From 1e2af2acc4cb789ba4c0e6935a4581ce4a050609 Mon Sep 17 00:00:00 2001 From: Giorgio Arena Date: Thu, 15 Oct 2020 17:39:41 +0100 Subject: COMPMID-3712 Remove OpenCL padding: CLDepthwiseConvolutionLayer3x3NHWCKernel FP16/32 Removed unused N from partial block loading macro Created utility to assert change in padding Signed-off-by: Giorgio Arena Change-Id: Ifdd30c66dbf5f2842c6b2d939000613d5011708e Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/4192 Reviewed-by: Gian Marco Iodice Tested-by: Arm Jenkins Comments-Addressed: Arm Jenkins --- .../CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp | 224 ++++++++++----------- 1 file changed, 109 insertions(+), 115 deletions(-) (limited to 'src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp') diff --git a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp index 5a0d2d0a62..876ef1ec5d 100644 --- a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp +++ b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp @@ -124,37 +124,33 @@ std::pair validate_and_configure_window(ITensorInfo *input, ITen const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation, ITensorInfo *output_multipliers, ITensorInfo *output_shifts) { - const size_t weights_width = 3; - const size_t weights_height = 3; - - // Get convolved dimensions - const TensorShape output_shape = arm_compute::misc::shape_calculator::compute_depthwise_convolution_shape( - *input, TensorInfo(TensorShape(weights_width, weights_height), 1, weights->data_type()).set_data_layout(DataLayout::NCHW), conv_info, depth_multiplier, dilation); + ARM_COMPUTE_UNUSED(weights); + ARM_COMPUTE_UNUSED(depth_multiplier); - auto_init_if_empty(*output, input->clone()->set_tensor_shape(output_shape).set_quantization_info(output->quantization_info())); + const bool is_stride_1_dilation_1 = ((conv_info.stride().first == conv_info.stride().second) && (conv_info.stride().first == 1) && dilation.x() == 1 && dilation.y() == 1); + unsigned int num_rows_processed_per_iteration = is_stride_1_dilation_1 ? 2 : 1; - const bool is_qasymm = is_data_type_quantized_asymmetric(input->data_type()); - const bool is_stride_1_dilation_1 = ((conv_info.stride().first == conv_info.stride().second) && (conv_info.stride().first == 1) && dilation.x() == 1 && dilation.y() == 1); + Window win{}; + Status err{}; - const unsigned int num_rows_processed_per_iteration = is_stride_1_dilation_1 ? 2 : 1; - const unsigned int num_elems_accessed_per_iteration = is_qasymm ? 4 : (8 / input->element_size()); - const unsigned int num_rows_read_per_iteration = num_rows_processed_per_iteration + 2; - const unsigned int num_rows_written_per_iteration = std::ceil(num_rows_processed_per_iteration / static_cast(conv_info.stride().first)); + if(is_data_type_quantized_asymmetric(input->data_type())) + { + const unsigned int num_elems_accessed_per_iteration = 4; + const unsigned int num_rows_read_per_iteration = num_rows_processed_per_iteration + 2; + const unsigned int num_rows_written_per_iteration = std::ceil(num_rows_processed_per_iteration / static_cast(conv_info.stride().first)); - BorderSize border_size; - border_size = BorderSize(conv_info.pad_left(), 0, std::max(std::max(conv_info.pad_right(), conv_info.pad_bottom()), conv_info.pad_top()), 0); + BorderSize border_size; + border_size = BorderSize(conv_info.pad_left(), 0, std::max(std::max(conv_info.pad_right(), conv_info.pad_bottom()), conv_info.pad_top()), 0); - // Configure kernel window - Window win = calculate_max_window(*output, Steps(num_elems_accessed_per_iteration, num_rows_written_per_iteration)); + // Configure kernel window + win = calculate_max_window(*output, Steps(num_elems_accessed_per_iteration, num_rows_written_per_iteration)); - AccessWindowStatic input_access(input, 0, -border_size.top, ceil_to_multiple(input->dimension(0), num_elems_accessed_per_iteration), - ceil_to_multiple(input->dimension(1) + border_size.bottom, num_rows_read_per_iteration)); - AccessWindowRectangle output_access(output, 0, 0, num_elems_accessed_per_iteration, num_rows_written_per_iteration); + AccessWindowStatic input_access(input, 0, -border_size.top, ceil_to_multiple(input->dimension(0), num_elems_accessed_per_iteration), + ceil_to_multiple(input->dimension(1) + border_size.bottom, num_rows_read_per_iteration)); + AccessWindowRectangle output_access(output, 0, 0, num_elems_accessed_per_iteration, num_rows_written_per_iteration); - bool window_changed = false; + bool window_changed = false; - if(is_qasymm) - { if((output_multipliers != nullptr) && (output_shifts != nullptr)) { AccessWindowHorizontal output_multipliers_access(output_multipliers, 0, num_elems_accessed_per_iteration); @@ -166,27 +162,28 @@ std::pair validate_and_configure_window(ITensorInfo *input, ITen Status err = ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "output_multipliers and output_shifts must be non-nullptr for quantized input"); return std::make_pair(err, win); } + + if(bias != nullptr) + { + AccessWindowHorizontal bias_access(bias, 0, num_elems_accessed_per_iteration); + window_changed = window_changed || update_window_and_padding(win, bias_access); + } + output_access.set_valid_region(win, ValidRegion(Coordinates(), output->tensor_shape())); + + err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; } else { - AccessWindowStatic weights_access(weights, 0, 0, ceil_to_multiple(weights->dimension(0), num_elems_accessed_per_iteration), weights->dimension(1)); - window_changed = update_window_and_padding(win, input_access, weights_access, output_access); - } - - if(bias != nullptr) - { - AccessWindowHorizontal bias_access(bias, 0, num_elems_accessed_per_iteration); - window_changed = window_changed || update_window_and_padding(win, bias_access); + unsigned int num_elems_accessed_per_iteration = adjust_vec_size(4 / input->element_size(), input->dimension(0)); + win = calculate_max_window(*output, Steps(num_elems_accessed_per_iteration, num_rows_processed_per_iteration)); } - output_access.set_valid_region(win, ValidRegion(Coordinates(), output->tensor_shape())); - Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; return std::make_pair(err, win); } } // namespace CLDepthwiseConvolutionLayer3x3NHWCKernel::CLDepthwiseConvolutionLayer3x3NHWCKernel() - : _num_rows_processed_per_iteration(1), _num_planes_processed_per_iteration(1) + : _num_planes_processed_per_iteration(1) { } @@ -211,15 +208,16 @@ void CLDepthwiseConvolutionLayer3x3NHWCKernel::configure(const CLCompileContext conv_info, depth_multiplier, act_info, dilation, (output_multipliers != nullptr) ? output_multipliers->info() : nullptr, (output_shifts != nullptr) ? output_shifts->info() : nullptr)); + + auto padding_info = get_padding_info({ input, weights, biases, output }); + auto win_config = validate_and_configure_window(input->info(), weights->info(), biases != nullptr ? biases->info() : nullptr, output->info(), conv_info, depth_multiplier, dilation, (output_multipliers != nullptr) ? output_multipliers->info() : nullptr, (output_shifts != nullptr) ? output_shifts->info() : nullptr); - ARM_COMPUTE_ERROR_THROW_ON(win_config.first); - - const bool is_stride_1 = ((conv_info.stride().first == conv_info.stride().second) && (conv_info.stride().first == 1)); - const bool is_stride_1_dilation_1 = (is_stride_1 && dilation.x() == 1 && dilation.y() == 1); + const bool is_stride_1 = ((conv_info.stride().first == conv_info.stride().second) && (conv_info.stride().first == 1)); + const bool is_stride_1_dilation_1 = (is_stride_1 && dilation.x() == 1 && dilation.y() == 1); const bool is_quantized_per_channel = is_data_type_quantized_per_channel(weights->info()->data_type()); const bool is_dot8_supported = dot8_supported(CLKernelLibrary::get().get_device()) && !is_quantized_per_channel; @@ -228,31 +226,37 @@ void CLDepthwiseConvolutionLayer3x3NHWCKernel::configure(const CLCompileContext _weights = weights; _biases = biases; _conv_stride_y = conv_info.stride().second; - _num_rows_processed_per_iteration = is_stride_1_dilation_1 ? 2 : 1; _num_planes_processed_per_iteration = is_stride_1_dilation_1 ? 2 : 1; _output_multipliers = output_multipliers; _output_shifts = output_shifts; _is_quantized = is_data_type_quantized_asymmetric(input->info()->data_type()); - // If QASYMM8 and the 8 bit dot product is available, force _num_planes_processed_per_iteration to 1 - if(is_dot8_supported && _is_quantized) + if(_is_quantized) { - _num_planes_processed_per_iteration = 1; - } + _border_size = BorderSize(is_stride_1 ? 0 : conv_info.pad_left(), 0, std::max(std::max(conv_info.pad_right(), conv_info.pad_bottom()), conv_info.pad_top()), 0); - _border_size = BorderSize(_is_quantized && is_stride_1 ? 0 : conv_info.pad_left(), 0, std::max(std::max(conv_info.pad_right(), conv_info.pad_bottom()), conv_info.pad_top()), 0); + // If QASYMM8 and the 8 bit dot product is available, force _num_planes_processed_per_iteration to 1 + if(is_dot8_supported) + { + _num_planes_processed_per_iteration = 1; + } + } - const unsigned int num_elems_accessed_per_iteration = _is_quantized ? 4 : (8 / input->info()->element_size()); + unsigned int num_elems_accessed_per_iteration = _is_quantized ? 4 : adjust_vec_size(4 / input->info()->element_size(), input->info()->dimension(0)); + unsigned int num_rows_processed_per_iteration = is_stride_1_dilation_1 ? 2 : 1; CLBuildOptions build_opts; + build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(_input->info()->data_type())); build_opts.add_option("-DACTIVATION_TYPE=" + lower_string(string_from_activation_func(act_info.activation()))); - build_opts.add_option_if(_biases != nullptr, "-DHAS_BIAS"); build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_accessed_per_iteration)); + build_opts.add_option("-DSRC_DIM_1=" + support::cpp11::to_string(_input->info()->dimension(1))); build_opts.add_option("-DSRC_DIM_2=" + support::cpp11::to_string(_input->info()->dimension(2))); build_opts.add_option("-DCONV_PAD_TOP=" + support::cpp11::to_string(conv_info.pad_top())); build_opts.add_option("-DCONV_PAD_LEFT=" + support::cpp11::to_string(conv_info.pad_left())); - build_opts.add_option("-DDILATION_X=" + support::cpp11::to_string(dilation.x())); - build_opts.add_option("-DDILATION_Y=" + support::cpp11::to_string(dilation.y())); + build_opts.add_option("-DPARTIAL_STORE_N0=" + support::cpp11::to_string(input->info()->dimension(0) % num_elems_accessed_per_iteration)); + build_opts.add_option_if(_biases != nullptr, "-DHAS_BIAS"); + build_opts.add_option_if(_input->info()->tensor_shape().total_size_upper(3) > 1, + "-DDST_DEPTH=" + support::cpp11::to_string(static_cast(std::ceil(_output->info()->dimension(2) / static_cast(_num_planes_processed_per_iteration))))); if(_is_quantized) { @@ -291,7 +295,6 @@ void CLDepthwiseConvolutionLayer3x3NHWCKernel::configure(const CLCompileContext build_opts.add_option("-DO1_VAL=" + support::cpp11::to_string(o1)); } - build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type())); build_opts.add_option("-DWEIGHTS_TYPE=" + get_cl_type_from_data_type(weights->info()->data_type())); build_opts.add_option("-DWEIGHTS_PROMOTED_TYPE=" + get_cl_promoted_type_from_data_type(weights->info()->data_type())); } @@ -299,22 +302,23 @@ void CLDepthwiseConvolutionLayer3x3NHWCKernel::configure(const CLCompileContext { build_opts.add_option_if(act_info.enabled(), "-DA_VAL=" + float_to_string_with_full_precision(act_info.a())); build_opts.add_option_if(act_info.enabled(), "-DB_VAL=" + float_to_string_with_full_precision(act_info.b())); - build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(_input->info()->data_type())); } if(is_stride_1_dilation_1) { - build_opts.add_option("-DNUM_ROWS_PROCESSED=" + support::cpp11::to_string(_num_rows_processed_per_iteration)); + build_opts.add_option("-DNUM_ROWS_PROCESSED=" + support::cpp11::to_string(num_rows_processed_per_iteration)); build_opts.add_option("-DNUM_PLANES_PROCESSED=" + support::cpp11::to_string(_num_planes_processed_per_iteration)); + build_opts.add_option("-DDST_DIM_1=" + support::cpp11::to_string(_output->info()->dimension(1))); build_opts.add_option("-DDST_DIM_2=" + support::cpp11::to_string(_output->info()->dimension(2))); + build_opts.add_option("-DPARTIAL_STORE_M0=" + support::cpp11::to_string((input->info()->dimension(1) + conv_info.pad_left() + conv_info.pad_right()) % num_rows_processed_per_iteration)); } else { build_opts.add_option("-DCONV_STRIDE_X=" + support::cpp11::to_string(conv_info.stride().first)); build_opts.add_option("-DCONV_STRIDE_Y=" + support::cpp11::to_string(_conv_stride_y)); + build_opts.add_option("-DDILATION_X=" + support::cpp11::to_string(dilation.x())); + build_opts.add_option("-DDILATION_Y=" + support::cpp11::to_string(dilation.y())); } - build_opts.add_option_if(_input->info()->tensor_shape().total_size_upper(3) > 1, - "-DDST_DEPTH=" + support::cpp11::to_string(static_cast(std::ceil(_output->info()->dimension(2) / static_cast(_num_planes_processed_per_iteration))))); std::string kernel_name; // Create kernel @@ -331,12 +335,11 @@ void CLDepthwiseConvolutionLayer3x3NHWCKernel::configure(const CLCompileContext kernel_name += (is_stride_1_dilation_1 ? "_stride1" : ""); } - build_opts.add_option_if(input->info()->data_type() == DataType::F16, "-DIS_F16"); - build_opts.add_option_if(input->info()->data_type() == DataType::F32, "-DIS_F32"); - ICLKernel::configure_internal(win_config.second); _kernel = create_kernel(compile_context, kernel_name, build_opts.options()); + ARM_COMPUTE_ERROR_ON(!_is_quantized && has_padding_changed(padding_info)); + // Set config_id for enabling LWS tuning _config_id = kernel_name; _config_id += "_"; @@ -364,7 +367,6 @@ Status CLDepthwiseConvolutionLayer3x3NHWCKernel::validate(const ITensorInfo *inp (output_multipliers != nullptr) ? output_multipliers->clone().get() : nullptr, (output_shifts != nullptr) ? output_shifts->clone().get() : nullptr) .first); - return Status{}; } @@ -373,23 +375,11 @@ void CLDepthwiseConvolutionLayer3x3NHWCKernel::run(const Window &window, cl::Com ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window); - // Collapse window - Window window_collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ); - const size_t total_batches = _input->info()->tensor_shape().total_size_upper(3); + const size_t total_batches = _input->info()->tensor_shape().total_size_upper(3); - Window win = window_collapsed; + Window win = window.collapse_if_possible(ICLKernel::window(), Window::DimZ); win.set(Window::DimZ, Window::Dimension(0, std::ceil(_output->info()->dimension(2) / static_cast(_num_planes_processed_per_iteration)) * total_batches, 1)); - // Create input window and adjust - Window win_in = win; - win_in.set_dimension_step(Window::DimY, _num_rows_processed_per_iteration); - win_in.set_dimension_step(Window::DimZ, _conv_stride_y); - - ARM_COMPUTE_ERROR_ON((win_in.y().step() < window.y().step()) || (win_in.z().step() < window.z().step())); - - Window slice_in = win_in.first_slice_window_4D(); - Window slice_out = win.first_slice_window_4D(); - unsigned int idx = 2 * num_arguments_per_4D_tensor() + (_is_quantized ? num_arguments_per_2D_tensor() : num_arguments_per_3D_tensor()); if(_is_quantized) @@ -409,60 +399,64 @@ void CLDepthwiseConvolutionLayer3x3NHWCKernel::run(const Window &window, cl::Com add_1D_tensor_argument(idx, _biases, win_biases); } - // Calculate the max_offset. - // max_offset is the offset for the last NOT valid value in the Z dimension (spatial dimension Y for NHWC) - // |******************| - // | pad_top | - // |******************| - // | | - // | plane0 | - // | batch0 | - // |__________________| - // |******************| Batch 0 - // | pad_bottom | - // | pad_top | - // |******************| - // | | - // | plane1 | - // | batch0 | - // |__________________|-----> max_offset - // |******************| - // | pad_bottom | - // | pad_top | - // |******************| - // | | - // | plane0 | - // | batch1 | - // |__________________| - // |******************| Batch 1 - // | pad_bottom | - // | pad_top | - // |******************| - // | | - // | plane1 | - // | batch1 | - // |__________________| - // | pad_bottom | - // |******************| - const int max_offset = _input->info()->strides_in_bytes().z() * _input->info()->dimension(2) - (_input->info()->padding().bottom + _input->info()->padding().top) * - _input->info()->strides_in_bytes().y(); - _kernel.setArg(idx, max_offset); + if(_is_quantized) + { + // Calculate the max_offset. + // max_offset is the offset for the last NOT valid value in the Z dimension (spatial dimension Y for NHWC) + // |******************| + // | pad_top | + // |******************| + // | | + // | plane0 | + // | batch0 | + // |__________________| + // |******************| Batch 0 + // | pad_bottom | + // | pad_top | + // |******************| + // | | + // | plane1 | + // | batch0 | + // |__________________|-----> max_offset + // |******************| + // | pad_bottom | + // | pad_top | + // |******************| + // | | + // | plane0 | + // | batch1 | + // |__________________| + // |******************| Batch 1 + // | pad_bottom | + // | pad_top | + // |******************| + // | | + // | plane1 | + // | batch1 | + // |__________________| + // | pad_bottom | + // |******************| + const int max_offset = _input->info()->strides_in_bytes().z() * _input->info()->dimension(2) - (_input->info()->padding().bottom + _input->info()->padding().top) * + _input->info()->strides_in_bytes().y(); + _kernel.setArg(idx, max_offset); + } + Window slice = win.first_slice_window_4D(); do { unsigned int idx = 0; - add_4D_tensor_argument(idx, _input, slice_in); - add_4D_tensor_argument(idx, _output, slice_out); + add_4D_tensor_argument(idx, _input, slice); + add_4D_tensor_argument(idx, _output, slice); if(_is_quantized) { - add_2D_tensor_argument(idx, _weights, slice_out); + add_2D_tensor_argument(idx, _weights, slice); } else { - add_3D_tensor_argument(idx, _weights, slice_out); + add_3D_tensor_argument(idx, _weights, slice); } - enqueue(queue, *this, slice_out, lws_hint()); + enqueue(queue, *this, slice, lws_hint()); } - while(win.slide_window_slice_4D(slice_out) && win_in.slide_window_slice_4D(slice_in)); + while(win.slide_window_slice_4D(slice)); } } // namespace arm_compute -- cgit v1.2.1