diff options
Diffstat (limited to 'src/core/CL/kernels/CLGEMMMatrixMultiplyNativeKernel.cpp')
| -rw-r--r-- | src/core/CL/kernels/CLGEMMMatrixMultiplyNativeKernel.cpp | 11 |
1 files changed, 2 insertions, 9 deletions
diff --git a/src/core/CL/kernels/CLGEMMMatrixMultiplyNativeKernel.cpp b/src/core/CL/kernels/CLGEMMMatrixMultiplyNativeKernel.cpp index 37fcd10511..c67d3601ad 100644 --- a/src/core/CL/kernels/CLGEMMMatrixMultiplyNativeKernel.cpp +++ b/src/core/CL/kernels/CLGEMMMatrixMultiplyNativeKernel.cpp @@ -155,17 +155,12 @@ std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input0, ITe num_elems_processed_per_iteration_x = rhs_info.n0; num_elems_processed_per_iteration_y = lhs_info.m0; - // 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 unsigned int m = reinterpret_output_as_3d ? gemm_info.m : output->dimension(1); - const unsigned 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)); AccessWindowStatic input0_access(input0, 0, 0, input0->dimension(0), - input0->dimension(1) + bottom_pad); + input0->dimension(1)); AccessWindowStatic input1_access(input1, 0, 0, ceil_to_multiple(input1->dimension(0), num_elems_processed_per_iteration_x), input1->dimension(1)); @@ -177,11 +172,9 @@ std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input0, ITe { const int bias_processed_per_iteration_x = num_elems_processed_per_iteration_x; - const int bias_processed_per_iteration_y = gemm_info.broadcast_bias ? 1 : num_elems_processed_per_iteration_y; - AccessWindowStatic input2_access(input2, 0, 0, ceil_to_multiple(input2->dimension(0), bias_processed_per_iteration_x), - ceil_to_multiple(input2->dimension(1), bias_processed_per_iteration_y)); + input2->dimension(1)); window_changed = update_window_and_padding(win, input0_access, input1_access, input2_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 |