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author | Gian Marco Iodice <gianmarco.iodice@arm.com> | 2018-07-26 11:44:03 +0100 |
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committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:54:54 +0000 |
commit | 68a3f56627b04acdefebe67d645727dd83889766 (patch) | |
tree | 4a3f4dc0facfda861a5ba7afa29d84d82d0829c2 /src/core/CL/kernels/CLGEMMInterleave4x4Kernel.cpp | |
parent | 4e0d3819be6c61cc00c7e0fa9b4b740738c703b7 (diff) | |
download | ComputeLibrary-68a3f56627b04acdefebe67d645727dd83889766.tar.gz |
COMPMID-1276 - Allow GEMM to work with 3D input tensor
Skipped im2col in CLGEMMConvolutionLayer for 1x1 convolutions with NHWC data layout
Change-Id: I894e6b952ed8605e8f3ffc0ffc25c24730d4664c
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/141909
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Diffstat (limited to 'src/core/CL/kernels/CLGEMMInterleave4x4Kernel.cpp')
-rw-r--r-- | src/core/CL/kernels/CLGEMMInterleave4x4Kernel.cpp | 73 |
1 files changed, 54 insertions, 19 deletions
diff --git a/src/core/CL/kernels/CLGEMMInterleave4x4Kernel.cpp b/src/core/CL/kernels/CLGEMMInterleave4x4Kernel.cpp index 12a40cd7dc..6ea1160c69 100644 --- a/src/core/CL/kernels/CLGEMMInterleave4x4Kernel.cpp +++ b/src/core/CL/kernels/CLGEMMInterleave4x4Kernel.cpp @@ -23,6 +23,7 @@ */ #include "arm_compute/core/CL/kernels/CLGEMMInterleave4x4Kernel.h" +#include "arm_compute/core/AccessWindowStatic.h" #include "arm_compute/core/CL/CLHelpers.h" #include "arm_compute/core/CL/CLKernelLibrary.h" #include "arm_compute/core/CL/CLValidate.h" @@ -30,6 +31,7 @@ #include "arm_compute/core/CL/OpenCL.h" #include "arm_compute/core/Error.h" #include "arm_compute/core/Helpers.h" +#include "arm_compute/core/TensorInfo.h" #include "arm_compute/core/Types.h" #include "arm_compute/core/Utils.h" #include "arm_compute/core/Window.h" @@ -40,7 +42,7 @@ using namespace arm_compute::misc::shape_calculator; namespace { -Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, int mult_interleave4x4_height) +Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, int mult_interleave4x4_height, bool reinterpret_input_as_3d) { ARM_COMPUTE_RETURN_ERROR_ON(mult_interleave4x4_height < 1); ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input); @@ -50,24 +52,30 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, i if(output->total_size() != 0) { - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), compute_interleaved_shape(*input, mult_interleave4x4_height)); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), compute_interleaved_shape(*input, mult_interleave4x4_height, reinterpret_input_as_3d)); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); } return Status{}; } -std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output, int mult_interleave4x4_height) +std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output, int mult_interleave4x4_height, bool reinterpret_input_as_3d) { constexpr unsigned int num_elems_processed_per_iteration_x = 4; constexpr unsigned int num_elems_processed_per_iteration_y = 4; const unsigned int num_elems_written_per_iteration = num_elems_processed_per_iteration_x * num_elems_processed_per_iteration_y * mult_interleave4x4_height; bool window_changed = false; - // Configure kernel window - Window win = calculate_max_window(*input, Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y)); - AccessWindowRectangle input_access(input, 0, 0, num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y); - window_changed = window_changed || update_window_and_padding(win, input_access); + TensorInfo tmp_info(*input); + + if(reinterpret_input_as_3d) + { + // Since the input tensor has to be reinterpreted as 3D and the execute window is based on a 2D interleave, + // the window needs to be constructed on the 2D collapsed version of the tensor + TensorShape tmp_shape(input->tensor_shape()); + tmp_shape.collapse(2U, 1U); + tmp_info.set_tensor_shape(tmp_shape); + } // Output auto inizialitation if not yet initialized auto_init_if_empty(*output, input->clone()->set_tensor_shape(compute_interleaved_shape(*input, mult_interleave4x4_height))); @@ -76,9 +84,22 @@ std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITen const float scale_x = 4.0f * static_cast<float>(mult_interleave4x4_height); const float scale_y = 1.0f / (scale_x); + // Note: bottom paddings are calculated manually as the input can be reinterpreted as 3D tensor + // The only way to set properly the paddings, it is to set those explicitly through the AccessWindowStatic + const int m = reinterpret_input_as_3d ? input->tensor_shape()[1] * input->tensor_shape()[2] : input->tensor_shape()[1]; + const int bottom_pad = (num_elems_processed_per_iteration_y - (m % num_elems_processed_per_iteration_y)) % num_elems_processed_per_iteration_y; + + Window win = calculate_max_window(tmp_info, Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y)); + Window win_in = calculate_max_window(*input, Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y)); + + AccessWindowStatic input_access(input, 0, 0, + ceil_to_multiple(input->dimension(0), num_elems_processed_per_iteration_x), + input->dimension(1) + bottom_pad); AccessWindowRectangle output_access(output, 0, 0, num_elems_written_per_iteration, 1, scale_x, scale_y); - window_changed = window_changed || update_window_and_padding(win, output_access); - output_access.set_valid_region(win, input->valid_region()); + + window_changed = update_window_and_padding(win_in, input_access) || // window used by the execute_window_loop + update_window_and_padding(win, output_access); // window used to update the padding requirements of output tensor + output_access.set_valid_region(win, ValidRegion(Coordinates(0, 0), output->tensor_shape())); // Collapse along the Z direction // This collapse needs to be here in order to tune the Z dimension of LWS @@ -90,26 +111,31 @@ std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITen } // namespace CLGEMMInterleave4x4Kernel::CLGEMMInterleave4x4Kernel() - : _input(nullptr), _output(nullptr) + : _input(nullptr), _output(nullptr), _reinterpret_input_as_3d(false) { } -void CLGEMMInterleave4x4Kernel::configure(const ICLTensor *input, ICLTensor *output, int mult_interleave4x4_height) +void CLGEMMInterleave4x4Kernel::configure(const ICLTensor *input, ICLTensor *output, int mult_interleave4x4_height, bool reinterpret_input_as_3d) { 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(compute_interleaved_shape(*input->info(), mult_interleave4x4_height))); + auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(compute_interleaved_shape(*input->info(), mult_interleave4x4_height, reinterpret_input_as_3d))); // Perform validate step - ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), mult_interleave4x4_height)); + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), mult_interleave4x4_height, reinterpret_input_as_3d)); - _input = input; - _output = output; + _input = input; + _output = output; + _reinterpret_input_as_3d = reinterpret_input_as_3d; // Create build options CLBuildOptions build_opts; build_opts.add_option("-DMULT_INTERLEAVE4X4_HEIGHT=" + support::cpp11::to_string(mult_interleave4x4_height)); + build_opts.add_option_if(_reinterpret_input_as_3d, "-DREINTERPRET_INPUT_AS_3D"); + build_opts.add_option_if(_reinterpret_input_as_3d, "-DHEIGHT_GEMM3D=" + support::cpp11::to_string(input->info()->dimension(1))); + build_opts.add_option_if(_reinterpret_input_as_3d, "-DDEPTH_GEMM3D=" + support::cpp11::to_string(input->info()->dimension(2))); + switch(input->info()->element_size()) { case 1: @@ -129,12 +155,13 @@ void CLGEMMInterleave4x4Kernel::configure(const ICLTensor *input, ICLTensor *out _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("gemm_interleave4x4", build_opts.options())); // Configure kernel window - auto win_config = validate_and_configure_window(input->info(), output->info(), mult_interleave4x4_height); + auto win_config = validate_and_configure_window(input->info(), output->info(), mult_interleave4x4_height, reinterpret_input_as_3d); ARM_COMPUTE_ERROR_THROW_ON(win_config.first); ICLKernel::configure(win_config.second); // Set config_id for enabling LWS tuning _config_id = "interleave4x4_"; + _config_id += (_reinterpret_input_as_3d ? "3d_" : ""); _config_id += lower_string(string_from_data_type(input->info()->data_type())); _config_id += "_"; _config_id += support::cpp11::to_string(output->info()->dimension(0)); @@ -146,10 +173,10 @@ void CLGEMMInterleave4x4Kernel::configure(const ICLTensor *input, ICLTensor *out _config_id += support::cpp11::to_string(output->info()->dimension(3)); } -Status CLGEMMInterleave4x4Kernel::validate(const ITensorInfo *input, const ITensorInfo *output, int mult_interleave4x4_height) +Status CLGEMMInterleave4x4Kernel::validate(const ITensorInfo *input, const ITensorInfo *output, int mult_interleave4x4_height, bool reinterpret_input_as_3d) { - ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, mult_interleave4x4_height)); - ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get(), mult_interleave4x4_height).first); + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, mult_interleave4x4_height, reinterpret_input_as_3d)); + ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get(), mult_interleave4x4_height, reinterpret_input_as_3d).first); return Status{}; } @@ -170,6 +197,14 @@ void CLGEMMInterleave4x4Kernel::run(const Window &window, cl::CommandQueue &queu */ Window slice = window.first_slice_window_3D(); + if(_reinterpret_input_as_3d) + { + // Pass bottom paddings to the kernel if the input has to be reinterpreted as 3D tensor + const unsigned int idx0 = 2 * num_arguments_per_3D_tensor(); + const unsigned int total_cross_plane_pad = _input->info()->padding().top + _input->info()->padding().bottom; + _kernel.setArg<cl_uint>(idx0, static_cast<unsigned int>(total_cross_plane_pad)); + } + do { unsigned int idx = 0; |