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-rw-r--r--libs/ARMComputeEx/src/core/CL/kernels/CLPixelWiseDivisionKernel.cpp280
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diff --git a/libs/ARMComputeEx/src/core/CL/kernels/CLPixelWiseDivisionKernel.cpp b/libs/ARMComputeEx/src/core/CL/kernels/CLPixelWiseDivisionKernel.cpp
deleted file mode 100644
index b985aa737..000000000
--- a/libs/ARMComputeEx/src/core/CL/kernels/CLPixelWiseDivisionKernel.cpp
+++ /dev/null
@@ -1,280 +0,0 @@
-/*
- * Copyright (c) 2018 Samsung Electronics Co., Ltd. All Rights Reserved
- * Copyright (c) 2016-2018 ARM Limited.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-#include "arm_compute/core/CL/kernels/CLPixelWiseDivisionKernel.h"
-
-#include "arm_compute/core/CL/CLHelpers.h"
-#include "arm_compute/core/CL/CLKernelLibraryEx.h"
-#include "arm_compute/core/CL/ICLTensor.h"
-
-using namespace arm_compute;
-
-namespace
-{
-constexpr unsigned int num_elems_processed_per_iteration = 16;
-
-Status validate_arguments(const ITensorInfo *input1, const ITensorInfo *input2,
- const ITensorInfo *output, float scale, ConvertPolicy overflow_policy,
- RoundingPolicy rounding_policy)
-{
- ARM_COMPUTE_UNUSED(overflow_policy);
- ARM_COMPUTE_UNUSED(rounding_policy);
-
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input1, 1, DataType::U8, DataType::S16,
- DataType::F16, DataType::F32);
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input2, 1, DataType::U8, DataType::S16,
- DataType::F16, DataType::F32);
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(scale < 0, "Scale cannot be negative.");
-
- 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, 1, DataType::U8, DataType::S16,
- DataType::F16, DataType::F32);
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(
- output->data_type() == DataType::U8 &&
- (input1->data_type() != DataType::U8 || input2->data_type() != DataType::U8),
- "Output can only be U8 if both inputs are U8");
- 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(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
- {
- set_shape_if_empty(*output, out_shape);
-
- if (input1->data_type() == DataType::S16 || input2->data_type() == DataType::S16)
- {
- set_format_if_unknown(*output, Format::S16);
- }
- else if (input1->data_type() == DataType::F32 || input2->data_type() == DataType::F32)
- {
- set_format_if_unknown(*output, Format::F32);
- }
- }
-
- Window win = calculate_max_window(valid_region, Steps(num_elems_processed_per_iteration));
- 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);
- AccessWindowHorizontal input2_access(input2, 0, num_elems_processed_per_iteration);
- AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration);
-
- 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
-
-CLPixelWiseDivisionKernel::CLPixelWiseDivisionKernel()
- : _input1(nullptr), _input2(nullptr), _output(nullptr)
-{
-}
-
-void CLPixelWiseDivisionKernel::configure(const ICLTensor *input1, const ICLTensor *input2,
- ICLTensor *output, float scale,
- ConvertPolicy overflow_policy,
- RoundingPolicy rounding_policy)
-{
- ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output);
- ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input1->info(), input2->info(), output->info(),
- scale, overflow_policy, rounding_policy));
-
- // Configure kernel window
- auto win_config = validate_and_configure_window(input1->info(), input2->info(), output->info());
- ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
-
- _input1 = input1;
- _input2 = input2;
- _output = output;
-
- int scale_int = -1;
- // Extract sign, exponent and mantissa
- int exponent = 0;
- float normalized_mantissa = std::frexp(scale, &exponent);
- // Use int scaling if factor is equal to 1/2^n for 0 <= n <= 15
- // frexp returns 0.5 as mantissa which means that the exponent will be in the range of -1 <= e <=
- // 14
- // Moreover, it will be negative as we deal with 1/2^n
- if ((normalized_mantissa == 0.5f) && (-14 <= exponent) && (exponent <= 1))
- {
- // Store the positive exponent. We know that we compute 1/2^n
- // Additionally we need to subtract 1 to compensate that frexp used a mantissa of 0.5
- scale_int = std::abs(exponent - 1);
- }
-
- std::string data_type;
- std::string compute_type;
- // Check if it has float inputs and output
- if (is_data_type_float(input1->info()->data_type()) ||
- is_data_type_float(input2->info()->data_type()))
- {
- scale_int = -1;
- compute_type = (input1->info()->data_type() == DataType::F32 ||
- input2->info()->data_type() == DataType::F32)
- ? "float"
- : "half";
- data_type = "DATA_TYPE_FLOAT";
- }
- else
- {
- if (input1->info()->data_type() == DataType::S16 ||
- input2->info()->data_type() == DataType::S16)
- {
- compute_type = "int";
- }
- else
- {
- compute_type = "ushort";
- }
- data_type = "DATA_TYPE_INT";
- }
-
- // Construct kernel name
- std::string kernel_name = "pixelwise_div";
- kernel_name += (scale_int >= 0) ? "_int" : "_float";
-
- // Set kernel build options
- std::set<std::string> build_opts;
- build_opts.emplace(
- (overflow_policy == ConvertPolicy::WRAP || is_data_type_float(output->info()->data_type()))
- ? "-DWRAP"
- : "-DSATURATE");
- build_opts.emplace((rounding_policy == RoundingPolicy::TO_ZERO) ? "-DROUND=_rtz"
- : "-DROUND=_rte");
- build_opts.emplace("-DDATA_TYPE_IN1=" + get_cl_type_from_data_type(input1->info()->data_type()));
- build_opts.emplace("-DDATA_TYPE_IN2=" + get_cl_type_from_data_type(input2->info()->data_type()));
- build_opts.emplace("-DDATA_TYPE_OUT=" + get_cl_type_from_data_type(output->info()->data_type()));
- build_opts.emplace("-DDATA_TYPE_RES=" + compute_type);
- build_opts.emplace("-D" + data_type);
-
- // Create kernel
- _kernel =
- static_cast<cl::Kernel>(CLKernelLibraryEx::get().create_kernel(kernel_name, build_opts));
-
- // Set scale argument
- unsigned int idx = 3 * num_arguments_per_3D_tensor(); // Skip the inputs and output parameters
-
- if (scale_int >= 0)
- {
- _kernel.setArg(idx++, scale_int);
- }
- else
- {
- _kernel.setArg(idx++, scale);
- }
-
- ICLKernel::configure_internal(win_config.second);
-}
-
-Status CLPixelWiseDivisionKernel::validate(const ITensorInfo *input1, const ITensorInfo *input2,
- const ITensorInfo *output, float scale,
- ConvertPolicy overflow_policy,
- RoundingPolicy rounding_policy)
-{
- ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output);
- ARM_COMPUTE_RETURN_ON_ERROR(
- validate_arguments(input1, input2, output, scale, overflow_policy, rounding_policy));
- ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input1->clone().get(),
- input2->clone().get(),
- output->clone().get())
- .first);
-
- return Status{};
-}
-
-void CLPixelWiseDivisionKernel::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 CLPixelWiseDivisionKernel::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 - 1U, replicateSize);
- return BorderSize(0, border, 0, 0);
-}