Conv1d

class Conv1d<T : DType, V>(val inChannels: Int, val outChannels: Int, val kernelSize: Int, val stride: Int = 1, val padding: Int = 0, val dilation: Int = 1, val groups: Int = 1, val bias: Boolean = true, val name: String = "Conv1d", initWeights: Tensor<T, V>, initBias: Tensor<T, V>? = null, val trainable: Boolean = true) : Module<T, V> , ModuleParameters<T, V> (source)

1D Convolutional layer that applies a convolution operation over 1D input.

This layer is commonly used for sequence data like time series or text.

Parameters

inChannels

Number of input channels

outChannels

Number of output channels/filters

kernelSize

Size of the convolving kernel

stride

Stride of the convolution (default: 1)

padding

Padding added to both sides of the input (default: 0)

dilation

Spacing between kernel elements (default: 1)

groups

Number of blocked connections from input channels to output channels (default: 1)

bias

Whether to add a learnable bias to the output (default: true)

name

Name of the module

initWeights

Initial weights tensor

initBias

Initial bias tensor (if bias is true)

Constructors

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constructor(inChannels: Int, outChannels: Int, kernelSize: Int, stride: Int = 1, padding: Int = 0, dilation: Int = 1, groups: Int = 1, bias: Boolean = true, name: String = "Conv1d", initWeights: Tensor<T, V>, initBias: Tensor<T, V>? = null, trainable: Boolean = true)

Properties

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val groups: Int
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open override val modules: List<Module<T, V>>
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open override val name: String
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open override val params: List<ModuleParameter<T, V>>

Parameters owned by this node (weights, biases, etc.).

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val stride: Int
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Functions

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open override fun forward(input: Tensor<T, V>, ctx: ExecutionContext): Tensor<T, V>
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fun outputSize(inputSize: Int): Int

Calculates the output size for a given input size and convolution parameters.