'''simple docstring'''

import copy
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
from ..auto import CONFIG_MAPPING


_UpperCAmelCase				: Dict							    =				logging.get_logger(__name__)

_UpperCAmelCase				: int							    =				{
    """microsoft/conditional-detr-resnet-50""": (
        """https://huggingface.co/microsoft/conditional-detr-resnet-50/resolve/main/config.json"""
    ),
}


class       a__				( __A      ):







				"""simple docstring"""



				__UpperCamelCase    :		List[str]	=	'conditional_detr'
				__UpperCamelCase    :		List[Any]	=	['past_key_values']
				__UpperCamelCase    :		Tuple	=	{
				    'hidden_size': 'd_model',
				    'num_attention_heads': 'encoder_attention_heads',
				}




				def __init__(self       ,			__lowercase=True       ,			__lowercase=None       ,			__lowercase=3       ,			__lowercase=3_00       ,			__lowercase=6       ,			__lowercase=20_48       ,			__lowercase=8       ,			__lowercase=6       ,			__lowercase=20_48       ,			__lowercase=8       ,			__lowercase=0.0       ,			__lowercase=0.0       ,			__lowercase=True       ,			__lowercase="relu"       ,			__lowercase=2_56       ,			__lowercase=0.1       ,			__lowercase=0.0       ,			__lowercase=0.0       ,			__lowercase=0.0_2       ,			__lowercase=1.0       ,			__lowercase=False       ,			__lowercase="sine"       ,			__lowercase="resnet50"       ,			__lowercase=True       ,			__lowercase=False       ,			__lowercase=2       ,			__lowercase=5       ,			__lowercase=2       ,			__lowercase=1       ,			__lowercase=1       ,			__lowercase=2       ,			__lowercase=5       ,			__lowercase=2       ,			__lowercase=0.2_5       ,			**__lowercase       ,			):
										if backbone_config is not None and use_timm_backbone:
																raise ValueError('''You can\'t specify both `backbone_config` and `use_timm_backbone`.'''		)

										if not use_timm_backbone:
																if backbone_config is None:
																						logger.info('''`backbone_config` is `None`. Initializing the config with the default `ResNet` backbone.'''		)
																						__lowerCAmelCase							       =				CONFIG_MAPPING['''resnet'''](out_features=['''stage4''']		)
																elif isinstance(__lowercase       ,			__lowercase		):
																						__lowerCAmelCase							       =				backbone_config.get('''model_type'''		)
																						__lowerCAmelCase							       =				CONFIG_MAPPING[backbone_model_type]
																						__lowerCAmelCase							       =				config_class.from_dict(__lowercase		)

										__lowerCAmelCase							       =				use_timm_backbone
										__lowerCAmelCase							       =				backbone_config
										__lowerCAmelCase							       =				num_channels
										__lowerCAmelCase							       =				num_queries
										__lowerCAmelCase							       =				d_model
										__lowerCAmelCase							       =				encoder_ffn_dim
										__lowerCAmelCase							       =				encoder_layers
										__lowerCAmelCase							       =				encoder_attention_heads
										__lowerCAmelCase							       =				decoder_ffn_dim
										__lowerCAmelCase							       =				decoder_layers
										__lowerCAmelCase							       =				decoder_attention_heads
										__lowerCAmelCase							       =				dropout
										__lowerCAmelCase							       =				attention_dropout
										__lowerCAmelCase							       =				activation_dropout
										__lowerCAmelCase							       =				activation_function
										__lowerCAmelCase							       =				init_std
										__lowerCAmelCase							       =				init_xavier_std
										__lowerCAmelCase							       =				encoder_layerdrop
										__lowerCAmelCase							       =				decoder_layerdrop
										__lowerCAmelCase							       =				encoder_layers
										__lowerCAmelCase							       =				auxiliary_loss
										__lowerCAmelCase							       =				position_embedding_type
										__lowerCAmelCase							       =				backbone
										__lowerCAmelCase							       =				use_pretrained_backbone
										__lowerCAmelCase							       =				dilation
										# Hungarian matcher
										__lowerCAmelCase							       =				class_cost
										__lowerCAmelCase							       =				bbox_cost
										__lowerCAmelCase							       =				giou_cost
										# Loss coefficients
										__lowerCAmelCase							       =				mask_loss_coefficient
										__lowerCAmelCase							       =				dice_loss_coefficient
										__lowerCAmelCase							       =				cls_loss_coefficient
										__lowerCAmelCase							       =				bbox_loss_coefficient
										__lowerCAmelCase							       =				giou_loss_coefficient
										__lowerCAmelCase							       =				focal_alpha
										super().__init__(is_encoder_decoder=__lowercase       ,			**__lowercase		)




				@property
				def 					_snake_case  (self		):
										return self.encoder_attention_heads




				@property
				def 					_snake_case  (self		):
										return self.d_model




				def 					_snake_case  (self		):
										__lowerCAmelCase							       =				copy.deepcopy(self.__dict__		)
										if self.backbone_config is not None:
																__lowerCAmelCase							       =				self.backbone_config.to_dict()
										__lowerCAmelCase							       =				self.__class__.model_type
										return output


class       a__				( __A      ):







				"""simple docstring"""



				__UpperCamelCase    :		List[str]	=	version.parse('1.11'      )




				@property
				def 					_snake_case  (self		):
										return OrderedDict(
										    [
										        ('''pixel_values''', {0: '''batch''', 1: '''num_channels''', 2: '''height''', 3: '''width'''}),
										        ('''pixel_mask''', {0: '''batch'''}),
										    ]		)




				@property
				def 					_snake_case  (self		):
										return 1e-5




				@property
				def 					_snake_case  (self		):
										return 12





'''simple docstring'''

import json
import sys

def 							__magic_name__(						lowerCamelCase,				lowerCamelCase):
						with open(lowerCamelCase,				encoding='''utf-8''') as f:
												__lowerCAmelCase							       =				json.load(lowerCamelCase)

						__lowerCAmelCase							       =				['''<details>''', '''<summary>Show updated benchmarks!</summary>''', ''' ''']

						for benchmark_name in sorted(lowerCamelCase):
												__lowerCAmelCase							       =				results[benchmark_name]

												__lowerCAmelCase							       =				benchmark_name.split('''/''')[-1]
												output_md.append(F"""### Benchmark: {benchmark_file_name}""")

												__lowerCAmelCase							       =				'''| metric |'''
												__lowerCAmelCase							       =				'''|--------|'''
												__lowerCAmelCase							       =				'''| new / old (diff) |'''
												for metric_name in sorted(lowerCamelCase):
																		__lowerCAmelCase							       =				benchmark_res[metric_name]
																		__lowerCAmelCase							       =				metric_vals['''new''']
																		__lowerCAmelCase							       =				metric_vals.get('''old''',				lowerCamelCase)
																		__lowerCAmelCase							       =				metric_vals.get('''diff''',				lowerCamelCase)

																		__lowerCAmelCase							       =				F""" {new_val:f}""" if isinstance(lowerCamelCase,				(int, float)) else '''None'''

																		if old_val is not None:
																								val_str += F""" / {old_val:f}""" if isinstance(lowerCamelCase,				(int, float)) else "None"
																		if dif_val is not None:
																								val_str += F""" ({dif_val:f})""" if isinstance(lowerCamelCase,				(int, float)) else "None"

																		title += " " + metric_name + " |"
																		lines += "---|"
																		value += val_str + " |"

												output_md += [title, lines, value, " "]

						output_md.append('''</details>''')

						with open(lowerCamelCase,				'''w''',				encoding='''utf-8''') as f:
												f.writelines('''\n'''.join(lowerCamelCase))


if __name__ == "__main__":
	_UpperCAmelCase				: str							    =				sys.argv[1]
	_UpperCAmelCase				: Optional[Any]							    =				sys.argv[2]

	format_json_to_md(input_json_file, output_md_file)

