




'''simple docstring'''


import inspect
import os
import unittest

import torch

import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
    execute_subprocess_async,
    require_cpu,
    require_huggingface_suite,
    require_multi_gpu,
    require_single_gpu,
)
from accelerate.utils import patch_environment






@require_huggingface_suite
class 		lowerCAmelCase_     (    unittest.TestCase				):







  '''simple docstring'''

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







       '''simple docstring'''



       A:						List[str]						=						inspect.getfile(accelerate.test_utils     )
       A:						Any						=						os.path.sep.join(
           mod_file.split(os.path.sep     )[:-1] + ['''scripts''', '''external_deps''', '''test_metrics.py''']     )

       from accelerate.test_utils.scripts.external_deps import test_metrics  # noqa: F401

       A:						int						=						test_metrics



  @require_cpu
  def  _snake_case			(      self							:				Any     )       ->						Tuple:







       '''simple docstring'''



       debug_launcher(self.test_metrics.main ,   num_processes=1     )



  @require_cpu
  def  _snake_case			(      self							:				Any     )       ->						Tuple:







       '''simple docstring'''



       debug_launcher(self.test_metrics.main     )



  @require_single_gpu
  def  _snake_case			(      self							:				int     )       ->						List[str]:







       '''simple docstring'''



       self.test_metrics.main()




  @require_multi_gpu
  def  _snake_case			(      self							:				int     )       ->						Tuple:







       '''simple docstring'''



       print(f"""Found {torch.cuda.device_count()} devices."""     )
       A:						Dict						=						['''torchrun''', f"""--nproc_per_node={torch.cuda.device_count()}""", self.test_file_path]
       with patch_environment(omp_num_threads=1     ):
            execute_subprocess_async(lowerCAmelCase__ ,   env=os.environ.copy()     )







from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


__a  :     Optional[int]       =  logging.get_logger(__name__)

__a  :     Tuple       =  {
    """facebook/data2vec-text-base""": """https://huggingface.co/data2vec/resolve/main/config.json""",
}




class    _UpperCamelCase      (						_UpperCAmelCase ):


			"""simple docstring"""






			__a  : Dict			 =						'''data2vec-text'''





			def __init__(   self      ,   lowerCAmelCase__=3_05_22      ,   lowerCAmelCase__=7_68      ,   lowerCAmelCase__=12      ,   lowerCAmelCase__=12      ,   lowerCAmelCase__=30_72      ,   lowerCAmelCase__="gelu"      ,   lowerCAmelCase__=0.1      ,   lowerCAmelCase__=0.1      ,   lowerCAmelCase__=5_12      ,   lowerCAmelCase__=2      ,   lowerCAmelCase__=0.02      ,   lowerCAmelCase__=1E-12      ,   lowerCAmelCase__=1      ,   lowerCAmelCase__=0      ,   lowerCAmelCase__=2      ,   lowerCAmelCase__="absolute"      ,   lowerCAmelCase__=True      ,   lowerCAmelCase__=None      ,   **lowerCAmelCase__      ,   )     ->					Any:

							'''simple docstring'''


							super().__init__(pad_token_id=lowerCAmelCase__      ,   bos_token_id=lowerCAmelCase__      ,   eos_token_id=lowerCAmelCase__      ,   **lowerCAmelCase__						)

							__lowercase 			=							vocab_size
							__lowercase 			=							hidden_size
							__lowercase 			=							num_hidden_layers
							__lowercase 			=							num_attention_heads
							__lowercase 			=							hidden_act
							__lowercase 			=							intermediate_size
							__lowercase 			=							hidden_dropout_prob
							__lowercase 			=							attention_probs_dropout_prob
							__lowercase 			=							max_position_embeddings
							__lowercase 			=							type_vocab_size
							__lowercase 			=							initializer_range
							__lowercase 			=							layer_norm_eps
							__lowercase 			=							position_embedding_type
							__lowercase 			=							use_cache
							__lowercase 			=							classifier_dropout




class    _UpperCamelCase      (						_UpperCAmelCase ):


			"""simple docstring"""






			@property
			def        _SCREAMING_SNAKE_CASE			(   self						)     ->					Mapping[str, Mapping[int, str]]:

							'''simple docstring'''


							if self.task == "multiple-choice":
											__lowercase 			=							{0: '''batch''', 1: '''choice''', 2: '''sequence'''}
							else:
											__lowercase 			=							{0: '''batch''', 1: '''sequence'''}
							return OrderedDict(
							    [
							        ('''input_ids''', dynamic_axis),
							        ('''attention_mask''', dynamic_axis),
							    ]						)