Add Fused Activation to OpenCL MatMul
- Added fused activation to MatMul function interface
- Added fused activation to CL backend
- Includes tests for supported Activation Functions in MatMul
Resolves: [COMPMID-6192]
Signed-off-by: Mohammed Suhail Munshi <MohammedSuhail.Munshi@arm.com>
Change-Id: Ie103212b600b60699eaf6a6394d609e6e1f5aba6
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/c/VisualCompute/ComputeLibrary/+/522465
Comments-Addressed: bsgcomp <bsgcomp@arm.com>
Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com>
Tested-by: bsgcomp <bsgcomp@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9714
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Jakub Sujak <jakub.sujak@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
diff --git a/src/gpu/cl/kernels/ClMatMulLowpNativeKernel.cpp b/src/gpu/cl/kernels/ClMatMulLowpNativeKernel.cpp
index d5ecdf7..9bbec90 100644
--- a/src/gpu/cl/kernels/ClMatMulLowpNativeKernel.cpp
+++ b/src/gpu/cl/kernels/ClMatMulLowpNativeKernel.cpp
@@ -98,34 +98,36 @@
{
_type = CLKernelType::GEMM;
}
-Status ClMatMulLowpNativeKernel::validate(const ITensorInfo *lhs, const ITensorInfo *rhs, const ITensorInfo *output, const MatMulKernelInfo &matmul_kernel_info)
+Status ClMatMulLowpNativeKernel::validate(const ITensorInfo *lhs, const ITensorInfo *rhs, const ITensorInfo *dst, const MatMulKernelInfo &matmul_kernel_info, const ActivationLayerInfo &act_info)
{
- ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(lhs, rhs, output);
+ ARM_COMPUTE_UNUSED(act_info);
+ ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(lhs, rhs, dst);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(lhs, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(lhs, rhs);
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));
- if(output->total_size() != 0)
+ if(dst->total_size() != 0)
{
- const TensorInfo tensor_info_output = output->clone()->set_tensor_shape(misc::shape_calculator::compute_matmul_shape(lhs->tensor_shape(), rhs->tensor_shape(), matmul_kernel_info));
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(output, &tensor_info_output);
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(lhs, output);
+ const TensorInfo tensor_info_output = dst->clone()->set_tensor_shape(misc::shape_calculator::compute_matmul_shape(lhs->tensor_shape(), rhs->tensor_shape(), matmul_kernel_info));
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(dst, &tensor_info_output);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(lhs, dst);
}
return Status{};
}
-void ClMatMulLowpNativeKernel::configure(const ClCompileContext &compile_context, ITensorInfo *lhs, ITensorInfo *rhs, ITensorInfo *output, const MatMulKernelInfo &matmul_kernel_info)
+void ClMatMulLowpNativeKernel::configure(const ClCompileContext &compile_context, ITensorInfo *lhs, ITensorInfo *rhs, ITensorInfo *dst, const MatMulKernelInfo &matmul_kernel_info,
+ const ActivationLayerInfo &act_info)
{
- ARM_COMPUTE_ERROR_ON_NULLPTR(lhs, rhs, output, &compile_context, &matmul_kernel_info);
- ARM_COMPUTE_LOG_PARAMS(lhs, rhs, output, matmul_kernel_info);
- ARM_COMPUTE_ERROR_THROW_ON(validate(lhs, rhs, output, matmul_kernel_info));
+ ARM_COMPUTE_ERROR_ON_NULLPTR(lhs, rhs, dst, &compile_context, &matmul_kernel_info);
+ ARM_COMPUTE_LOG_PARAMS(lhs, rhs, dst, matmul_kernel_info);
+ ARM_COMPUTE_ERROR_THROW_ON(validate(lhs, rhs, dst, matmul_kernel_info));
// output tensor auto initialization if not yet initialized
- auto_init_if_empty(*output, lhs->clone()->set_tensor_shape(misc::shape_calculator::compute_matmul_shape(lhs->tensor_shape(), rhs->tensor_shape(), matmul_kernel_info)));
+ 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)));
- const int m = output->dimension(1);
- const int n = output->dimension(0);
+ const int m = dst->dimension(1);
+ const int n = dst->dimension(0);
const int k = matmul_kernel_info.adj_lhs ? lhs->tensor_shape().y() : lhs->tensor_shape().x();
const bool adj_lhs = matmul_kernel_info.adj_lhs;
@@ -133,7 +135,7 @@
int n0 = adjust_vec_size(matmul_kernel_info.n0, n);
// Configure kernel window
- Window win = calculate_max_window(*output, Steps(n0, m0));
+ Window win = calculate_max_window(*dst, Steps(n0, m0));
win = win.collapse(win, Window::DimZ);
IClKernel::configure_internal(win);
@@ -152,7 +154,7 @@
const UniformQuantizationInfo lqinfo = lhs->quantization_info().uniform();
const UniformQuantizationInfo rqinfo = rhs->quantization_info().uniform();
- const UniformQuantizationInfo dqinfo = output->quantization_info().uniform();
+ const UniformQuantizationInfo dqinfo = dst->quantization_info().uniform();
float multiplier = lqinfo.scale * rqinfo.scale / dqinfo.scale;
int output_multiplier = 0;
@@ -166,6 +168,10 @@
build_opts.add_option("-DRHS_OFFSET=" + support::cpp11::to_string(-rqinfo.offset)); // Note this is passed as negative to maintain similarity with CLDirectConv2D
build_opts.add_option("-DDST_OFFSET=" + support::cpp11::to_string(dqinfo.offset)); // Passed as positive (unlike the above two)
+ build_opts.add_option(("-DA_VAL=" + float_to_string_with_full_precision(act_info.a())));
+ build_opts.add_option(("-DB_VAL=" + float_to_string_with_full_precision(act_info.b())));
+ build_opts.add_option("-DACTIVATION_TYPE=" + lower_string(string_from_activation_func(act_info.activation())));
+
std::string kernel_name("mat_mul_native_quantized");
kernel_name += matmul_kernel_info.adj_lhs ? "_t" : "_nt";
kernel_name += matmul_kernel_info.adj_rhs ? "_t" : "_nt";
@@ -177,7 +183,7 @@
_kernel = create_kernel(compile_context, kernel_name, build_opts.options());
// Set config_id for enabling LWS tuning
- const size_t number_of_batches = output->tensor_shape().total_size() / (m * n);
+ const size_t number_of_batches = dst->tensor_shape().total_size() / (m * n);
_config_id = kernel_name;
_config_id += "_";
@@ -203,18 +209,18 @@
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 *output = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST));
- ARM_COMPUTE_ERROR_ON_NULLPTR(lhs, rhs, output);
- ARM_COMPUTE_LOG_PARAMS(lhs, rhs, output);
+ 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));
+ ARM_COMPUTE_ERROR_ON_NULLPTR(lhs, rhs, dst);
+ ARM_COMPUTE_LOG_PARAMS(lhs, rhs, dst);
unsigned int idx = 0;
Window window_collapsed = window.collapse(ICLKernel::window(), Window::DimZ);
add_3d_tensor_nhw_argument(idx, lhs);
add_3d_tensor_nhw_argument(idx, rhs);
- add_3d_tensor_nhw_argument(idx, output);
+ add_3d_tensor_nhw_argument(idx, dst);
enqueue(queue, *this, window_collapsed, lws_hint());
}