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__					:       str		=       logging.get_logger(__name__)

lowerCAmelCase__					:       Any		=       {
    '''MBZUAI/swiftformer-xs''': '''https://huggingface.co/MBZUAI/swiftformer-xs/resolve/main/config.json''',
}





class 			__snake_case  (      _lowerCamelCase     ):
					__lowerCamelCase	 =       "swiftformer"




					def __init__(       self   ,	__UpperCamelCase=3   ,	__UpperCamelCase=[3, 3, 6, 4]   ,	__UpperCamelCase=[48, 56, 112, 220]   ,	__UpperCamelCase=4   ,	__UpperCamelCase=[True, True, True, True]   ,	__UpperCamelCase="gelu"   ,	__UpperCamelCase=3   ,	__UpperCamelCase=2   ,	__UpperCamelCase=1   ,	__UpperCamelCase=0.0   ,	__UpperCamelCase=True   ,	__UpperCamelCase=1E-5   ,	__UpperCamelCase=1E-5   ,	**__UpperCamelCase   ,	)					->  str:



									'''simple docstring'''







									super().__init__(**__A		)
									snake_case__ :     Any 							=				num_channels
									snake_case__ :     Any 							=				depths
									snake_case__ :     List[str] 							=				embed_dims
									snake_case__ :     int 							=				mlp_ratio
									snake_case__ :     Any 							=				downsamples
									snake_case__ :     Union[str, Any] 							=				hidden_act
									snake_case__ :     Dict 							=				down_patch_size
									snake_case__ :     str 							=				down_stride
									snake_case__ :     Dict 							=				down_pad
									snake_case__ :     List[str] 							=				drop_path_rate
									snake_case__ :     Tuple 							=				use_layer_scale
									snake_case__ :     Optional[int] 							=				layer_scale_init_value
									snake_case__ :     Dict 							=				batch_norm_eps





class 			__snake_case  (      _lowerCamelCase     ):
					__lowerCamelCase	 =       version.parse("""1.11"""     )




					@property
					def       __a      (       self		)					->  Union[str, Any]:



									'''simple docstring'''







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




					@property
					def       __a      (       self		)					->  str:



									'''simple docstring'''







									return 1E-4



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 			__snake_case  (      unittest.TestCase     ):




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



									'''simple docstring'''







									snake_case__ :     List[Any] 							=				inspect.getfile(accelerate.test_utils		)
									snake_case__ :     Tuple 							=				os.path.sep.join(mod_file.split(os.path.sep		)[:-1] + ['scripts', 'test_sync.py']		)




					@require_cpu
					def       __a      (       self		)					->  int:



									'''simple docstring'''







									debug_launcher(test_sync.main   ,	num_processes=1		)




					@require_cpu
					def       __a      (       self		)					->  Dict:



									'''simple docstring'''







									debug_launcher(test_sync.main		)




					@require_single_gpu
					def       __a      (       self		)					->  int:



									'''simple docstring'''







									test_sync.main()




					@require_multi_gpu
					def       __a      (       self		)					->  str:



									'''simple docstring'''







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


