ag_grad: Gradient of a tensor as an R matrix
In ggmlR: 'GGML' Tensor Operations for Machine Learning
ag_grad R Documentation
Gradient of a tensor as an R matrix
Description
After backward(), x$grad holds the gradient – as an R matrix
on the closure path, but as a device handle when the graph backward kept it
on the GPU (the default there). ag_grad() returns the value as a
matrix either way, so code that reads gradients does not depend on where
they live. In graph mode it is a synchronisation point.
Usage
ag_grad(x)
Arguments
x
An ag_tensor (usually a parameter).
Value
A numeric matrix, or NULL when x has no gradient.
Examples
w <- ag_param(matrix(1:4 + 0, 2, 2))
with_grad_tape({ loss <- ag_sum(ag_mul(w, w)) })
backward(loss)
ag_grad(w) # 2 * w
ggmlR documentation built on Oct. 23, 2026, 1:07 a.m.
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| ag_grad | R Documentation |
Gradient of a tensor as an R matrix
Description
After backward(), x$grad holds the gradient – as an R matrix
on the closure path, but as a device handle when the graph backward kept it
on the GPU (the default there). ag_grad() returns the value as a
matrix either way, so code that reads gradients does not depend on where
they live. In graph mode it is a synchronisation point.
Usage
ag_grad(x)
Arguments
x |
An ag_tensor (usually a parameter). |
Value
A numeric matrix, or NULL when x has no gradient.
Examples
w <- ag_param(matrix(1:4 + 0, 2, 2))
with_grad_tape({ loss <- ag_sum(ag_mul(w, w)) })
backward(loss)
ag_grad(w) # 2 * w
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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