from collections import OrderedDict
from typing import Mapping

from packaging import version

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


__lowerCamelCase			: int							   =		logging.get_logger(__name__)

__lowerCamelCase			: List[Any]							   =		{
    '''facebook/deit-base-distilled-patch16-224''': (
        '''https://huggingface.co/facebook/deit-base-patch16-224/resolve/main/config.json'''
    ),
    # See all DeiT models at https://huggingface.co/models?filter=deit
}







class __snake_case				(						lowerCamelCase_		):
   lowerCAmelCase_														=							"deit"




   def __init__(    self			:				Union[str, Any]       ,	_lowercase			:				Dict=7_68       ,	_lowercase			:				Dict=12       ,	_lowercase			:				List[str]=12       ,	_lowercase			:				List[Any]=30_72       ,	_lowercase			:				Dict="gelu"       ,	_lowercase			:				int=0.0       ,	_lowercase			:				Dict=0.0       ,	_lowercase			:				Dict=0.02       ,	_lowercase			:				Optional[int]=1E-12       ,	_lowercase			:				Any=2_24       ,	_lowercase			:				List[str]=16       ,	_lowercase			:				Optional[Any]=3       ,	_lowercase			:				List[Any]=True       ,	_lowercase			:				List[str]=16       ,	**_lowercase			:				Optional[Any]       ,	):



     """simple docstring"""






     super().__init__(**_lowercase      )

     SCREAMING_SNAKE_CASE__										=      hidden_size
     SCREAMING_SNAKE_CASE__										=      num_hidden_layers
     SCREAMING_SNAKE_CASE__										=      num_attention_heads
     SCREAMING_SNAKE_CASE__										=      intermediate_size
     SCREAMING_SNAKE_CASE__										=      hidden_act
     SCREAMING_SNAKE_CASE__										=      hidden_dropout_prob
     SCREAMING_SNAKE_CASE__										=      attention_probs_dropout_prob
     SCREAMING_SNAKE_CASE__										=      initializer_range
     SCREAMING_SNAKE_CASE__										=      layer_norm_eps
     SCREAMING_SNAKE_CASE__										=      image_size
     SCREAMING_SNAKE_CASE__										=      patch_size
     SCREAMING_SNAKE_CASE__										=      num_channels
     SCREAMING_SNAKE_CASE__										=      qkv_bias
     SCREAMING_SNAKE_CASE__										=      encoder_stride







class __snake_case				(						lowerCamelCase_		):
   lowerCAmelCase_														=							version.parse("1.11"		)




   @property
   def 	__a						(    self			:				Dict      ):



     """simple docstring"""






     return OrderedDict(
         [
             ("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""}),
         ]      )




   @property
   def 	__a						(    self			:				Optional[Any]      ):



     """simple docstring"""






     return 1E-4

import unittest
from dataclasses import dataclass

import pytest

from accelerate.commands.config.config_args import SageMakerConfig
from accelerate.utils import ComputeEnvironment
from accelerate.utils.launch import _convert_nargs_to_dict







@dataclass
class __snake_case				(						lowerCamelCase_		):
   lowerCAmelCase_														=							ComputeEnvironment.AMAZON_SAGEMAKER
   lowerCAmelCase_														=							True
   lowerCAmelCase_														=							"ml.p3.2xlarge"
   lowerCAmelCase_														=							"accelerate_sagemaker_execution_role"
   lowerCAmelCase_														=							"hf-sm"
   lowerCAmelCase_														=							"us-east-1"
   lowerCAmelCase_														=							1
   lowerCAmelCase_														=							"accelerate-sagemaker-1"
   lowerCAmelCase_														=							"1.6"
   lowerCAmelCase_														=							"4.4"
   lowerCAmelCase_														=							"train.py"
   lowerCAmelCase_														=							[
       "--model_name_or_path",
       "bert",
       "--do_train",
       "False",
       "--epochs",
       "3",
       "--learning_rate",
       "5e-5",
       "--max_steps",
       "50.5",
   ]
   lowerCAmelCase_														=							[
       "--model_name_or_path",
       "bert",
       "--do_train",
       "--do_test",
       "False",
       "--do_predict",
       "--epochs",
       "3",
       "--learning_rate",
       "5e-5",
       "--max_steps",
       "50.5",
   ]







class __snake_case				(						unittest.TestCase		):




   def 	__a						(    self			:				List[Any]      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      _convert_nargs_to_dict(MockLaunchConfig.success_training_script_args      )
     assert isinstance(converted_args["""model_name_or_path"""]       ,	_lowercase      )
     assert isinstance(converted_args["""do_train"""]       ,	_lowercase      )
     assert isinstance(converted_args["""epochs"""]       ,	_lowercase      )
     assert isinstance(converted_args["""learning_rate"""]       ,	_lowercase      )
     assert isinstance(converted_args["""max_steps"""]       ,	_lowercase      )

     with pytest.raises(_lowercase      ):
       _convert_nargs_to_dict(MockLaunchConfig.fail_training_script_args      )
