diff options
Diffstat (limited to 'src/gpu/cl/kernels/ClPool3dKernel.cpp')
| -rw-r--r-- | src/gpu/cl/kernels/ClPool3dKernel.cpp | 103 |
1 files changed, 60 insertions, 43 deletions
diff --git a/src/gpu/cl/kernels/ClPool3dKernel.cpp b/src/gpu/cl/kernels/ClPool3dKernel.cpp index d068832fed..a08c5d4be7 100644 --- a/src/gpu/cl/kernels/ClPool3dKernel.cpp +++ b/src/gpu/cl/kernels/ClPool3dKernel.cpp @@ -28,6 +28,7 @@ #include "arm_compute/core/utils/helpers/AdjustVecSize.h" #include "arm_compute/core/utils/misc/ShapeCalculator.h" #include "arm_compute/core/utils/StringUtils.h" + #include "src/core/CL/CLValidate.h" #include "src/core/helpers/AutoConfiguration.h" #include "src/core/helpers/WindowHelpers.h" @@ -50,10 +51,13 @@ Status validate_arguments(const ITensorInfo *src, const ITensorInfo *dst, const ARM_COMPUTE_RETURN_ERROR_ON_MSG(src->data_layout() != DataLayout::NDHWC, "Only NDHWC layout supported"); ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(src); - ARM_COMPUTE_RETURN_ERROR_ON_MSG((pool_info.stride.x() == 0 || pool_info.stride.y() == 0 || pool_info.stride.z() == 0), "Strides cannot be zero."); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src, 1, DataType::F16, DataType::F32, DataType::QASYMM8_SIGNED, DataType::QASYMM8); - ARM_COMPUTE_RETURN_ERROR_ON_MSG((!is_data_type_float(src->data_type())) && (!pool_info.exclude_padding - && (pool_info.pool_type == PoolingType::AVG)), + ARM_COMPUTE_RETURN_ERROR_ON_MSG( + (pool_info.stride.x() == 0 || pool_info.stride.y() == 0 || pool_info.stride.z() == 0), + "Strides cannot be zero."); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src, 1, DataType::F16, DataType::F32, DataType::QASYMM8_SIGNED, + DataType::QASYMM8); + ARM_COMPUTE_RETURN_ERROR_ON_MSG((!is_data_type_float(src->data_type())) && + (!pool_info.exclude_padding && (pool_info.pool_type == PoolingType::AVG)), "Exclude padding is unsupported for non-float types for Avg op"); const auto data_layout = src->data_layout(); @@ -68,17 +72,21 @@ Status validate_arguments(const ITensorInfo *src, const ITensorInfo *dst, const int output_height = 0; int output_depth = 0; - bool round_type_ceil_with_asymm_padding = (pool_info.round_type == DimensionRoundingType::CEIL) && (!is_symmetric(pool_info.padding)); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(round_type_ceil_with_asymm_padding, "Cannot use dimension round type CEIL when padding is asymmetric."); + bool round_type_ceil_with_asymm_padding = + (pool_info.round_type == DimensionRoundingType::CEIL) && (!is_symmetric(pool_info.padding)); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(round_type_ceil_with_asymm_padding, + "Cannot use dimension round type CEIL when padding is asymmetric."); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(is_pool_3d_region_entirely_outside_input(pool_info), "Pooling region that is entirely outside input tensor is unsupported"); - std::tie(output_width, output_height, output_depth) = scaled_3d_dimensions_signed(src->tensor_shape()[idx_width], src->tensor_shape()[idx_height], - src->tensor_shape()[idx_depth], pool_size_x, pool_size_y, - pool_size_z, pool_info); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(is_pool_3d_region_entirely_outside_input(pool_info), + "Pooling region that is entirely outside input tensor is unsupported"); + std::tie(output_width, output_height, output_depth) = + scaled_3d_dimensions_signed(src->tensor_shape()[idx_width], src->tensor_shape()[idx_height], + src->tensor_shape()[idx_depth], pool_size_x, pool_size_y, pool_size_z, pool_info); - ARM_COMPUTE_RETURN_ERROR_ON_MSG((output_width < 1 || output_height < 1 || output_depth < 1), "Calculated output dimension size is invalid"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG((output_width < 1 || output_height < 1 || output_depth < 1), + "Calculated output dimension size is invalid"); // Checks performed when dst is configured - if(dst->total_size() != 0) + if (dst->total_size() != 0) { ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src, dst); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(src, dst); @@ -95,11 +103,14 @@ ClPool3dKernel::ClPool3dKernel() _type = CLKernelType::POOL; } -void ClPool3dKernel::configure(const ClCompileContext &compile_context, const ITensorInfo *src, ITensorInfo *dst, const Pooling3dLayerInfo &pool_info) +void ClPool3dKernel::configure(const ClCompileContext &compile_context, + const ITensorInfo *src, + ITensorInfo *dst, + const Pooling3dLayerInfo &pool_info) { ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst); ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(src, dst, pool_info)); - auto padding_info = get_padding_info({ src, dst }); + auto padding_info = get_padding_info({src, dst}); // Auto init if empty TensorShape out_shape = compute_pool3d_shape(src->tensor_shape(), pool_info); @@ -112,23 +123,23 @@ void ClPool3dKernel::configure(const ClCompileContext &compile_context, const IT _num_elems_processed_per_iteration = (dst->data_type() == DataType::F32) ? 2 : 4; _num_elems_processed_per_iteration = adjust_vec_size(_num_elems_processed_per_iteration, dst->dimension(0)); - const PoolingType pool_type = pool_info.pool_type; - const int idx_width = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH); - const int idx_height = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::HEIGHT); - const int idx_depth = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::DEPTH); - const int idx_channel = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::CHANNEL); - const int idx_batch_size = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::BATCHES); - const int pool_size_x = pool_info.is_global_pooling ? src->dimension(idx_width) : pool_info.pool_size.width; - const int pool_size_y = pool_info.is_global_pooling ? src->dimension(idx_height) : pool_info.pool_size.height; - const int pool_size_z = pool_info.is_global_pooling ? src->dimension(idx_depth) : pool_info.pool_size.depth; - const bool exclude_padding = pool_info.exclude_padding; - const int pool_stride_x = pool_info.stride.x(); - const int pool_stride_y = pool_info.stride.y(); - const int pool_stride_z = pool_info.stride.z(); - const int pool_pad_top = pool_info.padding.top; - const int pool_pad_left = pool_info.padding.left; - const int pool_pad_front = pool_info.padding.front; - const DataType data_type = src->data_type(); + const PoolingType pool_type = pool_info.pool_type; + const int idx_width = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH); + const int idx_height = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::HEIGHT); + const int idx_depth = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::DEPTH); + const int idx_channel = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::CHANNEL); + const int idx_batch_size = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::BATCHES); + const int pool_size_x = pool_info.is_global_pooling ? src->dimension(idx_width) : pool_info.pool_size.width; + const int pool_size_y = pool_info.is_global_pooling ? src->dimension(idx_height) : pool_info.pool_size.height; + const int pool_size_z = pool_info.is_global_pooling ? src->dimension(idx_depth) : pool_info.pool_size.depth; + const bool exclude_padding = pool_info.exclude_padding; + const int pool_stride_x = pool_info.stride.x(); + const int pool_stride_y = pool_info.stride.y(); + const int pool_stride_z = pool_info.stride.z(); + const int pool_pad_top = pool_info.padding.top; + const int pool_pad_left = pool_info.padding.left; + const int pool_pad_front = pool_info.padding.front; + const DataType data_type = src->data_type(); // Set build options CLBuildOptions build_opts; @@ -149,7 +160,7 @@ void ClPool3dKernel::configure(const ClCompileContext &compile_context, const IT build_opts.add_option("-DSRC_DEPTH=" + support::cpp11::to_string(src->dimension(idx_depth))); // If datatype is quantized add relevant parameters - if(is_data_type_quantized_asymmetric(data_type) && src->quantization_info() != dst->quantization_info()) + if (is_data_type_quantized_asymmetric(data_type) && src->quantization_info() != dst->quantization_info()) { const UniformQuantizationInfo iq_info = src->quantization_info().uniform(); const UniformQuantizationInfo oq_info = dst->quantization_info().uniform(); @@ -161,9 +172,9 @@ void ClPool3dKernel::configure(const ClCompileContext &compile_context, const IT } // Set the initial value for the pooling operation accordingly with the data type - if(pool_type == PoolingType::MAX) + if (pool_type == PoolingType::MAX) { - if(is_data_type_quantized(data_type)) + if (is_data_type_quantized(data_type)) { PixelValue type_min{}; std::tie(type_min, std::ignore) = get_min_max(data_type); @@ -171,7 +182,8 @@ void ClPool3dKernel::configure(const ClCompileContext &compile_context, const IT } else { - build_opts.add_option("-DINITIAL_VALUE=" + float_to_string_with_full_precision(std::numeric_limits<float>::lowest())); + build_opts.add_option("-DINITIAL_VALUE=" + + float_to_string_with_full_precision(std::numeric_limits<float>::lowest())); } } else @@ -181,16 +193,18 @@ void ClPool3dKernel::configure(const ClCompileContext &compile_context, const IT } // Create kernel // Floating point mixed precision is support on F16 only - const auto use_fp_mixed_precision = (data_type == DataType::F16) && pool_info.fp_mixed_precision && pool_type != PoolingType::MAX; + const auto use_fp_mixed_precision = + (data_type == DataType::F16) && pool_info.fp_mixed_precision && pool_type != PoolingType::MAX; // Wider accumulation is required to avoid accuracy loss // Case 1: Floating point mixed precision (fp16 src data and fp32 accumulation) DataType acc_data_type = data_type; - if(use_fp_mixed_precision) + if (use_fp_mixed_precision) { acc_data_type = DataType::F32; } - else if(is_data_type_quantized(data_type) && pool_type != PoolingType::MAX) // Use S32 for avg pooling to allow for integer division + else if (is_data_type_quantized(data_type) && + pool_type != PoolingType::MAX) // Use S32 for avg pooling to allow for integer division { acc_data_type = DataType::S32; } @@ -202,11 +216,13 @@ void ClPool3dKernel::configure(const ClCompileContext &compile_context, const IT build_opts.add_option("-DDST_DEPTH=" + support::cpp11::to_string(dst->dimension(idx_depth))); build_opts.add_option("-DDST_CHANNELS=" + support::cpp11::to_string(dst->dimension(idx_channel))); build_opts.add_option("-DDST_BATCH_SIZE=" + support::cpp11::to_string(dst->dimension(idx_batch_size))); - build_opts.add_option("-DVEC_SIZE_LEFTOVER=" + support::cpp11::to_string(src->dimension(0) % _num_elems_processed_per_iteration)); + build_opts.add_option("-DVEC_SIZE_LEFTOVER=" + + support::cpp11::to_string(src->dimension(0) % _num_elems_processed_per_iteration)); // if datatype is quantized use quantized kernel function - std::string kernel_name = (is_data_type_quantized_asymmetric(data_type) ? "pooling_3d_layer_MxN_ndhwc_quantized" : "pooling_3d_layer_MxN_ndhwc"); - _kernel = create_kernel(compile_context, kernel_name, build_opts.options()); + std::string kernel_name = (is_data_type_quantized_asymmetric(data_type) ? "pooling_3d_layer_MxN_ndhwc_quantized" + : "pooling_3d_layer_MxN_ndhwc"); + _kernel = create_kernel(compile_context, kernel_name, build_opts.options()); // Configure kernel window Window win = calculate_max_window(*dst, Steps(_num_elems_processed_per_iteration)); @@ -240,8 +256,9 @@ void ClPool3dKernel::run_op(ITensorPack &tensors, const Window &window, cl::Comm ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window); - const auto src = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC)); - auto dst = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST_0)); + const auto src = + utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC)); + auto dst = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST_0)); // Collapse 3D window Window window_collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ); |