arm_compute v17.12
diff --git a/src/runtime/CL/functions/CLSoftmaxLayer.cpp b/src/runtime/CL/functions/CLSoftmaxLayer.cpp
index 7505a2c..7c96111 100644
--- a/src/runtime/CL/functions/CLSoftmaxLayer.cpp
+++ b/src/runtime/CL/functions/CLSoftmaxLayer.cpp
@@ -23,40 +23,59 @@
*/
#include "arm_compute/runtime/CL/functions/CLSoftmaxLayer.h"
+#include "arm_compute/core/CL/CLHelpers.h"
+#include "arm_compute/core/CL/ICLKernel.h"
#include "arm_compute/core/CL/kernels/CLSoftmaxLayerKernel.h"
#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/core/Utils.h"
#include "arm_compute/runtime/CL/CLMemoryGroup.h"
#include "arm_compute/runtime/CL/CLScheduler.h"
using namespace arm_compute;
CLSoftmaxLayer::CLSoftmaxLayer(std::shared_ptr<IMemoryManager> memory_manager)
- : _memory_group(std::move(memory_manager)), _max_kernel(), _shift_exp_sum_kernel(), _norm_kernel(), _max(), _sum(), _tmp()
+ : _memory_group(std::move(memory_manager)), _max_kernel(), _shift_exp_sum_kernel(), _max_shift_exp_sum_kernel(), _norm_kernel(), _max(), _sum(), _tmp(), _run_legacy_path(false)
{
}
-void CLSoftmaxLayer::configure(const ICLTensor *input, ICLTensor *output)
+void CLSoftmaxLayer::configure(const ICLTensor *input, ICLTensor *output, float beta)
{
- ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::QS16, DataType::F16, DataType::F32);
+ // Perform validation step
+ ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
+ ARM_COMPUTE_ERROR_THROW_ON(CLSoftmaxLayer::validate(input->info(), output->info()));
// Create intermediate tensors shapes
- _tmp.allocator()->init(TensorInfo(input->info()->tensor_shape(), input->info()->num_channels(), input->info()->data_type(), input->info()->fixed_point_position()));
+ const TensorInfo input_info = input->info()->clone()->reset_padding().set_is_resizable(true);
+ DataType tmp_data_type = is_data_type_quantized_asymmetric(input->info()->data_type()) ? DataType::S32 : input->info()->data_type();
+ TensorInfo tensor_info_tmp(input_info.clone()->set_data_type(tmp_data_type));
+ _tmp.allocator()->init(tensor_info_tmp);
- TensorShape shape = input->info()->tensor_shape();
- shape.set(0, 1);
- TensorInfo tensor_info_max_sum(shape, input->info()->num_channels(), input->info()->data_type(), input->info()->fixed_point_position());
- _max.allocator()->init(tensor_info_max_sum);
- _sum.allocator()->init(tensor_info_max_sum);
+ TensorShape max_sum_shape = input->info()->tensor_shape();
+ max_sum_shape.set(0, 1);
+ _max.allocator()->init(input_info.clone()->set_tensor_shape(max_sum_shape));
+ _sum.allocator()->init(input_info.clone()->set_tensor_shape(max_sum_shape).set_data_type(tmp_data_type));
+
+ // Set GPU target to kernels
+ _max_shift_exp_sum_kernel.set_target(CLScheduler::get().target());
// Manage intermediate buffers
_memory_group.manage(&_tmp);
_memory_group.manage(&_max);
_memory_group.manage(&_sum);
- // Configure Kernels
- _max_kernel.configure(input, &_max);
- _shift_exp_sum_kernel.configure(input, &_max, &_tmp, &_sum);
- _norm_kernel.configure(&_tmp, &_sum, output);
+ // Configure kernels
+ _run_legacy_path = is_data_type_quantized_asymmetric(input->info()->data_type());
+ if(_run_legacy_path)
+ {
+ _max_kernel.configure(input, &_max);
+ _shift_exp_sum_kernel.configure(input, &_max, &_tmp, &_sum, beta);
+ }
+ else
+ {
+ _max_shift_exp_sum_kernel.configure(input, &_max, &_tmp, &_sum, beta);
+ }
+ _norm_kernel.configure(&_tmp, &_sum, output, beta);
// Allocate intermediate buffers
_tmp.allocator()->allocate();
@@ -64,12 +83,48 @@
_sum.allocator()->allocate();
}
+Status CLSoftmaxLayer::validate(const ITensorInfo *input, const ITensorInfo *output)
+{
+ ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
+
+ // Create intermediate tensor info
+ DataType tmp_data_type = is_data_type_quantized_asymmetric(input->data_type()) ? DataType::S32 : input->data_type();
+ TensorInfo tensor_info_tmp(input->clone()->set_data_type(tmp_data_type));
+
+ TensorShape max_sum_shape = input->tensor_shape();
+ max_sum_shape.set(0, 1);
+ TensorInfo tensor_info_max(input->clone()->set_tensor_shape(max_sum_shape));
+ TensorInfo tensor_info_sum(input->clone()->set_tensor_shape(max_sum_shape).set_data_type(tmp_data_type).set_quantization_info(QuantizationInfo()));
+
+ bool run_legacy_path = is_data_type_quantized_asymmetric(input->data_type());
+ if(run_legacy_path)
+ {
+ ARM_COMPUTE_RETURN_ON_ERROR(CLLogits1DMaxKernel::validate(input, &tensor_info_max));
+ ARM_COMPUTE_RETURN_ON_ERROR(CLLogits1DShiftExpSumKernel::validate(input, &tensor_info_max, &tensor_info_tmp, &tensor_info_sum));
+ }
+ else
+ {
+ ARM_COMPUTE_RETURN_ON_ERROR(CLLogits1DMaxShiftExpSumKernel::validate(input, &tensor_info_max, &tensor_info_tmp, &tensor_info_sum));
+ }
+ ARM_COMPUTE_RETURN_ON_ERROR(CLLogits1DNormKernel::validate(&tensor_info_tmp, &tensor_info_sum, output));
+
+ return Status{};
+}
+
void CLSoftmaxLayer::run()
{
_memory_group.acquire();
- CLScheduler::get().enqueue(_max_kernel, false);
- CLScheduler::get().enqueue(_shift_exp_sum_kernel, false);
+ // Force to use the new fused kernel
+ if(_run_legacy_path)
+ {
+ CLScheduler::get().enqueue(_max_kernel, false);
+ CLScheduler::get().enqueue(_shift_exp_sum_kernel, false);
+ }
+ else
+ {
+ CLScheduler::get().enqueue(_max_shift_exp_sum_kernel, false);
+ }
CLScheduler::get().enqueue(_norm_kernel);
_memory_group.release();