ConvolutionTranspose3D: ConvolutionTranspose3D

In joeddav/CNTK-R: R Interface to the Microsoft Cognitive Toolkit (CNTK)

Description

Layer factory function to create a 3D convolution transpose layer with optional non-linearity. Same as ConvolutionTranspose() except that filter_shape is verified to be 3-dimensional. See ConvolutionTranspose() for extensive documentation.

Usage

ConvolutionTranspose3D(filter_shape, num_filters = NULL,
  activation = activation_identity, init = init_glorot_uniform(),
  pad = FALSE, strides = 1, bias = TRUE, init_bias = 0,
  output_shape = NULL, name = "")

Arguments

filter_shape	int or list of int - shape (spatial extent) of the receptive field, not including the input feature-map depth. E.g. (3,3) for a 2D convolution.
num_filters	(int, defaults to None) – number of filters (output feature-map depth), or () to denote scalar output items (output shape will have no depth axis).
activation	(Function) - optional activation Function
init	(scalar or matrix or initializer, defaults to init_glorot_uniform()) – initial value of weights W
pad	(bool or list of bools) – if False, then the operation will be shifted over the “valid” area of input, that is, no value outside the area is used. If pad=True on the other hand, the operation will be applied to all input positions, and positions outside the valid region will be considered containing zero. Use a list to specify a per-axis value.
strides	(int or tuple of ints, defaults to 1) – stride of the operation. Use a list of ints to specify a per-axis value.
bias	(bool) – whether to include bias
init_bias	(scalar or matrix or initializer, defaults to 0) – initial value of weights b
output_shape	(int or tuple of ints) – output shape. When strides > 2, the output shape is non-deterministic. User can specify the wanted output shape. Note the specified shape must satisify the condition that if a convolution is perform from the output with the same setting, the result must have same shape as the input.
name	string (optional) the name of the Function instance in the network

joeddav/CNTK-R documentation built on May 6, 2019, 7:28 a.m.