From aaa27189e0e75c3ebad57854ac8901d0140677ac Mon Sep 17 00:00:00 2001 From: Georgios Pinitas Date: Wed, 21 Nov 2018 16:32:15 +0000 Subject: COMPMID-1734: Implement CLSelect Change-Id: I49b2e8b4200c9ed654736d9451e4ab9c073b4b10 --- src/core/CL/CLKernelLibrary.cpp | 7 ++ src/core/CL/cl_kernels/select.cl | 216 +++++++++++++++++++++++++++++++++ src/core/CL/kernels/CLSelectKernel.cpp | 203 +++++++++++++++++++++++++++++++ 3 files changed, 426 insertions(+) create mode 100644 src/core/CL/cl_kernels/select.cl create mode 100644 src/core/CL/kernels/CLSelectKernel.cpp (limited to 'src/core') diff --git a/src/core/CL/CLKernelLibrary.cpp b/src/core/CL/CLKernelLibrary.cpp index 3a002e808d..12944061a9 100644 --- a/src/core/CL/CLKernelLibrary.cpp +++ b/src/core/CL/CLKernelLibrary.cpp @@ -386,6 +386,9 @@ const std::map CLKernelLibrary::_kernel_program_map = { "scale_bilinear_quantized_nchw", "scale_quantized.cl" }, { "scale_bilinear_quantized_nhwc", "scale_quantized.cl" }, { "scharr3x3", "scharr_filter.cl" }, + { "select_same_rank", "select.cl" }, + { "select_different_rank_2", "select.cl" }, + { "select_different_rank_n", "select.cl" }, { "sobel3x3", "sobel_filter.cl" }, { "sobel_separable5x1", "sobel_filter.cl" }, { "sobel_separable1x5", "sobel_filter.cl" }, @@ -812,6 +815,10 @@ const std::map CLKernelLibrary::_program_source_map = { "scharr_filter.cl", #include "./cl_kernels/scharr_filter.clembed" + }, + { + "select.cl", +#include "./cl_kernels/select.clembed" }, { "sobel_filter.cl", diff --git a/src/core/CL/cl_kernels/select.cl b/src/core/CL/cl_kernels/select.cl new file mode 100644 index 0000000000..d783ae212e --- /dev/null +++ b/src/core/CL/cl_kernels/select.cl @@ -0,0 +1,216 @@ +/* + * Copyright (c) 2018 ARM Limited. + * + * SPDX-License-Identifier: MIT + * + * Permission is hereby granted, free of charge, to any person obtaining a copy + * of this software and associated documentation files (the "Software"), to + * deal in the Software without restriction, including without limitation the + * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or + * sell copies of the Software, and to permit persons to whom the Software is + * furnished to do so, subject to the following conditions: + * + * The above copyright notice and this permission notice shall be included in all + * copies or substantial portions of the Software. + * + * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE + * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER + * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, + * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + * SOFTWARE. + */ +#include "helpers.h" + +#if defined(DATA_TYPE) && defined(SELECT_DATA_TYPE) && defined(VEC_SIZE) +/** This function perform a select operation between two tensors when condition tensor has the same rank. + * + * @attention The data_type need to be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=uchar + * @attention The select operation data_type need to be passed at compile time using -DSELECT_DATA_TYPE: e.g. -DSELECT_DATA_TYPE=uchar + * @attention Vector size should be given as a preprocessor argument using -DVEC_SIZE=size. e.g. -DVEC_SIZE=16 + * + * @param[in] c_ptr Pointer to the source tensor. Supported data types: U8 + * @param[in] c_stride_x Stride of the source tensor in X dimension (in bytes) + * @param[in] c_step_x c_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] c_stride_y Stride of the source tensor in Y dimension (in bytes) + * @param[in] c_step_y c_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] c_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] c_step_z c_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] c_offset_first_element_in_bytes The offset of the first element in the source tensor + * @param[in] x_ptr Pointer to the source tensor. Supported data types: U8/S8/QASYMM8/U16/S16/U32/S32/F16/F32 + * @param[in] x_stride_x Stride of the source tensor in X dimension (in bytes) + * @param[in] x_step_x x_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] x_stride_y Stride of the source tensor in Y dimension (in bytes) + * @param[in] x_step_y x_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] x_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] x_step_z x_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] x_offset_first_element_in_bytes The offset of the first element in the source tensor + * @param[in] y_ptr Pointer to the source tensor. Supported data types: U8/S8/QASYMM8/U16/S16/U32/S32/F16/F32 + * @param[in] y_stride_x Stride of the source tensor in X dimension (in bytes) + * @param[in] y_step_x y_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] y_stride_y Stride of the source tensor in Y dimension (in bytes) + * @param[in] y_step_y y_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] y_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] y_step_z y_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] y_offset_first_element_in_bytes The offset of the first element in the source tensor + * @param[out] out_ptr Pointer to the destination tensor. Supported data types: U8/S8/QASYMM8/U16/S16/U32/S32/F16/F32 + * @param[in] out_stride_x Stride of the destination tensor in X dimension (in bytes) + * @param[in] out_step_x out_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] out_stride_y Stride of the destination tensor in Y dimension (in bytes) + * @param[in] out_step_y out_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] out_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] out_step_z out_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] out_offset_first_element_in_bytes The offset of the first element in the destination tensor + */ +__kernel void select_same_rank( + TENSOR3D_DECLARATION(c), + TENSOR3D_DECLARATION(x), + TENSOR3D_DECLARATION(y), + TENSOR3D_DECLARATION(out)) +{ + // Get pixels pointer + Tensor3D c_t = CONVERT_TO_TENSOR3D_STRUCT(c); + Tensor3D x_t = CONVERT_TO_TENSOR3D_STRUCT(x); + Tensor3D y_t = CONVERT_TO_TENSOR3D_STRUCT(y); + Tensor3D out_t = CONVERT_TO_TENSOR3D_STRUCT(out); + + // Load values + VEC_DATA_TYPE(SELECT_DATA_TYPE, VEC_SIZE) + in_c = CONVERT((VLOAD(VEC_SIZE)(0, (__global uchar *)c_t.ptr)), VEC_DATA_TYPE(SELECT_DATA_TYPE, VEC_SIZE)); + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + in_x = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)x_t.ptr); + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + in_y = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)y_t.ptr); + + // Calculate and store result + VSTORE(VEC_SIZE) + (select(in_y, in_x, in_c > (SELECT_DATA_TYPE)0), 0, (__global DATA_TYPE *)out_t.ptr); +} + +/** This function perform a select operation between two tensors when condition tensor has a different rank. + * + * @attention The data_type need to be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=uchar + * @attention The select operation data_type need to be passed at compile time using -DSELECT_DATA_TYPE: e.g. -DSELECT_DATA_TYPE=uchar + * @attention Vector size should be given as a preprocessor argument using -DVEC_SIZE=size. e.g. -DVEC_SIZE=16 + * + * @param[in] c_ptr Pointer to the source tensor. Supported data types: U8 + * @param[in] c_stride_x Stride of the source tensor in X dimension (in bytes) + * @param[in] c_step_x c_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] c_offset_first_element_in_bytes The offset of the first element in the source tensor + * @param[in] x_ptr Pointer to the source tensor. Supported data types: U8/S8/QASYMM8/U16/S16/U32/S32/F16/F32 + * @param[in] x_stride_x Stride of the source tensor in X dimension (in bytes) + * @param[in] x_step_x x_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] x_stride_y Stride of the source tensor in Y dimension (in bytes) + * @param[in] x_step_y x_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] x_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] x_step_z x_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] x_offset_first_element_in_bytes The offset of the first element in the source tensor + * @param[in] y_ptr Pointer to the source tensor. Supported data types: U8/S8/QASYMM8/U16/S16/U32/S32/F16/F32 + * @param[in] y_stride_x Stride of the source tensor in X dimension (in bytes) + * @param[in] y_step_x y_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] y_stride_y Stride of the source tensor in Y dimension (in bytes) + * @param[in] y_step_y y_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] y_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] y_step_z y_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] y_offset_first_element_in_bytes The offset of the first element in the source tensor + * @param[out] out_ptr Pointer to the destination tensor. Supported data types: U8/S8/QASYMM8/U16/S16/U32/S32/F16/F32 + * @param[in] out_stride_x Stride of the destination tensor in X dimension (in bytes) + * @param[in] out_step_x out_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] out_stride_y Stride of the destination tensor in Y dimension (in bytes) + * @param[in] out_step_y out_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] out_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] out_step_z out_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] out_offset_first_element_in_bytes The offset of the first element in the destination tensor + */ +__kernel void select_different_rank_2( + VECTOR_DECLARATION(c), + TENSOR3D_DECLARATION(x), + TENSOR3D_DECLARATION(y), + TENSOR3D_DECLARATION(out)) +{ + const int c_idx = get_global_id(1); + + // Get pixels pointer + Vector c_t = CONVERT_TO_VECTOR_STRUCT_NO_STEP(c); + Tensor3D x_t = CONVERT_TO_TENSOR3D_STRUCT(x); + Tensor3D y_t = CONVERT_TO_TENSOR3D_STRUCT(y); + Tensor3D out_t = CONVERT_TO_TENSOR3D_STRUCT(out); + + // Load values + VEC_DATA_TYPE(SELECT_DATA_TYPE, VEC_SIZE) + in_c = *((__global uchar *)(c_t.ptr + c_idx * c_t.stride_x)); + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + in_x = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)x_t.ptr); + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + in_y = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)y_t.ptr); + + // Calculate and store result + VSTORE(VEC_SIZE) + (select(in_y, in_x, in_c > (SELECT_DATA_TYPE)0), 0, (__global DATA_TYPE *)out_t.ptr); +} +#endif /* defined(DATA_TYPE) && defined(SELECT_DATA_TYPE) && defined(VEC_SIZE) */ + +#if defined(DATA_TYPE) && defined(SELECT_DATA_TYPE) && defined(VEC_SIZE) && defined(DEPTH_SIZE) +/** This function perform a select operation between two tensors when condition tensor has a different rank. + * + * @attention The data_type need to be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=uchar + * @attention The select operation data_type need to be passed at compile time using -DSELECT_DATA_TYPE: e.g. -DSELECT_DATA_TYPE=uchar + * @attention Vector size should be given as a preprocessor argument using -DVEC_SIZE=size. e.g. -DVEC_SIZE=16 + * + * @param[in] c_ptr Pointer to the source tensor. Supported data types: U8 + * @param[in] c_stride_x Stride of the source tensor in X dimension (in bytes) + * @param[in] c_step_x c_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] c_offset_first_element_in_bytes The offset of the first element in the source tensor + * @param[in] x_ptr Pointer to the source tensor. Supported data types: U8/S8/QASYMM8/U16/S16/U32/S32/F16/F32 + * @param[in] x_stride_x Stride of the source tensor in X dimension (in bytes) + * @param[in] x_step_x x_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] x_stride_y Stride of the source tensor in Y dimension (in bytes) + * @param[in] x_step_y x_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] x_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] x_step_z x_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] x_offset_first_element_in_bytes The offset of the first element in the source tensor + * @param[in] y_ptr Pointer to the source tensor. Supported data types: U8/S8/QASYMM8/U16/S16/U32/S32/F16/F32 + * @param[in] y_stride_x Stride of the source tensor in X dimension (in bytes) + * @param[in] y_step_x y_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] y_stride_y Stride of the source tensor in Y dimension (in bytes) + * @param[in] y_step_y y_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] y_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] y_step_z y_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] y_offset_first_element_in_bytes The offset of the first element in the source tensor + * @param[out] out_ptr Pointer to the destination tensor. Supported data types: U8/S8/QASYMM8/U16/S16/U32/S32/F16/F32 + * @param[in] out_stride_x Stride of the destination tensor in X dimension (in bytes) + * @param[in] out_step_x out_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] out_stride_y Stride of the destination tensor in Y dimension (in bytes) + * @param[in] out_step_y out_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] out_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] out_step_z out_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] out_offset_first_element_in_bytes The offset of the first element in the destination tensor + */ +__kernel void select_different_rank_n( + VECTOR_DECLARATION(c), + TENSOR3D_DECLARATION(x), + TENSOR3D_DECLARATION(y), + TENSOR3D_DECLARATION(out)) +{ + const int c_idx = get_global_id(2) / DEPTH_SIZE; + + // Get pixels pointer + Vector c_t = CONVERT_TO_VECTOR_STRUCT_NO_STEP(c); + Tensor3D x_t = CONVERT_TO_TENSOR3D_STRUCT(x); + Tensor3D y_t = CONVERT_TO_TENSOR3D_STRUCT(y); + Tensor3D out_t = CONVERT_TO_TENSOR3D_STRUCT(out); + + // Load values + VEC_DATA_TYPE(SELECT_DATA_TYPE, VEC_SIZE) + in_c = *((__global uchar *)(c_t.ptr + c_idx * c_t.stride_x)); + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + in_x = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)x_t.ptr); + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + in_y = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)y_t.ptr); + + // Calculate and store result + VSTORE(VEC_SIZE) + (select(in_y, in_x, in_c > (SELECT_DATA_TYPE)0), 0, (__global DATA_TYPE *)out_t.ptr); +} +#endif /* defined(DATA_TYPE) && defined(SELECT_DATA_TYPE) && defined(VEC_SIZE) && defined(DEPTH_SIZE) */ \ No newline at end of file diff --git a/src/core/CL/kernels/CLSelectKernel.cpp b/src/core/CL/kernels/CLSelectKernel.cpp new file mode 100644 index 0000000000..c9e5da0670 --- /dev/null +++ b/src/core/CL/kernels/CLSelectKernel.cpp @@ -0,0 +1,203 @@ +/* + * Copyright (c) 2018 ARM Limited. + * + * SPDX-License-Identifier: MIT + * + * Permission is hereby granted, free of charge, to any person obtaining a copy + * of this software and associated documentation files (the "Software"), to + * deal in the Software without restriction, including without limitation the + * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or + * sell copies of the Software, and to permit persons to whom the Software is + * furnished to do so, subject to the following conditions: + * + * The above copyright notice and this permission notice shall be included in all + * copies or substantial portions of the Software. + * + * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE + * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER + * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, + * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + * SOFTWARE. + */ +#include "arm_compute/core/CL/kernels/CLSelectKernel.h" + +#include "arm_compute/core/CL/CLHelpers.h" +#include "arm_compute/core/CL/CLKernelLibrary.h" +#include "arm_compute/core/CL/CLValidate.h" +#include "arm_compute/core/CL/ICLTensor.h" +#include "arm_compute/core/Helpers.h" +#include "arm_compute/core/TensorInfo.h" +#include "arm_compute/core/Utils.h" +#include "arm_compute/core/Window.h" + +#include "support/ToolchainSupport.h" + +namespace arm_compute +{ +namespace +{ +Status validate_arguments(const ITensorInfo *c, const ITensorInfo *x, const ITensorInfo *y, const ITensorInfo *output) +{ + ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(x); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(x, + 1, + DataType::U8, DataType::S8, DataType::QASYMM8, + DataType::U16, DataType::S16, + DataType::U32, DataType::S32, + DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(x, y); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(x, y); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(c, 1, DataType::U8); + + const bool is_same_rank = (c->tensor_shape().num_dimensions() == x->tensor_shape().num_dimensions()); + ARM_COMPUTE_RETURN_ERROR_ON(is_same_rank && (x->tensor_shape() != c->tensor_shape())); + ARM_COMPUTE_RETURN_ERROR_ON(!is_same_rank && ((c->tensor_shape().num_dimensions() > 1) || (c->tensor_shape().x() != x->tensor_shape()[x->tensor_shape().num_dimensions() - 1]))); + + if(output != nullptr && output->total_size() != 0) + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(x, output); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(x, output); + } + + return Status{}; +} + +std::pair validate_and_configure_window(ITensorInfo *c, ITensorInfo *x, ITensorInfo *y, ITensorInfo *output) +{ + if(output != nullptr) + { + // Output tensor auto initialization if not yet initialized + auto_init_if_empty(*output, *x->clone()); + } + + const bool is_same_rank = (c->tensor_shape().num_dimensions() == x->tensor_shape().num_dimensions()); + + const unsigned int num_elems_processed_per_iteration = 16 / x->element_size(); + + // Configure kernel window + Window win = calculate_max_window(*x, Steps(num_elems_processed_per_iteration)); + AccessWindowHorizontal x_access(x, 0, num_elems_processed_per_iteration); + AccessWindowHorizontal y_access(y, 0, num_elems_processed_per_iteration); + bool window_changed = update_window_and_padding(win, x_access, y_access); + + // Update window for condition + if(is_same_rank) + { + AccessWindowHorizontal c_access(c, 0, num_elems_processed_per_iteration); + window_changed = window_changed || update_window_and_padding(win, c_access); + } + + // Update window for output + if(output != nullptr) + { + AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration); + window_changed = window_changed || update_window_and_padding(win, output_access); + output_access.set_valid_region(win, x->valid_region()); + } + + Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; + return std::make_pair(err, win); +} +} // namespace + +CLSelectKernel::CLSelectKernel() + : _c(nullptr), _x(nullptr), _y(nullptr), _output(nullptr), _has_same_rank(false) +{ +} +void CLSelectKernel::configure(const ICLTensor *c, const ICLTensor *x, const ICLTensor *y, ICLTensor *output) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(c, x, y, output); + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(c->info(), x->info(), y->info(), output->info())); + + _c = c; + _x = x; + _y = y; + _output = output; + _has_same_rank = (c->info()->tensor_shape().num_dimensions() == x->info()->tensor_shape().num_dimensions()); + + const unsigned int num_elems_processed_per_iteration = 16 / x->info()->element_size(); + + // Set build options + CLBuildOptions build_opts; + build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(x->info()->data_type())); + build_opts.add_option("-DSELECT_DATA_TYPE=" + get_cl_select_type_from_data_type(x->info()->data_type())); + build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration)); + + // Create kernel + std::string kernel_name = "select"; + if(_has_same_rank) + { + kernel_name += "_same_rank"; + } + else + { + const bool is_input_rank_greater_than_two = x->info()->tensor_shape().num_dimensions() > 2; + if(is_input_rank_greater_than_two) + { + const size_t width = x->info()->tensor_shape().x(); + const size_t height = x->info()->tensor_shape().y(); + const size_t outer_size = x->info()->tensor_shape()[x->info()->tensor_shape().num_dimensions() - 1]; + const size_t depth_size = x->info()->tensor_shape().total_size() / (width * height * outer_size); + build_opts.add_option("-DDEPTH_SIZE=" + support::cpp11::to_string(depth_size)); + } + kernel_name += "_different_rank"; + kernel_name += is_input_rank_greater_than_two ? "_n" : "_2"; + } + _kernel = static_cast(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options())); + + // Configure kernel window + auto win_config = validate_and_configure_window(c->info(), x->info(), y->info(), output->info()); + ARM_COMPUTE_ERROR_THROW_ON(win_config.first); + ICLKernel::configure_internal(win_config.second); + + _config_id = "select_"; + _config_id += string_from_data_type(x->info()->data_type()); + _config_id += "_"; + _config_id += support::cpp11::to_string(x->info()->dimension(0)); + _config_id += "_"; + _config_id += support::cpp11::to_string(x->info()->dimension(1)); + _config_id += "_"; + _config_id += support::cpp11::to_string(x->info()->dimension(2)); +} + +Status CLSelectKernel::validate(const ITensorInfo *c, const ITensorInfo *x, const ITensorInfo *y, const ITensorInfo *output) +{ + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(c, x, y, output)); + ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(c->clone().get(), x->clone().get(), y->clone().get(), output->clone().get()).first); + return Status{}; +} + +void CLSelectKernel::run(const arm_compute::Window &window, cl::CommandQueue &queue) +{ + ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); + ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window); + + Window collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ); + Window slice = collapsed.first_slice_window_3D(); + + if(!_has_same_rank) + { + Window vector_slice = window.first_slice_window_1D(); + vector_slice.set(Window::DimX, Window::Dimension(0, 0, 0)); + unsigned int idx = 0; + add_1D_tensor_argument(idx, _c, vector_slice); + } + + do + { + unsigned int idx = _has_same_rank ? 0 : num_arguments_per_1D_tensor(); + if(_has_same_rank) + { + add_3D_tensor_argument(idx, _c, slice); + } + add_3D_tensor_argument(idx, _x, slice); + add_3D_tensor_argument(idx, _y, slice); + add_3D_tensor_argument(idx, _output, slice); + + enqueue(queue, *this, slice, lws_hint()); + } + while(collapsed.slide_window_slice_3D(slice)); +} +} // namespace arm_compute -- cgit v1.2.1