Convolution..::..Conv1D Method (Tuple<(Of <(<'Int32, Int32>)>)>, Int32, Int32, Int32, Boolean, Int32, String, Boolean, String, String)
1D convolution layer (e.g. temporal convolution). This layer creates a convolution kernel that is convolved with the layer input over a single spatial (or temporal) dimension to produce a tensor of outputs. If use_bias is True, a bias vector is created and added to the outputs. Finally, if activation is not None, it is applied to the outputs as well.
Namespace:
SiaNet.NNAssembly: SiaNet (in SiaNet.dll)
Syntax
public static Function Conv1D( Tuple<int, int> shape, int channels, int kernalSize, int strides, bool padding, int dialation, string activation, bool useBias, string weightInitializer, string biasInitializer )
Public Shared Function Conv1D ( _ shape As Tuple(Of Integer, Integer), _ channels As Integer, _ kernalSize As Integer, _ strides As Integer, _ padding As Boolean, _ dialation As Integer, _ activation As String, _ useBias As Boolean, _ weightInitializer As String, _ biasInitializer As String _ ) As Function
Parameters
- channels
- Type: Int32
Integer, the dimensionality of the output space
- kernalSize
- Type: Int32
An integer specifying the length of the 1D convolution window.
- strides
- Type: Int32
An integer specifying the stride length of the convolution.
- padding
- Type: Boolean
Boolean, if true results in padding the input such that the output has the same length as the original input.
- dialation
- Type: Int32
An integer specifying the dilation rate to use for dilated convolution. Currently, specifying any dilation_rate value != 1 is incompatible with specifying any strides value != 1.
- activation
- Type: String
Activation function to use. If you don't specify anything, no activation is applied (ie. "linear" activation: a(x) = x). OptActivations
- useBias
- Type: Boolean
Boolean, whether the layer uses a bias vector.
- weightInitializer
- Type: String
Initializer for the kernel weights matrix. OptInitializers
- biasInitializer
- Type: String
Initializer for the bias vector. OptInitializers