




import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..bit import BitConfig


lowercase__				:     str 		=						logging.get_logger(__name__)

lowercase__				:     Union[str, Any] 		=						{
    '''Intel/dpt-large''': '''https://huggingface.co/Intel/dpt-large/resolve/main/config.json''',
    # See all DPT models at https://huggingface.co/models?filter=dpt
}
class 		UpperCAmelCase   (				a_			):







						'''simple docstring'''





						lowerCAmelCase_     		=   '''dpt'''






						def __init__(						self							:     Tuple       ,	__lowercase							:     List[Any]=7_68       ,	__lowercase							:     List[Any]=12       ,	__lowercase							:     Optional[Any]=12       ,	__lowercase							:     List[Any]=30_72       ,	__lowercase							:     str="gelu"       ,	__lowercase							:     Dict=0.0       ,	__lowercase							:     Optional[Any]=0.0       ,	__lowercase							:     List[str]=0.02       ,	__lowercase							:     List[str]=1E-12       ,	__lowercase							:     Union[str, Any]=3_84       ,	__lowercase							:     Any=16       ,	__lowercase							:     Tuple=3       ,	__lowercase							:     List[str]=False       ,	__lowercase							:     Dict=True       ,	__lowercase							:     List[str]=[2, 5, 8, 11]       ,	__lowercase							:     Optional[Any]="project"       ,	__lowercase							:     Union[str, Any]=[4, 2, 1, 0.5]       ,	__lowercase							:     int=[96, 1_92, 3_84, 7_68]       ,	__lowercase							:     List[str]=2_56       ,	__lowercase							:     int=-1       ,	__lowercase							:     List[Any]=False       ,	__lowercase							:     List[Any]=True       ,	__lowercase							:     str=0.4       ,	__lowercase							:     Optional[Any]=2_55       ,	__lowercase							:     Optional[Any]=0.1       ,	__lowercase							:     List[Any]=[1, 10_24, 24, 24]       ,	__lowercase							:     int=[0, 1]       ,	__lowercase							:     Optional[int]=None       ,	**__lowercase							:     Optional[Any]       ,	):






							"""simple docstring"""






							super().__init__(**lowercase_						)

							snake_case_		    =     hidden_size
							snake_case_		    =     is_hybrid

							if self.is_hybrid:
								if backbone_config is None:
									logger.info("Initializing the config with a `BiT` backbone."						)
									snake_case_		    =     {
									    '''global_padding''': '''same''',
									    '''layer_type''': '''bottleneck''',
									    '''depths''': [3, 4, 9],
									    '''out_features''': ['''stage1''', '''stage2''', '''stage3'''],
									    '''embedding_dynamic_padding''': True,
									}
									snake_case_		    =     BitConfig(**lowercase_						)
								elif isinstance(lowercase_       ,	lowercase_						):
									logger.info("Initializing the config with a `BiT` backbone."						)
									snake_case_		    =     BitConfig(**lowercase_						)
								elif isinstance(lowercase_       ,	lowercase_						):
									snake_case_		    =     backbone_config
								else:
									raise ValueError(
									    f"backbone_config must be a dictionary or a `PretrainedConfig`, got {backbone_config.__class__}."						)

								snake_case_		    =     backbone_featmap_shape
								snake_case_		    =     neck_ignore_stages

								if readout_type != "project":
									raise ValueError("Readout type must be \'project\' when using `DPT-hybrid` mode."						)
							else:
								snake_case_		    =     None
								snake_case_		    =     None
								snake_case_		    =     []

							snake_case_		    =     num_hidden_layers
							snake_case_		    =     num_attention_heads
							snake_case_		    =     intermediate_size
							snake_case_		    =     hidden_act
							snake_case_		    =     hidden_dropout_prob
							snake_case_		    =     attention_probs_dropout_prob
							snake_case_		    =     initializer_range
							snake_case_		    =     layer_norm_eps
							snake_case_		    =     image_size
							snake_case_		    =     patch_size
							snake_case_		    =     num_channels
							snake_case_		    =     qkv_bias
							snake_case_		    =     backbone_out_indices
							if readout_type not in ["ignore", "add", "project"]:
								raise ValueError("Readout_type must be one of [\'ignore\', \'add\', \'project\']"						)
							snake_case_		    =     readout_type
							snake_case_		    =     reassemble_factors
							snake_case_		    =     neck_hidden_sizes
							snake_case_		    =     fusion_hidden_size
							snake_case_		    =     head_in_index
							snake_case_		    =     use_batch_norm_in_fusion_residual
							# auxiliary head attributes (semantic segmentation)
							snake_case_		    =     use_auxiliary_head
							snake_case_		    =     auxiliary_loss_weight
							snake_case_		    =     semantic_loss_ignore_index
							snake_case_		    =     semantic_classifier_dropout






						def        snake_case__						(						self							:     int						):






							"""simple docstring"""






							snake_case_		    =     copy.deepcopy(self.__dict__						)

							if output["backbone_config"] is not None:
								snake_case_		    =     self.backbone_config.to_dict()

							snake_case_		    =     self.__class__.model_type
							return output



"""simple docstring"""





# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import argparse
import os

from accelerate.test_utils import execute_subprocess_async

def   __SCREAMING_SNAKE_CASE  (      A_=None ):
	if subparsers is not None:
		lowerCAmelCase__	:						Optional[Any]  				=	subparsers.add_parser('''test''' )
	else:
		lowerCAmelCase__	:						List[str]  				=	argparse.ArgumentParser('''Accelerate test command''' )

	parser.add_argument(
	    '''--config_file'''						,     default=A_						,     help=(
	        '''The path to use to store the config file. Will default to a file named default_config.yaml in the cache '''
	        '''location, which is the content of the environment `HF_HOME` suffixed with \'accelerate\', or if you don\'t have '''
	        '''such an environment variable, your cache directory (\'~/.cache\' or the content of `XDG_CACHE_HOME`) suffixed '''
	        '''with \'huggingface\'.'''
	    )						,     )

	if subparsers is not None:
		parser.set_defaults(func=A_ )
	return parser

def   __SCREAMING_SNAKE_CASE  (      A_ ):
	lowerCAmelCase__	:						Optional[int]  				=	os.path.sep.join(__file__.split(os.path.sep )[:-2] + ['''test_utils''', '''scripts''', '''test_script.py'''] )

	if args.config_file is None:
		lowerCAmelCase__	:						Optional[Any]  				=	script_name
	else:
		lowerCAmelCase__	:						Any  				=	f'--config_file={args.config_file} {script_name}'

	lowerCAmelCase__	:						List[Any]  				=	['''accelerate-launch'''] + test_args.split()
	lowerCAmelCase__	:						int  				=	execute_subprocess_async(A_						,     env=os.environ.copy() )
	if result.returncode == 0:
		print('''Test is a success! You are ready for your distributed training!''' )

def   __SCREAMING_SNAKE_CASE  (      ):
	lowerCAmelCase__	:						Any  				=	test_command_parser()
	lowerCAmelCase__	:						List[Any]  				=	parser.parse_args()
	test_command(A_ )


if __name__ == "__main__":
							main()




