ggml_set_loss: Mark a Tensor as the Loss
In ggmlR: 'GGML' Tensor Operations for Machine Learning
ggml_set_loss R Documentation
Mark a Tensor as the Loss
Description
Marks a tensor as the quantity to differentiate.
ggml_build_backward_expand requires the graph to contain one –
together with at least one ggml_set_param tensor, these are the
two ends of the backward pass.
Usage
ggml_set_loss(tensor)
Arguments
tensor
Tensor pointer, usually a scalar produced by
ggml_sum or a loss op
Details
A graph missing either is rejected with an error rather than aborting inside
ggml.
Value
The tensor (for chaining)
See Also
ggml_set_param,
ggml_build_forward_expand_grads
ggmlR documentation built on Oct. 23, 2026, 1:07 a.m.
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| ggml_set_loss | R Documentation |
Mark a Tensor as the Loss
Description
Marks a tensor as the quantity to differentiate.
ggml_build_backward_expand requires the graph to contain one –
together with at least one ggml_set_param tensor, these are the
two ends of the backward pass.
Usage
ggml_set_loss(tensor)
Arguments
tensor |
Tensor pointer, usually a scalar produced by
|
Details
A graph missing either is rejected with an error rather than aborting inside ggml.
Value
The tensor (for chaining)
See Also
ggml_set_param,
ggml_build_forward_expand_grads
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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