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Versions: 43
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Stored size: 1.25 KB
Contents
module Torch
module NN
class Conv2d < ConvNd
def initialize(in_channels, out_channels, kernel_size, stride: 1,
padding: 0, dilation: 1, groups: 1, bias: true, padding_mode: "zeros")
kernel_size = _pair(kernel_size)
stride = _pair(stride)
padding = _pair(padding)
dilation = _pair(dilation)
super(in_channels, out_channels, kernel_size, stride, padding, dilation, false, _pair(0), groups, bias, padding_mode)
end
def forward(input)
if @padding_mode == "circular"
raise NotImplementedError
end
F.conv2d(input, @weight, @bias, @stride, @padding, @dilation, @groups)
end
def extra_inspect
s = String.new("%{in_channels}, %{out_channels}, kernel_size: %{kernel_size}, stride: %{stride}")
s += ", padding: %{padding}" if @padding != [0] * @padding.size
s += ", dilation: %{dilation}" if @dilation != [1] * @dilation.size
s += ", output_padding: %{output_padding}" if @output_padding != [0] * @output_padding.size
s += ", groups: %{groups}" if @groups != 1
s += ", bias: false" unless @bias
s += ", padding_mode: %{padding_mode}" if @padding_mode != "zeros"
format(s, **dict)
end
end
end
end
Version data entries
43 entries across 43 versions & 1 rubygems