Torch-style 2D convolution in NCHW layout: x is
[batch, in_channels, height, width], weight is
[out_channels, in_channels / groups, kh, kw], output is
[batch, out_channels, out_h, out_w]. Symmetric zero padding.
Usage
nv_conv2d(
x,
weight,
stride = 1L,
padding = 0L,
dilation = 1L,
groups = 1L,
precision = "highest"
)Arguments
- x
(
arrayish)[N, C_in, H, W].- weight
(
arrayish)[C_out, C_in / groups, kH, kW].- stride
(
integer())
Length 1 or 2.- padding
(
integer())
Symmetric padding, length 1 or 2.- dilation
(
integer())
Kernel dilation, length 1 or 2.- groups
(
integer(1))
Grouped/depthwise convolution.- precision
(
character(1))"highest","high"or"default".
Value
arrayish [N, C_out, out_H, out_W].