ggml_pool_2d: 2D Pooling (Graph)
In ggmlR: 'GGML' Tensor Operations for Machine Learning
ggml_pool_2d R Documentation
2D Pooling (Graph)
Description
Applies 2D pooling operation.
Usage
ggml_pool_2d(ctx, a, op, k0, k1, s0 = k0, s1 = k1, p0 = 0, p1 = 0)
Arguments
ctx
GGML context
a
Input tensor
op
Pool operation: GGML_OP_POOL_MAX (0) or GGML_OP_POOL_AVG (1)
k0
Kernel size dimension 0
k1
Kernel size dimension 1
s0
Stride dimension 0 (default = k0)
s1
Stride dimension 1 (default = k1)
p0
Padding dimension 0 (default 0)
p1
Padding dimension 1 (default 0)
Value
Pooled tensor
ggmlR documentation built on July 14, 2026, 1:08 a.m.
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| ggml_pool_2d | R Documentation |
2D Pooling (Graph)
Description
Applies 2D pooling operation.
Usage
ggml_pool_2d(ctx, a, op, k0, k1, s0 = k0, s1 = k1, p0 = 0, p1 = 0)
Arguments
ctx |
GGML context |
a |
Input tensor |
op |
Pool operation: GGML_OP_POOL_MAX (0) or GGML_OP_POOL_AVG (1) |
k0 |
Kernel size dimension 0 |
k1 |
Kernel size dimension 1 |
s0 |
Stride dimension 0 (default = k0) |
s1 |
Stride dimension 1 (default = k1) |
p0 |
Padding dimension 0 (default 0) |
p1 |
Padding dimension 1 (default 0) |
Value
Pooled 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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