COMPMID-2062 Rework CL ConcatenateLayer
Change-Id: I5a60cd0e822b8912132a6785057921bbf6ef8f7f
Signed-off-by: Michalis Spyrou <michalis.spyrou@arm.com>
Reviewed-on: https://review.mlplatform.org/c/951
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
diff --git a/src/runtime/CL/functions/CLConcatenateLayer.cpp b/src/runtime/CL/functions/CLConcatenateLayer.cpp
index 13164fd..7edea3e 100644
--- a/src/runtime/CL/functions/CLConcatenateLayer.cpp
+++ b/src/runtime/CL/functions/CLConcatenateLayer.cpp
@@ -38,39 +38,16 @@
namespace arm_compute
{
CLConcatenateLayer::CLConcatenateLayer()
- : _concat_function(nullptr),
- _hconcat_kernels(),
+ : _concat_kernels(),
_num_inputs(0),
_axis(Window::DimX)
{
}
-Status CLConcatenateLayer::validate_h_concatenate(const std::vector<ITensorInfo *> &inputs_vector, const ITensorInfo *output) // NOLINT
+void CLConcatenateLayer::configure(const std::vector<ICLTensor *> &inputs_vector, ICLTensor *output, DataLayoutDimension axis)
{
- const unsigned int num_inputs = inputs_vector.size();
-
- ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output);
- ARM_COMPUTE_RETURN_ERROR_ON(num_inputs < 2);
-
- // Output auto inizialitation if not yet initialized
- TensorInfo tmp_output_info = *output->clone();
- const TensorShape output_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(inputs_vector, Window::DimY);
- auto_init_if_empty(tmp_output_info, output_shape, 1, inputs_vector[0]->data_type());
-
- unsigned int height_offset = 0;
- // Validate generic case of WidthConcatenate kernel
- for(const auto &input : inputs_vector)
- {
- ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input);
- ARM_COMPUTE_RETURN_ON_ERROR(CLHeightConcatenateLayerKernel::validate(input, height_offset, &tmp_output_info));
- height_offset += input->dimension(Window::DimY);
- }
-
- return Status{};
-}
-
-void CLConcatenateLayer::configure_h_concatenate(std::vector<ICLTensor *> inputs_vector, ICLTensor *output) // NOLINT
-{
+ ARM_COMPUTE_ERROR_ON(output == nullptr);
+ _axis = get_data_layout_dimension_index(output->info()->data_layout(), axis);
_num_inputs = inputs_vector.size();
std::vector<ITensorInfo *> inputs_vector_info(inputs_vector.size());
@@ -79,103 +56,166 @@
ARM_COMPUTE_ERROR_ON_NULLPTR(t);
return t->info();
});
-
- const TensorShape output_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(inputs_vector, Window::DimY);
+ TensorShape output_shape{};
+ if(_axis == Window::DimZ)
+ {
+ output_shape = arm_compute::misc::shape_calculator::calculate_depth_concatenate_shape(inputs_vector);
+ }
+ else
+ {
+ output_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(inputs_vector, _axis);
+ }
// Output auto inizialitation if not yet initialized
auto_init_if_empty(*output->info(), output_shape, 1, inputs_vector[0]->info()->data_type());
+ ARM_COMPUTE_ERROR_THROW_ON(CLConcatenateLayer::validate(inputs_vector_info, output->info(), axis));
- ARM_COMPUTE_ERROR_THROW_ON(CLConcatenateLayer::validate_h_concatenate(inputs_vector_info, output->info()));
-
- // Configure generic case WidthConcatenate kernels
- _hconcat_kernels = arm_compute::support::cpp14::make_unique<CLHeightConcatenateLayerKernel[]>(_num_inputs);
-
- unsigned int height_offset = 0;
- unsigned int i = 0;
- std::transform(inputs_vector.begin(), inputs_vector.end(), inputs_vector.begin(), [&](ICLTensor * t)
- {
- auto &kernel = _hconcat_kernels[i++];
- kernel.configure(t, height_offset, output);
- height_offset += t->info()->dimension(Window::DimY);
- return t;
- });
-}
-
-void CLConcatenateLayer::configure(const std::vector<ICLTensor *> &inputs_vector, ICLTensor *output, DataLayoutDimension axis)
-{
- ARM_COMPUTE_ERROR_ON(output == nullptr);
- _axis = get_data_layout_dimension_index(output->info()->data_layout(), axis);
+ unsigned int offset = 0;
switch(_axis)
{
- case 0:
+ case Window::DimX:
{
- auto func = support::cpp14::make_unique<CLWidthConcatenateLayer>();
- func->configure(inputs_vector, output);
- _concat_function = std::move(func);
+ switch(_num_inputs)
+ {
+ case 2:
+ {
+ // Configure WidthConcatenate2Tensors kernel
+ auto kernel = support::cpp14::make_unique<CLWidthConcatenate2TensorsKernel>();
+ kernel->configure(inputs_vector.at(0), inputs_vector.at(1), output);
+ _concat_kernels.emplace_back(std::move(kernel));
+ break;
+ }
+ case 4:
+ {
+ // Configure WidthConcatenate4Tensors kernel
+ auto kernel = support::cpp14::make_unique<CLWidthConcatenate4TensorsKernel>();
+ kernel->configure(inputs_vector.at(0), inputs_vector.at(1), inputs_vector.at(2), inputs_vector.at(3), output);
+ _concat_kernels.emplace_back(std::move(kernel));
+ break;
+ }
+ default:
+ {
+ // Configure generic case WidthConcatenate kernels
+ for(unsigned int i = 0; i < _num_inputs; ++i)
+ {
+ auto kernel = support::cpp14::make_unique<CLWidthConcatenateLayerKernel>();
+ kernel->configure(inputs_vector.at(i), offset, output);
+ offset += inputs_vector.at(i)->info()->dimension(_axis);
+ _concat_kernels.emplace_back(std::move(kernel));
+ }
+ break;
+ }
+ }
break;
}
- case 1:
+ case Window::DimY:
{
- configure_h_concatenate(inputs_vector, output);
+ for(unsigned int i = 0; i < _num_inputs; ++i)
+ {
+ auto kernel = support::cpp14::make_unique<CLHeightConcatenateLayerKernel>();
+ kernel->configure(inputs_vector.at(i), offset, output);
+ offset += inputs_vector.at(i)->info()->dimension(_axis);
+ _concat_kernels.emplace_back(std::move(kernel));
+ }
break;
}
- case 2:
+ case Window::DimZ:
{
- auto func = support::cpp14::make_unique<CLDepthConcatenateLayer>();
- func->configure(inputs_vector, output);
- _concat_function = std::move(func);
+ for(unsigned int i = 0; i < _num_inputs; ++i)
+ {
+ auto kernel = support::cpp14::make_unique<CLDepthConcatenateLayerKernel>();
+ kernel->configure(inputs_vector.at(i), offset, output);
+ offset += inputs_vector.at(i)->info()->dimension(_axis);
+ _concat_kernels.emplace_back(std::move(kernel));
+ }
break;
}
default:
- ARM_COMPUTE_ERROR("Concatenation is supported across width, height and depth only!");
+ ARM_COMPUTE_ERROR("Axis not supported");
}
}
Status CLConcatenateLayer::validate(const std::vector<ITensorInfo *> &inputs_vector, const ITensorInfo *output, DataLayoutDimension axis)
{
ARM_COMPUTE_RETURN_ERROR_ON(output == nullptr);
+ const unsigned int num_inputs = inputs_vector.size();
- switch(get_data_layout_dimension_index(output->data_layout(), axis))
+ ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output);
+ ARM_COMPUTE_RETURN_ERROR_ON(num_inputs < 2);
+ const unsigned int _axis = get_data_layout_dimension_index(inputs_vector[0]->data_layout(), axis);
+
+ // Output auto inizialitation if not yet initialized
+ TensorInfo tmp_output_info = *output->clone();
+ TensorShape output_shape{};
+ if(_axis == Window::DimZ)
{
- case 0:
- ARM_COMPUTE_RETURN_ON_ERROR(CLWidthConcatenateLayer::validate(inputs_vector, output));
- break;
- case 1:
- ARM_COMPUTE_RETURN_ON_ERROR(CLConcatenateLayer::validate_h_concatenate(inputs_vector, output));
- break;
- case 2:
- ARM_COMPUTE_RETURN_ON_ERROR(CLDepthConcatenateLayer::validate(inputs_vector, output));
- break;
- default:
- ARM_COMPUTE_RETURN_ERROR_MSG("Concatenation is supported across width and depth only!");
+ output_shape = arm_compute::misc::shape_calculator::calculate_depth_concatenate_shape(inputs_vector);
}
+ else
+ {
+ output_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(inputs_vector, _axis);
+ }
+ auto_init_if_empty(tmp_output_info, output_shape, 1, inputs_vector[0]->data_type());
+
+ unsigned int offset = 0;
+ switch(_axis)
+ {
+ case Window::DimX:
+ {
+ switch(num_inputs)
+ {
+ case 2:
+ // Validate WidthConcatenate2Tensors kernels if there are 2 inputs
+ ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(inputs_vector[0], inputs_vector[1]);
+ ARM_COMPUTE_RETURN_ON_ERROR(CLWidthConcatenate2TensorsKernel::validate(inputs_vector[0], inputs_vector[1], &tmp_output_info));
+ break;
+ case 4:
+ // Validate WidthConcatenate4Tensors kernels if there are 4 inputs
+ ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(inputs_vector[0], inputs_vector[1], inputs_vector[2], inputs_vector[3]);
+ ARM_COMPUTE_RETURN_ON_ERROR(CLWidthConcatenate4TensorsKernel::validate(inputs_vector[0], inputs_vector[1], inputs_vector[2], inputs_vector[3], &tmp_output_info));
+ break;
+ default:
+ // Validate generic case of WidthConcatenate kernel
+ for(const auto &input : inputs_vector)
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input);
+ ARM_COMPUTE_RETURN_ON_ERROR(CLWidthConcatenateLayerKernel::validate(input, offset, &tmp_output_info));
+ offset += input->dimension(_axis);
+ }
+ break;
+ }
+ break;
+ }
+ case Window::DimY:
+ {
+ for(const auto &input : inputs_vector)
+ {
+ ARM_COMPUTE_RETURN_ON_ERROR(CLHeightConcatenateLayerKernel::validate(input, offset, &tmp_output_info));
+ offset += input->dimension(_axis);
+ }
+ break;
+ }
+ case Window::DimZ:
+ {
+ for(const auto &input : inputs_vector)
+ {
+ ARM_COMPUTE_RETURN_ON_ERROR(CLDepthConcatenateLayerKernel::validate(input, offset, &tmp_output_info));
+ offset += input->dimension(_axis);
+ }
+ break;
+ }
+ default:
+ ARM_COMPUTE_ERROR("Axis not supported");
+ }
+
return Status{};
}
void CLConcatenateLayer::run()
{
- switch(_axis)
+ for(auto &kernel : _concat_kernels)
{
- case 0:
- case 2:
- {
- ARM_COMPUTE_ERROR_ON(_concat_function == nullptr);
- _concat_function->run();
- break;
- }
- case 1:
- {
- for(unsigned int i = 0; i < _num_inputs; ++i)
- {
- CLScheduler::get().enqueue(_hconcat_kernels[i], true);
- }
- break;
- }
- default:
- {
- ARM_COMPUTE_ERROR("Axis not supported");
- break;
- }
+ CLScheduler::get().enqueue(*kernel, true);
}
}
} // namespace arm_compute