From 89d71731d8922bc302ac57046126cdaedcf6e96b Mon Sep 17 00:00:00 2001 From: Georgios Pinitas Date: Mon, 29 Oct 2018 20:07:15 +0000 Subject: COMPMID-1704: Collapse the 4th dimension in CLPoolingLayerKernel Change-Id: I76e57af6608b55b6f59a5d06aecc30063ee4c3cc Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/155733 Tested-by: bsgcomp Reviewed-by: Michele DiGiorgio Reviewed-by: Anthony Barbier --- src/core/CL/cl_kernels/pooling_layer.cl | 39 ++++++++++++++++---- src/core/CL/cl_kernels/pooling_layer_quantized.cl | 45 +++++++++++++++++------ src/core/CL/kernels/CLPoolingLayerKernel.cpp | 20 ++++++---- 3 files changed, 78 insertions(+), 26 deletions(-) (limited to 'src/core/CL') diff --git a/src/core/CL/cl_kernels/pooling_layer.cl b/src/core/CL/cl_kernels/pooling_layer.cl index 080835348d..7d15d100e9 100644 --- a/src/core/CL/cl_kernels/pooling_layer.cl +++ b/src/core/CL/cl_kernels/pooling_layer.cl @@ -489,7 +489,11 @@ DATA_TYPE calculate_avg_scale_nhwc(const int pool_size_x, const int pool_size_y, const int pad_x, const int pad_y, const int stride_x, const int stride_y) { int start_x = get_global_id(1) * stride_x - pad_x; +#if defined(DST_DEPTH) + int start_y = (get_global_id(2) % DST_DEPTH) * stride_y - pad_y; +#else /* defined(DST_DEPTH) */ int start_y = get_global_id(2) * stride_y - pad_y; +#endif /* defined(DST_DEPTH) */ #if !defined(EXCLUDE_PADDING) upper_bound_w += pad_x; @@ -522,30 +526,43 @@ DATA_TYPE calculate_avg_scale_nhwc(const int pool_size_x, const int pool_size_y, * @param[in] input_step_y input_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] input_stride_z Stride of the source tensor in Z dimension (in bytes) * @param[in] input_step_z input_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] input_stride_w Stride of the source tensor in W dimension (in bytes) + * @param[in] input_step_w input_stride_w * number of elements along W processed per workitem(in bytes) * @param[in] input_offset_first_element_in_bytes The offset of the first element in the source image * @param[out] output_ptr Pointer to the destination image. Supported data types: same as @p input_ptr - * @param[in] output_stride_x Stride of the destination image in X dimension (in bytes) + * @param[in] output_stride_x Stride of the destination tensor in X dimension (in bytes) * @param[in] output_step_x output_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] output_stride_y Stride of the destination image in Y dimension (in bytes) + * @param[in] output_stride_y Stride of the destination tensor in Y dimension (in bytes) * @param[in] output_step_y output_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] output_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] output_stride_z Stride of the destination tensor in Z dimension (in bytes) * @param[in] output_step_z output_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] output_stride_w Stride of the destination tensor in W dimension (in bytes) + * @param[in] output_step_w output_stride_w * number of elements along W processed per workitem(in bytes) * @param[in] output_offset_first_element_in_bytes The offset of the first element in the destination image */ __kernel void pooling_layer_MxN_nhwc( - TENSOR3D_DECLARATION(input), - TENSOR3D_DECLARATION(output)) + TENSOR4D_DECLARATION(input), + TENSOR4D_DECLARATION(output)) { // Get pixels pointer - Tensor3D input = CONVERT_TO_TENSOR3D_STRUCT(input); - Tensor3D output = CONVERT_TO_TENSOR3D_STRUCT(output); +#if defined(DST_DEPTH) + Tensor4D input = CONVERT_TO_TENSOR4D_STRUCT(input, DST_DEPTH); + Tensor4D output = CONVERT_TO_TENSOR4D_STRUCT(output, DST_DEPTH); +#else /* defined(DST_DEPTH) */ + Tensor3D input = CONVERT_TO_TENSOR3D_STRUCT(input); + Tensor3D output = CONVERT_TO_TENSOR3D_STRUCT(output); +#endif /* defined(DST_DEPTH) */ VEC_DATA_TYPE(DATA_TYPE, 8) vdata = INITIAL_VALUE; DATA_TYPE sdata = INITIAL_VALUE; - const int idx_width = get_global_id(1) * STRIDE_X; + const int idx_width = get_global_id(1) * STRIDE_X; +#if defined(DST_DEPTH) + const int idx_height = (get_global_id(2) % DST_DEPTH) * STRIDE_Y; +#else /* defined(DST_DEPTH) */ const int idx_height = get_global_id(2) * STRIDE_Y; +#endif /* defined(DST_DEPTH) */ for(int y = 0; y < POOL_SIZE_Y; ++y) { @@ -555,8 +572,14 @@ __kernel void pooling_layer_MxN_nhwc( int x1 = select(x, PAD_X - idx_width - 1, x + idx_width - PAD_X < 0 || x + idx_width - PAD_X >= MAX_WIDTH); x1 = select(x1, PAD_X - idx_width - 1, y != y1); +#if defined(DST_DEPTH) + VEC_DATA_TYPE(DATA_TYPE, 8) + data0 = vload8(0, (__global DATA_TYPE *)tensor4D_offset(&input, 0, x1 - PAD_X, y1 - PAD_Y, 0)); +#else /* defined(DST_DEPTH) */ VEC_DATA_TYPE(DATA_TYPE, 8) data0 = vload8(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, x1 - PAD_X, y1 - PAD_Y)); +#endif /* defined(DST_DEPTH) */ + #if defined(POOL_L2) // Raise to power of 2 for L2 Pooling data0 *= data0; diff --git a/src/core/CL/cl_kernels/pooling_layer_quantized.cl b/src/core/CL/cl_kernels/pooling_layer_quantized.cl index 17d893a013..58d89871e3 100644 --- a/src/core/CL/cl_kernels/pooling_layer_quantized.cl +++ b/src/core/CL/cl_kernels/pooling_layer_quantized.cl @@ -126,7 +126,11 @@ int calculate_avg_scale_nhwc(const int pool_size_x, const int pool_size_y, int u const int pad_x, const int pad_y, const int stride_x, const int stride_y) { int start_x = get_global_id(1) * stride_x - pad_x; - int start_y = get_global_id(2) * stride_y - pad_y; +#if defined(DST_DEPTH) + int start_y = (get_global_id(2) % DST_DEPTH) * stride_y - pad_y; +#else /* defined(DST_DEPTH) */ + int start_y = get_global_id(2) * stride_y - pad_y; +#endif /* defined(DST_DEPTH) */ const int end_x = min(start_x + pool_size_x, upper_bound_w); const int end_y = min(start_y + pool_size_y, upper_bound_h); @@ -153,39 +157,58 @@ int calculate_avg_scale_nhwc(const int pool_size_x, const int pool_size_y, int u * @param[in] input_step_y input_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] input_stride_z Stride of the source tensor in Z dimension (in bytes) * @param[in] input_step_z input_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] input_stride_w Stride of the source tensor in W dimension (in bytes) + * @param[in] input_step_w input_stride_w * number of elements along W processed per workitem(in bytes) * @param[in] input_offset_first_element_in_bytes The offset of the first element in the source image * @param[out] output_ptr Pointer to the destination image. Supported data types: same as @p input_ptr - * @param[in] output_stride_x Stride of the destination image in X dimension (in bytes) + * @param[in] output_stride_x Stride of the destination tensor in X dimension (in bytes) * @param[in] output_step_x output_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] output_stride_y Stride of the destination image in Y dimension (in bytes) + * @param[in] output_stride_y Stride of the destination tensor in Y dimension (in bytes) * @param[in] output_step_y output_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] output_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] output_stride_z Stride of the destination tensor in Z dimension (in bytes) * @param[in] output_step_z output_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] output_stride_w Stride of the destination tensor in W dimension (in bytes) + * @param[in] output_step_w output_stride_w * number of elements along W processed per workitem(in bytes) * @param[in] output_offset_first_element_in_bytes The offset of the first element in the destination image */ __kernel void pooling_layer_MxN_quantized_nhwc( - TENSOR3D_DECLARATION(input), - TENSOR3D_DECLARATION(output)) + TENSOR4D_DECLARATION(input), + TENSOR4D_DECLARATION(output)) { // Get pixels pointer +#if defined(DST_DEPTH) + Tensor4D input = CONVERT_TO_TENSOR4D_STRUCT(input, DST_DEPTH); + Tensor4D output = CONVERT_TO_TENSOR4D_STRUCT(output, DST_DEPTH); +#else /* defined(DST_DEPTH) */ Tensor3D input = CONVERT_TO_TENSOR3D_STRUCT(input); Tensor3D output = CONVERT_TO_TENSOR3D_STRUCT(output); +#endif /* defined(DST_DEPTH) */ int8 vdata = 0; - const int idx_width = get_global_id(1) * STRIDE_X; + const int idx_width = get_global_id(1) * STRIDE_X; +#if defined(DST_DEPTH) + const int idx_height = (get_global_id(2) % DST_DEPTH) * STRIDE_Y; +#else /* defined(DST_DEPTH) */ const int idx_height = get_global_id(2) * STRIDE_Y; +#endif /* defined(DST_DEPTH) */ for(int y = 0; y < POOL_SIZE_Y; ++y) { int y1 = select(y, PAD_Y - idx_height, y + idx_height < PAD_Y || y + idx_height > MAX_HEIGHT); for(int x = 0; x < POOL_SIZE_X; ++x) { - int x1 = select(x, PAD_X - idx_width - 1, x + idx_width < PAD_X || x + idx_width > MAX_WIDTH); - x1 = select(x1, PAD_X - idx_width - 1, y != y1); + int x1 = select(x, PAD_X - idx_width - 1, x + idx_width < PAD_X || x + idx_width > MAX_WIDTH); + x1 = select(x1, PAD_X - idx_width - 1, y != y1); + +#if defined(DST_DEPTH) + uchar8 data = vload8(0, (__global uchar *)tensor4D_offset(&input, 0, x1 - PAD_X, y1 - PAD_Y, 0)); +#else /* defined(DST_DEPTH) */ uchar8 data = vload8(0, (__global uchar *)tensor3D_offset(&input, 0, x1 - PAD_X, y1 - PAD_Y)); - int8 data0 = convert_int8(data); - vdata = POOL_OP(vdata, data0); +#endif /* defined(DST_DEPTH) */ + + int8 data0 = convert_int8(data); + vdata = POOL_OP(vdata, data0); } } diff --git a/src/core/CL/kernels/CLPoolingLayerKernel.cpp b/src/core/CL/kernels/CLPoolingLayerKernel.cpp index df13068239..bd21ea0a6c 100644 --- a/src/core/CL/kernels/CLPoolingLayerKernel.cpp +++ b/src/core/CL/kernels/CLPoolingLayerKernel.cpp @@ -257,6 +257,8 @@ void CLPoolingLayerKernel::configure(const ICLTensor *input, ICLTensor *output, build_opts.add_option_if(exclude_padding, "-DEXCLUDE_PADDING"); build_opts.add_option("-DMAX_WIDTH=" + support::cpp11::to_string(input->info()->dimension(idx_width))); build_opts.add_option("-DMAX_HEIGHT=" + support::cpp11::to_string(input->info()->dimension(idx_height))); + build_opts.add_option_if(output->info()->tensor_shape().total_size_upper(3) > 1, + "-DDST_DEPTH=" + support::cpp11::to_string(output->info()->dimension(idx_height))); std::string kernel_name = is_data_type_quantized_asymmetric(data_type) ? "pooling_layer_MxN_quantized_nhwc" : "pooling_layer_MxN_nhwc"; _kernel = static_cast(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options())); break; @@ -315,12 +317,14 @@ void CLPoolingLayerKernel::run(const Window &window, cl::CommandQueue &queue) unsigned int pool_stride_y = 0; std::tie(pool_stride_x, pool_stride_y) = _pool_info.pad_stride_info().stride(); + // Collapse window + Window window_collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ); + switch(_input->info()->data_layout()) { case DataLayout::NCHW: { - Window window_collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ); - Window slice = window_collapsed.first_slice_window_3D(); + Window slice = window_collapsed.first_slice_window_3D(); do { // Upsample input by pool size @@ -343,21 +347,23 @@ void CLPoolingLayerKernel::run(const Window &window, cl::CommandQueue &queue) } case DataLayout::NHWC: { - Window slice = window.first_slice_window_3D(); + const size_t total_batches = _output->info()->tensor_shape().total_size_upper(3); - Window in_slice = window.first_slice_window_3D(); + Window slice = window_collapsed.first_slice_window_4D(); + Window in_slice = window_collapsed.first_slice_window_4D(); in_slice.set(Window::DimX, Window::Dimension(0, _input->info()->dimension(0), _num_elems_processed_per_iteration)); in_slice.set(Window::DimY, Window::Dimension(0, _input->info()->dimension(1), pool_stride_x)); in_slice.set(Window::DimZ, Window::Dimension(0, _input->info()->dimension(2), pool_stride_y)); + in_slice.set(3, Window::Dimension(0, total_batches, 1)); do { // Set inputs unsigned int idx = 0; - add_3D_tensor_argument(idx, _input, in_slice); - add_3D_tensor_argument(idx, _output, slice); + add_4D_tensor_argument(idx, _input, in_slice); + add_4D_tensor_argument(idx, _output, slice); enqueue(queue, *this, slice, lws_hint()); } - while(window.slide_window_slice_3D(slice) && window.slide_window_slice_3D(in_slice)); + while(window.slide_window_slice_4D(slice) && window.slide_window_slice_4D(in_slice)); break; } default: -- cgit v1.2.1