diff options
Diffstat (limited to 'src/core/CL/kernels/CLPoolingLayerKernel.cpp')
| -rw-r--r-- | src/core/CL/kernels/CLPoolingLayerKernel.cpp | 137 |
1 files changed, 110 insertions, 27 deletions
diff --git a/src/core/CL/kernels/CLPoolingLayerKernel.cpp b/src/core/CL/kernels/CLPoolingLayerKernel.cpp index bdc88a4f86..d60e196b7f 100644 --- a/src/core/CL/kernels/CLPoolingLayerKernel.cpp +++ b/src/core/CL/kernels/CLPoolingLayerKernel.cpp @@ -60,13 +60,20 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, c { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output); ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(indices, "Indices not supported in the CL backend."); ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::F16, DataType::F32); ARM_COMPUTE_RETURN_ERROR_ON_MSG((is_data_type_quantized_asymmetric(input->data_type()) && pool_info.pool_type == PoolingType::L2), "Unsupported combination of parameters!"); ARM_COMPUTE_RETURN_ERROR_ON_MSG(is_data_type_quantized(input->data_type()) && !pool_info.exclude_padding && (pool_info.pool_type == PoolingType::AVG) && pool_info.pad_stride_info.has_padding() && (input->data_layout() == DataLayout::NHWC), "exclude_padding equal false is not supported for AVG Pooling with padding on quantized types"); + // Check indices + if(indices) + { + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(indices, 1, DataType::U32); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(pool_info.pool_type != PoolingType::MAX, "Pooling indices only supported for MAX pooling method"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG((pool_info.pool_size != Size2D(2, 2)), "Pooling indices only supported for pool size 2x2"); + } // Checks performed when output is configured if(output->total_size() != 0) @@ -80,7 +87,7 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, c return Status{}; } -std::tuple<Status, Window, CLPoolingConfig> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output, const PoolingLayerInfo &pool_info) +std::tuple<Status, Window, CLPoolingConfig> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output, const PoolingLayerInfo &pool_info, ITensorInfo *indices = nullptr) { ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); @@ -140,7 +147,19 @@ std::tuple<Status, Window, CLPoolingConfig> validate_and_configure_window(ITenso AccessWindowRectangle input_access(input, -pool_pad_left, -pool_pad_top, num_elems_read_per_iteration, pool_size_y, pool_stride_x, pool_stride_y); AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration); - window_changed = update_window_and_padding(win, input_access, output_access); + + // Update indices window + if(indices) + { + AccessWindowHorizontal indices_access(indices, 0, num_elems_processed_per_iteration); + window_changed = update_window_and_padding(win, input_access, output_access, indices_access); + indices_access.set_valid_region(win, ValidRegion(Coordinates(), indices->tensor_shape())); + } + else + { + window_changed = update_window_and_padding(win, input_access, output_access); + } + output_access.set_valid_region(win, ValidRegion(Coordinates(), output->tensor_shape())); break; } @@ -153,7 +172,19 @@ std::tuple<Status, Window, CLPoolingConfig> validate_and_configure_window(ITenso 0, -1, ceil_to_multiple(input->dimension(0), num_elems_processed_per_iteration), input->dimension(1)); AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration); - window_changed = update_window_and_padding(win, input_access, output_access); + + // Update indices window + if(indices) + { + AccessWindowHorizontal indices_access(indices, 0, num_elems_processed_per_iteration); + window_changed = update_window_and_padding(win, input_access, output_access, indices_access); + indices_access.set_valid_region(win, ValidRegion(Coordinates(), indices->tensor_shape())); + } + else + { + window_changed = update_window_and_padding(win, input_access, output_access); + } + output_access.set_valid_region(win, ValidRegion(Coordinates(), output->tensor_shape())); break; } @@ -207,8 +238,39 @@ void CLPoolingLayerKernel::configure(const CLCompileContext &compile_context, co // Set build options CLBuildOptions build_opts; + const DataType data_type = input->info()->data_type(); + + // Configure kernel window + auto win_config = validate_and_configure_window(input->info(), output->info(), pool_info, (indices ? indices->info() : nullptr)); + + ARM_COMPUTE_ERROR_THROW_ON(std::get<0>(win_config)); + ICLKernel::configure_internal(std::get<1>(win_config)); + + if(_data_layout == DataLayout::NCHW) + { + CLPoolingConfig pooling_config = std::get<2>(win_config); + _num_elems_processed_per_iteration = pooling_config.first; + _border_size = pooling_config.second; + } + else + { + _border_size = BorderSize(1, 0, 0, 0); + _num_elems_processed_per_iteration = 8; + } - if(is_data_type_quantized_asymmetric(input->info()->data_type()) && input->info()->quantization_info() != output->info()->quantization_info()) + // Tensor paddings are used to calculate the indicies for MAX pooling + if(pool_info.pool_size == Size2D(2, 2) && pool_type == PoolingType::MAX && _indices && is_data_type_float(data_type)) + { + build_opts.add_option("-DPAD_TENSOR_LEFT=" + support::cpp11::to_string(input->info()->padding().left)); + build_opts.add_option("-DPAD_TENSOR_RIGHT=" + support::cpp11::to_string(input->info()->padding().right)); + build_opts.add_option("-DPAD_TENSOR_TOP=" + support::cpp11::to_string(input->info()->padding().top)); + build_opts.add_option("-DPAD_TENSOR_BOTTOM=" + support::cpp11::to_string(input->info()->padding().bottom)); + build_opts.add_option("-DTENSOR_CHANNEL=" + support::cpp11::to_string(input->info()->dimension(idx_channel))); + build_opts.add_option("-DTENSOR_WIDTH=" + support::cpp11::to_string(input->info()->dimension(idx_width))); + build_opts.add_option("-DTENSOR_HEIGHT=" + support::cpp11::to_string(input->info()->dimension(idx_height))); + } + + if(is_data_type_quantized_asymmetric(data_type) && input->info()->quantization_info() != output->info()->quantization_info()) { const UniformQuantizationInfo iq_info = input->info()->quantization_info().uniform(); const UniformQuantizationInfo oq_info = output->info()->quantization_info().uniform(); @@ -223,8 +285,6 @@ void CLPoolingLayerKernel::configure(const CLCompileContext &compile_context, co auto_init(input->info(), output->info(), pool_info); ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), pool_info, (indices) ? indices->info() : nullptr)); - const DataType data_type = input->info()->data_type(); - build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(data_type)); build_opts.add_option("-DPOOL_" + string_from_pooling_type(pool_type)); build_opts.add_option("-DSTRIDE_X=" + support::cpp11::to_string(pool_stride_x)); @@ -282,6 +342,20 @@ void CLPoolingLayerKernel::configure(const CLCompileContext &compile_context, co + support::cpp11::to_string(pool_size_x); _kernel = create_kernel(compile_context, kernel_name, build_opts.options()); } + else if(pool_info.pool_size == Size2D(2, 2) && pool_type == PoolingType::MAX && _indices && is_data_type_float(data_type)) + { + // For max pooling with pool2x2, store indicies which will be used in max unpooling + if(data_type == DataType::F32) + { + std::string kernel_name = "pooling_layer_2_nchw_indices_fp32"; + _kernel = create_kernel(compile_context, kernel_name, build_opts.options()); + } + else if(data_type == DataType::F16) + { + std::string kernel_name = "pooling_layer_2_nchw_indices_fp16"; + _kernel = create_kernel(compile_context, kernel_name, build_opts.options()); + } + } else // Run general case { std::string kernel_name = is_data_type_quantized_asymmetric(data_type) ? "pooling_layer_MxN_quantized_nchw" : "pooling_layer_MxN_nchw"; @@ -296,32 +370,33 @@ void CLPoolingLayerKernel::configure(const CLCompileContext &compile_context, co 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 = create_kernel(compile_context, kernel_name, build_opts.options()); + build_opts.add_option_if(output->info()->tensor_shape().total_size_upper(3) > 1, + "-DBATCH_SIZE=" + support::cpp11::to_string(output->info()->tensor_shape().total_size_upper(3))); + + if(pool_info.pool_size == Size2D(2, 2) && pool_type == PoolingType::MAX && _indices && is_data_type_float(data_type)) + { + if(data_type == DataType::F32) + { + std::string kernel_name = "pooling_layer_2_nhwc_indices_fp32"; + _kernel = create_kernel(compile_context, kernel_name, build_opts.options()); + } + else if(data_type == DataType::F16) + { + std::string kernel_name = "pooling_layer_2_nhwc_indices_fp16"; + _kernel = create_kernel(compile_context, kernel_name, build_opts.options()); + } + } + else + { + std::string kernel_name = is_data_type_quantized_asymmetric(data_type) ? "pooling_layer_MxN_quantized_nhwc" : "pooling_layer_MxN_nhwc"; + _kernel = create_kernel(compile_context, kernel_name, build_opts.options()); + } break; } default: ARM_COMPUTE_ERROR("Not implemented"); } - // Configure kernel window - auto win_config = validate_and_configure_window(input->info(), output->info(), pool_info); - - ARM_COMPUTE_ERROR_THROW_ON(std::get<0>(win_config)); - ICLKernel::configure_internal(std::get<1>(win_config)); - - if(_data_layout == DataLayout::NCHW) - { - CLPoolingConfig pooling_config = std::get<2>(win_config); - _num_elems_processed_per_iteration = pooling_config.first; - _border_size = pooling_config.second; - } - else - { - _border_size = BorderSize(1, 0, 0, 0); - _num_elems_processed_per_iteration = 8; - } - // Set config_id for enabling LWS tuning _config_id = "pooling_layer_"; _config_id += lower_string(string_from_data_type(data_type)); @@ -377,6 +452,10 @@ void CLPoolingLayerKernel::run(const Window &window, cl::CommandQueue &queue) unsigned int idx = 0; add_3D_tensor_argument(idx, _input, in_slice); add_3D_tensor_argument(idx, _output, slice); + if(_indices && is_data_type_float(_input->info()->data_type()) && (_pool_info.pool_type == PoolingType::MAX) && (_pool_info.pool_size == Size2D(2, 2))) + { + add_3D_tensor_argument(idx, _indices, slice); + } enqueue(queue, *this, slice, lws_hint()); } while(window_collapsed.slide_window_slice_3D(slice)); @@ -398,6 +477,10 @@ void CLPoolingLayerKernel::run(const Window &window, cl::CommandQueue &queue) unsigned int idx = 0; add_4D_tensor_argument(idx, _input, in_slice); add_4D_tensor_argument(idx, _output, slice); + if(_indices && is_data_type_float(_input->info()->data_type()) && (_pool_info.pool_type == PoolingType::MAX) && (_pool_info.pool_size == Size2D(2, 2))) + { + add_4D_tensor_argument(idx, _indices, slice); + } enqueue(queue, *this, slice, lws_hint()); } while(window.slide_window_slice_4D(slice) && window.slide_window_slice_4D(in_slice)); |