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doc: update supported attributes section for matmul

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Maria Zhukova
2025-10-16 10:58:37 -07:00
parent 52077ed87c
commit dc1d8c3d55
1 changed files with 5 additions and 4 deletions
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doc/primitives/matmul.md
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@ -146,9 +146,10 @@ The following attributes and post-ops are supported:
| Type | Operation | Description | Restrictions |
|:----------|:---------------------------------------------------------------|:------------------------------------------------------------------------------|:------------------------------------|
| Attribute | [Scales](@ref dnnl::primitive_attr::set_scales_mask) | Scales the result by given scale factor(s) | |
| Attribute | [Zero-points](@ref dnnl::primitive_attr::set_zero_points_mask) | Sets zero point(s) for the corresponding tensors | Int8 computations only |
| Attribute | [Scales](@ref dnnl::primitive_attr::set_scales_mask) | Scales the result by given scaling factor(s) | |
| Attribute | [Zero-points](@ref dnnl::primitive_attr::set_zero_points_mask) | Sets zero-point(s) for the corresponding tensors | `int8` computations only |
| Attribute | [Dropout](@ref dnnl::primitive_attr::set_dropout) | Applies pseudo-random dropout to destination buffer, also fills mask buffer | |
| Attribute | [Precomputed reductions](@ref dnnl::primitive_attr::set_precomputed_reductions) | Sets precomputed reductions for the corresponding tensors | Requires weight zero-points and full matrix mask |
| Post-op | [Eltwise](@ref dnnl::post_ops::append_eltwise) | Applies an @ref dnnl_api_eltwise operation to the result | |
| Post-op | [Sum](@ref dnnl::post_ops::append_sum) | Adds the operation result to the destination tensor instead of overwriting it | |
| Post-op | [Binary](@ref dnnl::post_ops::append_binary) | Applies a @ref dnnl_api_binary operation to the result | General binary post-op restrictions |
@ -266,7 +267,7 @@ information on sparse encding.
- Sum post-op doesn't support data type other than destination data type.
- Bias of bf16 data type is supported for configuration with bf16 source data
type and weights bf16 data type, and up to three dimensional matrices.
- Optimized implementations for fp8 data type are available only on Intel(R)
- Optimized implementations for fp8 data type are available only on Intel(R)
Data Center GPU Max Series and Intel(R) Xe2 Graphics.
- Configuration with int8 source data type, s8 weight data type and bf16
destination data type don't support:
@ -282,7 +283,7 @@ information on sparse encding.
- Configuration with floating point source data type, integer weights data
type and floating point destination data type is not optimized.
- The layout of dropout mask has to be exactly the same as that of dst.
## Performance Tips
- Use #dnnl::memory::format_tag::any for either of the input tensors if and