Add Bias to MatMul Kernels and add support for use in Fully Connected Layer
Resolves: [COMPMID-6316]
Signed-off-by: Mohammed Suhail Munshi <MohammedSuhail.Munshi@arm.com>
Change-Id: I08e6bac9e6b46b76978da0dc6a48ccfe3dde5086
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9833
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
diff --git a/src/gpu/cl/kernels/ClMatMulNativeMMULKernel.cpp b/src/gpu/cl/kernels/ClMatMulNativeMMULKernel.cpp
index 4630ec0..0efcfb1 100644
--- a/src/gpu/cl/kernels/ClMatMulNativeMMULKernel.cpp
+++ b/src/gpu/cl/kernels/ClMatMulNativeMMULKernel.cpp
@@ -60,9 +60,9 @@
Status validate_matmul_kernel_info(const MatMulKernelInfo &matmul_kernel_info)
{
const bool adj_lhs = matmul_kernel_info.adj_lhs;
- const int m0 = matmul_kernel_info.m0;
- const int n0 = matmul_kernel_info.n0;
- const int k0 = matmul_kernel_info.k0;
+ const int m0 = matmul_kernel_info.m0;
+ const int n0 = matmul_kernel_info.n0;
+ const int k0 = matmul_kernel_info.k0;
// Validate M0
ARM_COMPUTE_RETURN_ERROR_ON_MSG(m0 < 1, "Only positive integers are supported for M0");
@@ -149,7 +149,7 @@
_type = CLKernelType::GEMM;
}
-Status ClMatMulNativeMMULKernel::validate(const ITensorInfo *lhs, const ITensorInfo *rhs, const ITensorInfo *dst, const MatMulKernelInfo &matmul_kernel_info)
+Status ClMatMulNativeMMULKernel::validate(const ITensorInfo *lhs, const ITensorInfo *rhs, const ITensorInfo *bias, const ITensorInfo *dst, const MatMulKernelInfo &matmul_kernel_info)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(lhs, rhs, dst);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(lhs, 1, DataType::F32, DataType::F16);
@@ -158,20 +158,29 @@
ARM_COMPUTE_RETURN_ON_ERROR(validate_matmul_kernel_info(matmul_kernel_info));
ARM_COMPUTE_RETURN_ON_ERROR(validate_input_shapes(lhs->tensor_shape(), rhs->tensor_shape(), matmul_kernel_info));
+ const TensorShape expected_output_shape = misc::shape_calculator::compute_matmul_shape(lhs->tensor_shape(), rhs->tensor_shape(), matmul_kernel_info);
+
if(dst->total_size() != 0)
{
- const TensorInfo tensor_info_dst = dst->clone()->set_tensor_shape(misc::shape_calculator::compute_matmul_shape(lhs->tensor_shape(), rhs->tensor_shape(), matmul_kernel_info));
+ const TensorInfo tensor_info_dst = dst->clone()->set_tensor_shape(expected_output_shape);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(dst, &tensor_info_dst);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(lhs, dst);
}
+ if(bias != nullptr)
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG((bias->num_dimensions() > 1), "Multi dimensional bias is unsupported.");
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(bias->dimension(0) != expected_output_shape[0], "First dimension of bias and output tensors must match.");
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(lhs, bias);
+ }
+
return Status{};
}
-void ClMatMulNativeMMULKernel::configure(const ClCompileContext &compile_context, ITensorInfo *lhs, ITensorInfo *rhs, ITensorInfo *dst, const MatMulKernelInfo &matmul_kernel_info)
+void ClMatMulNativeMMULKernel::configure(const ClCompileContext &compile_context, ITensorInfo *lhs, ITensorInfo *rhs, ITensorInfo *bias, ITensorInfo *dst, const MatMulKernelInfo &matmul_kernel_info)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(lhs, rhs, dst);
- ARM_COMPUTE_LOG_PARAMS(lhs, rhs, dst, matmul_kernel_info);
- ARM_COMPUTE_ERROR_THROW_ON(validate(lhs, rhs, dst, matmul_kernel_info));
+ ARM_COMPUTE_LOG_PARAMS(lhs, rhs, bias, dst, matmul_kernel_info);
+ ARM_COMPUTE_ERROR_THROW_ON(validate(lhs, rhs, bias, dst, matmul_kernel_info));
// dst tensor auto initialization if not yet initialized
auto_init_if_empty(*dst, lhs->clone()->set_tensor_shape(misc::shape_calculator::compute_matmul_shape(lhs->tensor_shape(), rhs->tensor_shape(), matmul_kernel_info)));
@@ -207,6 +216,7 @@
build_opts.add_option("-DMMUL_M0=" + support::cpp11::to_string(mmul_m0));
build_opts.add_option("-DMMUL_N0=" + support::cpp11::to_string(mmul_n0));
build_opts.add_option("-DMMUL_K0=" + support::cpp11::to_string(mmul_k0));
+ build_opts.add_option_if(bias != nullptr, "-DBIAS");
std::string kernel_name("mat_mul_native_mmul");
kernel_name += matmul_kernel_info.adj_lhs ? "_t" : "_nt";
@@ -239,15 +249,20 @@
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window);
- const ICLTensor *lhs = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_0));
- const ICLTensor *rhs = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_1));
- ICLTensor *dst = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST));
+ const ICLTensor *lhs = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_0));
+ const ICLTensor *rhs = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_1));
+ const ICLTensor *bias = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_2)); // nullptr if bias is not present
+ ICLTensor *dst = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST));
ARM_COMPUTE_ERROR_ON_NULLPTR(lhs, rhs, dst);
- ARM_COMPUTE_LOG_PARAMS(lhs, rhs, dst);
+ ARM_COMPUTE_LOG_PARAMS(lhs, rhs, bias, dst);
unsigned int idx = 0;
add_3d_tensor_nhw_argument(idx, lhs);
add_3d_tensor_nhw_argument(idx, rhs);
+ if(bias != nullptr)
+ {
+ add_3d_tensor_nhw_argument(idx, bias);
+ }
add_3d_tensor_nhw_argument(idx, dst);
// Pass m and n at runtime as signed ints, to ensure results of any subtractions they could be operand in, would still be signed.