COMPMID-911: Allow GEMM to work with 3D tensors
Change-Id: I8c4823a0d909e19e9ef548f00b9ae98c66de61dd
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/123569
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
diff --git a/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.cpp b/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.cpp
index fc52f4e..2c2a92d 100644
--- a/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.cpp
@@ -56,19 +56,13 @@
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input0, 1, DataType::QS8, DataType::QS16, DataType::F16, DataType::F32);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input0, input1);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input0, input1);
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(is_data_type_fixed_point(input0->data_type()) && (reshape_info.depth_output_gemm3d() != 1), "GEMM3D only supports floating point data types");
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(input0->num_dimensions() > 4, "The number of dimensions for the matrix A must be <= 4");
ARM_COMPUTE_RETURN_ERROR_ON_MSG(input1->num_dimensions() > 3, "The number of dimensions for the matrix B must be <= 3");
if(!is_interleaved_transposed)
{
ARM_COMPUTE_RETURN_ERROR_ON(input0->dimension(0) != input1->dimension(1));
-
- if(output->total_size() != 0)
- {
- ARM_COMPUTE_RETURN_ERROR_ON(input1->dimension(0) != output->dimension(0));
- ARM_COMPUTE_RETURN_ERROR_ON(input0->dimension(1) != output->dimension(1));
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input0, output);
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input0, output);
- }
}
else
{
@@ -94,14 +88,14 @@
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input0, &tensor_info_reshaped0);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input1, &tensor_info_reshaped1);
+ }
- if(output->total_size() != 0)
- {
- ARM_COMPUTE_RETURN_ERROR_ON(output->dimension(0) != static_cast<size_t>(n));
- ARM_COMPUTE_RETURN_ERROR_ON(output->dimension(1) != static_cast<size_t>(m));
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input0, output);
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input0, output);
- }
+ if(output->total_size() != 0)
+ {
+ const TensorInfo tensor_info_output = output->clone()->set_tensor_shape(compute_mm_shape(*input0, *input1, is_interleaved_transposed, reshape_info));
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(output, &tensor_info_output);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input0, output);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input0, output);
}
return Status{};
@@ -113,6 +107,7 @@
{
bool window_changed = false;
Window win{};
+ Window win_out{};
const DataType data_type = input0->data_type();
unsigned int &num_elems_processed_per_iteration_x = num_elements_processed[0];
@@ -121,23 +116,43 @@
// Output tensor auto inizialitation if not yet initialized
auto_init_if_empty(*output, input0->clone()->set_tensor_shape(compute_mm_shape(*input0, *input1, is_interleaved_transposed, reshape_info)));
+ TensorInfo tmp_info(*output);
+
+ if(reshape_info.depth_output_gemm3d() != 1)
+ {
+ // Since the output tensor has to be reinterpreted as 3D and the execute window is based on a 2D GEMM,
+ // the window needs to be constructed on the 2D collapsed version of the tensor
+ TensorShape tmp_shape(output->tensor_shape());
+ tmp_shape.collapse(2U, 1U);
+ tmp_info.set_tensor_shape(tmp_shape);
+ }
+
if(is_interleaved_transposed)
{
// Configure kernel window
num_elems_processed_per_iteration_x = max_cl_vector_width / data_size_from_type(data_type);
num_elems_processed_per_iteration_y = 4;
- win = calculate_max_window(*output, Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y));
+ // Note: bottom paddings are calculated manually as the output 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 = reshape_info.m();
+ const int bottom_pad = (num_elems_processed_per_iteration_y - (m % num_elems_processed_per_iteration_y)) % num_elems_processed_per_iteration_y;
+
+ win = calculate_max_window(tmp_info, Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y));
+ win_out = calculate_max_window(*output, Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y));
AccessWindowRectangle input0_access(input0, 0, 0, num_elems_processed_per_iteration_y, 1, 1.f, 0.25f);
AccessWindowStatic input1_access(input1, 0, 0,
ceil_to_multiple(input1->dimension(0), num_elems_processed_per_iteration_x),
ceil_to_multiple(input1->dimension(1), num_elems_processed_per_iteration_y));
- AccessWindowRectangle output_access(output, 0, 0, num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y);
+ AccessWindowStatic output_access(output, 0, 0,
+ ceil_to_multiple(output->dimension(0), num_elems_processed_per_iteration_x),
+ output->dimension(1) + bottom_pad);
- window_changed = update_window_and_padding(win, input0_access, input1_access, output_access);
+ window_changed = update_window_and_padding(win, input0_access, input1_access) || // window used by the execute_window_loop
+ update_window_and_padding(win_out, 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()));
+ output_access.set_valid_region(win_out, ValidRegion(Coordinates(0, 0), output->tensor_shape()));
}
else // The input tensors have not been reshaped
{
@@ -145,6 +160,11 @@
num_elems_processed_per_iteration_x = max_cl_vector_width / data_size_from_type(data_type);
num_elems_processed_per_iteration_y = std::min(static_cast<int>(output->dimension(1)), 4);
+ // Note: bottom paddings are calculated manually as the output 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 = input0->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;
+
// Create kernels according to the architecture, data type and input size.
GPUTarget arch_target = get_arch_from_target(gpu_target);
if(arch_target == GPUTarget::BIFROST && data_type == DataType::F32)
@@ -153,17 +173,21 @@
}
// Configure window
- win = calculate_max_window(*output, Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y));
+ win = calculate_max_window(tmp_info, Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y));
+ win_out = calculate_max_window(*output, Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y));
- AccessWindowStatic input0_access(input0, 0, 0, input0->dimension(0), ceil_to_multiple(input0->dimension(1), num_elems_processed_per_iteration_y));
- AccessWindowStatic input1_access(input1, 0, 0, ceil_to_multiple(input1->dimension(0), num_elems_processed_per_iteration_x), input1->dimension(1));
- AccessWindowRectangle output_access(output, 0, 0, num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y);
+ AccessWindowStatic input0_access(input0, 0, 0, input0->dimension(0), ceil_to_multiple(input0->dimension(1), num_elems_processed_per_iteration_y));
+ AccessWindowStatic input1_access(input1, 0, 0, ceil_to_multiple(input1->dimension(0), num_elems_processed_per_iteration_x), input1->dimension(1));
+ AccessWindowStatic output_access(output, 0, 0,
+ ceil_to_multiple(output->dimension(0), num_elems_processed_per_iteration_x),
+ output->dimension(1) + bottom_pad);
- window_changed = update_window_and_padding(win, input0_access, input1_access, output_access);
+ window_changed = update_window_and_padding(win, input0_access, input1_access) || // window used by the execute_window_loop
+ update_window_and_padding(win_out, output_access); // window used to update the padding requirements of output tensor
Coordinates coord;
coord.set_num_dimensions(output->num_dimensions());
- output_access.set_valid_region(win, ValidRegion(coord, output->tensor_shape()));
+ output_access.set_valid_region(win_out, ValidRegion(coord, output->tensor_shape()));
}
// Collapse along the Z direction
@@ -178,7 +202,7 @@
} // namespace
CLGEMMMatrixMultiplyKernel::CLGEMMMatrixMultiplyKernel()
- : _input0(nullptr), _input1(nullptr), _output(nullptr), _slide_matrix_b(true)
+ : _input0(nullptr), _input1(nullptr), _output(nullptr), _slide_matrix_b(true), _is_gemm3d(false)
{
}
@@ -194,9 +218,14 @@
_output = output;
_slide_matrix_b = _input1->info()->num_dimensions() >= _input0->info()->num_dimensions();
- const DataType data_type = input0->info()->data_type();
- const int fp_pos = input0->info()->fixed_point_position();
- const GPUTarget gpu_target = get_target();
+ const DataType data_type = input0->info()->data_type();
+ const int fp_pos = input0->info()->fixed_point_position();
+
+ // Get target architecture
+ GPUTarget gpu_target = get_target();
+
+ // Check if the output has to be reinterpreted as 3D
+ _is_gemm3d = (reshape_info.depth_output_gemm3d() != 1) && is_data_type_float(data_type);
ElementsProcessed num_elements_processed{};
@@ -216,6 +245,9 @@
"-DALPHA=" + support::cpp11::to_string((data_type == DataType::QS8 ? sqcvt_qs8_f32(alpha, fp_pos) : sqcvt_qs16_f32(alpha, fp_pos))),
"-DALPHA=" + float_to_string_with_full_precision(alpha));
}
+ build_opts.add_option_if(_is_gemm3d, "-DREINTERPRET_OUTPUT_AS_3D");
+ build_opts.add_option_if(_is_gemm3d, "-DHEIGHT_GEMM3D=" + support::cpp11::to_string(output->info()->dimension(1)));
+ build_opts.add_option_if(_is_gemm3d, "-DDEPTH_GEMM3D=" + support::cpp11::to_string(output->info()->dimension(2)));
// Do not slide matrix B if _slide_matrix_b = false
build_opts.add_option_if(!_slide_matrix_b, "-DMATRIX_B_DEPTH=" + support::cpp11::to_string(input1->info()->dimension(2)));
@@ -285,6 +317,7 @@
// Set config_id for enabling LWS tuning
_config_id = "gemm_";
_config_id += (is_interleaved_transposed ? "reshaped_" : "");
+ _config_id += (_is_gemm3d ? "3d_" : "");
_config_id += lower_string(string_from_data_type(input0->info()->data_type()));
_config_id += "_";
_config_id += support::cpp11::to_string(output->info()->dimension(1));
@@ -334,6 +367,13 @@
slice_matrix_b.set(Window::DimX, Window::Dimension(0, 1, 1));
slice_matrix_b.set(Window::DimY, Window::Dimension(0, 1, 1));
+ if(_is_gemm3d)
+ {
+ // Pass bottom paddings to the kernel if the output has to be reinterpreted as 3D tensor
+ const unsigned int idx0 = 3 * num_arguments_per_2D_tensor() + 3;
+ _kernel.setArg<cl_uint>(idx0, static_cast<unsigned int>(_output->info()->padding().bottom));
+ }
+
do
{
Window slice_b = slice;