diff options
Diffstat (limited to 'src/core/experimental/dynamic_fusion/ClKernelBuildingImpl/components/ClElementwiseKernelComponent.cpp')
| -rw-r--r-- | src/core/experimental/dynamic_fusion/ClKernelBuildingImpl/components/ClElementwiseKernelComponent.cpp | 61 |
1 files changed, 53 insertions, 8 deletions
diff --git a/src/core/experimental/dynamic_fusion/ClKernelBuildingImpl/components/ClElementwiseKernelComponent.cpp b/src/core/experimental/dynamic_fusion/ClKernelBuildingImpl/components/ClElementwiseKernelComponent.cpp index 24a9eee9a3..7515aec27a 100644 --- a/src/core/experimental/dynamic_fusion/ClKernelBuildingImpl/components/ClElementwiseKernelComponent.cpp +++ b/src/core/experimental/dynamic_fusion/ClKernelBuildingImpl/components/ClElementwiseKernelComponent.cpp @@ -24,6 +24,7 @@ #ifdef ENABLE_EXPERIMENTAL_DYNAMIC_FUSION #include "src/core/experimental/dynamic_fusion/ClKernelBuildingImpl/components/ClElementwiseKernelComponent.h" +#include "arm_compute/core/Error.h" #include "arm_compute/core/Validate.h" #include "src/core/helpers/AutoConfiguration.h" #include "src/core/helpers/WindowHelpers.h" @@ -57,9 +58,13 @@ Window ClElementwiseKernelComponent::get_window() const auto_init_if_empty(*dst_info, out_shape, 1, lhs_info->data_type()); + TensorShape output_shape = dst_info->tensor_shape(); + // Collapse Dim 1 (W) and Dim 2 (H) together, leave Dim 0 (C) and upper dimensions unchanged + // This is in line with the collapsing convention used by Conv2d + output_shape.collapse(2U, 1U); const unsigned int vector_size_byte_opencl = 16; const unsigned int num_elems_processed_per_iteration = adjust_vec_size(vector_size_byte_opencl / dst_info->element_size(), dst_info->dimension(0)); - Window win = calculate_max_window(*dst_info, Steps(num_elems_processed_per_iteration)); + Window win = calculate_max_window(output_shape, Steps(num_elems_processed_per_iteration)); return win; } @@ -83,8 +88,12 @@ std::string ClElementwiseKernelComponent::get_component_code() const TILE({{DATA_TYPE}}, M0, N0, lhs_tile); TILE({{DATA_TYPE}}, M0, N0, rhs_tile); + // Since mout maps to dimensions 1 (y) and dimension 2 (z) of the input tensor because of the collapsed window, bout maps to dimension 3 (w) + {{lhs}}_offset_first_element_in_bytes += bout * {{lhs}}_stride_w; + {{rhs}}_offset_first_element_in_bytes += bout * {{rhs}}_stride_w; + T_LOAD({{DATA_TYPE}}, M0, N0, BUFFER, {{lhs}}, cout, mout, 1, {{lhs}}_stride_y, lhs_tile); - T_LOAD({{DATA_TYPE}}, M0, N0, BUFFER, {{rhs}}, cout, mout, 1, {{rhs}}_stride_y, rhs_tile); + T_LOAD({{DATA_TYPE}}, {{rhs_m0}}, {{rhs_n0}}, BUFFER, {{rhs}}, {{rhs_start_x}}, {{rhs_start_y}}, 1, {{rhs}}_stride_y, rhs_tile); #if defined(IS_BROADCAST) T_ELTWISE_BROADCAST_{{ELTWISE_OP}}_X({{DATA_TYPE}}, M0, N0, lhs_tile, rhs_tile, {{dst}}); @@ -107,7 +116,7 @@ std::string ClElementwiseKernelComponent::get_component_code() const { TILE({{DATA_TYPE}}, M0, N0, addend_tile); - T_LOAD({{DATA_TYPE}}, M0, N0, BUFFER, {{addend}}, cout, mout, 1, {{addend}}_stride_y, addend_tile); + T_LOAD({{DATA_TYPE}}, {{rhs_m0}}, {{rhs_n0}}, BUFFER, {{addend}}, {{rhs_start_x}}, {{rhs_start_y}}, 1, {{addend}}_stride_y, addend_tile); #if defined(IS_BROADCAST) T_ELTWISE_BROADCAST_{{ELTWISE_OP}}_X({{DATA_TYPE}}, M0, N0, {{acc}}, addend_tile, {{acc}}); @@ -122,16 +131,18 @@ std::string ClElementwiseKernelComponent::get_component_code() const CLBuildOptions ClElementwiseKernelComponent::generate_build_options() const { - const auto t_src_info = _blueprint->impl().get_kernel_argument_info(_rhs.arg_id); + const auto t_rhs_info = _blueprint->impl().get_kernel_argument_info(_rhs.arg_id); const auto t_dst_info = _blueprint->impl().get_kernel_argument_info(_blueprint->impl().get_dst_id()); - CLBuildOptions build_opts{}; - const auto n0 = _blueprint->impl().get_execution_window().x().step(); - const auto m0 = _blueprint->impl().get_execution_window().y().step(); - const bool is_broadcast = t_src_info->tensor_shape() != t_dst_info->tensor_shape(); + CLBuildOptions build_opts{}; + const auto n0 = _blueprint->impl().get_execution_window().x().step(); + const auto m0 = _blueprint->impl().get_execution_window().y().step(); + const unsigned int partial_store_n0 = t_dst_info->dimension(0) % n0; + const bool is_broadcast = t_rhs_info->tensor_shape() != t_dst_info->tensor_shape(); build_opts.add_option("-DM0=" + support::cpp11::to_string(m0)); build_opts.add_option("-DN0=" + support::cpp11::to_string(n0)); + build_opts.add_option("-DPARTIAL_N0=" + support::cpp11::to_string(partial_store_n0)); build_opts.add_option_if(is_broadcast, "-DIS_BROADCAST"); return build_opts; @@ -166,6 +177,7 @@ ClElementwiseKernelComponent::TagLUT ClElementwiseKernelComponent::get_tag_lut(c { TagLUT lut{}; const auto t_dst_info = _blueprint->impl().get_kernel_argument_info(_blueprint->impl().get_dst_id()); + const auto t_rhs_info = _blueprint->impl().get_kernel_argument_info(_rhs.arg_id); // Arguments and global shared variables const bool is_root = _blueprint->impl().group(_lhs.arg_id) == SharedVarGroup::Argument && _blueprint->impl().group(_rhs.arg_id) == SharedVarGroup::Argument; if(is_root) @@ -211,6 +223,39 @@ ClElementwiseKernelComponent::TagLUT ClElementwiseKernelComponent::get_tag_lut(c default: ARM_COMPUTE_ERROR("Arithmetic Operation not supported"); } + + // Set broadcast parameters + // PRE: All tensors are broadcast-compatible + const bool is_broadcast = t_rhs_info->tensor_shape() != t_dst_info->tensor_shape(); + if(is_broadcast) + { + // Note that n0 maps to input tensor dimension 0, m0 maps to input dimensions 1 and 2 because of our collapse strategy + if(t_rhs_info->dimension(0) == 1U && t_rhs_info->dimension(1) == 1U && t_rhs_info->dimension(2) == 1U) // Broadcast in X, Y, Z: collapsed rhs win [M0xN0] = [1x1] + { + lut["rhs_m0"] = "1"; + lut["rhs_n0"] = "1"; + lut["rhs_start_y"] = "0"; + lut["rhs_start_x"] = "0"; + } + else if(t_rhs_info->dimension(1) == 1U && t_rhs_info->dimension(2) == 1U) // Broadcast in Y and Z: collapsed rhs win [M0xN0] = [1xN] + { + lut["rhs_m0"] = "1"; + lut["rhs_n0"] = "N0"; + lut["rhs_start_y"] = "0"; + lut["rhs_start_x"] = "cout"; + } + else + { + ARM_COMPUTE_ERROR("Only support rhs broadcasting in all X, Y, Z dimensions, or just in Y and Z dimensions"); + } + } + else + { + lut["rhs_m0"] = "M0"; + lut["rhs_n0"] = "N0"; + lut["rhs_start_y"] = "mout"; + lut["rhs_start_x"] = "cout"; + } return lut; } } // namespace dynamic_fusion |