ggml_set_param: Set Tensor as Trainable Parameter
In ggmlR: 'GGML' Tensor Operations for Machine Learning
ggml_set_param R Documentation
Set Tensor as Trainable Parameter
Description
Marks a tensor as a trainable parameter for backpropagation.
The optimizer will compute gradients for this tensor during training.
Usage
ggml_set_param(tensor)
Arguments
tensor
Tensor pointer
Value
The tensor (for chaining)
See Also
ggml_set_loss, which marks the other end of the
backward pass, and ggml_build_backward_expand.
ggmlR documentation built on Oct. 23, 2026, 1:07 a.m.
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| ggml_set_param | R Documentation |
Set Tensor as Trainable Parameter
Description
Marks a tensor as a trainable parameter for backpropagation. The optimizer will compute gradients for this tensor during training.
Usage
ggml_set_param(tensor)
Arguments
tensor |
Tensor pointer |
Value
The tensor (for chaining)
See Also
ggml_set_loss, which marks the other end of the
backward pass, and ggml_build_backward_expand.
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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