ggml: add map_ternary_f32() #1482
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| struct ggml_tensor * a, | ||
| struct ggml_tensor * b, | ||
| struct ggml_tensor * c, | ||
| const ggml_ternary_op_f32_t fun); |
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warning: parameter 'fun' is const-qualified in the function declaration; const-qualification of parameters only has an effect in function definitions [readability-avoid-const-params-in-decls]
Suggested change
| const ggml_ternary_op_f32_t fun); | |
| ggml_ternary_op_f32_t fun); |
ggerganov
requested changes
May 19, 2023
| @@ -4034,6 +4035,7 @@ struct ggml_tensor * ggml_new_tensor_impl( | |||
| /*.grad =*/ NULL, | |||
| /*.src0 =*/ NULL, | |||
| /*.src1 =*/ NULL, | |||
| /*.src2 =*/ NULL, | |||
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Can you make it use opt instead of src2?
The problem with src2 is that there is logic for constructing computation graphs that currently considers src0, src1 and opt. So it would need to be updated if we introduce src2, but I want to do that at a later stage
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sure, I will change that
|
sorry, I will have a look at this later, and probably in the ggml repo which I am using as a submodule |
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Adding the ability to use custom ternary functions as described here: ggerganov/ggml#128
I have checked that it works both with this repo and also in the https://github.com/cztomsik/ggml-js where it's supposed to be used (as an optimization).
It seems to have very little perf. impact (1% at most) so I'm not sure if it's worth adding, but at least it opens some door for 3-var custom kernels.
It seems to work but I have no prior experience with this project, so please check carefully. Thanks :)
EDIT: Maybe there's at least a memory usage improvement, but it's hard for me to check that precisely because I'm using ggml with node.js.