

# 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


_SCREAMING_SNAKE_CASE	:    str       =     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	:    Any       =     {'''base''': '''patrickvonplaten/wav2vec2_tiny_random''', '''robust''': '''patrickvonplaten/wav2vec2_tiny_random_robust'''}

_SCREAMING_SNAKE_CASE	:    List[str]       =     '''zero2'''
_SCREAMING_SNAKE_CASE	:    Optional[int]       =     '''zero3'''
_SCREAMING_SNAKE_CASE	:    Union[str, Any]       =     [ZEROa, ZEROa]
def 							UpperCAmelCase_  (		_A ,						_A ,						_A							):





     '''simple docstring'''




     SCREAMING_SNAKE_CASE__       =       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
_SCREAMING_SNAKE_CASE	:    Optional[Any]       =     list(itertools.product(stages, models.keys()))







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






  """simple docstring"""


  @parameterized.expand(__lowerCamelCase      ,  name_func=__lowerCamelCase   )
  def  lowercase_						(				self		:						Optional[Any]      ,  __lowerCamelCase		:						str      ,  __lowerCamelCase		:						Dict   )						->				Optional[Any]:
       self.run_and_check(
           stage=__lowerCamelCase      ,  model=__lowerCamelCase      ,  distributed=__lowerCamelCase      ,  fpaa=__lowerCamelCase      ,  )






  @require_torch_multi_gpu
  @parameterized.expand(__lowerCamelCase      ,  name_func=__lowerCamelCase   )
  def  lowercase_						(				self		:						Any      ,  __lowerCamelCase		:						Tuple      ,  __lowerCamelCase		:						int   )						->				List[Any]:
       self.run_and_check(
           stage=__lowerCamelCase      ,  model=__lowerCamelCase      ,  distributed=__lowerCamelCase      ,  fpaa=__lowerCamelCase      ,  )






  @parameterized.expand(__lowerCamelCase      ,  name_func=__lowerCamelCase   )
  def  lowercase_						(				self		:						Dict      ,  __lowerCamelCase		:						List[Any]      ,  __lowerCamelCase		:						List[Any]   )						->				List[Any]:
       self.run_and_check(
           stage=__lowerCamelCase      ,  model=__lowerCamelCase      ,  distributed=__lowerCamelCase      ,  fpaa=__lowerCamelCase      ,  )






  @require_torch_multi_gpu
  @parameterized.expand(__lowerCamelCase      ,  name_func=__lowerCamelCase   )
  def  lowercase_						(				self		:						Optional[Any]      ,  __lowerCamelCase		:						Tuple      ,  __lowerCamelCase		:						List[Any]   )						->				Any:
       self.run_and_check(
           stage=__lowerCamelCase      ,  model=__lowerCamelCase      ,  distributed=__lowerCamelCase      ,  fpaa=__lowerCamelCase      ,  )






  def  lowercase_						(				self		:						int      ,  __lowerCamelCase		:						int   )						->				Optional[Any]:
       pass






  def  lowercase_						(				self		:						Optional[Any]      ,  __lowerCamelCase		:						str      ,  __lowerCamelCase		:						str      ,  __lowerCamelCase		:						int = 10      ,  __lowerCamelCase		:						bool = True      ,  __lowerCamelCase		:						bool = True      ,  __lowerCamelCase		:						bool = True      ,  )						->				Union[str, Any]:
       SCREAMING_SNAKE_CASE__       =       models[model]

       SCREAMING_SNAKE_CASE__       =       self.run_trainer(
           stage=__lowerCamelCase      ,  model_name=__lowerCamelCase      ,  eval_steps=__lowerCamelCase      ,  num_train_epochs=1      ,  distributed=__lowerCamelCase      ,  fpaa=__lowerCamelCase      ,  )

       self.do_checks(__lowerCamelCase   )

       return output_dir






  def  lowercase_						(				self		:						Optional[int]      ,  __lowerCamelCase		:						str      ,  __lowerCamelCase		:						str      ,  __lowerCamelCase		:						int = 10      ,  __lowerCamelCase		:						int = 1      ,  __lowerCamelCase		:						bool = True      ,  __lowerCamelCase		:						bool = True      ,  )						->				str:
       SCREAMING_SNAKE_CASE__       =       self.get_auto_remove_tmp_dir('''./xxx'''      ,  after=__lowerCamelCase   )
       SCREAMING_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(__lowerCamelCase   )}
            --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
       SCREAMING_SNAKE_CASE__       =       f'''--deepspeed {self.test_file_dir_str}/ds_config_wav2vec2_{stage}.json'''.split()
       SCREAMING_SNAKE_CASE__       =       [f'''{self.examples_dir_str}/research_projects/wav2vec2/run_asr.py''']
       SCREAMING_SNAKE_CASE__       =       self.get_launcher(__lowerCamelCase   )

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

       return output_dir







  def  lowercase_						(				self		:						Tuple      ,  __lowerCamelCase		:						List[Any]=False   )						->				Optional[int]:
       SCREAMING_SNAKE_CASE__       =       min(2      ,  get_gpu_count()   ) if distributed else 1
       return f'''deepspeed --num_nodes 1 --num_gpus {num_gpus}'''.split()




# Function to print upper half of diamond (pyramid)


def    a      ( a	)     ->Optional[Any]:




			'''simple docstring'''


			for i in range(0		,						a	):
						for _ in range(0		,						n - i - 1	):  # printing spaces
									print(''' '''		,						end=''''''	)
						for _ in range(0		,						i + 1	):  # printing stars
									print('''* '''		,						end=''''''	)
						print()


def    a      ( a	)     ->Union[str, Any]:




			'''simple docstring'''


			for i in range(a		,						0		,						-1	):
						for _ in range(a		,						0		,						-1	):  # printing stars
									print('''* '''		,						end=''''''	)
						print()
						for _ in range(n - i + 1		,						0		,						-1	):  # printing spaces
									print(''' '''		,						end=''''''	)


def    a      ( a	)     ->Optional[int]:




			'''simple docstring'''


			if n <= 0:
						print('''       ...       ....        nothing printing :('''	)
						return
			floyd(a	)  # upper half
			reverse_floyd(a	)  # lower half


if __name__ == "__main__":
							print(R'| /\ | |- |  |-  |--| |\  /| |-')
							print(R'|/  \| |- |_ |_  |__| | \/ | |_')
							__lowerCAmelCase					   =       1
							while K:
														__lowerCAmelCase					   =       int(input('enter the number and , and see the magic : '))
														print()
														pretty_print(user_number)
														__lowerCAmelCase					   =       int(input('press 0 to exit... and 1 to continue...'))

							print('Good Bye...')