Skip to content

[WebGPU EP] Remove unused has_bias in MatMul::ComputeInternal #27211

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Draft
Jiawei-Shao wants to merge 1 commit into
base: main
Choose a base branch
from
+3 −18
Draft

[WebGPU EP] Remove unused has_bias in MatMul::ComputeInternal #27211

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
21 changes: 3 additions & 18 deletions onnxruntime/core/providers/webgpu/math/matmul.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -115,7 +115,6 @@ Status MatMul::ComputeInternal(ComputeContext& context) const {
// If the output tensor is empty, we can return early.
return Status::OK();
}
bool has_bias = context.InputCount() > 2;

if (helper.N() < 8 && helper.K() < 8) { // call MatMulNaiveProgram

Expand All @@ -136,18 +135,11 @@ Status MatMul::ComputeInternal(ComputeContext& context) const {
const int64_t a_rows = a->Shape().NumDimensions() > 1 ? a->Shape()[a->Shape().NumDimensions() - 2] : 1;
TensorShape output_shape_shader({batch_size, a_rows, helper.N() / components});

MatMulNaiveProgram program{Activation(), output_rank, output_number, has_bias};

MatMulNaiveProgram program{Activation(), output_rank, output_number, /*has_bias*/ false};
program
.CacheHint(std::to_string(components), std::to_string(a_components), std::to_string(output_number))
.AddInputs({{a, ProgramTensorMetadataDependency::TypeAndRank, a_components},
{b, ProgramTensorMetadataDependency::TypeAndRank, components}});

if (has_bias) {
const auto* bias = context.Input(2);
program.AddInput({bias, ProgramTensorMetadataDependency::Rank, 1});
}
program
{b, ProgramTensorMetadataDependency::TypeAndRank, components}})
.AddOutputs({{output_tensor, ProgramTensorMetadataDependency::None, output_shape_shader, components}})
.SetDispatchGroupSize(CeilDiv(output_size, 64u))
.AddIndices(outer_dims)
Expand All @@ -156,14 +148,7 @@ Status MatMul::ComputeInternal(ComputeContext& context) const {
return context.RunProgram(program);
}

std::vector<const Tensor*> inputs(has_bias ? 3 : 2);
inputs[0] = a;
inputs[1] = b;
if (has_bias) {
const auto* bias = context.Input(2);
inputs.push_back(bias);
}

std::vector<const Tensor*> inputs = {a, b};
if (intel::CanApplyMatMulIntel(context, helper.M(), helper.N(), helper.K())) {
return intel::ApplyMatMulIntel(context, Activation(), inputs, output_tensor);
}
Expand Down
Loading