


'''simple docstring'''

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/table-transformer-detection""": (
        """https://huggingface.co/microsoft/table-transformer-detection/resolve/main/config.json"""
    ),
}


class       a__				( __A      ):







				"""simple docstring"""



				__UpperCamelCase    :		Any	=	'table-transformer'
				__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=1_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=1       ,			__lowercase=5       ,			__lowercase=2       ,			__lowercase=1       ,			__lowercase=1       ,			__lowercase=5       ,			__lowercase=2       ,			__lowercase=0.1       ,			**__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		)
																# set timm attributes to None
																__lowerCAmelCase       ,					__lowerCAmelCase       ,					__lowerCAmelCase							       =				None, None, None

										__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							       =				bbox_loss_coefficient
										__lowerCAmelCase							       =				giou_loss_coefficient
										__lowerCAmelCase							       =				eos_coefficient
										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


class       a__				( __A      ):







				"""simple docstring"""



				__UpperCamelCase    :		Tuple	=	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 sys

from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core


# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be checked before tokenizers

_UpperCAmelCase				: Tuple							    =				"""python tqdm regex requests packaging filelock numpy tokenizers""".split()
if sys.version_info < (3, 7):
	pkgs_to_check_at_runtime.append("""dataclasses""")
if sys.version_info < (3, 8):
	pkgs_to_check_at_runtime.append("""importlib_metadata""")

for pkg in pkgs_to_check_at_runtime:
	if pkg in deps:
		if pkg == "tokenizers":
			# must be loaded here, or else tqdm check may fail
			from .utils import is_tokenizers_available

			if not is_tokenizers_available():
				continue  # not required, check version only if installed

		require_version_core(deps[pkg])
	else:
		raise ValueError(f"""can't find {pkg} in {deps.keys()}, check dependency_versions_table.py""")

def 							__magic_name__(						lowerCamelCase,				lowerCamelCase=None):
						require_version(deps[pkg],				lowerCamelCase)

