MSE-CNN Implementation 1
Code database with the implementation of MSE-CNN, from the paper 'DeepQTMT: A Deep Learning Approach for Fast QTMT-based CU Partition of Intra-mode VVC'
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Public Member Functions | Public Attributes | List of all members
msecnn_raulkviana.msecnn.MseCnnStg1 Class Reference
Inheritance diagram for msecnn_raulkviana.msecnn.MseCnnStg1:
msecnn_raulkviana.msecnn.MseCnnStgX

Public Member Functions

 __init__ (self, device="cpu", QP=32)
 
 residual_unit_stg1 (self, x, nr)
 Generic residual unit.
 
 residual_unit_stg2 (self, x, nr)
 Generic residual unit.
 
 nr_calc (self, ac, ap)
 Calculate the number of residual units.
 
 split (self, cu, coords, sizes, split)
 Splits feature maps in specific way.
 
 forward (self, cu, sizes=None, coords=None)
 This functions propagates the input to the output.
 

Public Attributes

 first_simple_conv
 
 simple_conv_stg1
 
 simple_conv_no_activation_stg1
 
 simple_conv2_stg1
 
 simple_conv_no_activation2_stg1
 
 activation_PRelu_stg1
 
 activation_PRelu2_stg1
 
 simple_conv_stg2
 
 simple_conv_no_activation_stg2
 
 simple_conv2_stg2
 
 simple_conv_no_activation2_stg2
 
 activation_PRelu_stg2
 
 activation_PRelu2_stg2
 
 sub_net
 

Constructor & Destructor Documentation

◆ __init__()

msecnn_raulkviana.msecnn.MseCnnStg1.__init__ (   self,
  device = "cpu",
  QP = 32 
)

Member Function Documentation

◆ forward()

msecnn_raulkviana.msecnn.MseCnnStg1.forward (   self,
  cu,
  sizes = None,
  coords = None 
)

This functions propagates the input to the output.

Parameters
[in]cuInput to the model
[out]logitsVector of raw predictions that a classification model generates

Reimplemented in msecnn_raulkviana.msecnn.MseCnnStgX.

◆ nr_calc()

msecnn_raulkviana.msecnn.MseCnnStg1.nr_calc (   self,
  ac,
  ap 
)

Calculate the number of residual units.

Parameters
[in]acMinimum value of the current input axises
[in]apMinimum value of the parent input axises
[out]nrNumber of residual units

◆ residual_unit_stg1()

msecnn_raulkviana.msecnn.MseCnnStg1.residual_unit_stg1 (   self,
  x,
  nr 
)

Generic residual unit.

Parameters
[in]xInput of the network
[in]nrNumber of residual units

Reimplemented in msecnn_raulkviana.msecnn.MseCnnStgX.

◆ residual_unit_stg2()

msecnn_raulkviana.msecnn.MseCnnStg1.residual_unit_stg2 (   self,
  x,
  nr 
)

Generic residual unit.

Parameters
[in]xInput of the network
[in]nrNumber of residual units

Reimplemented in msecnn_raulkviana.msecnn.MseCnnStgX.

◆ split()

msecnn_raulkviana.msecnn.MseCnnStg1.split (   self,
  cu,
  coords,
  sizes,
  split 
)

Splits feature maps in specific way.

Parameters
[in]cuInput to the model
[in]coordsCoordinates of the new CUs
[in]sizeSize of the new CUs
[in]splitWay to split CU
[out]cu_outNew Feature maps

Member Data Documentation

◆ activation_PRelu2_stg1

msecnn_raulkviana.msecnn.MseCnnStg1.activation_PRelu2_stg1

◆ activation_PRelu2_stg2

msecnn_raulkviana.msecnn.MseCnnStg1.activation_PRelu2_stg2

◆ activation_PRelu_stg1

msecnn_raulkviana.msecnn.MseCnnStg1.activation_PRelu_stg1

◆ activation_PRelu_stg2

msecnn_raulkviana.msecnn.MseCnnStg1.activation_PRelu_stg2

◆ first_simple_conv

msecnn_raulkviana.msecnn.MseCnnStg1.first_simple_conv

◆ simple_conv2_stg1

msecnn_raulkviana.msecnn.MseCnnStg1.simple_conv2_stg1

◆ simple_conv2_stg2

msecnn_raulkviana.msecnn.MseCnnStg1.simple_conv2_stg2

◆ simple_conv_no_activation2_stg1

msecnn_raulkviana.msecnn.MseCnnStg1.simple_conv_no_activation2_stg1

◆ simple_conv_no_activation2_stg2

msecnn_raulkviana.msecnn.MseCnnStg1.simple_conv_no_activation2_stg2

◆ simple_conv_no_activation_stg1

msecnn_raulkviana.msecnn.MseCnnStg1.simple_conv_no_activation_stg1

◆ simple_conv_no_activation_stg2

msecnn_raulkviana.msecnn.MseCnnStg1.simple_conv_no_activation_stg2

◆ simple_conv_stg1

msecnn_raulkviana.msecnn.MseCnnStg1.simple_conv_stg1

◆ simple_conv_stg2

msecnn_raulkviana.msecnn.MseCnnStg1.simple_conv_stg2

◆ sub_net

msecnn_raulkviana.msecnn.MseCnnStg1.sub_net

The documentation for this class was generated from the following file: