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-rw-r--r--src/core/CL/kernels/CLCol2ImKernel.cpp14
-rw-r--r--src/core/NEON/kernels/NECol2ImKernel.cpp48
2 files changed, 30 insertions, 32 deletions
diff --git a/src/core/CL/kernels/CLCol2ImKernel.cpp b/src/core/CL/kernels/CLCol2ImKernel.cpp
index 40032f97c4..74bbb9b4df 100644
--- a/src/core/CL/kernels/CLCol2ImKernel.cpp
+++ b/src/core/CL/kernels/CLCol2ImKernel.cpp
@@ -40,7 +40,7 @@ using namespace arm_compute::misc::shape_calculator;
namespace
{
-Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, std::pair<unsigned int, unsigned int> convolved_dims, unsigned int num_groups)
+Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const Size2D &convolved_dims, unsigned int num_groups)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input);
@@ -49,7 +49,7 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, s
// Checks performed when output is configured
if(output->total_size() != 0)
{
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), compute_col2im_shape(*input, convolved_dims, num_groups));
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), compute_col2im_shape(*input, convolved_dims, true, num_groups));
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(input, output);
ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->data_layout() != DataLayout::NCHW, "Col2Im output's data layout must always be NCHW");
@@ -58,11 +58,11 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, s
return Status{};
}
-std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output, std::pair<unsigned int, unsigned int> convolved_dims, unsigned int num_groups)
+std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output, const Size2D &convolved_dims, unsigned int num_groups)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
// Output auto inizialitation if not yet initialized
- auto_init_if_empty(*output, input->clone()->set_tensor_shape(compute_col2im_shape(*input, convolved_dims, num_groups)).set_data_layout(DataLayout::NCHW));
+ auto_init_if_empty(*output, input->clone()->set_tensor_shape(compute_col2im_shape(*input, convolved_dims, true, num_groups)).set_data_layout(DataLayout::NCHW));
const unsigned int num_elems_read_per_iteration = 8;
@@ -87,7 +87,7 @@ CLCol2ImKernel::CLCol2ImKernel()
{
}
-void CLCol2ImKernel::configure(const ICLTensor *input, ICLTensor *output, std::pair<unsigned int, unsigned int> convolved_dims, unsigned int num_groups)
+void CLCol2ImKernel::configure(const ICLTensor *input, ICLTensor *output, const Size2D &convolved_dims, unsigned int num_groups)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
@@ -105,7 +105,7 @@ void CLCol2ImKernel::configure(const ICLTensor *input, ICLTensor *output, std::p
build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(data_type));
build_opts.add_option("-DELEMENT_SIZE=" + support::cpp11::to_string(input->info()->element_size()));
build_opts.add_option("-DWIDTH_INPUT=" + support::cpp11::to_string(input->info()->dimension(0)));
- build_opts.add_option("-DWIDTH_OUTPUT=" + support::cpp11::to_string(_convolved_dims.first));
+ build_opts.add_option("-DWIDTH_OUTPUT=" + support::cpp11::to_string(_convolved_dims.width));
build_opts.add_option_if(num_groups > 1, "-DGROUPING");
_kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("col2im", build_opts.options()));
@@ -130,7 +130,7 @@ void CLCol2ImKernel::configure(const ICLTensor *input, ICLTensor *output, std::p
_config_id += support::cpp11::to_string(output->info()->dimension(1));
}
-Status CLCol2ImKernel::validate(const ITensorInfo *input, const ITensorInfo *output, std::pair<unsigned int, unsigned int> convolved_dims, unsigned int num_groups)
+Status CLCol2ImKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const Size2D &convolved_dims, unsigned int num_groups)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, convolved_dims, num_groups));
diff --git a/src/core/NEON/kernels/NECol2ImKernel.cpp b/src/core/NEON/kernels/NECol2ImKernel.cpp
index bb8e758b78..d6517ac072 100644
--- a/src/core/NEON/kernels/NECol2ImKernel.cpp
+++ b/src/core/NEON/kernels/NECol2ImKernel.cpp
@@ -29,26 +29,17 @@
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/core/Validate.h"
+#include "arm_compute/core/utils/misc/ShapeCalculator.h"
#include <arm_neon.h>
#include <cstddef>
#include <cstdint>
using namespace arm_compute;
+using namespace misc::shape_calculator;
namespace
{
-TensorShape get_output_shape(const ITensorInfo *input, const Size2D &convolved_dims)
-{
- TensorShape output_shape = input->tensor_shape();
- output_shape.set(0, convolved_dims.width);
- output_shape.set(1, convolved_dims.height);
- output_shape.set(2, input->tensor_shape()[0]);
- output_shape.set(3, input->tensor_shape()[3]); // For NEON the batch size is on the fourth dimension of the input tensor
-
- return output_shape;
-}
-
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const Size2D &convolved_dims)
{
//Note: ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(input) is not needed here as this kernel doesn't use NEON FP16 instructions.
@@ -60,12 +51,28 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, c
// Validate configured output
if(output->total_size() != 0)
{
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), get_output_shape(input, convolved_dims));
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), compute_col2im_shape(*input, convolved_dims, false));
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
}
return Status{};
}
+
+std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output, const Size2D &convolved_dims)
+{
+ // Output auto inizialitation if not yet initialized
+ auto_init_if_empty(*output, input->clone()->set_tensor_shape(compute_col2im_shape(*input, convolved_dims, false)));
+
+ // Configure kernel window
+ Window win = calculate_max_window(*input, Steps());
+
+ // The NECol2ImKernel doesn't need padding so update_window_and_padding() can be skipped
+ Coordinates coord;
+ coord.set_num_dimensions(output->num_dimensions());
+ output->set_valid_region(ValidRegion(coord, output->tensor_shape()));
+
+ return std::make_pair(Status{}, win);
+}
} // namespace
template <typename T>
@@ -102,11 +109,6 @@ NECol2ImKernel::NECol2ImKernel()
void NECol2ImKernel::configure(const ITensor *input, ITensor *output, const Size2D &convolved_dims)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
-
- // Output auto inizialitation if not yet initialized
- auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(get_output_shape(input->info(), convolved_dims)));
-
- // Perform validation step
ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), convolved_dims));
_input = input;
@@ -130,19 +132,15 @@ void NECol2ImKernel::configure(const ITensor *input, ITensor *output, const Size
}
// Configure kernel window
- Window win = calculate_max_window(*input->info(), Steps());
-
- // The NECol2ImKernel doesn't need padding so update_window_and_padding() can be skipped
- Coordinates coord;
- coord.set_num_dimensions(output->info()->num_dimensions());
- output->info()->set_valid_region(ValidRegion(coord, output->info()->tensor_shape()));
-
- INEKernel::configure(win);
+ auto win_config = validate_and_configure_window(input->info(), output->info(), convolved_dims);
+ ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
+ INEKernel::configure(win_config.second);
}
Status NECol2ImKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const Size2D &convolved_dims)
{
ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, convolved_dims));
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get(), convolved_dims).first);
return Status{};
}
generated by cgit v1.2.1 (git 2.23.0) at 2024-07-04 18:26:01 +0000