


'''simple docstring'''







from collections import OrderedDict
from typing import Mapping

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


A__:   Tuple    =	logging.get_logger(__name__)

A__:   str    =	{
    '''flaubert/flaubert_small_cased''': '''https://huggingface.co/flaubert/flaubert_small_cased/resolve/main/config.json''',
    '''flaubert/flaubert_base_uncased''': '''https://huggingface.co/flaubert/flaubert_base_uncased/resolve/main/config.json''',
    '''flaubert/flaubert_base_cased''': '''https://huggingface.co/flaubert/flaubert_base_cased/resolve/main/config.json''',
    '''flaubert/flaubert_large_cased''': '''https://huggingface.co/flaubert/flaubert_large_cased/resolve/main/config.json''',
}







class A__	(						UpperCAmelCase__				):
      __UpperCamelCase	:  List[str]     	=							"flaubert"
      __UpperCamelCase	:  Optional[int]     	=							{
          "hidden_size": "emb_dim",
          "num_attention_heads": "n_heads",
          "num_hidden_layers": "n_layers",
          "n_words": "vocab_size",  # For backward compatibility
      }






      def __init__(			self      :int					,						SCREAMING_SNAKE_CASE      :Union[str, Any]=False					,						SCREAMING_SNAKE_CASE      :List[Any]=0.0					,						SCREAMING_SNAKE_CASE      :Optional[int]=3_0_1_4_5					,						SCREAMING_SNAKE_CASE      :Optional[Any]=2_0_4_8					,						SCREAMING_SNAKE_CASE      :int=1_2					,						SCREAMING_SNAKE_CASE      :Optional[int]=1_6					,						SCREAMING_SNAKE_CASE      :List[Any]=0.1					,						SCREAMING_SNAKE_CASE      :Any=0.1					,						SCREAMING_SNAKE_CASE      :List[str]=True					,						SCREAMING_SNAKE_CASE      :Union[str, Any]=False					,						SCREAMING_SNAKE_CASE      :List[Any]=False					,						SCREAMING_SNAKE_CASE      :List[Any]=False					,						SCREAMING_SNAKE_CASE      :int=1					,						SCREAMING_SNAKE_CASE      :List[str]=True					,						SCREAMING_SNAKE_CASE      :Any=5_1_2					,						SCREAMING_SNAKE_CASE      :Dict=2_0_4_8**-0.5					,						SCREAMING_SNAKE_CASE      :Dict=1e-12					,						SCREAMING_SNAKE_CASE      :Union[str, Any]=0.02					,						SCREAMING_SNAKE_CASE      :str=0					,						SCREAMING_SNAKE_CASE      :List[str]=1					,						SCREAMING_SNAKE_CASE      :str=2					,						SCREAMING_SNAKE_CASE      :int=3					,						SCREAMING_SNAKE_CASE      :Optional[Any]=5					,						SCREAMING_SNAKE_CASE      :Union[str, Any]=True					,						SCREAMING_SNAKE_CASE      :Tuple="first"					,						SCREAMING_SNAKE_CASE      :int=True					,						SCREAMING_SNAKE_CASE      :Optional[int]=None					,						SCREAMING_SNAKE_CASE      :Dict=True					,						SCREAMING_SNAKE_CASE      :Optional[Any]=0.1					,						SCREAMING_SNAKE_CASE      :Dict=5					,						SCREAMING_SNAKE_CASE      :List[str]=5					,						SCREAMING_SNAKE_CASE      :Optional[int]=0					,						SCREAMING_SNAKE_CASE      :str=0					,						SCREAMING_SNAKE_CASE      :List[Any]=2					,						SCREAMING_SNAKE_CASE      :Union[str, Any]=0					,						**SCREAMING_SNAKE_CASE      :List[str]					,						)	-> List[str]:




             '''simple docstring'''
             _a   :			Optional[int]					 =pre_norm
             _a   :			Union[str, Any]					 =layerdrop
             _a   :			str					 =vocab_size
             _a   :			List[str]					 =emb_dim
             _a   :			List[str]					 =n_layers
             _a   :			List[Any]					 =n_heads
             _a   :			str					 =dropout
             _a   :			Optional[Any]					 =attention_dropout
             _a   :			List[Any]					 =gelu_activation
             _a   :			str					 =sinusoidal_embeddings
             _a   :			List[str]					 =causal
             _a   :			Optional[int]					 =asm
             _a   :			Dict					 =n_langs
             _a   :			Union[str, Any]					 =use_lang_emb
             _a   :			Dict					 =layer_norm_eps
             _a   :			Optional[Any]					 =bos_index
             _a   :			int					 =eos_index
             _a   :			Dict					 =pad_index
             _a   :			Tuple					 =unk_index
             _a   :			Union[str, Any]					 =mask_index
             _a   :			List[str]					 =is_encoder
             _a   :			Tuple					 =max_position_embeddings
             _a   :			Tuple					 =embed_init_std
             _a   :			List[str]					 =init_std
             _a   :			List[str]					 =summary_type
             _a   :			Any					 =summary_use_proj
             _a   :			Dict					 =summary_activation
             _a   :			Dict					 =summary_proj_to_labels
             _a   :			str					 =summary_first_dropout
             _a   :			Optional[int]					 =start_n_top
             _a   :			Optional[int]					 =end_n_top
             _a   :			int					 =mask_token_id
             _a   :			Dict					 =lang_id

             if "n_words" in kwargs:
                    _a   :			Optional[int]					 =kwargs["""n_words"""]

             super().__init__(pad_token_id=SCREAMING_SNAKE_CASE					,						bos_token_id=SCREAMING_SNAKE_CASE					,						**SCREAMING_SNAKE_CASE     )







class A__	(						UpperCAmelCase__				):






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




             '''simple docstring'''
             if self.task == "multiple-choice":
                    _a   :			List[str]					 ={0: """batch""", 1: """choice""", 2: """sequence"""}
             else:
                    _a   :			Optional[int]					 ={0: """batch""", 1: """sequence"""}
             return OrderedDict(
                 [
                     ("""input_ids""", dynamic_axis),
                     ("""attention_mask""", dynamic_axis),
                 ]     )






'''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_multi_gpu,
    require_single_gpu,
    test_sync,
)
from accelerate.utils import patch_environment







class A__	(						unittest.TestCase				):






      def __UpperCAmelCase	(			self      :List[Any]     )	-> List[str]:




             '''simple docstring'''
             _a   :			Union[str, Any]					 =inspect.getfile(accelerate.test_utils     )
             _a   :			Any					 =os.path.sep.join(mod_file.split(os.path.sep     )[:-1] + ["""scripts""", """test_sync.py"""]     )






      @require_cpu
      def __UpperCAmelCase	(			self      :List[str]     )	-> Optional[Any]:




             '''simple docstring'''
             debug_launcher(test_sync.main					,						num_processes=1     )






      @require_cpu
      def __UpperCAmelCase	(			self      :int     )	-> Union[str, Any]:




             '''simple docstring'''
             debug_launcher(test_sync.main     )






      @require_single_gpu
      def __UpperCAmelCase	(			self      :Any     )	-> Optional[int]:




             '''simple docstring'''
             test_sync.main()






      @require_multi_gpu
      def __UpperCAmelCase	(			self      :Optional[Any]     )	-> int:




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


