"""simple docstring"""



from collections import OrderedDict
from typing import Mapping

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


_UpperCamelCase         =		logging.get_logger(__name__)

_UpperCamelCase         =		{
    "google/mobilebert-uncased": "https://huggingface.co/google/mobilebert-uncased/resolve/main/config.json"
}
class 	__UpperCAmelCase						(__A    ):







			'''simple docstring'''
			_UpperCamelCase     :	List[Any]				    =							MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP
			_UpperCamelCase     :	Tuple				    =							'mobilebert'





			def __init__( self      ,			snake_case_=30_522      ,			snake_case_=512      ,			snake_case_=24      ,			snake_case_=4      ,			snake_case_=512      ,			snake_case_="relu"      ,			snake_case_=0.0      ,			snake_case_=0.1      ,			snake_case_=512      ,			snake_case_=2      ,			snake_case_=0.02      ,			snake_case_=1E-12      ,			snake_case_=0      ,			snake_case_=128      ,			snake_case_=True      ,			snake_case_=True      ,			snake_case_=128      ,			snake_case_=False      ,			snake_case_=True      ,			snake_case_=4      ,			snake_case_="no_norm"      ,			snake_case_=True      ,			snake_case_=None      ,			**snake_case_      ,			):







										'''simple docstring'''


										super().__init__(pad_token_id=snake_case_      ,			**snake_case_       )

										A__					:    List[str]														= vocab_size
										A__					:    Optional[int]														= hidden_size
										A__					:    List[Any]														= num_hidden_layers
										A__					:    List[str]														= num_attention_heads
										A__					:    Union[str, Any]														= hidden_act
										A__					:    Tuple														= intermediate_size
										A__					:    List[str]														= hidden_dropout_prob
										A__					:    int														= attention_probs_dropout_prob
										A__					:    List[str]														= max_position_embeddings
										A__					:    str														= type_vocab_size
										A__					:    str														= initializer_range
										A__					:    Dict														= layer_norm_eps
										A__					:    str														= embedding_size
										A__					:    Optional[int]														= trigram_input
										A__					:    List[Any]														= use_bottleneck
										A__					:    List[str]														= intra_bottleneck_size
										A__					:    Tuple														= use_bottleneck_attention
										A__					:    Any														= key_query_shared_bottleneck
										A__					:    int														= num_feedforward_networks
										A__					:    List[Any]														= normalization_type
										A__					:    Union[str, Any]														= classifier_activation

										if self.use_bottleneck:
																	A__					:    List[str]														= intra_bottleneck_size
										else:
																	A__					:    Optional[Any]														= hidden_size

										A__					:    Any														= classifier_dropout





class 	__UpperCAmelCase						(__A    ):







			'''simple docstring'''





			@property
			def 		lowerCamelCase				( self       ):







										'''simple docstring'''


										if self.task == "multiple-choice":
																	A__					:    int														= {0: """batch""", 1: """choice""", 2: """sequence"""}
										else:
																	A__					:    Tuple														= {0: """batch""", 1: """sequence"""}
										return OrderedDict(
										    [
										        ("""input_ids""", dynamic_axis),
										        ("""attention_mask""", dynamic_axis),
										        ("""token_type_ids""", 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 	__UpperCAmelCase						(unittest.TestCase    ):







			'''simple docstring'''





			def 		lowerCamelCase				( self       ):







										'''simple docstring'''


										A__					:    Optional[int]														= inspect.getfile(accelerate.test_utils       )
										A__					:    Tuple														= os.path.sep.join(mod_file.split(os.path.sep       )[:-1] + ["""scripts""", """test_sync.py"""]       )





			@require_cpu
			def 		lowerCamelCase				( self       ):







										'''simple docstring'''


										debug_launcher(test_sync.main      ,			num_processes=1       )





			@require_cpu
			def 		lowerCamelCase				( self       ):







										'''simple docstring'''


										debug_launcher(test_sync.main       )





			@require_single_gpu
			def 		lowerCamelCase				( self       ):







										'''simple docstring'''


										test_sync.main()





			@require_multi_gpu
			def 		lowerCamelCase				( self       ):







										'''simple docstring'''


										print(F'''Found {torch.cuda.device_count()} devices.'''       )
										A__					:    List[str]														= ["""torchrun""", F'''--nproc_per_node={torch.cuda.device_count()}''', self.test_file_path]
										with patch_environment(omp_num_threads=1       ):
																	execute_subprocess_async(snake_case_      ,			env=os.environ.copy()       )





