import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING


SCREAMING_SNAKE_CASE			:						Optional[int]				  =		logging.get_logger(__name__)

SCREAMING_SNAKE_CASE			:						Tuple				  =		{
    """ut/deta""": """https://huggingface.co/ut/deta/resolve/main/config.json""",
}
class  A_			(							a_			):
  _SCREAMING_SNAKE_CASE     					=      """deta"""
  _SCREAMING_SNAKE_CASE     					=      {
      """hidden_size""": """d_model""",
      """num_attention_heads""": """encoder_attention_heads""",
  }

  def __init__(		self			:   str  ,				__SCREAMING_SNAKE_CASE			:   Optional[Any]=None  ,				__SCREAMING_SNAKE_CASE			:   int=9_00  ,				__SCREAMING_SNAKE_CASE			:   Union[str, Any]=20_48  ,				__SCREAMING_SNAKE_CASE			:   Dict=6  ,				__SCREAMING_SNAKE_CASE			:   Dict=20_48  ,				__SCREAMING_SNAKE_CASE			:   List[str]=8  ,				__SCREAMING_SNAKE_CASE			:   Optional[Any]=6  ,				__SCREAMING_SNAKE_CASE			:   Any=10_24  ,				__SCREAMING_SNAKE_CASE			:   Union[str, Any]=8  ,				__SCREAMING_SNAKE_CASE			:   Dict=0.0  ,				__SCREAMING_SNAKE_CASE			:   Tuple=True  ,				__SCREAMING_SNAKE_CASE			:   Optional[int]="relu"  ,				__SCREAMING_SNAKE_CASE			:   Tuple=2_56  ,				__SCREAMING_SNAKE_CASE			:   Any=0.1  ,				__SCREAMING_SNAKE_CASE			:   Dict=0.0  ,				__SCREAMING_SNAKE_CASE			:   Union[str, Any]=0.0  ,				__SCREAMING_SNAKE_CASE			:   int=0.02  ,				__SCREAMING_SNAKE_CASE			:   Any=1.0  ,				__SCREAMING_SNAKE_CASE			:   str=True  ,				__SCREAMING_SNAKE_CASE			:   Dict=False  ,				__SCREAMING_SNAKE_CASE			:   str="sine"  ,				__SCREAMING_SNAKE_CASE			:   Any=5  ,				__SCREAMING_SNAKE_CASE			:   int=4  ,				__SCREAMING_SNAKE_CASE			:   Dict=4  ,				__SCREAMING_SNAKE_CASE			:   Union[str, Any]=True  ,				__SCREAMING_SNAKE_CASE			:   Optional[int]=3_00  ,				__SCREAMING_SNAKE_CASE			:   List[Any]=True  ,				__SCREAMING_SNAKE_CASE			:   Any=True  ,				__SCREAMING_SNAKE_CASE			:   Tuple=1  ,				__SCREAMING_SNAKE_CASE			:   Any=5  ,				__SCREAMING_SNAKE_CASE			:   Optional[Any]=2  ,				__SCREAMING_SNAKE_CASE			:   Optional[int]=1  ,				__SCREAMING_SNAKE_CASE			:   Optional[Any]=1  ,				__SCREAMING_SNAKE_CASE			:   Tuple=5  ,				__SCREAMING_SNAKE_CASE			:   List[str]=2  ,				__SCREAMING_SNAKE_CASE			:   List[str]=0.1  ,				__SCREAMING_SNAKE_CASE			:   int=0.25  ,				**__SCREAMING_SNAKE_CASE			:   List[str]  ,				):
   if backbone_config is None:
    logger.info("`backbone_config` is `None`. Initializing the config with the default `ResNet` backbone."							)
    __a							=	CONFIG_MAPPING["resnet"](out_features=["stage2", "stage3", "stage4"]							)
   else:
    if isinstance(__SCREAMING_SNAKE_CASE  ,				__SCREAMING_SNAKE_CASE							):
     __a							=	backbone_config.pop("model_type"							)
     __a							=	CONFIG_MAPPING[backbone_model_type]
     __a							=	config_class.from_dict(__SCREAMING_SNAKE_CASE							)

   __a							=	backbone_config
   __a							=	num_queries
   __a							=	max_position_embeddings
   __a							=	d_model
   __a							=	encoder_ffn_dim
   __a							=	encoder_layers
   __a							=	encoder_attention_heads
   __a							=	decoder_ffn_dim
   __a							=	decoder_layers
   __a							=	decoder_attention_heads
   __a							=	dropout
   __a							=	attention_dropout
   __a							=	activation_dropout
   __a							=	activation_function
   __a							=	init_std
   __a							=	init_xavier_std
   __a							=	encoder_layerdrop
   __a							=	auxiliary_loss
   __a							=	position_embedding_type
   # deformable attributes
   __a							=	num_feature_levels
   __a							=	encoder_n_points
   __a							=	decoder_n_points
   __a							=	two_stage
   __a							=	two_stage_num_proposals
   __a							=	with_box_refine
   __a							=	assign_first_stage
   if two_stage is True and with_box_refine is False:
    raise ValueError("If two_stage is True, with_box_refine must be True."							)
   # Hungarian matcher
   __a							=	class_cost
   __a							=	bbox_cost
   __a							=	giou_cost
   # Loss coefficients
   __a							=	mask_loss_coefficient
   __a							=	dice_loss_coefficient
   __a							=	bbox_loss_coefficient
   __a							=	giou_loss_coefficient
   __a							=	eos_coefficient
   __a							=	focal_alpha
   super().__init__(is_encoder_decoder=__SCREAMING_SNAKE_CASE  ,				**__SCREAMING_SNAKE_CASE							)

  @property
  def 		_UpperCAmelCase (		self			:   Dict							):
   return self.encoder_attention_heads

  @property
  def 		_UpperCAmelCase (		self			:   Tuple							):
   return self.d_model

  def 		_UpperCAmelCase (		self			:   Dict							):
   __a							=	copy.deepcopy(self.__dict__							)
   __a							=	self.backbone_config.to_dict()
   __a							=	self.__class__.model_type
   return output



# 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.

from argparse import ArgumentParser

from accelerate.commands.config import get_config_parser
from accelerate.commands.env import env_command_parser
from accelerate.commands.launch import launch_command_parser
from accelerate.commands.test import test_command_parser
from accelerate.commands.tpu import tpu_command_parser



def 	__A		(      ):



 """simple docstring"""


 __a							=	ArgumentParser("Accelerate CLI tool"				,					usage="accelerate <command> [<args>]"				,					allow_abbrev=_A       )
 __a							=	parser.add_subparsers(help="accelerate command helpers"       )

 # Register commands
 get_config_parser(subparsers=_A       )
 env_command_parser(subparsers=_A       )
 launch_command_parser(subparsers=_A       )
 tpu_command_parser(subparsers=_A       )
 test_command_parser(subparsers=_A       )

 # Let's go
 __a							=	parser.parse_args()

 if not hasattr(_A				,					"func"       ):
  parser.print_help()
  exit(1       )

 # Run
 args.func(_A       )


if __name__ == "__main__":
  main()


