From d051e97e36b9981f411093904cc019c2c7f9ac75 Mon Sep 17 00:00:00 2001 From: Giorgio Arena Date: Wed, 20 Jun 2018 11:46:42 +0100 Subject: COMPMID-811 Add NHWC data format support for CL depthwise convolution Change-Id: I574f7945f0be009c638d860028bce8b52b4120fd Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/136484 Tested-by: Jenkins Reviewed-by: Gian Marco Iodice --- .../CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp | 171 ++++++++++++++------- 1 file changed, 118 insertions(+), 53 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 d24ef0f496..1de08aa1a2 100644 --- a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp +++ b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp @@ -44,18 +44,27 @@ namespace Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier, const ActivationLayerInfo &act_info) { - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8); - ARM_COMPUTE_RETURN_ERROR_ON_MSG((act_info.enabled()) && (act_info.activation() != ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU) - && (act_info.activation() != ActivationLayerInfo::ActivationFunction::BOUNDED_RELU) - && (act_info.activation() != ActivationLayerInfo::ActivationFunction::RELU), - "For QASYMM8 only relu, lower bounded relu and lower-upper bounded relu are supported"); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32, DataType::QASYMM8); + ARM_COMPUTE_RETURN_ERROR_ON_MSG((act_info.enabled()) && (input->data_type() == DataType::F32 || ((act_info.activation() != ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU) + && (act_info.activation() != ActivationLayerInfo::ActivationFunction::BOUNDED_RELU) + && (act_info.activation() != ActivationLayerInfo::ActivationFunction::RELU))), + "For QASYMM8 only relu, lower bounded relu and lower-upper bounded relu are supported"); //COMPMID-1317 add fused activation for F32 ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights); ARM_COMPUTE_RETURN_ERROR_ON(depth_multiplier > 1); // COMPMID-1071 Add depth multiplier support for NHWC ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(1) != 3 || weights->dimension(2) != 3); + const bool is_qasymm = is_data_type_quantized_asymmetric(input->data_type()); + if(biases != nullptr) { - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(biases, 1, DataType::S32); + if(is_qasymm) + { + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(biases, 1, DataType::S32); + } + else + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(weights, biases); + } ARM_COMPUTE_RETURN_ERROR_ON(biases->dimension(0) != weights->dimension(0)); ARM_COMPUTE_RETURN_ERROR_ON(biases->num_dimensions() > 1); } @@ -72,12 +81,23 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, std::pair validate_and_configure_window(ITensorInfo *input, ITensorInfo *weights, ITensorInfo *bias, ITensorInfo *output, const PadStrideInfo &conv_info) { - const unsigned int num_rows_processed_per_iteration = 4; - const unsigned int num_elems_accessed_per_iteration = 4; + const bool is_qasymm = is_data_type_quantized_asymmetric(input->data_type()); + const bool is_stride_1 = ((conv_info.stride().first == conv_info.stride().second) && (conv_info.stride().first == 1)); + + const unsigned int num_rows_processed_per_iteration = is_qasymm ? 4 : (is_stride_1 ? 2 : 1); + const unsigned int num_elems_accessed_per_iteration = is_qasymm ? 4 : 2; const unsigned int num_rows_read_per_iteration = num_rows_processed_per_iteration + 2; - const unsigned int num_rows_written_per_iteration = num_rows_processed_per_iteration / conv_info.stride().first; + const unsigned int num_rows_written_per_iteration = std::ceil(num_rows_processed_per_iteration / static_cast(conv_info.stride().first)); - const BorderSize border_size(std::max(conv_info.pad_left(), conv_info.pad_top()), 0, std::max(conv_info.pad_right(), conv_info.pad_bottom()), 0); + BorderSize border_size; + if(is_qasymm) + { + border_size = BorderSize(std::max(conv_info.pad_left(), conv_info.pad_top()), 0, std::max(conv_info.pad_right(), conv_info.pad_bottom()), 0); + } + else + { + 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)); @@ -103,7 +123,7 @@ std::pair validate_and_configure_window(ITensorInfo *input, ITen } // namespace CLDepthwiseConvolutionLayer3x3NHWCKernel::CLDepthwiseConvolutionLayer3x3NHWCKernel() - : _num_rows_processed_per_iteration(1) + : _num_rows_processed_per_iteration(1), _num_planes_processed_per_iteration(1) { } @@ -135,66 +155,97 @@ void CLDepthwiseConvolutionLayer3x3NHWCKernel::configure(const ICLTensor *input, ARM_COMPUTE_ERROR_ON(conv_stride_x < 1 || conv_stride_x > 2); ARM_COMPUTE_ERROR_ON(std::max(conv_info.pad_top(), conv_info.pad_bottom()) > 1); - _input = input; - _output = output; - _weights = weights; - _biases = biases; - _conv_stride_y = conv_info.stride().second; - _num_rows_processed_per_iteration = 4; + const bool is_qasymm = is_data_type_quantized_asymmetric(input->info()->data_type()); + const bool is_stride_1 = ((conv_info.stride().first == conv_info.stride().second) && (conv_info.stride().first == 1)); - const unsigned int num_elems_accessed_per_iteration = 4; + _input = input; + _output = output; + _weights = weights; + _biases = biases; + _conv_stride_y = conv_info.stride().second; + _num_rows_processed_per_iteration = is_qasymm ? 4 : (is_stride_1 ? 2 : 1); + _num_planes_processed_per_iteration = (is_stride_1 && !is_qasymm) ? 2 : 1; - _border_size = BorderSize(std::max(conv_info.pad_left(), conv_info.pad_top()), 0, std::max(conv_info.pad_right(), conv_info.pad_bottom()), 0); + const unsigned int num_elems_accessed_per_iteration = is_qasymm ? 4 : 2; - float multiplier = _input->info()->quantization_info().scale * _weights->info()->quantization_info().scale / _output->info()->quantization_info().scale; - int output_multiplier = 0; - int output_shift = 0; - quantization::calculate_quantized_multiplier_less_than_one(multiplier, &output_multiplier, &output_shift); + if(is_qasymm) + { + _border_size = BorderSize(std::max(conv_info.pad_left(), conv_info.pad_top()), 0, std::max(conv_info.pad_right(), conv_info.pad_bottom()), 0); + } + else + { + _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); + } CLBuildOptions build_opts; build_opts.add_option_if(_biases != nullptr, "-DHAS_BIAS"); - build_opts.add_option("-DINPUT_OFFSET=" + support::cpp11::to_string(-_input->info()->quantization_info().offset)); - build_opts.add_option("-DWEIGHTS_OFFSET=" + support::cpp11::to_string(-_weights->info()->quantization_info().offset)); - build_opts.add_option("-DOUTPUT_OFFSET=" + support::cpp11::to_string(_output->info()->quantization_info().offset)); - build_opts.add_option("-DK_OFFSET=" + support::cpp11::to_string(9 * input->info()->quantization_info().offset * weights->info()->quantization_info().offset)); - build_opts.add_option("-DOUTPUT_MULTIPLIER=" + support::cpp11::to_string(output_multiplier)); - build_opts.add_option("-DOUTPUT_SHIFT=" + support::cpp11::to_string(output_shift)); 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())); - if(act_info.enabled()) + if(is_qasymm) { - const int a_val = input->info()->quantization_info().quantize(act_info.a(), RoundingPolicy::TO_NEAREST_UP); - const int b_val = input->info()->quantization_info().quantize(act_info.b(), RoundingPolicy::TO_NEAREST_UP); - const int o1 = input->info()->quantization_info().offset; - - build_opts.add_option("-DFUSED_ACTIVATION=" + lower_string(string_from_activation_func(act_info.activation()))); - build_opts.add_option("-DA_VAL=" + support::cpp11::to_string(a_val)); - build_opts.add_option("-DB_VAL=" + support::cpp11::to_string(b_val)); - build_opts.add_option("-DCONST_0=" + support::cpp11::to_string(o1)); - - if(output != nullptr) + float multiplier = _input->info()->quantization_info().scale * _weights->info()->quantization_info().scale / _output->info()->quantization_info().scale; + int output_multiplier = 0; + int output_shift = 0; + quantization::calculate_quantized_multiplier_less_than_one(multiplier, &output_multiplier, &output_shift); + + build_opts.add_option("-DSRC_DIM_1=" + support::cpp11::to_string(_input->info()->dimension(1))); + build_opts.add_option("-DINPUT_OFFSET=" + support::cpp11::to_string(-_input->info()->quantization_info().offset)); + build_opts.add_option("-DWEIGHTS_OFFSET=" + support::cpp11::to_string(-_weights->info()->quantization_info().offset)); + build_opts.add_option("-DOUTPUT_OFFSET=" + support::cpp11::to_string(_output->info()->quantization_info().offset)); + build_opts.add_option("-DK_OFFSET=" + support::cpp11::to_string(9 * input->info()->quantization_info().offset * weights->info()->quantization_info().offset)); + build_opts.add_option("-DOUTPUT_MULTIPLIER=" + support::cpp11::to_string(output_multiplier)); + build_opts.add_option("-DOUTPUT_SHIFT=" + support::cpp11::to_string(output_shift)); + + if(act_info.enabled()) { - const float s1 = input->info()->quantization_info().scale; - const float s2 = output->info()->quantization_info().scale; - const int o2 = output->info()->quantization_info().offset; + const int a_val = input->info()->quantization_info().quantize(act_info.a(), RoundingPolicy::TO_NEAREST_UP); + const int b_val = input->info()->quantization_info().quantize(act_info.b(), RoundingPolicy::TO_NEAREST_UP); + const int o1 = input->info()->quantization_info().offset; + + build_opts.add_option("-DFUSED_ACTIVATION=" + lower_string(string_from_activation_func(act_info.activation()))); + build_opts.add_option("-DA_VAL=" + support::cpp11::to_string(a_val)); + build_opts.add_option("-DB_VAL=" + support::cpp11::to_string(b_val)); + build_opts.add_option("-DCONST_0=" + support::cpp11::to_string(o1)); - if(o1 != o2 || s1 != s2) + if(output != nullptr) { - build_opts.add_option("-DS1_VAL=" + float_to_string_with_full_precision(s1)); - build_opts.add_option("-DS2_VAL=" + float_to_string_with_full_precision(s2)); - build_opts.add_option("-DO1_VAL=" + support::cpp11::to_string(o1)); - build_opts.add_option("-DO2_VAL=" + support::cpp11::to_string(o2)); + const float s1 = input->info()->quantization_info().scale; + const float s2 = output->info()->quantization_info().scale; + const int o2 = output->info()->quantization_info().offset; + + if(o1 != o2 || s1 != s2) + { + build_opts.add_option("-DS1_VAL=" + float_to_string_with_full_precision(s1)); + build_opts.add_option("-DS2_VAL=" + float_to_string_with_full_precision(s2)); + build_opts.add_option("-DO1_VAL=" + support::cpp11::to_string(o1)); + build_opts.add_option("-DO2_VAL=" + support::cpp11::to_string(o2)); + } } } } + else if(is_stride_1) + { + 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_2=" + support::cpp11::to_string(_output->info()->dimension(2))); + } + else + { + build_opts.add_option("-DCONV_STRIDE_X=" + support::cpp11::to_string(conv_stride_x)); + build_opts.add_option("-DCONV_STRIDE_Y=" + support::cpp11::to_string(_conv_stride_y)); + } // Create kernel - std::string kernel_name = std::string("depthwise_convolution_3x3_quantized_nhwc_stride") + support::cpp11::to_string(conv_stride_x); - _kernel = static_cast(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options())); + std::string kernel_name = std::string("depthwise_convolution_3x3") + (is_qasymm ? std::string("_quantized") : std::string()) + std::string("_nhwc"); + if(is_qasymm || is_stride_1) + { + kernel_name += std::string("_stride") + support::cpp11::to_string(conv_stride_x); + } + + _kernel = static_cast(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options())); // Configure kernel window auto win_config = validate_and_configure_window(input->info(), weights->info(), biases != nullptr ? biases->info() : nullptr, output->info(), conv_info); @@ -213,6 +264,8 @@ void CLDepthwiseConvolutionLayer3x3NHWCKernel::configure(const ICLTensor *input, _config_id += support::cpp11::to_string(output->info()->dimension(0)); _config_id += "_"; _config_id += support::cpp11::to_string(output->info()->dimension(1)); + _config_id += "_"; + _config_id += string_from_data_type(input->info()->data_type()); } Status CLDepthwiseConvolutionLayer3x3NHWCKernel::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, @@ -233,15 +286,18 @@ void CLDepthwiseConvolutionLayer3x3NHWCKernel::run(const Window &window, cl::Com ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window); + Window win = window; + win.set(Window::DimZ, Window::Dimension(0, std::ceil(_output->info()->dimension(2) / static_cast(_num_planes_processed_per_iteration)), 1)); + // Create input window and adjust - Window win_in = window; + 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_3D(); - Window slice_out = window.first_slice_window_3D(); + Window slice_out = win.first_slice_window_3D(); if(_biases != nullptr) { @@ -252,6 +308,15 @@ void CLDepthwiseConvolutionLayer3x3NHWCKernel::run(const Window &window, cl::Com add_1D_tensor_argument(idx, _biases, win_biases); } + if(!(is_data_type_quantized_asymmetric(_input->info()->data_type()))) + { + unsigned int idx = 3 * num_arguments_per_3D_tensor() + ((_biases != nullptr) ? num_arguments_per_1D_tensor() : 0); + 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); + } + do { unsigned int idx = 0; -- cgit v1.2.1