From df4cf57c7394265b27d051cb1cf0152c53659126 Mon Sep 17 00:00:00 2001 From: Michele Di Giorgio Date: Wed, 9 Oct 2019 15:32:39 +0100 Subject: COMPMID-2306: CLDepthwiseConvolution: support for QUANT8_PER_CHANNEL_SYMM Change-Id: I18c886400daa2dcba0b91011bc4e503d807a4732 Signed-off-by: Michele Di Giorgio Reviewed-on: https://review.mlplatform.org/c/2143 Comments-Addressed: Arm Jenkins Reviewed-by: Giorgio Arena Tested-by: Arm Jenkins --- .../CLDepthwiseConvolutionLayerNativeKernel.cpp | 131 +++++++++++++++------ 1 file changed, 98 insertions(+), 33 deletions(-) (limited to 'src/core/CL/kernels/CLDepthwiseConvolutionLayerNativeKernel.cpp') diff --git a/src/core/CL/kernels/CLDepthwiseConvolutionLayerNativeKernel.cpp b/src/core/CL/kernels/CLDepthwiseConvolutionLayerNativeKernel.cpp index 2115fc614d..3fc236eaa7 100644 --- a/src/core/CL/kernels/CLDepthwiseConvolutionLayerNativeKernel.cpp +++ b/src/core/CL/kernels/CLDepthwiseConvolutionLayerNativeKernel.cpp @@ -42,13 +42,13 @@ namespace arm_compute namespace { Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const DWCWeightsKernelInfo &dwc_weights_info, - const DWCKernelInfo &dwc_info, const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation) + const DWCKernelInfo &dwc_info, const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation, + const ITensorInfo *output_multipliers, const ITensorInfo *output_shifts) { ARM_COMPUTE_UNUSED(dwc_info); ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input); ARM_COMPUTE_RETURN_ERROR_ON_DATA_LAYOUT_NOT_IN(input, DataLayout::NHWC); ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F16, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights); ARM_COMPUTE_RETURN_ERROR_ON(depth_multiplier > 1 && dwc_weights_info.n0 != 1); ARM_COMPUTE_RETURN_ERROR_ON(conv_info.stride().first < 1); ARM_COMPUTE_RETURN_ERROR_ON(conv_info.stride().second < 1); @@ -57,24 +57,53 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, ARM_COMPUTE_UNUSED(idx_c); ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(idx_c) != (input->dimension(idx_c) * depth_multiplier)); + const TensorShape output_shape = arm_compute::misc::shape_calculator::compute_depthwise_convolution_shape(*input, *weights, conv_info, depth_multiplier, dilation); + + const bool is_quantized = is_data_type_quantized(input->data_type()); + if(biases != nullptr) { - ARM_COMPUTE_RETURN_ERROR_ON(biases->dimension(0) != weights->dimension(0)); + ARM_COMPUTE_RETURN_ERROR_ON(biases->dimension(0) != output_shape[idx_c]); ARM_COMPUTE_RETURN_ERROR_ON(biases->num_dimensions() > 1); - if(is_data_type_quantized(input->data_type())) + if(is_quantized) { 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_MISMATCHING_DATA_TYPES(input, biases); + } + } + + if(is_quantized) + { + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output_multipliers, output_shifts); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output_multipliers, 1, DataType::S32); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output_shifts, 1, DataType::S32); + ARM_COMPUTE_RETURN_ERROR_ON(output_multipliers->num_dimensions() > 1); + ARM_COMPUTE_RETURN_ERROR_ON(output_shifts->num_dimensions() > 1); + + if(is_data_type_quantized_per_channel(weights->data_type())) + { + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(weights, 1, DataType::QSYMM8_PER_CHANNEL); + ARM_COMPUTE_RETURN_ERROR_ON(output_shape[idx_c] != output_multipliers->dimension(0)); + ARM_COMPUTE_RETURN_ERROR_ON(output_shape[idx_c] != output_shifts->dimension(0)); + } + else + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights); + ARM_COMPUTE_RETURN_ERROR_ON(1 != output_multipliers->dimension(0)); + ARM_COMPUTE_RETURN_ERROR_ON(1 != output_shifts->dimension(0)); } } + else + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights); + } if(output->total_size() != 0) { - const TensorShape output_shape = arm_compute::misc::shape_calculator::compute_depthwise_convolution_shape(*input, *weights, conv_info, depth_multiplier, dilation); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), output_shape); } @@ -82,7 +111,8 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, } std::pair validate_and_configure_window(ITensorInfo *input, ITensorInfo *weights, ITensorInfo *bias, ITensorInfo *output, const DWCWeightsKernelInfo &dwc_weights_info, - const DWCKernelInfo &dwc_info, const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation) + const DWCKernelInfo &dwc_info, const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation, + ITensorInfo *output_multipliers, ITensorInfo *output_shifts) { ARM_COMPUTE_UNUSED(dwc_info); @@ -113,6 +143,21 @@ std::pair validate_and_configure_window(ITensorInfo *input, ITen window_changed = update_window_and_padding(win, input_access, weights_access, output_access); } + if(is_data_type_quantized(input->data_type())) + { + if((output_multipliers != nullptr) && (output_shifts != nullptr)) + { + AccessWindowHorizontal output_multipliers_access(output_multipliers, 0, n0); + AccessWindowHorizontal output_shifts_access(output_shifts, 0, n0); + window_changed = window_changed || update_window_and_padding(win, output_multipliers_access, output_shifts_access); + } + else + { + 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); + } + } + 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{}; @@ -121,32 +166,44 @@ std::pair validate_and_configure_window(ITensorInfo *input, ITen } // namespace CLDepthwiseConvolutionLayerNativeKernel::CLDepthwiseConvolutionLayerNativeKernel() - : _input(nullptr), _weights(nullptr), _biases(nullptr), _output(nullptr), _depth_multiplier(1) + : _input(nullptr), + _weights(nullptr), + _biases(nullptr), + _output(nullptr), + _depth_multiplier(1), + _output_multipliers(nullptr), + _output_shifts(nullptr), + _is_quantized(false) { } void CLDepthwiseConvolutionLayerNativeKernel::configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const DWCWeightsKernelInfo &dwc_weights_info, - const DWCKernelInfo &dwc_info, const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation) + const DWCKernelInfo &dwc_info, const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation, + const ICLTensor *output_multipliers, const ICLTensor *output_shifts) { ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output); - ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), weights->info(), (biases != nullptr) ? biases->info() : nullptr, output->info(), dwc_weights_info, dwc_info, conv_info, depth_multiplier, - dilation)); + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), weights->info(), (biases != nullptr) ? biases->info() : nullptr, output->info(), + dwc_weights_info, dwc_info, conv_info, depth_multiplier, dilation, + (output_multipliers != nullptr) ? output_multipliers->info() : nullptr, (output_shifts != nullptr) ? output_shifts->info() : nullptr)); - auto win_config = validate_and_configure_window(input->info(), weights->info(), biases != nullptr ? biases->info() : nullptr, output->info(), dwc_weights_info, dwc_info, conv_info, depth_multiplier, - dilation); + auto win_config = validate_and_configure_window(input->info(), weights->info(), biases != nullptr ? biases->info() : nullptr, output->info(), + dwc_weights_info, dwc_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); - _input = input; - _output = output; - _weights = weights; - _biases = biases; - _depth_multiplier = depth_multiplier; + _input = input; + _output = output; + _weights = weights; + _biases = biases; + _depth_multiplier = depth_multiplier; + _output_multipliers = output_multipliers; + _output_shifts = output_shifts; + _is_quantized = is_data_type_quantized(input->info()->data_type()); const size_t idx_w = get_data_layout_dimension_index(input->info()->data_layout(), DataLayoutDimension::WIDTH); const size_t idx_h = get_data_layout_dimension_index(input->info()->data_layout(), DataLayoutDimension::HEIGHT); const size_t weights_width = weights->info()->dimension(idx_w); const size_t weights_height = weights->info()->dimension(idx_h); - const bool is_quantized = is_data_type_quantized(input->info()->data_type()); CLBuildOptions build_opts; build_opts.add_option_if(_biases != nullptr, "-DHAS_BIAS"); @@ -166,24 +223,18 @@ void CLDepthwiseConvolutionLayerNativeKernel::configure(const ICLTensor *input, build_opts.add_option("-DDILATION_X=" + support::cpp11::to_string(dilation.x())); build_opts.add_option("-DDILATION_Y=" + support::cpp11::to_string(dilation.y())); - std::string kernel_name = (is_quantized) ? "dwc_MxN_native_quantized8_nhwc" : "dwc_MxN_native_fp_nhwc"; + std::string kernel_name = (_is_quantized) ? "dwc_MxN_native_quantized8_nhwc" : "dwc_MxN_native_fp_nhwc"; - if(is_quantized) + if(_is_quantized) { const UniformQuantizationInfo iq_info = _input->info()->quantization_info().uniform(); const UniformQuantizationInfo wq_info = _weights->info()->quantization_info().uniform(); const UniformQuantizationInfo oq_info = _output->info()->quantization_info().uniform(); - float multiplier = iq_info.scale * wq_info.scale / oq_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("-DINPUT_OFFSET=" + support::cpp11::to_string(-iq_info.offset)); build_opts.add_option("-DWEIGHTS_OFFSET=" + support::cpp11::to_string(-wq_info.offset)); build_opts.add_option("-DOUTPUT_OFFSET=" + support::cpp11::to_string(oq_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_if(is_data_type_quantized_per_channel(weights->info()->data_type()), "-DPER_CHANNEL_QUANTIZATION"); if(dwc_info.activation_info.enabled()) { @@ -199,6 +250,9 @@ void CLDepthwiseConvolutionLayerNativeKernel::configure(const ICLTensor *input, build_opts.add_option("-DS1_VAL=" + float_to_string_with_full_precision(s1)); 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())); } else { @@ -228,12 +282,15 @@ void CLDepthwiseConvolutionLayerNativeKernel::configure(const ICLTensor *input, } Status CLDepthwiseConvolutionLayerNativeKernel::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, - const DWCWeightsKernelInfo &dwc_weights_info, const DWCKernelInfo &dwc_info, const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation) + const DWCWeightsKernelInfo &dwc_weights_info, const DWCKernelInfo &dwc_info, const PadStrideInfo &conv_info, + unsigned int depth_multiplier, const Size2D &dilation, const ITensorInfo *output_multipliers, const ITensorInfo *output_shifts) { - ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, weights, biases, output, dwc_weights_info, dwc_info, conv_info, depth_multiplier, dilation)); + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, weights, biases, output, dwc_weights_info, dwc_info, conv_info, depth_multiplier, dilation, output_multipliers, output_shifts)); ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), weights->clone().get(), biases != nullptr ? biases->clone().get() : nullptr, - output->clone().get(), dwc_weights_info, dwc_info, conv_info, depth_multiplier, dilation) + output->clone().get(), dwc_weights_info, dwc_info, conv_info, depth_multiplier, dilation, + output_multipliers != nullptr ? output_multipliers->clone().get() : nullptr, + output_shifts != nullptr ? output_shifts->clone().get() : nullptr) .first); return Status{}; @@ -255,15 +312,23 @@ void CLDepthwiseConvolutionLayerNativeKernel::run(const Window &window, cl::Comm slice_out.set(Window::DimX, Window::Dimension(0, _input->info()->tensor_shape()[0], 1)); } + unsigned int idx = 2 * num_arguments_per_4D_tensor() + num_arguments_per_3D_tensor(); + + // Set output multipliers in case of quantized data type + if(_is_quantized) + { + add_1D_tensor_argument(idx, _output_multipliers, slice_in); + add_1D_tensor_argument(idx, _output_shifts, slice_in); + } + if(_biases != nullptr) { - unsigned int idx = 2 * num_arguments_per_4D_tensor() + num_arguments_per_3D_tensor(); add_1D_tensor_argument(idx, _biases, slice_in); } do { - unsigned int idx = 0; + idx = 0; add_4D_tensor_argument(idx, _input, slice_in); add_4D_tensor_argument(idx, _output, slice_out); add_3D_tensor_argument(idx, _weights, slice_out); -- cgit v1.2.1