




import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List

from ..utils import logging


UpperCAmelCase_									=	logging.get_logger(__name__)




def 					lowerCamelCase__       (						A__       :					str=None  ,			A__       :					Optional[Any]=None	):





       '''simple docstring'''



       return field(default_factory=lambda: default  ,			metadata=__snake_case	)





@dataclass
class     lowerCamelCase__:
      UpperCAmelCase__      :	Tuple    		=   list_field(
          default=[] ,     metadata={
              'help': (
                  'Model checkpoints to be provided to the AutoModel classes. Leave blank to benchmark the base version'
                  ' of all available models'
              )
          } ,     )

      UpperCAmelCase__      :	Tuple    		=   list_field(
          default=[8] ,     metadata={'help': 'List of batch sizes for which memory and time performance will be evaluated'})

      UpperCAmelCase__      :	Optional[int]    		=   list_field(
          default=[8, 32, 128, 512] ,     metadata={'help': 'List of sequence lengths for which memory and time performance will be evaluated'} ,     )

      UpperCAmelCase__      :	Optional[int]    		=   field(
          default=__lowerCamelCase ,     metadata={'help': 'Whether to benchmark inference of model. Inference can be disabled via --no-inference.'} ,     )
      UpperCAmelCase__      :	Dict    		=   field(
          default=__lowerCamelCase ,     metadata={'help': 'Whether to run on available cuda devices. Cuda can be disabled via --no-cuda.'} ,     )
      UpperCAmelCase__      :	Dict    		=   field(
          default=__lowerCamelCase ,     metadata={'help': 'Whether to run on available tpu devices. TPU can be disabled via --no-tpu.'})
      UpperCAmelCase__      :	Dict    		=   field(default=__lowerCamelCase ,     metadata={'help': 'Use FP16 to accelerate inference.'})
      UpperCAmelCase__      :	int    		=   field(default=__lowerCamelCase ,     metadata={'help': 'Benchmark training of model'})
      UpperCAmelCase__      :	Any    		=   field(default=__lowerCamelCase ,     metadata={'help': 'Verbose memory tracing'})
      UpperCAmelCase__      :	str    		=   field(
          default=__lowerCamelCase ,     metadata={'help': 'Whether to perform speed measurements. Speed measurements can be disabled via --no-speed.'} ,     )
      UpperCAmelCase__      :	Any    		=   field(
          default=__lowerCamelCase ,     metadata={
              'help': 'Whether to perform memory measurements. Memory measurements can be disabled via --no-memory'
          } ,     )
      UpperCAmelCase__      :	int    		=   field(default=__lowerCamelCase ,     metadata={'help': 'Trace memory line by line'})
      UpperCAmelCase__      :	str    		=   field(default=__lowerCamelCase ,     metadata={'help': 'Save result to a CSV file'})
      UpperCAmelCase__      :	str    		=   field(default=__lowerCamelCase ,     metadata={'help': 'Save all print statements in a log file'})
      UpperCAmelCase__      :	Optional[int]    		=   field(default=__lowerCamelCase ,     metadata={'help': 'Whether to print environment information'})
      UpperCAmelCase__      :	str    		=   field(
          default=__lowerCamelCase ,     metadata={
              'help': (
                  'Whether to use multiprocessing for memory and speed measurement. It is highly recommended to use'
                  ' multiprocessing for accurate CPU and GPU memory measurements. This option should only be disabled'
                  ' for debugging / testing and on TPU.'
              )
          } ,     )
      UpperCAmelCase__      :	Tuple    		=   field(
          default=F'''inference_time_{round(time())}.csv''' ,     metadata={'help': 'CSV filename used if saving time results to csv.'} ,     )
      UpperCAmelCase__      :	str    		=   field(
          default=F'''inference_memory_{round(time())}.csv''' ,     metadata={'help': 'CSV filename used if saving memory results to csv.'} ,     )
      UpperCAmelCase__      :	Optional[int]    		=   field(
          default=F'''train_time_{round(time())}.csv''' ,     metadata={'help': 'CSV filename used if saving time results to csv for training.'} ,     )
      UpperCAmelCase__      :	Tuple    		=   field(
          default=F'''train_memory_{round(time())}.csv''' ,     metadata={'help': 'CSV filename used if saving memory results to csv for training.'} ,     )
      UpperCAmelCase__      :	Any    		=   field(
          default=F'''env_info_{round(time())}.csv''' ,     metadata={'help': 'CSV filename used if saving environment information.'} ,     )
      UpperCAmelCase__      :	Optional[Any]    		=   field(
          default=F'''log_{round(time())}.csv''' ,     metadata={'help': 'Log filename used if print statements are saved in log.'} ,     )
      UpperCAmelCase__      :	Optional[Any]    		=   field(default=3 ,     metadata={'help': 'Times an experiment will be run.'})
      UpperCAmelCase__      :	List[Any]    		=   field(
          default=__lowerCamelCase ,     metadata={
              'help': (
                  'Instead of loading the model as defined in `config.architectures` if exists, just load the pretrain'
                  ' model weights.'
              )
          } ,     )
      def 			lowerCAmelCase__						(				self: str   ):
             warnings.warn(
                 F'The class {self.__class__} is deprecated. Hugging Face Benchmarking utils'
                 """ are deprecated in general and it is advised to use external Benchmarking libraries """
                 """ to benchmark Transformer models."""    ,       __lowerCAmelCase    ,       )
      def 			lowerCAmelCase__						(				self: List[str]   ):
             return json.dumps(dataclasses.asdict(self   )    ,       indent=2   )
      @property
      def 			lowerCAmelCase__						(				self: List[Any]   ):







             if len(self.models   ) <= 0:
                    raise ValueError(
                        """Please make sure you provide at least one model name / model identifier, *e.g.* `--models"""
                        """ bert-base-cased` or `args.models = [\'bert-base-cased\']."""   )
             return self.models




      @property
      def 			lowerCAmelCase__						(				self: int   ):







             if not self.multi_process:
                    return False
             elif self.is_tpu:
                    logger.info("""Multiprocessing is currently not possible on TPU."""   )
                    return False
             else:
                    return True








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


_a 						=      logging.get_logger(__name__)

_a 						=      {
    "hustvl/yolos-small": "https://huggingface.co/hustvl/yolos-small/resolve/main/config.json",
    # See all YOLOS models at https://huggingface.co/models?filter=yolos
}






class 					__A    (    lowerCAmelCase ):

			'''simple docstring'''







			lowerCAmelCase_							     =						"""yolos"""





			def __init__(    self       ,  __lowerCAmelCase=7_6_8       ,  __lowerCAmelCase=1_2       ,  __lowerCAmelCase=1_2       ,  __lowerCAmelCase=3_0_7_2       ,  __lowerCAmelCase="gelu"       ,  __lowerCAmelCase=0.0       ,  __lowerCAmelCase=0.0       ,  __lowerCAmelCase=0.02       ,  __lowerCAmelCase=1E-12       ,  __lowerCAmelCase=[5_1_2, 8_6_4]       ,  __lowerCAmelCase=1_6       ,  __lowerCAmelCase=3       ,  __lowerCAmelCase=True       ,  __lowerCAmelCase=1_0_0       ,  __lowerCAmelCase=True       ,  __lowerCAmelCase=False       ,  __lowerCAmelCase=1       ,  __lowerCAmelCase=5       ,  __lowerCAmelCase=2       ,  __lowerCAmelCase=5       ,  __lowerCAmelCase=2       ,  __lowerCAmelCase=0.1       ,  **__lowerCAmelCase       ,  ):



				'''simple docstring'''







				super().__init__(**__lowerCAmelCase							)

				lowerCamelCase__								=		hidden_size
				lowerCamelCase__								=		num_hidden_layers
				lowerCamelCase__								=		num_attention_heads
				lowerCamelCase__								=		intermediate_size
				lowerCamelCase__								=		hidden_act
				lowerCamelCase__								=		hidden_dropout_prob
				lowerCamelCase__								=		attention_probs_dropout_prob
				lowerCamelCase__								=		initializer_range
				lowerCamelCase__								=		layer_norm_eps
				lowerCamelCase__								=		image_size
				lowerCamelCase__								=		patch_size
				lowerCamelCase__								=		num_channels
				lowerCamelCase__								=		qkv_bias
				lowerCamelCase__								=		num_detection_tokens
				lowerCamelCase__								=		use_mid_position_embeddings
				lowerCamelCase__								=		auxiliary_loss
				# Hungarian matcher
				lowerCamelCase__								=		class_cost
				lowerCamelCase__								=		bbox_cost
				lowerCamelCase__								=		giou_cost
				# Loss coefficients
				lowerCamelCase__								=		bbox_loss_coefficient
				lowerCamelCase__								=		giou_loss_coefficient
				lowerCamelCase__								=		eos_coefficient






class 					__A    (    lowerCAmelCase ):

			'''simple docstring'''







			lowerCAmelCase_							     =						version.parse("""1.11""" )





			@property
			def 		__lowerCamelCase				(    self							):



				'''simple docstring'''







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





			@property
			def 		__lowerCamelCase				(    self							):



				'''simple docstring'''







				return 1E-4





			@property
			def 		__lowerCamelCase				(    self							):



				'''simple docstring'''







				return 1_2



