R/backend.R

k_local_conv2d

Apply 2D conv with un-shared weights.

Description

Apply 2D conv with un-shared weights.

Usage

 
k_local_conv2d( 
  inputs, 
  kernel, 
  kernel_size, 
  strides, 
  output_shape, 
  data_format = NULL 
) 

Arguments

Arguments Description
inputs 4D tensor with shape: (batch_size, filters, new_rows, new_cols) if data_format=‘channels_first’ or 4D tensor with shape: (batch_size, new_rows, new_cols, filters) if data_format=‘channels_last’.
kernel the unshared weight for convolution, with shape (output_items, feature_dim, filters)
kernel_size a list of 2 integers, specifying the width and height of the 2D convolution window.
strides a list of 2 integers, specifying the strides of the convolution along the width and height.
output_shape a list with (output_row, output_col)
data_format the data format, channels_first or channels_last

Section

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://keras.rstudio.com/articles/backend.html#backend-functions.

Value

A 4d tensor with shape: (batch_size, filters, new_rows, new_cols) if data_format=‘channels_first’ or 4D tensor with shape: (batch_size, new_rows, new_cols, filters) if data_format=‘channels_last’.