





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_												=     logging.get_logger(__name__)

A_												=     {
    '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 SCREAMING_SNAKE_CASE_ (					UpperCamelCase_   ):





					"""simple docstring"""


					A__				 =    "detr"
					A__				 =    ["past_key_values"]
					A__				 =    {
					    "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	,  ):





										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(UpperCamelCase__	,  UpperCamelCase__	):
																				lowerCamelCase__       =       backbone_config.get("model_type"	)
																				lowerCamelCase__       =       CONFIG_MAPPING[backbone_model_type]
																				lowerCamelCase__       =       config_class.from_dict(UpperCamelCase__	)
															# set timm attributes to None
															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=UpperCamelCase__	,  **UpperCamelCase__	)





					@property
					def 					__magic_name__ ( self	):
										return self.encoder_attention_heads





					@property
					def 					__magic_name__ ( self	):
										return self.d_model





					@classmethod
					def 					__magic_name__ ( cls	,  _lowerCAmelCase	,  **_lowerCAmelCase	):
										return cls(backbone_config=UpperCamelCase__	,  **UpperCamelCase__	)






					def 					__magic_name__ ( self	):
										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 SCREAMING_SNAKE_CASE_ (					UpperCamelCase_   ):





					"""simple docstring"""


					A__				 =    version.parse("1.11"   )





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





					@property
					def 					__magic_name__ ( self	):
										return 1E-5






					@property
					def 					__magic_name__ ( self	):
										return 12








from __future__ import annotations

class SCREAMING_SNAKE_CASE_ :





					"""simple docstring"""


					def __init__( self	,  _lowerCAmelCase	,  _lowerCAmelCase	):
										lowerCamelCase__    ,		lowerCamelCase__       =       text, pattern
										lowerCamelCase__    ,		lowerCamelCase__       =       len(_lowerCAmelCase	), len(_lowerCAmelCase	)





					def 					__magic_name__ ( self	,  _lowerCAmelCase	):

										for i in range(self.patLen - 1	,  -1	,  -1	):
															if char == self.pattern[i]:
																				return i
										return -1





					def 					__magic_name__ ( self	,  _lowerCAmelCase	):

										for i in range(self.patLen - 1	,  -1	,  -1	):
															if self.pattern[i] != self.text[current_pos + i]:
																				return current_pos + i
										return -1






					def 					__magic_name__ ( self	):
										# searches pattern in text and returns index positions
										lowerCamelCase__       =       []
										for i in range(self.textLen - self.patLen + 1	):
															lowerCamelCase__       =       self.mismatch_in_text(_lowerCAmelCase	)
															if mismatch_index == -1:
																				positions.append(_lowerCAmelCase	)
															else:
																				lowerCamelCase__       =       self.match_in_pattern(self.text[mismatch_index]	)
																				lowerCamelCase__       =       (
																				    mismatch_index - match_index
																				)  # shifting index lgtm [py/multiple-definition]
										return positions

A_												=     "ABAABA"
A_												=     "AB"
A_												=     BoyerMooreSearch(text, pattern)
A_												=     bms.bad_character_heuristic()

if len(positions) == 0:
						print("No match found")
else:
						print("Pattern found in following positions: ")
						print(positions)

