowerCAmelCase			):






										"""simple docstring"""

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

				@parameterized.expand(__a						,			name_func=__a			)
				def 						snake_case       ( self						,			lowerCAmelCase						,			lowerCAmelCase			):






										"""simple docstring"""

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

				@require_torch_multi_gpu
				@parameterized.expand(__a						,			name_func=__a			)
				def 						snake_case       ( self						,			lowerCAmelCase						,			lowerCAmelCase			):






										"""simple docstring"""

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

				def 						snake_case       ( self						,			lowerCAmelCase			):






										"""simple docstring"""

										pass

				def 						snake_case       ( self						,			lowerCAmelCase						,			lowerCAmelCase						,			lowerCAmelCase = 10						,			lowerCAmelCase = True						,			lowerCAmelCase = True						,			lowerCAmelCase = True						,			):






										"""simple docstring"""

										snake_case	    =	models[model]

										snake_case	    =	self.run_trainer(
										    stage=__a						,			model_name=__a						,			eval_steps=__a						,			num_train_epochs=1						,			distributed=__a						,			fpaa=__a						,			)

										self.do_checks(__a			)

										return output_dir

				def 						snake_case       ( self						,			lowerCAmelCase						,			lowerCAmelCase						,			lowerCAmelCase = 10						,			lowerCAmelCase = 1						,			lowerCAmelCase = True						,			lowerCAmelCase = True						,			):






										"""simple docstring"""

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

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

										return output_dir

				def 						snake_case       ( self						,			lowerCAmelCase=False			):






										"""simple docstring"""

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



'''simple docstring'''





def 	lowerCAmelCase_				(					snake_case_       : int					,    snake_case_       : int			)    ->      str:


     '''simple docstring'''




     if a < 0 or b < 0:
          raise ValueError("the value of both inputs must be positive"			)
     UpperCAmelCase_           =   str(bin(snake_case_			)			)[2:]  # remove the leading "0b"
     UpperCAmelCase_           =   str(bin(snake_case_			)			)[2:]
     UpperCAmelCase_           =   max(len(snake_case_			)					,    len(snake_case_			)			)
     return "0b" + "".join(
         str(int("1" in (char_a, char_b)			)			)
         for char_a, char_b in zip(a_binary.zfill(snake_case_			)					,    b_binary.zfill(snake_case_			)			)			)


if __name__ == "__main__":
    import doctest

    doctest.testmod()




