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());
}
diff --git a/src/gpu/cl/kernels/ClMatMulLowpNativeKernel.h b/src/gpu/cl/kernels/ClMatMulLowpNativeKernel.h
index d70ff30..67d1a66 100644
--- a/src/gpu/cl/kernels/ClMatMulLowpNativeKernel.h
+++ b/src/gpu/cl/kernels/ClMatMulLowpNativeKernel.h
@@ -24,6 +24,7 @@
#ifndef ACL_SRC_GPU_CL_KERNELS_CLMATMULLOWPNATIVEKERNEL
#define ACL_SRC_GPU_CL_KERNELS_CLMATMULLOWPNATIVEKERNEL
+#include "arm_compute/core/ActivationLayerInfo.h"
#include "src/core/common/Macros.h"
#include "src/gpu/cl/ClCompileContext.h"
#include "src/gpu/cl/IClKernel.h"
@@ -43,22 +44,24 @@
ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE(ClMatMulLowpNativeKernel);
/** Initialise the kernel's input and output.
*
- * @param[in] compile_context The compile context to be used.
- * @param[in] lhs Input tensor for the LHS matrix. Data type supported: QASYMM8_SIGNED/QASYMM8.
- * Dimensions above 2 are collapsed onto dimension 2 and represent the batch.
- * @param[in] rhs Input tensor for the RHS matrix. Data type supported: same as @p lhs.
- * Dimensions above 2 are collapsed onto dimension 2 and represent the batch.
- * @param[out] dst Output tensor info. Data type supported: same as @p lhs
- * @param[in] matmul_info Attributes for Batch MatMul Kernel
+ * @param[in] compile_context The compile context to be used.
+ * @param[in] lhs Input tensor for the LHS matrix. Data type supported: QASYMM8_SIGNED/QASYMM8.
+ * Dimensions above 2 are collapsed onto dimension 2 and represent the batch.
+ * @param[in] rhs Input tensor for the RHS matrix. Data type supported: same as @p lhs.
+ * Dimensions above 2 are collapsed onto dimension 2 and represent the batch.
+ * @param[out] dst Output tensor info. Data type supported: same as @p lhs
+ * @param[in] matmul_kernel_info Attributes for Batch MatMul Kernel
+ * @param[in] act_info Class containing information about fused activation function.
*/
- void configure(const ClCompileContext &compile_context, ITensorInfo *lhs, ITensorInfo *rhs, ITensorInfo *dst, const MatMulKernelInfo &matmul_info);
+ void configure(const ClCompileContext &compile_context, ITensorInfo *lhs, ITensorInfo *rhs, ITensorInfo *dst, const MatMulKernelInfo &matmul_kernel_info,
+ const ActivationLayerInfo &act_info = ActivationLayerInfo());
/** Static function to check if given info will lead to a valid configuration
*
* Similar to @ref ClMatMulLowpNativeKernel::configure()
*
* @return a status
*/
- static Status validate(const ITensorInfo *lhs, const ITensorInfo *rhs, const ITensorInfo *dst, const MatMulKernelInfo &matmul_info);
+ static Status validate(const ITensorInfo *lhs, const ITensorInfo *rhs, const ITensorInfo *dst, const MatMulKernelInfo &matmul_kernel_info, const ActivationLayerInfo &act_info = ActivationLayerInfo());
// Inherited methods overridden:
void run_op(ITensorPack &tensors, const Window &window, cl::CommandQueue &queue) override;
diff --git a/src/gpu/cl/kernels/ClMatMulNativeKernel.cpp b/src/gpu/cl/kernels/ClMatMulNativeKernel.cpp
index 8f53c19..205396a 100644
--- a/src/gpu/cl/kernels/ClMatMulNativeKernel.cpp
+++ b/src/gpu/cl/kernels/ClMatMulNativeKernel.cpp
@@ -112,7 +112,7 @@
ARM_COMPUTE_RETURN_ERROR_ON_MSG(!export_to_cl_image(rhs), "Export to CLImage is not supported for this device/configuration");
}
- return Status {};
+ return Status{};
}
}
ClMatMulNativeKernel::ClMatMulNativeKernel()
@@ -120,8 +120,9 @@
_type = CLKernelType::GEMM;
}
-Status ClMatMulNativeKernel::validate(const ITensorInfo *lhs, const ITensorInfo *rhs, const ITensorInfo *dst, const MatMulKernelInfo &matmul_kernel_info)
+Status ClMatMulNativeKernel::validate(const ITensorInfo *lhs, const ITensorInfo *rhs, const ITensorInfo *dst, const MatMulKernelInfo &matmul_kernel_info, const ActivationLayerInfo &act_info)
{
+ 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::F32, DataType::F16);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(lhs, rhs);
@@ -138,7 +139,8 @@
return Status{};
}
-void ClMatMulNativeKernel::configure(const ClCompileContext &compile_context, ITensorInfo *lhs, ITensorInfo *rhs, ITensorInfo *dst, const MatMulKernelInfo &matmul_kernel_info)
+void ClMatMulNativeKernel::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, dst, &compile_context, &matmul_kernel_info);
ARM_COMPUTE_LOG_PARAMS(lhs, rhs, dst, matmul_kernel_info);
@@ -176,6 +178,11 @@
build_opts.add_option("-DK=" + support::cpp11::to_string(k));
build_opts.add_option_if_else(_export_rhs_to_cl_image, "-DRHS_TENSOR_TYPE=IMAGE", "-DRHS_TENSOR_TYPE=BUFFER");
+ // Define values for activation function
+ 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");
kernel_name += matmul_kernel_info.adj_lhs ? "_t" : "_nt";
kernel_name += matmul_kernel_info.adj_rhs ? "_t" : "_nt";
@@ -218,8 +225,8 @@
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));
+ 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);
diff --git a/src/gpu/cl/kernels/ClMatMulNativeKernel.h b/src/gpu/cl/kernels/ClMatMulNativeKernel.h
index f706256..02d8ac3 100644
--- a/src/gpu/cl/kernels/ClMatMulNativeKernel.h
+++ b/src/gpu/cl/kernels/ClMatMulNativeKernel.h
@@ -42,22 +42,24 @@
ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE(ClMatMulNativeKernel);
/** Initialise the kernel's input and output.
*
- * @param[in] compile_context The compile context to be used.
- * @param[in] lhs Input tensor for the LHS matrix. Data type supported: F32/F16.
- * Dimensions above 2 are collapsed onto dimension 2 and represent the batch.
- * @param[in] rhs Input tensor for the RHS matrix. Data type supported: same as @p lhs.
- * Dimensions above 2 are collapsed onto dimension 2 and represent the batch.
- * @param[out] dst Output tensor info. Data type supported: same as @p lhs
- * @param[in] matmul_info Attributes for Batch MatMul Kernel
+ * @param[in] compile_context The compile context to be used.
+ * @param[in] lhs Input tensor for the LHS matrix. Data type supported: F32/F16.
+ * Dimensions above 2 are collapsed onto dimension 2 and represent the batch.
+ * @param[in] rhs Input tensor for the RHS matrix. Data type supported: same as @p lhs.
+ * Dimensions above 2 are collapsed onto dimension 2 and represent the batch.
+ * @param[out] dst Output tensor info. Data type supported: same as @p lhs
+ * @param[in] matmul_kernel_info Attributes for Batch MatMul Kernel
+ * @param[in] act_info Specifies activation function to use after Matrix multiplication. Default is Identity function.
*/
- void configure(const ClCompileContext &compile_context, ITensorInfo *lhs, ITensorInfo *rhs, ITensorInfo *dst, const MatMulKernelInfo &matmul_info);
+ void configure(const ClCompileContext &compile_context, ITensorInfo *lhs, ITensorInfo *rhs, ITensorInfo *dst, const MatMulKernelInfo &matmul_kernel_info,
+ const ActivationLayerInfo &act_info = ActivationLayerInfo());
/** Static function to check if given info will lead to a valid configuration
*
* Similar to @ref ClMatMulNativeKernel::configure()
*
* @return a status
*/
- static Status validate(const ITensorInfo *lhs, const ITensorInfo *rhs, const ITensorInfo *dst, const MatMulKernelInfo &matmul_info);
+ static Status validate(const ITensorInfo *lhs, const ITensorInfo *rhs, const ITensorInfo *dst, const MatMulKernelInfo &matmul_kernel_info, const ActivationLayerInfo &act_info = ActivationLayerInfo());
// Inherited methods overridden:
void run_op(ITensorPack &tensors, const Window &window, cl::CommandQueue &queue) override;
diff --git a/src/gpu/cl/operators/ClMatMul.cpp b/src/gpu/cl/operators/ClMatMul.cpp
index 3822c16..c453761 100644
--- a/src/gpu/cl/operators/ClMatMul.cpp
+++ b/src/gpu/cl/operators/ClMatMul.cpp
@@ -47,7 +47,7 @@
{
}
-Status ClMatMul::validate(const ITensorInfo *lhs, const ITensorInfo *rhs, const ITensorInfo *dst, const MatMulInfo &matmul_info)
+Status ClMatMul::validate(const ITensorInfo *lhs, const ITensorInfo *rhs, const ITensorInfo *dst, const MatMulInfo &matmul_info, const ActivationLayerInfo &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, DataType::F16, DataType::F32);
@@ -57,15 +57,15 @@
std::unique_ptr<IClMatMulNativeKernelConfig> t = ClMatMulNativeKernelConfigurationFactory::create(gpu_target);
- MatMulKernelInfo kernel_info = t->configure(lhs, rhs, matmul_info);
+ const MatMulKernelInfo kernel_info = t->configure(lhs, rhs, matmul_info);
- bool is_quantized = is_data_type_quantized_asymmetric(lhs->data_type());
+ const bool is_quantized = is_data_type_quantized_asymmetric(lhs->data_type());
- return is_quantized ? ClMatMulLowpNativeKernel::validate(lhs, rhs, dst, kernel_info) :
- ClMatMulNativeKernel::validate(lhs, rhs, dst, kernel_info);
+ return is_quantized ? ClMatMulLowpNativeKernel::validate(lhs, rhs, dst, kernel_info, act_info) :
+ ClMatMulNativeKernel::validate(lhs, rhs, dst, kernel_info, act_info);
}
-void ClMatMul::configure(const CLCompileContext &compile_context, ITensorInfo *lhs, ITensorInfo *rhs, ITensorInfo *dst, const MatMulInfo &matmul_info)
+void ClMatMul::configure(const CLCompileContext &compile_context, ITensorInfo *lhs, ITensorInfo *rhs, ITensorInfo *dst, const MatMulInfo &matmul_info, const ActivationLayerInfo &act_info)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(lhs, rhs, dst);
ARM_COMPUTE_LOG_PARAMS(lhs, rhs, dst, matmul_info);
@@ -86,14 +86,14 @@
_matmul_lowp_native_kernel->set_target(gpu_target);
// Configure the low-precision native matrix multiply kernel
- _matmul_lowp_native_kernel->configure(compile_context, lhs, rhs, dst, kernel_info);
+ _matmul_lowp_native_kernel->configure(compile_context, lhs, rhs, dst, kernel_info, act_info);
}
else
{
_matmul_native_kernel->set_target(gpu_target);
// Configure the native matrix multiply kernel
- _matmul_native_kernel->configure(compile_context, lhs, rhs, dst, kernel_info);
+ _matmul_native_kernel->configure(compile_context, lhs, rhs, dst, kernel_info, act_info);
}
}
diff --git a/src/gpu/cl/operators/ClMatMul.h b/src/gpu/cl/operators/ClMatMul.h
index 6aba801..9dce528 100644
--- a/src/gpu/cl/operators/ClMatMul.h
+++ b/src/gpu/cl/operators/ClMatMul.h
@@ -21,14 +21,14 @@
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
-#ifndef ACL_ARM_COMPUTE_SRC_GPU_CL_OPERATORS_CLMATMUL
-#define ACL_ARM_COMPUTE_SRC_GPU_CL_OPERATORS_CLMATMUL
+#ifndef ACL_SRC_GPU_CL_OPERATORS_CLMATMUL
+#define ACL_SRC_GPU_CL_OPERATORS_CLMATMUL
#include "arm_compute/core/ActivationLayerInfo.h"
#include "arm_compute/core/MatMulInfo.h"
#include "src/gpu/cl/IClOperator.h"
-#include "src/gpu/cl/kernels/ClMatMulNativeKernel.h"
#include "src/gpu/cl/kernels/ClMatMulLowpNativeKernel.h"
+#include "src/gpu/cl/kernels/ClMatMulNativeKernel.h"
#include <memory>
@@ -71,24 +71,26 @@
* @param[in] rhs Right-hand side tensor info. Data types supported: same as @p lhs.
* @param[out] dst Output tensor to store the result of the batched matrix multiplication. Data types supported: same as @p lhs.
* @param[in] matmul_info Contains MatMul operation information described in @ref MatMulInfo.
+ * @param[in] act_info Class containing information about fused activation function.
*/
- void configure(const CLCompileContext &compile_context, ITensorInfo *lhs, ITensorInfo *rhs, ITensorInfo *dst, const MatMulInfo &matmul_info);
+ void configure(const CLCompileContext &compile_context, ITensorInfo *lhs, ITensorInfo *rhs, ITensorInfo *dst, const MatMulInfo &matmul_info,
+ const ActivationLayerInfo &act_info = ActivationLayerInfo());
/** Static function to check if given info will lead to a valid configuration
*
* Similar to @ref ClMatMul::configure()
*
* @return a status
*/
- static Status validate(const ITensorInfo *lhs, const ITensorInfo *rhs, const ITensorInfo *dst, const MatMulInfo &matmul_info);
+ static Status validate(const ITensorInfo *lhs, const ITensorInfo *rhs, const ITensorInfo *dst, const MatMulInfo &matmul_info, const ActivationLayerInfo &act_info = ActivationLayerInfo());
// Inherited methods overridden:
void run(ITensorPack &tensors) override;
private:
- std::unique_ptr<kernels::ClMatMulNativeKernel> _matmul_native_kernel{nullptr};
- std::unique_ptr<kernels::ClMatMulLowpNativeKernel> _matmul_lowp_native_kernel{nullptr};
+ std::unique_ptr<kernels::ClMatMulNativeKernel> _matmul_native_kernel{ nullptr };
+ std::unique_ptr<kernels::ClMatMulLowpNativeKernel> _matmul_lowp_native_kernel{ nullptr };
bool _is_quantized{ false };
};
} // namespace opencl
} // namespace arm_compute
-#endif /* ACL_ARM_COMPUTE_SRC_GPU_CL_OPERATORS_CLMATMUL */
+#endif /* ACL_SRC_GPU_CL_OPERATORS_CLMATMUL */