





# 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


_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)

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

_snake_case           =			"""zero2"""
_snake_case           =			"""zero3"""
_snake_case           =			[ZEROa, ZEROa]


def _A       (   __magic_name__  , __magic_name__  , __magic_name__	):
   # 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__			       =  parameterized.to_safe_name("_".join(str(__magic_name__	) for x in param.args	)	)
   return f'''{func.__name__}_{param_based_name}'''


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







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







  @parameterized.expand(_lowercase   ,							name_func=_lowercase )
  def   UpperCAmelCase					(      self  :List[str]   ,							_lowercase  :Tuple   ,							_lowercase  :Optional[int] ):






     '''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   UpperCAmelCase					(      self  :Optional[int]   ,							_lowercase  :Any   ,							_lowercase  :Tuple ):






     '''simple docstring'''





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







  @parameterized.expand(_lowercase   ,							name_func=_lowercase )
  def   UpperCAmelCase					(      self  :Dict   ,							_lowercase  :List[Any]   ,							_lowercase  :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   UpperCAmelCase					(      self  :int   ,							_lowercase  :int   ,							_lowercase  :Optional[int] ):






     '''simple docstring'''





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







  def   UpperCAmelCase					(      self  :List[str]   ,							_lowercase  :Optional[Any] ):






     '''simple docstring'''





     pass







  def   UpperCAmelCase					(      self  :List[Any]   ,							_lowercase  :str   ,							_lowercase  :str   ,							_lowercase  :int = 10   ,							_lowercase  :bool = True   ,							_lowercase  :bool = True   ,							_lowercase  :bool = True   ,							):






     '''simple docstring'''





     lowercase__			       =  models[model]

     lowercase__			       =  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   UpperCAmelCase					(      self  :Optional[int]   ,							_lowercase  :str   ,							_lowercase  :str   ,							_lowercase  :int = 10   ,							_lowercase  :int = 1   ,							_lowercase  :bool = True   ,							_lowercase  :bool = True   ,							):






     '''simple docstring'''





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

     lowercase__			       =  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   UpperCAmelCase					(      self  :Any   ,							_lowercase  :Optional[Any]=False ):






     '''simple docstring'''





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













from __future__ import annotations


def _A       (   __magic_name__  , __magic_name__	):
   lowercase__			       =  []
   create_all_state(1  , __magic_name__  , __magic_name__  , []  , __magic_name__	)
   return result


def _A       (   __magic_name__  , __magic_name__  , __magic_name__  , __magic_name__  , __magic_name__  , ):
   if level == 0:
      total_list.append(current_list[:]	)
      return

   for i in range(__magic_name__  , total_number - level + 2	):
      current_list.append(__magic_name__	)
      create_all_state(i + 1  , __magic_name__  , level - 1  , __magic_name__  , __magic_name__	)
      current_list.pop()


def _A       (   __magic_name__	):
   for i in total_list:
      print(*__magic_name__	)


if __name__ == "__main__":
  _snake_case           =			4
  _snake_case           =			2
  _snake_case           =			generate_all_combinations(n, k)
  print_all_state(total_list)






