ggml_conv_2d: 2D Convolution (Graph)
In ggmlR: 'GGML' Tensor Operations for Machine Learning
ggml_conv_2d R Documentation
2D Convolution (Graph)
Description
Applies 2D convolution to input data.
Usage
ggml_conv_2d(ctx, a, b, s0 = 1L, s1 = 1L, p0 = 0L, p1 = 0L, d0 = 1L, d1 = 1L)
Arguments
ctx
GGML context
a
Convolution kernel tensor [KW, KH, IC, OC]
b
Input data tensor [W, H, C, N]
s0
Stride dimension 0 (default 1)
s1
Stride dimension 1 (default 1)
p0
Padding dimension 0 (default 0)
p1
Padding dimension 1 (default 0)
d0
Dilation dimension 0 (default 1)
d1
Dilation dimension 1 (default 1)
Value
Convolved tensor
ggmlR documentation built on July 14, 2026, 1:08 a.m.
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| ggml_conv_2d | R Documentation |
2D Convolution (Graph)
Description
Applies 2D convolution to input data.
Usage
ggml_conv_2d(ctx, a, b, s0 = 1L, s1 = 1L, p0 = 0L, p1 = 0L, d0 = 1L, d1 = 1L)
Arguments
ctx |
GGML context |
a |
Convolution kernel tensor [KW, KH, IC, OC] |
b |
Input data tensor [W, H, C, N] |
s0 |
Stride dimension 0 (default 1) |
s1 |
Stride dimension 1 (default 1) |
p0 |
Padding dimension 0 (default 0) |
p1 |
Padding dimension 1 (default 0) |
d0 |
Dilation dimension 0 (default 1) |
d1 |
Dilation dimension 1 (default 1) |
Value
Convolved tensor
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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