k_local_conv1d: Apply 1D conv with un-shared weights.

In keras: R Interface to 'Keras'

Apply 1D conv with un-shared weights.

Description

Apply 1D conv with un-shared weights.

Usage

k_local_conv1d(inputs, kernel, kernel_size, strides, data_format = NULL)

Arguments

inputs	3D tensor with shape: (batch_size, steps, input_dim)
kernel	the unshared weight for convolution, with shape (output_length, feature_dim, filters)
kernel_size	a list of a single integer, specifying the length of the 1D convolution window
strides	a list of a single integer, specifying the stride length of the convolution
data_format	the data format, channels_first or channels_last

Value

the tensor after 1d conv with un-shared weights, with shape (batch_size, output_length, filters)

Keras Backend

This function is part of a set of Keras backend functions that enable lower level access to the core operations of the backend tensor engine (e.g. TensorFlow, CNTK, Theano, etc.).

You can see a list of all available backend functions here: https://tensorflow.rstudio.com/reference/keras/index.html#backend.

keras documentation built on May 29, 2024, 3:20 a.m.