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path: root/src/core/CL/kernels/CLArgMinMaxLayerKernel.cpp
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Diffstat (limited to 'src/core/CL/kernels/CLArgMinMaxLayerKernel.cpp')
-rw-r--r--src/core/CL/kernels/CLArgMinMaxLayerKernel.cpp138
1 files changed, 71 insertions, 67 deletions
diff --git a/src/core/CL/kernels/CLArgMinMaxLayerKernel.cpp b/src/core/CL/kernels/CLArgMinMaxLayerKernel.cpp
index 909972482f..5b72354abe 100644
--- a/src/core/CL/kernels/CLArgMinMaxLayerKernel.cpp
+++ b/src/core/CL/kernels/CLArgMinMaxLayerKernel.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2019-2021 Arm Limited.
+ * Copyright (c) 2019-2021, 2023 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -29,37 +29,36 @@
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/Utils.h"
+#include "arm_compute/core/utils/helpers/AdjustVecSize.h"
#include "arm_compute/core/Validate.h"
+
#include "src/core/CL/CLValidate.h"
#include "src/core/helpers/AutoConfiguration.h"
#include "src/core/helpers/WindowHelpers.h"
-
#include "support/StringSupport.h"
namespace arm_compute
{
namespace
{
-Status validate_arguments(const ITensorInfo *input, const ITensorInfo *prev_output, const ITensorInfo *output, unsigned int axis, ReductionOperation op)
+Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, unsigned int axis, ReductionOperation op)
{
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::QASYMM8_SIGNED, DataType::S32, DataType::F16, DataType::F32);
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(op != ReductionOperation::ARG_IDX_MAX && op != ReductionOperation::ARG_IDX_MIN, "Only ARG_IDX_MAX and ARG_IDX_MIN are supported");
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(axis >= TensorShape::num_max_dimensions, "Reduction axis greater than max number of dimensions");
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED,
+ DataType::S32, DataType::F16, DataType::F32);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::S32, DataType::S64);
+
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(op != ReductionOperation::ARG_IDX_MAX && op != ReductionOperation::ARG_IDX_MIN,
+ "Only ARG_IDX_MAX and ARG_IDX_MIN are supported");
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(axis >= TensorShape::num_max_dimensions,
+ "Reduction axis greater than max number of dimensions");
ARM_COMPUTE_RETURN_ERROR_ON_MSG(axis > 3, "Unsupported reduction axis");
- if(output->total_size() != 0)
+ if (output->total_size() != 0)
{
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U32, DataType::S32);
- }
- if(prev_output != nullptr && prev_output->total_size() != 0)
- {
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(prev_output, 1, DataType::U32, DataType::S32);
- if(output->total_size() != 0)
- {
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(prev_output, output);
- }
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U32, DataType::S32, DataType::S64,
+ DataType::U64);
}
return Status{};
@@ -67,59 +66,70 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *prev_outp
} // namespace
CLArgMinMaxLayerKernel::CLArgMinMaxLayerKernel()
- : _input(nullptr), _prev_output(nullptr), _output(nullptr), _reduction_axis(0), _op(ReductionOperation::ARG_IDX_MAX)
+ : _input(nullptr), _output(nullptr), _reduction_axis(0), _op(ReductionOperation::ARG_IDX_MAX)
{
+ _type = CLKernelType::ELEMENTWISE;
}
-void CLArgMinMaxLayerKernel::configure(const ICLTensor *input, const ICLTensor *prev_output, ICLTensor *output, unsigned int axis, ReductionOperation op)
+void CLArgMinMaxLayerKernel::configure(const ICLTensor *input,
+ ICLTensor *output,
+ unsigned int axis,
+ ReductionOperation op)
{
- configure(CLKernelLibrary::get().get_compile_context(), input, prev_output, output, axis, op);
+ configure(CLKernelLibrary::get().get_compile_context(), input, output, axis, op);
}
-void CLArgMinMaxLayerKernel::configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *prev_output, ICLTensor *output, unsigned int axis, ReductionOperation op)
+void CLArgMinMaxLayerKernel::configure(const CLCompileContext &compile_context,
+ const ICLTensor *input,
+ ICLTensor *output,
+ unsigned int axis,
+ ReductionOperation op)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
- TensorShape output_shape{ input->info()->tensor_shape() };
+ TensorShape output_shape{input->info()->tensor_shape()};
output_shape.set(axis, 1);
- auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(output_shape).set_data_type(DataType::S32).reset_padding().set_is_resizable(true));
+ auto_init_if_empty(*output->info(), input->info()
+ ->clone()
+ ->set_tensor_shape(output_shape)
+ .set_data_type(DataType::S32)
+ .reset_padding()
+ .set_is_resizable(true));
- ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), (prev_output != nullptr) ? prev_output->info() : nullptr, output->info(), axis, op));
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), axis, op));
- auto padding_info = get_padding_info({ input, prev_output, output });
+ auto padding_info = get_padding_info({input, output});
_input = input;
- _prev_output = prev_output;
_output = output;
_reduction_axis = axis;
_op = op;
// Set build options
- const auto vector_size = (axis == 0) ? 16U : adjust_vec_size(16U, input->info()->dimension(0));
+ const auto adjusted_vector_size = adjust_vec_size(16U, input->info()->dimension(0));
+ const auto vector_size = (adjusted_vector_size == 3U && axis == 0U)
+ ? 2U
+ : adjusted_vector_size; // the opencl kernel only supports sizes 2, 4, 8 and 16.
CLBuildOptions build_opts;
- build_opts.add_option_if(_prev_output != nullptr, "-DPREV_OUTPUT");
build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
- build_opts.add_option("-DVEC_SIZE_LEFTOVER=" + support::cpp11::to_string(input->info()->dimension(0) % vector_size));
+ build_opts.add_option("-DVEC_SIZE_LEFTOVER=" +
+ support::cpp11::to_string(input->info()->dimension(0) % vector_size));
build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(vector_size));
build_opts.add_option_if(is_data_type_float(input->info()->data_type()), "-DFLOAT_DATA_TYPE");
build_opts.add_option_if_else(op == ReductionOperation::ARG_IDX_MAX, "-DARG_MAX", "-DARG_MIN");
build_opts.add_option("-DDATA_TYPE_OUTPUT=" + get_cl_type_from_data_type(output->info()->data_type()));
+ build_opts.add_option("-DCOND_DATA_TYPE=" + get_cl_select_type_from_data_type(input->info()->data_type()));
+ build_opts.add_option("-DUNROLL_WITH_PRAGMA=1");
// Create kernel
- cl::NDRange lws_hint = CLKernelLibrary::get().default_ndrange();
std::string kernel_axis_name;
- switch(axis)
+ switch (axis)
{
case 0:
- {
- const ICLTensor *input_for_width = prev_output != nullptr ? _prev_output : _input;
- build_opts.add_option("-DWIDTH=" + support::cpp11::to_string(input_for_width->info()->dimension(0)));
-
+ build_opts.add_option("-DWIDTH=" + support::cpp11::to_string(input->info()->dimension(0)));
kernel_axis_name = "x";
- lws_hint = create_lws_hint_parallel_implementations(input_for_width->info()->dimension(0), vector_size);
- }
- break;
+ break;
case 1:
build_opts.add_option("-DHEIGHT=" + support::cpp11::to_string(input->info()->dimension(1)));
kernel_axis_name = "y";
@@ -139,15 +149,18 @@ void CLArgMinMaxLayerKernel::configure(const CLCompileContext &compile_context,
_kernel = create_kernel(compile_context, "arg_min_max_" + kernel_axis_name, build_opts.options());
// Configure kernel window
- Window win = calculate_max_window((prev_output != nullptr) ? (*prev_output->info()) : (*input->info()), Steps(vector_size));
- ICLKernel::configure_internal(win, lws_hint);
+ Window win = calculate_max_window(*input->info(), Steps(vector_size));
+ ICLKernel::configure_internal(win);
ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info));
}
-Status CLArgMinMaxLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *prev_output, const ITensorInfo *output, unsigned int axis, ReductionOperation op)
+Status CLArgMinMaxLayerKernel::validate(const ITensorInfo *input,
+ const ITensorInfo *output,
+ unsigned int axis,
+ ReductionOperation op)
{
- ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, prev_output, output, axis, op));
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, axis, op));
return Status{};
}
@@ -156,43 +169,36 @@ void CLArgMinMaxLayerKernel::run(const Window &window, cl::CommandQueue &queue)
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);
- switch(_reduction_axis)
+ switch (_reduction_axis)
{
case 0:
{
// Set out window
Window out_window(window);
+ Window in_window(window);
out_window.set(Window::DimX, Window::Dimension(0, 0, 0));
+ in_window.set(Window::DimX,
+ Window::Dimension(0, _input->info()->dimension(0), _input->info()->dimension(0)));
+ in_window.set(Window::DimY, Window::Dimension(0, _input->info()->dimension(1), 1u));
// Get first input and output slices
- Window in_slice = window.first_slice_window_2D();
+ Window in_slice = in_window.first_slice_window_2D();
Window out_slice = out_window.first_slice_window_2D();
-
- // Reshape window
- const unsigned int num_tensors = _prev_output != nullptr ? 3 : 2;
-
- // Set local sums buffer
- unsigned int local_res_size = lws_hint()[0] * _output->info()->element_size();
- _kernel.setArg(num_arguments_per_2D_tensor() * num_tensors, local_res_size, nullptr);
do
{
unsigned int idx = 0;
add_2D_tensor_argument(idx, _input, in_slice);
- if(_prev_output != nullptr)
- {
- add_2D_tensor_argument(idx, _prev_output, in_slice);
- }
add_2D_tensor_argument(idx, _output, out_slice);
enqueue(queue, *this, in_slice, lws_hint());
- }
- while(window.slide_window_slice_2D(in_slice) && window.slide_window_slice_2D(out_slice));
+ } while (in_window.slide_window_slice_2D(in_slice) && out_window.slide_window_slice_2D(out_slice));
}
break;
case 1:
{
// Get first input and output slices
- Window window_in{ window };
- window_in.set(Window::DimY, Window::Dimension(0, _input->info()->dimension(1), _input->info()->dimension(1)));
+ Window window_in{window};
+ window_in.set(Window::DimY,
+ Window::Dimension(0, _input->info()->dimension(1), _input->info()->dimension(1)));
Window in_slice = window_in.first_slice_window_2D();
Window out_slice = window.first_slice_window_2D();
@@ -202,15 +208,15 @@ void CLArgMinMaxLayerKernel::run(const Window &window, cl::CommandQueue &queue)
add_2D_tensor_argument(idx, _input, in_slice);
add_2D_tensor_argument(idx, _output, out_slice);
enqueue(queue, *this, in_slice, lws_hint());
- }
- while(window_in.slide_window_slice_2D(in_slice) && window.slide_window_slice_2D(out_slice));
+ } while (window_in.slide_window_slice_2D(in_slice) && window.slide_window_slice_2D(out_slice));
}
break;
case 2:
{
// Get first input and output slices
- Window window_in{ window };
- window_in.set(Window::DimZ, Window::Dimension(0, _input->info()->dimension(2), _input->info()->dimension(2)));
+ Window window_in{window};
+ window_in.set(Window::DimZ,
+ Window::Dimension(0, _input->info()->dimension(2), _input->info()->dimension(2)));
Window in_slice = window_in.first_slice_window_3D();
Window out_slice = window.first_slice_window_3D();
@@ -220,14 +226,13 @@ void CLArgMinMaxLayerKernel::run(const Window &window, cl::CommandQueue &queue)
add_3D_tensor_argument(idx, _input, in_slice);
add_3D_tensor_argument(idx, _output, out_slice);
enqueue(queue, *this, in_slice, lws_hint());
- }
- while(window_in.slide_window_slice_3D(in_slice) && window.slide_window_slice_3D(out_slice));
+ } while (window_in.slide_window_slice_3D(in_slice) && window.slide_window_slice_3D(out_slice));
}
break;
case 3:
{
// Get first input and output slices
- Window window_in{ window };
+ Window window_in{window};
window_in.set(3, Window::Dimension(0, 1, 1));
Window in_slice = window_in.first_slice_window_4D();
Window out_slice = window.first_slice_window_4D();
@@ -238,8 +243,7 @@ void CLArgMinMaxLayerKernel::run(const Window &window, cl::CommandQueue &queue)
add_4D_tensor_argument(idx, _input, in_slice);
add_4D_tensor_argument(idx, _output, out_slice);
enqueue(queue, *this, in_slice, lws_hint());
- }
- while(window_in.slide_window_slice_4D(in_slice) && window.slide_window_slice_4D(out_slice));
+ } while (window_in.slide_window_slice_4D(in_slice) && window.slide_window_slice_4D(out_slice));
}
break;
default: