




from math import cos, sin, sqrt, tau

from audio_filters.iir_filter import IIRFilter

def  SCREAMING_SNAKE_CASE							(       __UpperCamelCase		, __UpperCamelCase		, __UpperCamelCase = 1 / sqrt(2))      ->					IIRFilter:
					a     =				tau * frequency / samplerate
					a     =				sin(__UpperCamelCase)
					a     =				cos(__UpperCamelCase)
					a     =				_sin / (2 * q_factor)

					a     =				(1 - _cos) / 2
					a     =				1 - _cos

					a     =				1 + alpha
					a     =				-2 * _cos
					a     =				1 - alpha

					a     =				IIRFilter(2)
					filt.set_coefficients([aa, aa, aa]		, [ba, ba, ba])
					return filt

def  SCREAMING_SNAKE_CASE							(       __UpperCamelCase		, __UpperCamelCase		, __UpperCamelCase = 1 / sqrt(2))      ->					IIRFilter:
					a     =				tau * frequency / samplerate
					a     =				sin(__UpperCamelCase)
					a     =				cos(__UpperCamelCase)
					a     =				_sin / (2 * q_factor)

					a     =				(1 + _cos) / 2
					a     =				-1 - _cos

					a     =				1 + alpha
					a     =				-2 * _cos
					a     =				1 - alpha

					a     =				IIRFilter(2)
					filt.set_coefficients([aa, aa, aa]		, [ba, ba, ba])
					return filt

def  SCREAMING_SNAKE_CASE							(       __UpperCamelCase		, __UpperCamelCase		, __UpperCamelCase = 1 / sqrt(2))      ->					IIRFilter:
					a     =				tau * frequency / samplerate
					a     =				sin(__UpperCamelCase)
					a     =				cos(__UpperCamelCase)
					a     =				_sin / (2 * q_factor)

					a     =				_sin / 2
					a     =				0
					a     =				-ba

					a     =				1 + alpha
					a     =				-2 * _cos
					a     =				1 - alpha

					a     =				IIRFilter(2)
					filt.set_coefficients([aa, aa, aa]		, [ba, ba, ba])
					return filt

def  SCREAMING_SNAKE_CASE							(       __UpperCamelCase		, __UpperCamelCase		, __UpperCamelCase = 1 / sqrt(2))      ->					IIRFilter:
					a     =				tau * frequency / samplerate
					a     =				sin(__UpperCamelCase)
					a     =				cos(__UpperCamelCase)
					a     =				_sin / (2 * q_factor)

					a     =				1 - alpha
					a     =				-2 * _cos
					a     =				1 + alpha

					a     =				IIRFilter(2)
					filt.set_coefficients([ba, ba, ba]		, [ba, ba, ba])
					return filt

def  SCREAMING_SNAKE_CASE							(       __UpperCamelCase		, __UpperCamelCase		, __UpperCamelCase		, __UpperCamelCase = 1 / sqrt(2)		, )      ->					IIRFilter:
					a     =				tau * frequency / samplerate
					a     =				sin(__UpperCamelCase)
					a     =				cos(__UpperCamelCase)
					a     =				_sin / (2 * q_factor)
					a     =				10 ** (gain_db / 40)

					a     =				1 + alpha * big_a
					a     =				-2 * _cos
					a     =				1 - alpha * big_a
					a     =				1 + alpha / big_a
					a     =				-2 * _cos
					a     =				1 - alpha / big_a

					a     =				IIRFilter(2)
					filt.set_coefficients([aa, aa, aa]		, [ba, ba, ba])
					return filt

def  SCREAMING_SNAKE_CASE							(       __UpperCamelCase		, __UpperCamelCase		, __UpperCamelCase		, __UpperCamelCase = 1 / sqrt(2)		, )      ->					IIRFilter:
					a     =				tau * frequency / samplerate
					a     =				sin(__UpperCamelCase)
					a     =				cos(__UpperCamelCase)
					a     =				_sin / (2 * q_factor)
					a     =				10 ** (gain_db / 40)
					a     =				(big_a + 1) - (big_a - 1) * _cos
					a     =				(big_a + 1) + (big_a - 1) * _cos
					a     =				(big_a - 1) - (big_a + 1) * _cos
					a     =				(big_a - 1) + (big_a + 1) * _cos
					a     =				2 * sqrt(__UpperCamelCase) * alpha

					a     =				big_a * (pmc + aaa)
					a     =				2 * big_a * mpc
					a     =				big_a * (pmc - aaa)
					a     =				ppmc + aaa
					a     =				-2 * pmpc
					a     =				ppmc - aaa

					a     =				IIRFilter(2)
					filt.set_coefficients([aa, aa, aa]		, [ba, ba, ba])
					return filt





def  SCREAMING_SNAKE_CASE							(       __UpperCamelCase		, __UpperCamelCase		, __UpperCamelCase		, __UpperCamelCase = 1 / sqrt(2)		, )      ->					IIRFilter:
					a     =				tau * frequency / samplerate
					a     =				sin(__UpperCamelCase)
					a     =				cos(__UpperCamelCase)
					a     =				_sin / (2 * q_factor)
					a     =				10 ** (gain_db / 40)
					a     =				(big_a + 1) - (big_a - 1) * _cos
					a     =				(big_a + 1) + (big_a - 1) * _cos
					a     =				(big_a - 1) - (big_a + 1) * _cos
					a     =				(big_a - 1) + (big_a + 1) * _cos
					a     =				2 * sqrt(__UpperCamelCase) * alpha

					a     =				big_a * (ppmc + aaa)
					a     =				-2 * big_a * pmpc
					a     =				big_a * (ppmc - aaa)
					a     =				pmc + aaa
					a     =				2 * mpc
					a     =				pmc - aaa

					a     =				IIRFilter(2)
					filt.set_coefficients([aa, aa, aa]		, [ba, ba, ba])
					return filt







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
from ..auto import CONFIG_MAPPING


lowercase__				:      Optional[Any]	   = logging.get_logger(__name__)

lowercase__				:      str	   = {
    "microsoft/table-transformer-detection": (
        "https://huggingface.co/microsoft/table-transformer-detection/resolve/main/config.json"
    ),
}




class       a__	( UpperCamelCase__				):
     a		:      Optional[int]		 =     """table-transformer"""
     a		:      Tuple		 =     ["""past_key_values"""]
     a		:      int		 =     {
         """hidden_size""": """d_model""",
         """num_attention_heads""": """encoder_attention_heads""",
     }







     def __init__(     self  ,		A=True  ,		A=None  ,		A=3  ,		A=100  ,		A=6  ,		A=2048  ,		A=8  ,		A=6  ,		A=2048  ,		A=8  ,		A=0.0  ,		A=0.0  ,		A=True  ,		A="relu"  ,		A=256  ,		A=0.1  ,		A=0.0  ,		A=0.0  ,		A=0.0_2  ,		A=1.0  ,		A=False  ,		A="sine"  ,		A="resnet50"  ,		A=True  ,		A=False  ,		A=1  ,		A=5  ,		A=2  ,		A=1  ,		A=1  ,		A=5  ,		A=2  ,		A=0.1  ,		**A  ,		)  ->   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."			)
                    a     =				CONFIG_MAPPING["resnet"](out_features=["stage4"]			)
               elif isinstance(A  ,		A			):
                    a     =				backbone_config.get("model_type"			)
                    a     =				CONFIG_MAPPING[backbone_model_type]
                    a     =				config_class.from_dict(A			)
               # set timm attributes to None
               a  ,				a  ,				a     =				None, None, None

          a     =				use_timm_backbone
          a     =				backbone_config
          a     =				num_channels
          a     =				num_queries
          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     =				decoder_layerdrop
          a     =				encoder_layers
          a     =				auxiliary_loss
          a     =				position_embedding_type
          a     =				backbone
          a     =				use_pretrained_backbone
          a     =				dilation
          # 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
          super().__init__(is_encoder_decoder=A  ,		**A			)







     @property
     def       lowerCAmelCase_    (     self			)  ->   int:



          '''simple docstring'''



          return self.encoder_attention_heads







     @property
     def       lowerCAmelCase_    (     self			)  ->   int:



          '''simple docstring'''



          return self.d_model







class       a__	( UpperCamelCase__				):
     a		:      Any		 =     version.parse("""1.11"""				)







     @property
     def       lowerCAmelCase_    (     self			)  ->   Mapping[str, Mapping[int, str]]:



          '''simple docstring'''



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







     @property
     def       lowerCAmelCase_    (     self			)  ->   float:



          '''simple docstring'''



          return 1e-5







     @property
     def       lowerCAmelCase_    (     self			)  ->   int:



          '''simple docstring'''



          return 12

