Inheritance diagram for 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. | |
| residual_unit (self, x, nr) | |
| Generic residual unit. | |
| pass_through_subnet (self, x) | |
| This functions propagates the it's input through a specific subnetwork depending on the shape of the input. | |
| forward (self, cu, ap, splits=None, sizes=None, coords=None) | |
| This functions propagates the input to the output. | |
 Public Member Functions inherited from msecnn_raulkviana.msecnn.MseCnnStg1 | |
| __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. | |
Constructor & Destructor Documentation
◆ __init__()
| msecnn_raulkviana.msecnn.MseCnnStgX.__init__ | ( | self, | |
device = "cpu", |
|||
QP = 32 |
|||
| ) |
Reimplemented from msecnn_raulkviana.msecnn.MseCnnStg1.
Member Function Documentation
◆ forward()
| msecnn_raulkviana.msecnn.MseCnnStgX.forward | ( | self, | |
| cu, | |||
| ap, | |||
splits = None, |
|||
sizes = None, |
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coords = None |
|||
| ) |
This functions propagates the input to the output.
- Parameters
-
[in] cu Input to the model [out] logits Vector of raw predictions that a classification model generates
Reimplemented from msecnn_raulkviana.msecnn.MseCnnStg1.
◆ pass_through_subnet()
| msecnn_raulkviana.msecnn.MseCnnStgX.pass_through_subnet | ( | self, | |
| x | |||
| ) |
This functions propagates the it's input through a specific subnetwork depending on the shape of the input.
- Parameters
-
[in] x Input to the model [out] logits Vector of raw predictions that a classification model generates
◆ residual_unit()
| msecnn_raulkviana.msecnn.MseCnnStgX.residual_unit | ( | self, | |
| x, | |||
| nr | |||
| ) |
Generic residual unit.
- Parameters
-
[in] x Input of the network [in] nr Number of residual units
◆ residual_unit_stg1()
| msecnn_raulkviana.msecnn.MseCnnStgX.residual_unit_stg1 | ( | self, | |
| x, | |||
| nr | |||
| ) |
Generic residual unit.
- Parameters
-
[in] x Input of the network [in] nr Number of residual units
Reimplemented from msecnn_raulkviana.msecnn.MseCnnStg1.
◆ residual_unit_stg2()
| msecnn_raulkviana.msecnn.MseCnnStgX.residual_unit_stg2 | ( | self, | |
| x, | |||
| nr | |||
| ) |
Generic residual unit.
- Parameters
-
[in] x Input of the network [in] nr Number of residual units
Reimplemented from msecnn_raulkviana.msecnn.MseCnnStg1.
Member Data Documentation
◆ activation_PRelu
| msecnn_raulkviana.msecnn.MseCnnStgX.activation_PRelu |
◆ activation_PRelu2
| msecnn_raulkviana.msecnn.MseCnnStgX.activation_PRelu2 |
◆ activation_PRelu2_stg1
| msecnn_raulkviana.msecnn.MseCnnStgX.activation_PRelu2_stg1 |
◆ activation_PRelu2_stg2
| msecnn_raulkviana.msecnn.MseCnnStgX.activation_PRelu2_stg2 |
◆ activation_PRelu_stg1
| msecnn_raulkviana.msecnn.MseCnnStgX.activation_PRelu_stg1 |
◆ activation_PRelu_stg2
| msecnn_raulkviana.msecnn.MseCnnStgX.activation_PRelu_stg2 |
◆ conv_16_16
| msecnn_raulkviana.msecnn.MseCnnStgX.conv_16_16 |
◆ conv_16_32
| msecnn_raulkviana.msecnn.MseCnnStgX.conv_16_32 |
◆ conv_16_64
| msecnn_raulkviana.msecnn.MseCnnStgX.conv_16_64 |
◆ conv_32_32
| msecnn_raulkviana.msecnn.MseCnnStgX.conv_32_32 |
◆ conv_32_64
| msecnn_raulkviana.msecnn.MseCnnStgX.conv_32_64 |
Sub-networks Convolutional layers Min 32.
◆ conv_4_16
| msecnn_raulkviana.msecnn.MseCnnStgX.conv_4_16 |
◆ conv_4_32
| msecnn_raulkviana.msecnn.MseCnnStgX.conv_4_32 |
◆ conv_4_4
| msecnn_raulkviana.msecnn.MseCnnStgX.conv_4_4 |
◆ conv_4_8
| msecnn_raulkviana.msecnn.MseCnnStgX.conv_4_8 |
◆ conv_8_16
| msecnn_raulkviana.msecnn.MseCnnStgX.conv_8_16 |
◆ conv_8_32
| msecnn_raulkviana.msecnn.MseCnnStgX.conv_8_32 |
◆ conv_8_64
| msecnn_raulkviana.msecnn.MseCnnStgX.conv_8_64 |
◆ conv_8_8
| msecnn_raulkviana.msecnn.MseCnnStgX.conv_8_8 |
◆ first_simple_conv
| msecnn_raulkviana.msecnn.MseCnnStgX.first_simple_conv |
◆ simple_conv
| msecnn_raulkviana.msecnn.MseCnnStgX.simple_conv |
◆ simple_conv2
| msecnn_raulkviana.msecnn.MseCnnStgX.simple_conv2 |
◆ simple_conv2_stg1
| msecnn_raulkviana.msecnn.MseCnnStgX.simple_conv2_stg1 |
◆ simple_conv2_stg2
| msecnn_raulkviana.msecnn.MseCnnStgX.simple_conv2_stg2 |
◆ simple_conv_no_activation
| msecnn_raulkviana.msecnn.MseCnnStgX.simple_conv_no_activation |
◆ simple_conv_no_activation2
| msecnn_raulkviana.msecnn.MseCnnStgX.simple_conv_no_activation2 |
◆ simple_conv_no_activation2_stg1
| msecnn_raulkviana.msecnn.MseCnnStgX.simple_conv_no_activation2_stg1 |
◆ simple_conv_no_activation2_stg2
| msecnn_raulkviana.msecnn.MseCnnStgX.simple_conv_no_activation2_stg2 |
◆ simple_conv_no_activation_stg1
| msecnn_raulkviana.msecnn.MseCnnStgX.simple_conv_no_activation_stg1 |
◆ simple_conv_no_activation_stg2
| msecnn_raulkviana.msecnn.MseCnnStgX.simple_conv_no_activation_stg2 |
◆ simple_conv_stg1
| msecnn_raulkviana.msecnn.MseCnnStgX.simple_conv_stg1 |
◆ simple_conv_stg2
| msecnn_raulkviana.msecnn.MseCnnStgX.simple_conv_stg2 |
◆ sub_net
| msecnn_raulkviana.msecnn.MseCnnStgX.sub_net |
◆ sub_net_min_16
| msecnn_raulkviana.msecnn.MseCnnStgX.sub_net_min_16 |
◆ sub_net_min_32
| msecnn_raulkviana.msecnn.MseCnnStgX.sub_net_min_32 |
◆ sub_net_min_4
| msecnn_raulkviana.msecnn.MseCnnStgX.sub_net_min_4 |
◆ sub_net_min_8
| msecnn_raulkviana.msecnn.MseCnnStgX.sub_net_min_8 |
The documentation for this class was generated from the following file:
- src/msecnn_raulkviana/msecnn.py
