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Contents
module Torch module NN class ConvNd < Module def initialize(in_channels, out_channels, kernel_size, stride, padding, dilation, transposed, output_padding, groups, bias, padding_mode) super() raise ArgumentError, "in_channels must be divisible by groups" if in_channels % groups != 0 raise ArgumentError, "out_channels must be divisible by groups" if out_channels % groups != 0 @in_channels = in_channels @out_channels = out_channels @kernel_size = kernel_size @stride = stride @padding = padding @dilation = dilation @transposed = transposed @output_padding = output_padding @groups = groups @padding_mode = padding_mode if transposed @weight = Parameter.new(Tensor.new(in_channels, out_channels / groups, *kernel_size)) else @weight = Parameter.new(Tensor.new(out_channels, in_channels / groups, *kernel_size)) end if bias @bias = Parameter.new(Tensor.new(out_channels)) else register_parameter("bias", nil) end reset_parameters end def reset_parameters Init.kaiming_uniform!(@weight, a: Math.sqrt(5)) if @bias fan_in, _ = Init._calculate_fan_in_and_fan_out(@weight) bound = 1 / Math.sqrt(fan_in) Init.uniform!(@bias, a: -bound, b: bound) end end end end end
Version data entries
23 entries across 23 versions & 1 rubygems
Version | Path |
---|---|
torch-rb-0.2.6 | lib/torch/nn/convnd.rb |
torch-rb-0.2.5 | lib/torch/nn/convnd.rb |
torch-rb-0.2.4 | lib/torch/nn/convnd.rb |