arm_compute v19.11.1
diff --git a/src/runtime/CL/functions/CLReduceMean.cpp b/src/runtime/CL/functions/CLReduceMean.cpp
index a3634cd..c5de43d 100644
--- a/src/runtime/CL/functions/CLReduceMean.cpp
+++ b/src/runtime/CL/functions/CLReduceMean.cpp
@@ -26,20 +26,81 @@
#include "arm_compute/core/CL/CLValidate.h"
#include "arm_compute/core/CL/ICLTensor.h"
#include "arm_compute/core/CL/kernels/CLReductionOperationKernel.h"
+#include "arm_compute/core/Error.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/core/utils/helpers/tensor_transform.h"
+#include "arm_compute/core/utils/misc/ShapeCalculator.h"
#include "arm_compute/runtime/CL/CLScheduler.h"
#include "support/ToolchainSupport.h"
namespace arm_compute
{
+namespace
+{
+Status validate_config(const ITensorInfo *input, const Coordinates &reduction_axis, bool keep_dims, const ITensorInfo *output)
+{
+ ARM_COMPUTE_UNUSED(keep_dims);
+ ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
+ ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F16, DataType::F32);
+ ARM_COMPUTE_RETURN_ERROR_ON(reduction_axis.num_dimensions() < 1);
+ ARM_COMPUTE_RETURN_ERROR_ON(reduction_axis.num_dimensions() > input->num_dimensions());
+
+ const unsigned int reduction_ops = reduction_axis.num_dimensions();
+ const int input_dims = input->num_dimensions();
+ Coordinates axis_local = reduction_axis;
+
+ for(unsigned int i = 0; i < axis_local.num_dimensions(); ++i)
+ {
+ //axis: The dimensions to reduce. Must be in the range [-rank(input_tensor), rank(input_tensor)).
+ ARM_COMPUTE_RETURN_ERROR_ON(axis_local[i] < (-static_cast<int>(input->num_dimensions())));
+ ARM_COMPUTE_RETURN_ERROR_ON(axis_local[i] >= static_cast<int>(input->num_dimensions()));
+ }
+
+ if(output->tensor_shape().total_size() != 0)
+ {
+ // Only validate if not using auto_init for the output tensor
+ TensorShape out_shape = input->tensor_shape();
+ // Validate output_shape only if not using auto_init
+ convert_negative_axis(axis_local, input_dims);
+ std::sort(axis_local.begin(), axis_local.begin() + reduction_ops);
+ for(unsigned int i = 0; i < reduction_ops; ++i)
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON(axis_local[i] > 3);
+ ARM_COMPUTE_RETURN_ERROR_ON(static_cast<unsigned int>(axis_local[i]) > input->num_dimensions() - 1);
+ if(output->total_size() > 0 && keep_dims)
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON(output->dimension(axis_local[i]) != 1);
+ }
+ if(keep_dims)
+ {
+ out_shape.set(axis_local[i], 1);
+ }
+ else
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON(i > static_cast<unsigned int>(axis_local[i]));
+ const unsigned int remove_index = axis_local[i] - i;
+ ARM_COMPUTE_RETURN_ERROR_ON(remove_index >= out_shape.num_dimensions());
+ out_shape.remove_dimension(remove_index);
+ }
+ }
+ const TensorInfo out_info = input->clone()->set_tensor_shape(out_shape);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(output, &out_info);
+ }
+ return Status{};
+}
+}
CLReduceMean::CLReduceMean(std::shared_ptr<IMemoryManager> memory_manager)
: _memory_group(std::move(memory_manager)), _reduction_kernels(), _reduced_outs(), _reshape(), _reduction_ops(), _keep_dims()
{
}
void CLReduceMean::configure(ICLTensor *input, const Coordinates &reduction_axis, bool keep_dims, ICLTensor *output)
{
- ARM_COMPUTE_ERROR_ON_NULLPTR(input);
+ // Perform validate step
+ ARM_COMPUTE_ERROR_THROW_ON(CLReduceMean::validate(input->info(), reduction_axis, keep_dims, output->info()));
+ // Output auto inizialitation if not yet initialized
+ const TensorShape output_shape = arm_compute::misc::shape_calculator::calculate_reduce_mean_shape(input, reduction_axis, keep_dims);
+ auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(output_shape));
_reduction_ops = reduction_axis.num_dimensions();
_reduction_kernels.resize(_reduction_ops);
@@ -49,14 +110,10 @@
Coordinates axis_local = reduction_axis;
const int input_dims = input->info()->num_dimensions();
- // Convert negative axis
- for(unsigned int i = 0; i < _reduction_ops; ++i)
- {
- axis_local[i] = wrap_around(axis_local[i], input_dims);
- }
+ convert_negative_axis(axis_local, input_dims);
// Perform reduction for every axis
- for(unsigned int i = 0; i < _reduction_ops; ++i)
+ for(int i = 0; i < _reduction_ops; ++i)
{
TensorShape out_shape = i == 0 ? input->info()->tensor_shape() : (&_reduced_outs[i - 1])->info()->tensor_shape();
out_shape.set(axis_local[i], 1);
@@ -75,7 +132,7 @@
}
// Allocate intermediate tensors
- for(unsigned int i = 0; i < _reduction_ops - (keep_dims ? 1 : 0); ++i)
+ for(int i = 0; i < _reduction_ops - (keep_dims ? 1 : 0); ++i)
{
_reduced_outs[i].allocator()->allocate();
}
@@ -88,7 +145,7 @@
// We have to sort the reduction axis vectors in order for remove_dimension
// to work properly
std::sort(axis_local.begin(), axis_local.begin() + _reduction_ops);
- for(unsigned int i = 0; i < _reduction_ops; ++i)
+ for(int i = 0; i < _reduction_ops; ++i)
{
out_shape.remove_dimension(axis_local[i] - i);
}
@@ -99,55 +156,16 @@
Status CLReduceMean::validate(const ITensorInfo *input, const Coordinates &reduction_axis, bool keep_dims, const ITensorInfo *output)
{
- ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input);
- ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input);
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F16, DataType::F32);
- ARM_COMPUTE_RETURN_ERROR_ON(reduction_axis.num_dimensions() > input->num_dimensions());
-
- TensorShape out_shape = input->tensor_shape();
-
- Coordinates axis_sorted = reduction_axis;
- const unsigned int reduction_ops = reduction_axis.num_dimensions();
- const int input_dims = input->num_dimensions();
-
- // Convert negative axis
- for(unsigned int i = 0; i < reduction_ops; ++i)
- {
- axis_sorted[i] = wrap_around(axis_sorted[i], input_dims);
- }
-
- std::sort(axis_sorted.begin(), axis_sorted.begin() + reduction_ops);
- for(unsigned int i = 0; i < reduction_ops; ++i)
- {
- ARM_COMPUTE_RETURN_ERROR_ON(axis_sorted[i] > 3);
- ARM_COMPUTE_RETURN_ERROR_ON(static_cast<unsigned int>(axis_sorted[i]) > input->num_dimensions() - 1);
- if(output->total_size() > 0 && keep_dims)
- {
- ARM_COMPUTE_RETURN_ERROR_ON(output->dimension(axis_sorted[i]) != 1);
- }
- if(keep_dims)
- {
- out_shape.set(axis_sorted[i], 1);
- }
- else
- {
- out_shape.remove_dimension(axis_sorted[i] - i);
- }
- }
-
- const TensorInfo out_info = input->clone()->set_tensor_shape(out_shape);
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(output, &out_info);
-
- return Status{};
+ return validate_config(input, reduction_axis, keep_dims, output);
}
void CLReduceMean::run()
{
MemoryGroupResourceScope scope_mg(_memory_group);
- for(unsigned int i = 0; i < _reduction_ops; ++i)
+ for(auto &kernel : _reduction_kernels)
{
- _reduction_kernels[i].run();
+ kernel.run();
}
if(!_keep_dims)