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authorGeorgios Pinitas <georgios.pinitas@arm.com>2019-03-26 17:23:28 +0000
committerGian Marco Iodice <gianmarco.iodice@arm.com>2019-04-11 09:34:26 +0000
commit8be9148814b88e5b0cabd5a4d2b1f4ff470a8c1c (patch)
tree760658b8c7b8917379467bd3fc119a5502faa850 /src/core/CL/kernels/CLPixelWiseMultiplicationKernel.cpp
parenta50e702289af66944e860eafc7f3b32f6c5f30be (diff)
downloadComputeLibrary-8be9148814b88e5b0cabd5a4d2b1f4ff470a8c1c.tar.gz
COMPMID-1959: Implements 2D FFT on OpenCL
Change-Id: I73cf3984a5463acc854c8a59dc2bd9a5234cd99c Signed-off-by: Georgios Pinitas <georgios.pinitas@arm.com> Reviewed-on: https://review.mlplatform.org/c/936 Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Diffstat (limited to 'src/core/CL/kernels/CLPixelWiseMultiplicationKernel.cpp')
-rw-r--r--src/core/CL/kernels/CLPixelWiseMultiplicationKernel.cpp142
1 files changed, 139 insertions, 3 deletions
diff --git a/src/core/CL/kernels/CLPixelWiseMultiplicationKernel.cpp b/src/core/CL/kernels/CLPixelWiseMultiplicationKernel.cpp
index 286b94ebdc..9fa92bde75 100644
--- a/src/core/CL/kernels/CLPixelWiseMultiplicationKernel.cpp
+++ b/src/core/CL/kernels/CLPixelWiseMultiplicationKernel.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2016-2018 ARM Limited.
+ * Copyright (c) 2016-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -38,8 +38,8 @@
#include <set>
#include <string>
-using namespace arm_compute;
-
+namespace arm_compute
+{
namespace
{
constexpr unsigned int num_elems_processed_per_iteration = 16;
@@ -276,3 +276,139 @@ BorderSize CLPixelWiseMultiplicationKernel::border_size() const
const unsigned int border = std::min<unsigned int>(num_elems_processed_per_iteration - 1U, replicateSize);
return BorderSize(0, border, 0, 0);
}
+
+namespace
+{
+constexpr unsigned int num_elems_processed_per_iteration_complex = 1;
+
+Status validate_arguments_complex(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output)
+{
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input1, 2, DataType::F32);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input2, 2, DataType::F32);
+
+ const TensorShape &out_shape = TensorShape::broadcast_shape(input1->tensor_shape(), input2->tensor_shape());
+
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(out_shape.total_size() == 0, "Inputs are not broadcast compatible");
+
+ // Validate in case of configured output
+ if(output->total_size() > 0)
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 2, DataType::F32);
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(detail::have_different_dimensions(out_shape, output->tensor_shape(), 0), "Wrong shape for output");
+ }
+
+ return Status{};
+}
+
+std::pair<Status, Window> validate_and_configure_window_complex(ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output)
+{
+ const std::pair<TensorShape, ValidRegion> broadcast_pair = ITensorInfo::broadcast_shape_and_valid_region(*input1, *input2);
+ const TensorShape &out_shape = broadcast_pair.first;
+ const ValidRegion &valid_region = broadcast_pair.second;
+
+ // Auto initialize output if not initialized
+ const TensorInfo out_info(out_shape, input1->num_channels(), input1->data_type());
+ auto_init_if_empty(*output, out_info);
+
+ Window win = calculate_max_window(valid_region, Steps(num_elems_processed_per_iteration_complex));
+ Window win_input1 = win.broadcast_if_dimension_le_one(*input1);
+ Window win_input2 = win.broadcast_if_dimension_le_one(*input2);
+
+ AccessWindowHorizontal input1_access(input1, 0, num_elems_processed_per_iteration_complex);
+ AccessWindowHorizontal input2_access(input2, 0, num_elems_processed_per_iteration_complex);
+ AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration_complex);
+
+ bool window_changed = update_window_and_padding(win_input1, input1_access)
+ || update_window_and_padding(win_input2, input2_access)
+ || update_window_and_padding(win, output_access);
+
+ output_access.set_valid_region(win, valid_region);
+
+ Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
+ return std::make_pair(err, win);
+}
+} // namespace
+
+CLComplexPixelWiseMultiplicationKernel::CLComplexPixelWiseMultiplicationKernel()
+ : _input1(nullptr), _input2(nullptr), _output(nullptr)
+{
+}
+
+void CLComplexPixelWiseMultiplicationKernel::configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output)
+{
+ ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output);
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_complex(input1->info(), input2->info(), output->info()));
+
+ // Configure kernel window
+ auto win_config = validate_and_configure_window_complex(input1->info(), input2->info(), output->info());
+ ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
+
+ _input1 = input1;
+ _input2 = input2;
+ _output = output;
+
+ // Create kernel
+ _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("pixelwise_mul_complex"));
+
+ ICLKernel::configure_internal(win_config.second);
+}
+
+Status CLComplexPixelWiseMultiplicationKernel::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output)
+{
+ ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output);
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_complex(input1, input2, output));
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window_complex(input1->clone().get(), input2->clone().get(), output->clone().get()).first);
+
+ return Status{};
+}
+
+void CLComplexPixelWiseMultiplicationKernel::run(const Window &window, cl::CommandQueue &queue)
+{
+ ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
+ ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window);
+
+ const TensorShape &in_shape1 = _input1->info()->tensor_shape();
+ const TensorShape &in_shape2 = _input2->info()->tensor_shape();
+ const TensorShape &out_shape = _output->info()->tensor_shape();
+
+ bool can_collapse = true;
+ if(std::min(in_shape1.total_size(), in_shape2.total_size()) > 1)
+ {
+ can_collapse = (std::min(in_shape1.num_dimensions(), in_shape2.num_dimensions()) > Window::DimZ);
+ for(size_t d = Window::DimZ; can_collapse && (d < out_shape.num_dimensions()); ++d)
+ {
+ can_collapse = (in_shape1[d] == in_shape2[d]);
+ }
+ }
+
+ bool has_collapsed = false;
+ Window collapsed = can_collapse ? window.collapse_if_possible(ICLKernel::window(), Window::DimZ, &has_collapsed) : window;
+
+ const TensorShape &in_shape1_collapsed = has_collapsed ? in_shape1.collapsed_from(Window::DimZ) : in_shape1;
+ const TensorShape &in_shape2_collapsed = has_collapsed ? in_shape2.collapsed_from(Window::DimZ) : in_shape2;
+
+ Window slice = collapsed.first_slice_window_3D();
+ Window slice_input1 = slice.broadcast_if_dimension_le_one(in_shape1_collapsed);
+ Window slice_input2 = slice.broadcast_if_dimension_le_one(in_shape2_collapsed);
+
+ do
+ {
+ unsigned int idx = 0;
+ add_3D_tensor_argument(idx, _input1, slice_input1);
+ add_3D_tensor_argument(idx, _input2, slice_input2);
+ add_3D_tensor_argument(idx, _output, slice);
+ enqueue(queue, *this, slice);
+
+ collapsed.slide_window_slice_3D(slice_input1);
+ collapsed.slide_window_slice_3D(slice_input2);
+ }
+ while(collapsed.slide_window_slice_3D(slice));
+}
+
+BorderSize CLComplexPixelWiseMultiplicationKernel::border_size() const
+{
+ const unsigned int replicateSize = _output->info()->dimension(0) - std::min(_input1->info()->dimension(0), _input2->info()->dimension(0));
+ const unsigned int border = std::min<unsigned int>(num_elems_processed_per_iteration_complex - 1U, replicateSize);
+ return BorderSize(0, border, 0, 0);
+}
+} // namespace arm_compute \ No newline at end of file