


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


A      :    Tuple		=					logging.get_logger(__name__)

A      :    Tuple		=					{
    "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 			_lowercase (							lowercase__):


       """simple docstring"""




       A__											=			"detr"
       A__											=			["past_key_values"]
       A__											=			{
           "hidden_size": "d_model",
           "num_attention_heads": "encoder_attention_heads",
       }





       def __init__(   self							:			Tuple					,      __lowerCamelCase							:			Optional[int]=True					,      __lowerCamelCase							:			List[str]=None					,      __lowerCamelCase							:			Dict=3					,      __lowerCamelCase							:			Union[str, Any]=100					,      __lowerCamelCase							:			Optional[int]=6					,      __lowerCamelCase							:			Union[str, Any]=2048					,      __lowerCamelCase							:			Optional[int]=8					,      __lowerCamelCase							:			str=6					,      __lowerCamelCase							:			Optional[int]=2048					,      __lowerCamelCase							:			str=8					,      __lowerCamelCase							:			Optional[int]=0.0					,      __lowerCamelCase							:			Union[str, Any]=0.0					,      __lowerCamelCase							:			Dict=True					,      __lowerCamelCase							:			Optional[int]="relu"					,      __lowerCamelCase							:			Any=256					,      __lowerCamelCase							:			str=0.1					,      __lowerCamelCase							:			str=0.0					,      __lowerCamelCase							:			Dict=0.0					,      __lowerCamelCase							:			Dict=0.0_2					,      __lowerCamelCase							:			Tuple=1.0					,      __lowerCamelCase							:			Tuple=False					,      __lowerCamelCase							:			Optional[Any]="sine"					,      __lowerCamelCase							:			int="resnet50"					,      __lowerCamelCase							:			str=True					,      __lowerCamelCase							:			Any=False					,      __lowerCamelCase							:			List[str]=1					,      __lowerCamelCase							:			List[Any]=5					,      __lowerCamelCase							:			List[Any]=2					,      __lowerCamelCase							:			Union[str, Any]=1					,      __lowerCamelCase							:			Union[str, Any]=1					,      __lowerCamelCase							:			Optional[Any]=5					,      __lowerCamelCase							:			Dict=2					,      __lowerCamelCase							:			Any=0.1					,      **__lowerCamelCase							:			List[str]					,      ):


             '''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__		:				Any    =  CONFIG_MAPPING["resnet"](out_features=["stage4"]       )
                   elif isinstance(__lowerCamelCase					,      __lowerCamelCase       ):
                         lowerCamelCase__		:				List[Any]    =  backbone_config.get("model_type"       )
                         lowerCamelCase__		:				Union[str, Any]    =  CONFIG_MAPPING[backbone_model_type]
                         lowerCamelCase__		:				int    =  config_class.from_dict(__lowerCamelCase       )
                   # set timm attributes to None
                   lowerCamelCase__    ,   lowerCamelCase__    ,   lowerCamelCase__		:				Optional[Any]    =  None, None, None

             lowerCamelCase__		:				str    =  use_timm_backbone
             lowerCamelCase__		:				List[Any]    =  backbone_config
             lowerCamelCase__		:				Any    =  num_channels
             lowerCamelCase__		:				Tuple    =  num_queries
             lowerCamelCase__		:				List[str]    =  d_model
             lowerCamelCase__		:				Optional[Any]    =  encoder_ffn_dim
             lowerCamelCase__		:				Any    =  encoder_layers
             lowerCamelCase__		:				Union[str, Any]    =  encoder_attention_heads
             lowerCamelCase__		:				Optional[int]    =  decoder_ffn_dim
             lowerCamelCase__		:				Tuple    =  decoder_layers
             lowerCamelCase__		:				Optional[Any]    =  decoder_attention_heads
             lowerCamelCase__		:				List[Any]    =  dropout
             lowerCamelCase__		:				Optional[int]    =  attention_dropout
             lowerCamelCase__		:				List[str]    =  activation_dropout
             lowerCamelCase__		:				int    =  activation_function
             lowerCamelCase__		:				int    =  init_std
             lowerCamelCase__		:				int    =  init_xavier_std
             lowerCamelCase__		:				Optional[Any]    =  encoder_layerdrop
             lowerCamelCase__		:				List[Any]    =  decoder_layerdrop
             lowerCamelCase__		:				int    =  encoder_layers
             lowerCamelCase__		:				Optional[Any]    =  auxiliary_loss
             lowerCamelCase__		:				List[Any]    =  position_embedding_type
             lowerCamelCase__		:				Tuple    =  backbone
             lowerCamelCase__		:				Optional[Any]    =  use_pretrained_backbone
             lowerCamelCase__		:				str    =  dilation
             # Hungarian matcher
             lowerCamelCase__		:				List[str]    =  class_cost
             lowerCamelCase__		:				List[str]    =  bbox_cost
             lowerCamelCase__		:				str    =  giou_cost
             # Loss coefficients
             lowerCamelCase__		:				Optional[Any]    =  mask_loss_coefficient
             lowerCamelCase__		:				Optional[int]    =  dice_loss_coefficient
             lowerCamelCase__		:				List[str]    =  bbox_loss_coefficient
             lowerCamelCase__		:				Tuple    =  giou_loss_coefficient
             lowerCamelCase__		:				Any    =  eos_coefficient
             super().__init__(is_encoder_decoder=__lowerCamelCase					,      **__lowerCamelCase       )





       @property
       def 						lowerCAmelCase     (   self							:			str       ):


             '''simple docstring'''



             return self.encoder_attention_heads





       @property
       def 						lowerCAmelCase     (   self							:			Optional[Any]       ):


             '''simple docstring'''



             return self.d_model





       @classmethod
       def 						lowerCAmelCase     (   cls							:			List[str]					,      __lowerCamelCase							:			PretrainedConfig					,      **__lowerCamelCase							:			List[Any]       ):


             '''simple docstring'''



             return cls(backbone_config=__lowerCamelCase					,      **__lowerCamelCase       )





       def 						lowerCAmelCase     (   self							:			Any       ):


             '''simple docstring'''



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







class 			_lowercase (							lowercase__):


       """simple docstring"""




       A__											=			version.parse("1.11")





       @property
       def 						lowerCAmelCase     (   self							:			Union[str, Any]       ):


             '''simple docstring'''



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





       @property
       def 						lowerCAmelCase     (   self							:			Optional[int]       ):


             '''simple docstring'''



             return 1E-5





       @property
       def 						lowerCAmelCase     (   self							:			Dict       ):


             '''simple docstring'''



             return 12






import math
import os
import sys

def       lowercase_		(		_A			:    str						):

      """simple docstring"""




      lowerCamelCase__		:				str    =  ""
      try:
            with open(_A    ,					"rb"						) as binary_file:
                  lowerCamelCase__		:				Union[str, Any]    =  binary_file.read()
            for dat in data:
                  lowerCamelCase__		:				Optional[Any]    =  F"{dat:08b}"
                  result += curr_byte
            return result
      except OSError:
            print("File not accessible"						)
            sys.exit()

def       lowercase_		(		_A			:    dict[str, str]    ,					_A			:    str    ,					_A			:    int    ,					_A			:    str						):

      """simple docstring"""




      lexicon.pop(_A						)
      lowerCamelCase__		:				List[Any]    =  last_match_id

      if math.loga(_A						).is_integer():
            for curr_key in lexicon:
                  lowerCamelCase__		:				Any    =  "0" + lexicon[curr_key]

      lowerCamelCase__		:				Tuple    =  bin(_A						)[2:]

def       lowercase_		(		_A			:    str						):

      """simple docstring"""




      lowerCamelCase__		:				Tuple    =  {"0": "0", "1": "1"}
      lowerCamelCase__    ,   lowerCamelCase__		:				int    =  "", ""
      lowerCamelCase__		:				int    =  len(_A						)

      for i in range(len(_A						)						):
            curr_string += data_bits[i]
            if curr_string not in lexicon:
                  continue

            lowerCamelCase__		:				Optional[Any]    =  lexicon[curr_string]
            result += last_match_id
            add_key_to_lexicon(_A    ,					_A    ,					_A    ,					_A						)
            index += 1
            lowerCamelCase__		:				Dict    =  ""

      while curr_string != "" and curr_string not in lexicon:
            curr_string += "0"

      if curr_string != "":
            lowerCamelCase__		:				int    =  lexicon[curr_string]
            result += last_match_id

      return result

def       lowercase_		(		_A			:    str    ,					_A			:    str						):

      """simple docstring"""




      lowerCamelCase__		:				List[str]    =  os.path.getsize(_A						)
      lowerCamelCase__		:				Dict    =  bin(_A						)[2:]
      lowerCamelCase__		:				List[Any]    =  len(_A						)

      return "0" * (length_length - 1) + file_length_binary + compressed

def       lowercase_		(		_A			:    str    ,					_A			:    str						):

      """simple docstring"""




      lowerCamelCase__		:				Dict    =  8
      try:
            with open(_A    ,					"wb"						) as opened_file:
                  lowerCamelCase__		:				Any    =  [
                      to_write[i : i + byte_length]
                      for i in range(0    ,					len(_A						)    ,					_A						)
                  ]

                  if len(result_byte_array[-1]						) % byte_length == 0:
                        result_byte_array.append("10000000"						)
                  else:
                        result_byte_array[-1] += "1" + "0" * (
                            byte_length - len(result_byte_array[-1]						) - 1
                        )

                  for elem in result_byte_array:
                        opened_file.write(int(_A    ,					2						).to_bytes(1    ,					byteorder="big"						)						)
      except OSError:
            print("File not accessible"						)
            sys.exit()

def       lowercase_		(		_A			:    str    ,					_A			:    str						):

      """simple docstring"""




      lowerCamelCase__		:				Dict    =  read_file_binary(_A						)
      lowerCamelCase__		:				List[Any]    =  compress_data(_A						)
      lowerCamelCase__		:				str    =  add_file_length(_A    ,					_A						)
      write_file_binary(_A    ,					_A						)


if __name__ == "__main__":
    compress(sys.argv[1], sys.argv[2])


