'''simple docstring'''




import copy
from collections import OrderedDict
from typing import Dict, Mapping

from packaging import version

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


__lowercase        =    logging.get_logger(__name__)

__lowercase        =    {
    '''facebook/detr-resnet-50''': '''https://huggingface.co/facebook/detr-resnet-50/resolve/main/config.json''',
    # See all DETR models at https://huggingface.co/models?filter=detr
}






class 							a__(   lowerCAmelCase__      ):


			'''simple docstring'''






			UpperCAmelCase_     :	Dict						=			'''detr'''
			UpperCAmelCase_     :	List[str]						=			['''past_key_values''']
			UpperCAmelCase_     :	List[Any]						=			{
			    '''hidden_size''': '''d_model''',
			    '''num_attention_heads''': '''encoder_attention_heads''',
			}



			def __init__(  self			,       __lowerCAmelCase=True			,       __lowerCAmelCase=None			,       __lowerCAmelCase=3			,       __lowerCAmelCase=100			,       __lowerCAmelCase=6			,       __lowerCAmelCase=2048			,       __lowerCAmelCase=8			,       __lowerCAmelCase=6			,       __lowerCAmelCase=2048			,       __lowerCAmelCase=8			,       __lowerCAmelCase=0.0			,       __lowerCAmelCase=0.0			,       __lowerCAmelCase=True			,       __lowerCAmelCase="relu"			,       __lowerCAmelCase=256			,       __lowerCAmelCase=0.1			,       __lowerCAmelCase=0.0			,       __lowerCAmelCase=0.0			,       __lowerCAmelCase=0.02			,       __lowerCAmelCase=1.0			,       __lowerCAmelCase=False			,       __lowerCAmelCase="sine"			,       __lowerCAmelCase="resnet50"			,       __lowerCAmelCase=True			,       __lowerCAmelCase=False			,       __lowerCAmelCase=1			,       __lowerCAmelCase=5			,       __lowerCAmelCase=2			,       __lowerCAmelCase=1			,       __lowerCAmelCase=1			,       __lowerCAmelCase=5			,       __lowerCAmelCase=2			,       __lowerCAmelCase=0.1			,       **__lowerCAmelCase			,       ):




					"""simple docstring"""


					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(__lowerCAmelCase			,       __lowerCAmelCase):
									lowerCAmelCase     =    backbone_config.get("""model_type""")
									lowerCAmelCase     =    CONFIG_MAPPING[backbone_model_type]
									lowerCAmelCase     =    config_class.from_dict(__lowerCAmelCase)
							# 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=__lowerCAmelCase			,       **__lowerCAmelCase)



			@property
			def 				a_			(  self):




					"""simple docstring"""


					return self.encoder_attention_heads



			@property
			def 				a_			(  self):




					"""simple docstring"""


					return self.d_model



			@classmethod
			def 				a_			(  cls			,       __lowerCAmelCase			,       **__lowerCAmelCase):




					"""simple docstring"""


					return cls(backbone_config=__lowerCAmelCase			,       **__lowerCAmelCase)







			def 				a_			(  self):




					"""simple docstring"""


					lowerCAmelCase     =    copy.deepcopy(self.__dict__)
					if output["backbone_config"] is not None:
							lowerCAmelCase     =    self.backbone_config.to_dict()
					lowerCAmelCase     =    self.__class__.model_type
					return output







class 							a__(   lowerCAmelCase__      ):


			'''simple docstring'''






			UpperCAmelCase_     :	int						=			version.parse('''1.11'''      )



			@property
			def 				a_			(  self):




					"""simple docstring"""


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



			@property
			def 				a_			(  self):




					"""simple docstring"""


					return 1E-5







			@property
			def 				a_			(  self):




					"""simple docstring"""


					return 12





'''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.

from pathlib import Path

import torch

from ...utils import is_npu_available, is_xpu_available
from .config_args import ClusterConfig, default_json_config_file
from .config_utils import SubcommandHelpFormatter


__lowercase        =    '''Create a default config file for Accelerate with only a few flags set.'''






def 							snake_case__				(     _A:   Dict="no" ,  _A:   str = default_json_config_file ,  _A:   bool = False					)       ->      List[str]:

		'''simple docstring'''


		lowerCAmelCase     =    Path(_A					)
		path.parent.mkdir(parents=_A ,  exist_ok=_A					)
		if path.exists():
				print(
				    f"Configuration already exists at {save_location}, will not override. Run `accelerate config` manually or pass a different `save_location`."					)
				return False
		lowerCAmelCase     =    mixed_precision.lower()
		if mixed_precision not in ["no", "fp16", "bf16", "fp8"]:
				raise ValueError(
				    f"`mixed_precision` should be one of 'no', 'fp16', 'bf16', or 'fp8'. Received {mixed_precision}"					)
		lowerCAmelCase     =    {
		    """compute_environment""": """LOCAL_MACHINE""",
		    """mixed_precision""": mixed_precision,
		}
		if torch.cuda.is_available():
				lowerCAmelCase     =    torch.cuda.device_count()
				lowerCAmelCase     =    num_gpus
				lowerCAmelCase     =    False
				if num_gpus > 1:
						lowerCAmelCase     =    """MULTI_GPU"""
				else:
						lowerCAmelCase     =    """NO"""
		elif is_xpu_available() and use_xpu:
				lowerCAmelCase     =    torch.xpu.device_count()
				lowerCAmelCase     =    num_xpus
				lowerCAmelCase     =    False
				if num_xpus > 1:
						lowerCAmelCase     =    """MULTI_XPU"""
				else:
						lowerCAmelCase     =    """NO"""
		elif is_npu_available():
				lowerCAmelCase     =    torch.npu.device_count()
				lowerCAmelCase     =    num_npus
				lowerCAmelCase     =    False
				if num_npus > 1:
						lowerCAmelCase     =    """MULTI_NPU"""
				else:
						lowerCAmelCase     =    """NO"""
		else:
				lowerCAmelCase     =    0
				lowerCAmelCase     =    True
				lowerCAmelCase     =    1
				lowerCAmelCase     =    """NO"""
		lowerCAmelCase     =    ClusterConfig(**_A					)
		config.to_json_file(_A					)
		return path






def 							snake_case__				(     _A:   str ,  _A:   Any					)       ->      Optional[Any]:

		'''simple docstring'''


		lowerCAmelCase     =    parser.add_parser("""default""" ,  parents=_A ,  help=_A ,  formatter_class=_A					)
		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'."""
		    ) ,  dest="""save_location""" ,  )

		parser.add_argument(
		    """--mixed_precision""" ,  choices=["""no""", """fp16""", """bf16"""] ,  type=_A ,  help="""Whether or not to use mixed precision training. """
		    """Choose between FP16 and BF16 (bfloat16) training. """
		    """BF16 training is only supported on Nvidia Ampere GPUs and PyTorch 1.10 or later.""" ,  default="""no""" ,  )
		parser.set_defaults(func=_A					)
		return parser






def 							snake_case__				(     _A:   Optional[int]					)       ->      Optional[int]:

		'''simple docstring'''


		lowerCAmelCase     =    write_basic_config(args.mixed_precision ,  args.save_location					)
		if config_file:
				print(f"accelerate configuration saved at {config_file}"					)




