diff options
Diffstat (limited to 'src/runtime/NEON/functions/NEGEMMLowp.cpp')
-rw-r--r-- | src/runtime/NEON/functions/NEGEMMLowp.cpp | 160 |
1 files changed, 72 insertions, 88 deletions
diff --git a/src/runtime/NEON/functions/NEGEMMLowp.cpp b/src/runtime/NEON/functions/NEGEMMLowp.cpp index 12136cbcb5..ab7fa079b1 100644 --- a/src/runtime/NEON/functions/NEGEMMLowp.cpp +++ b/src/runtime/NEON/functions/NEGEMMLowp.cpp @@ -31,120 +31,104 @@ #include "arm_compute/core/Types.h" #include "arm_compute/core/Validate.h" #include "arm_compute/runtime/NEON/NEScheduler.h" +#include "arm_compute/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.h" #include "arm_compute/runtime/TensorAllocator.h" #include "support/ToolchainSupport.h" using namespace arm_compute; -#define NEGEMMLOWP_VALIDATE_DIMENSIONS(a, b, output) \ - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN((a), 1, DataType::U8); \ - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN((b), 1, DataType::U8); \ - ARM_COMPUTE_ERROR_ON_MSG((a)->info()->dimension(0) != (b)->info()->dimension(1), "The product AB is defined only if the number of columns in A is equal to the number of rows in B"); \ - ARM_COMPUTE_ERROR_ON_MSG((a)->info()->dimension(1) != (output)->info()->dimension(1), "The C matrix must have the same number of rows as the matrix A"); \ - ARM_COMPUTE_ERROR_ON_MSG((b)->info()->dimension(0) != (output)->info()->dimension(0), "The C matrix must have the same number of columns as the matrix C"); - NEGEMMLowp::NEGEMMLowp(std::shared_ptr<IMemoryManager> memory_manager) - : _memory_group(std::move(memory_manager)), _interleave_kernel(), _transpose_kernel(), _mm_kernel(), _mm_optimised_kernel(nullptr), _interleave_blocked(), _interleave_blocked_transposed(), _tmp_a(), - _tmp_b() + : _memory_group(std::move(memory_manager)), _mm_func(), _mtx_a_reduction_kernel(), _mtx_b_reduction_kernel(), _finalize_kernel(), _vector_sum_col(), _vector_sum_row(), _mm_output(), _a_offset(0), + _b_offset(0) { } -void NEGEMMLowp::configure(const ITensor *a, const ITensor *b, ITensor *output) +void NEGEMMLowp::configure(const ITensor *a, const ITensor *b, ITensor *output, int32_t a_offset, int32_t b_offset, int32_t c_offset, int32_t output_mult_int, int32_t shift) { - NEGEMMLOWP_VALIDATE_DIMENSIONS(a, b, output); - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U32); + ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN((a), 1, DataType::U8); + ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(a, b, output); + ARM_COMPUTE_ERROR_ON_MSG((a)->info()->dimension(0) != (b)->info()->dimension(1), "The product AB is defined only if the number of columns in A is equal to the number of rows in B"); + ARM_COMPUTE_ERROR_ON_MSG((a)->info()->dimension(1) != (output)->info()->dimension(1), "The output matrix must have the same number of rows as the matrix A"); + ARM_COMPUTE_ERROR_ON_MSG((b)->info()->dimension(0) != (output)->info()->dimension(0), "The output matrix must have the same number of columns as the matrix B"); + + _a_offset = a_offset; + _b_offset = b_offset; + + // Initialize matrix multiply output tensor + const TensorShape &shape_mm_output = output->info()->tensor_shape(); + TensorInfo info_mm_output(shape_mm_output, 1, DataType::S32); + _mm_output.allocator()->init(info_mm_output); + _memory_group.manage(&_mm_output); - const struct CPUInfo ci = NEScheduler::get().cpu_info(); - const int cpu_has_dotprod = static_cast<int>(ci.CPU) & static_cast<int>(CPUTarget::DOT); - if(cpu_has_dotprod != 0) + // Initialize Matrix B reduction kernel only if _a_offset is not equal to 0 + if(_a_offset != 0) { -#ifdef ARM_COMPUTE_AARCH64_V8_2 - // NEGEMMLowpAArch64V8P4Kernel only compiled in AArch64 targets - _mm_optimised_kernel = support::cpp14::make_unique<NEGEMMLowpAArch64V8P4Kernel>(); - TensorShape shape_a_int = a->info()->tensor_shape(); - shape_a_int.set(0, a->info()->dimension(0) * 8.f); - shape_a_int.set(1, std::ceil(a->info()->dimension(1) / 8.f)); - - TensorShape shape_b_int = b->info()->tensor_shape(); - shape_b_int.set(0, b->info()->dimension(0) * 12.f); - shape_b_int.set(1, std::ceil(b->info()->dimension(1) / 12.f)); - - TensorInfo info_a_int(shape_a_int, 1, a->info()->data_type()); - TensorInfo info_b_int(shape_b_int, 1, b->info()->data_type()); - _tmp_a.allocator()->init(info_a_int); - _tmp_b.allocator()->init(info_b_int); - - _memory_group.manage(&_tmp_a); - _memory_group.manage(&_tmp_b); - - _interleave_blocked.configure(a, &_tmp_a, 8, 4, false); - _interleave_blocked_transposed.configure(b, &_tmp_b, 12, 4, true); - _mm_optimised_kernel->configure(&_tmp_a, &_tmp_b, output); - - _tmp_a.allocator()->allocate(); - _tmp_b.allocator()->allocate(); -#endif /* ARM_COMPUTE_AARCH64_V8_2 */ + TensorShape shape_vector_sum_col = b->info()->tensor_shape(); + shape_vector_sum_col.remove_dimension(1); + TensorInfo info_vector_sum_col(shape_vector_sum_col, 1, DataType::S32); + _vector_sum_col.allocator()->init(info_vector_sum_col); + _memory_group.manage(&_vector_sum_col); + + // Configure Matrix B reduction kernel + _mtx_b_reduction_kernel.configure(b, &_vector_sum_col, a->info()->dimension(0), false); } - else + + // Initialize Matrix A reduction kernel only if _b_offset is not equal to 0 + if(_b_offset != 0) { - ARM_COMPUTE_ERROR("Not implemented"); - //FIXME: This is in the process of being updated, for more info please refer to COMPMID-624. + TensorShape shape_vector_sum_row = a->info()->tensor_shape(); + shape_vector_sum_row.set(Window::DimX, a->info()->dimension(1)); + shape_vector_sum_row.remove_dimension(1); + TensorInfo info_vector_sum_row(shape_vector_sum_row, 1, DataType::S32); + _vector_sum_row.allocator()->init(info_vector_sum_row); + _memory_group.manage(&_vector_sum_row); + + // Configure Matrix A reduction kernel + _mtx_a_reduction_kernel.configure(a, &_vector_sum_row, a->info()->dimension(0), false); } -} -void NEGEMMLowp::run() -{ - _memory_group.acquire(); + // Configure matrix multiply function + _mm_func.configure(a, b, &_mm_output); + + // Configure finalize kernel + _finalize_kernel.configure(_a_offset == 0 ? nullptr : &_vector_sum_col, _b_offset == 0 ? nullptr : &_vector_sum_row, &_mm_output, output, a->info()->dimension(0), a_offset, b_offset, c_offset, + output_mult_int, shift); - if(_mm_optimised_kernel != nullptr) + // Allocate tensors + _mm_output.allocator()->allocate(); + + if(_a_offset != 0) { - NEScheduler::get().schedule(&_interleave_blocked, Window::DimY); - NEScheduler::get().schedule(&_interleave_blocked_transposed, Window::DimY); - NEScheduler::get().schedule(_mm_optimised_kernel.get(), Window::DimY); + _vector_sum_col.allocator()->allocate(); } - else + + if(_b_offset != 0) { - /* Run interleave kernel */ - NEScheduler::get().schedule(&_interleave_kernel, Window::DimY); - /* Run transpose kernel */ - NEScheduler::get().schedule(&_transpose_kernel, Window::DimY); - /* Run matrix multiply kernel */ - NEScheduler::get().schedule(&_mm_kernel, Window::DimY); + _vector_sum_row.allocator()->allocate(); } - - _memory_group.release(); } -void NEGEMMLowp::configure(const ITensor *a, const ITensor *b, ITensor *output, int32_t a_offset, int32_t b_offset, int32_t output_offset, int32_t output_mult_int, int32_t shift) +void NEGEMMLowp::run() { - NEGEMMLOWP_VALIDATE_DIMENSIONS(a, b, output); - ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(a, b, output); - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8); - - /* The interleaved output matrix will have the following shape: [ a_height * 4, ceil(a_width / 4.0f) ] */ - TensorShape shape_tmp_a = a->info()->tensor_shape(); - shape_tmp_a.set(0, a->info()->dimension(0) * 4); - shape_tmp_a.set(1, std::ceil(a->info()->dimension(1) / 4.f)); - - TensorShape shape_tmp_b = b->info()->tensor_shape(); - shape_tmp_b.set(0, b->info()->dimension(1) * 16); - shape_tmp_b.set(1, std::ceil(b->info()->dimension(0) / 16.f)); + _memory_group.acquire(); - TensorInfo info_a(shape_tmp_a, 1, a->info()->data_type()); - TensorInfo info_b(shape_tmp_b, 1, b->info()->data_type()); - _tmp_a.allocator()->init(info_a); - _tmp_b.allocator()->init(info_b); + // Run matrix A reduction kernel only if _b_offset is not equal to 0 + if(_b_offset != 0) + { + NEScheduler::get().schedule(&_mtx_a_reduction_kernel, Window::DimX); + } - // Manage intermediate buffers - _memory_group.manage(&_tmp_a); - _memory_group.manage(&_tmp_b); + // Run matrix B reduction kernel only if _a_offset is not equal to 0 + if(_a_offset != 0) + { + NEScheduler::get().schedule(&_mtx_b_reduction_kernel, Window::DimX); + } - _interleave_kernel.configure(a, &_tmp_a); - _transpose_kernel.configure(b, &_tmp_b); - _mm_kernel.configure(&_tmp_a, &_tmp_b, output, a_offset, b_offset, output_offset, output_mult_int, shift); + // Run matrix multiply core function + _mm_func.run(); - _tmp_a.allocator()->allocate(); - _tmp_b.allocator()->allocate(); -} + // Run finalise kernel + NEScheduler::get().schedule(&_finalize_kernel, Window::DimY); -#undef NEGEMMLOWP_VALIDATE_DIMENSIONS + _memory_group.release(); +}
\ No newline at end of file |