diff options
Diffstat (limited to 'src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp')
| -rw-r--r-- | src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp | 298 |
1 files changed, 36 insertions, 262 deletions
diff --git a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp index f7603e6397..2a1365e6e2 100644 --- a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp +++ b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp @@ -30,7 +30,6 @@ #include "arm_compute/core/TensorInfo.h" #include "arm_compute/core/Utils.h" #include "arm_compute/core/utils/misc/ShapeCalculator.h" -#include "arm_compute/core/utils/quantization/AsymmHelpers.h" #include "src/core/AccessWindowStatic.h" #include "src/core/CL/CLValidate.h" #include "src/core/CL/ICLKernel.h" @@ -43,17 +42,11 @@ namespace arm_compute 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, const Size2D &dilation, - const ITensorInfo *output_multipliers, const ITensorInfo *output_shifts) + const PadStrideInfo &conv_info, unsigned int depth_multiplier, const ActivationLayerInfo &act_info, const Size2D &dilation) { + ARM_COMPUTE_UNUSED(act_info); ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32, DataType::QASYMM8, DataType::QASYMM8_SIGNED); - ARM_COMPUTE_RETURN_ERROR_ON_MSG((act_info.enabled()) && (input->data_type() == DataType::QASYMM8 || input->data_type() == DataType::QASYMM8_SIGNED) - && (act_info.activation() != ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU) - && (act_info.activation() != ActivationLayerInfo::ActivationFunction::BOUNDED_RELU) - && (act_info.activation() != ActivationLayerInfo::ActivationFunction::RELU) - && (act_info.activation() != ActivationLayerInfo::ActivationFunction::LOGISTIC), - "For QASYMM8 only logistic, relu, lower bounded relu and lower-upper bounded relu are supported"); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32); ARM_COMPUTE_RETURN_ERROR_ON(depth_multiplier > 1); // COMPMID-1071 Add depth multiplier support for NHWC ARM_COMPUTE_RETURN_ERROR_ON(conv_info.stride().first < 1); @@ -61,54 +54,21 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, ARM_COMPUTE_RETURN_ERROR_ON((dilation.x() < 1) || (dilation.y() < 1)); - const bool is_qasymm = is_data_type_quantized_asymmetric(input->data_type()); const size_t weights_width = 3; const size_t weights_height = 3; const ConvolutionInfo info{ conv_info, depth_multiplier, ActivationLayerInfo(), dilation }; - 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), info); - if(is_qasymm) - { - DepthwiseConvolutionReshapeInfo info; - info.c0 = 4; - ARM_COMPUTE_RETURN_ERROR_ON((weights->dimension(0) / info.c0) != weights_width * weights_height); - - 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(output_shape[0] != output_multipliers->dimension(0)); - ARM_COMPUTE_RETURN_ERROR_ON(output_shape[0] != 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); - ARM_COMPUTE_RETURN_ERROR_ON((weights->dimension(1) != weights_width) || (weights->dimension(2) != weights_height)); - } + + 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), info); + + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights); + ARM_COMPUTE_RETURN_ERROR_ON((weights->dimension(1) != weights_width) || (weights->dimension(2) != weights_height)); if(biases != nullptr) { ARM_COMPUTE_RETURN_ERROR_ON(biases->dimension(0) != output_shape[0]); - 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_MISMATCHING_DATA_TYPES(weights, biases); ARM_COMPUTE_RETURN_ERROR_ON(biases->num_dimensions() > 1); } @@ -122,10 +82,9 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, } std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *weights, ITensorInfo *bias, ITensorInfo *output, - const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation, - ITensorInfo *output_multipliers, ITensorInfo *output_shifts) + const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation) { - ARM_COMPUTE_UNUSED(weights); + ARM_COMPUTE_UNUSED(weights, bias); ARM_COMPUTE_UNUSED(depth_multiplier); 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); @@ -134,115 +93,46 @@ std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITen Window win{}; Status err{}; - 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<float>(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); - - // 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); - - bool window_changed = false; - - if((output_multipliers != nullptr) && (output_shifts != nullptr)) - { - AccessWindowHorizontal output_multipliers_access(output_multipliers, 0, num_elems_accessed_per_iteration); - AccessWindowHorizontal output_shifts_access(output_shifts, 0, num_elems_accessed_per_iteration); - window_changed = window_changed || update_window_and_padding(win, input_access, output_access, 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); - } - - if(bias != nullptr) - { - AccessWindowHorizontal bias_access(bias, 0, num_elems_accessed_per_iteration); - window_changed = window_changed || update_window_and_padding(win, bias_access); - } - - err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; - } - else - { - 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)); - } + 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)); return std::make_pair(err, win); } } // namespace CLDepthwiseConvolutionLayer3x3NHWCKernel::CLDepthwiseConvolutionLayer3x3NHWCKernel() - : _num_planes_processed_per_iteration(1) -{ -} - -BorderSize CLDepthwiseConvolutionLayer3x3NHWCKernel::border_size() const + : _input(), _output(), _weights(), _biases(), _num_planes_processed_per_iteration(1) { - return _border_size; } void CLDepthwiseConvolutionLayer3x3NHWCKernel::configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, - const PadStrideInfo &conv_info, unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation, - const ICLTensor *output_multipliers, const ICLTensor *output_shifts) + const PadStrideInfo &conv_info, unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation) { - configure(CLKernelLibrary::get().get_compile_context(), input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation, output_multipliers, output_shifts); + configure(CLKernelLibrary::get().get_compile_context(), input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation); } void CLDepthwiseConvolutionLayer3x3NHWCKernel::configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, - const PadStrideInfo &conv_info, unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation, - const ICLTensor *output_multipliers, const ICLTensor *output_shifts) + const PadStrideInfo &conv_info, unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation) { 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(), - conv_info, depth_multiplier, act_info, dilation, - (output_multipliers != nullptr) ? output_multipliers->info() : nullptr, - (output_shifts != nullptr) ? output_shifts->info() : nullptr)); + conv_info, depth_multiplier, act_info, dilation)); 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); + conv_info, depth_multiplier, dilation); - 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; + 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); _input = input; _output = output; _weights = weights; _biases = biases; - _conv_stride_y = conv_info.stride().second; _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(_is_quantized) - { - _border_size = BorderSize(input->info()->padding()); - - // 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; - } - } - - 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_elems_accessed_per_iteration = 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; @@ -257,54 +147,8 @@ void CLDepthwiseConvolutionLayer3x3NHWCKernel::configure(const CLCompileContext 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<int>(std::ceil(_output->info()->dimension(2) / static_cast<float>(_num_planes_processed_per_iteration))))); - - 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(); - - 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(-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("-DK_OFFSET=" + support::cpp11::to_string(9 * iq_info.offset * wq_info.offset)); - build_opts.add_option_if(is_quantized_per_channel, "-DPER_CHANNEL_QUANTIZATION"); - build_opts.add_option_if(is_dot8_supported, "-DIS_DOT8"); - - // Compute non-per-channel multiplier and shift anyway to make OpenCL kernel simpler - float multiplier = iq_info.scale * wq_info.scale / oq_info.scale; - int output_multiplier = 0; - int output_shift = 0; - quantization::calculate_quantized_multiplier(multiplier, &output_multiplier, &output_shift); - 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()) - { - int a_val{}; - int b_val{}; - std::tie(b_val, a_val) = get_quantized_activation_min_max(act_info, input->info()->data_type(), oq_info); - - const int o1 = oq_info.offset; - - 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)); - - const float s1 = iq_info.scale; - 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("-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())); - } - else - { - 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_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())); if(is_stride_1_dilation_1) { @@ -317,30 +161,20 @@ void CLDepthwiseConvolutionLayer3x3NHWCKernel::configure(const CLCompileContext 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("-DCONV_STRIDE_Y=" + support::cpp11::to_string(conv_info.stride().second)); 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; // Create kernel - if(_is_quantized) - { - kernel_name = std::string("dwc_3x3_reshaped_quantized8"); - kernel_name += (is_dot8_supported && is_stride_1_dilation_1 ? "_dot8" : ""); - kernel_name += (is_stride_1_dilation_1 ? "_stride1" : ""); - kernel_name += "_nhwc"; - } - else - { - kernel_name = std::string("depthwise_convolution_3x3_nhwc"); - kernel_name += (is_stride_1_dilation_1 ? "_stride1" : ""); - } + std::string kernel_name; + kernel_name = std::string("depthwise_convolution_3x3_nhwc"); + kernel_name += (is_stride_1_dilation_1 ? "_stride1" : ""); 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)); + ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info)); // Set config_id for enabling LWS tuning _config_id = kernel_name; @@ -359,15 +193,12 @@ void CLDepthwiseConvolutionLayer3x3NHWCKernel::configure(const CLCompileContext } Status CLDepthwiseConvolutionLayer3x3NHWCKernel::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, - const PadStrideInfo &conv_info, unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation, - const ITensorInfo *output_multipliers, const ITensorInfo *output_shifts) + const PadStrideInfo &conv_info, unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation) { - ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation, output_multipliers, output_shifts)); + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation)); ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), weights->clone().get(), biases != nullptr ? biases->clone().get() : nullptr, - output->clone().get(), conv_info, depth_multiplier, dilation, - (output_multipliers != nullptr) ? output_multipliers->clone().get() : nullptr, - (output_shifts != nullptr) ? output_shifts->clone().get() : nullptr) + output->clone().get(), conv_info, depth_multiplier, dilation) .first); return Status{}; } @@ -382,16 +213,7 @@ void CLDepthwiseConvolutionLayer3x3NHWCKernel::run(const Window &window, cl::Com 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<float>(_num_planes_processed_per_iteration)) * total_batches, 1)); - unsigned int idx = 2 * num_arguments_per_4D_tensor() + (_is_quantized ? num_arguments_per_2D_tensor() : num_arguments_per_3D_tensor()); - - if(_is_quantized) - { - Window slice; - slice.use_tensor_dimensions(_output_multipliers->info()->tensor_shape()); - slice.set_dimension_step(Window::DimX, window.x().step()); - add_1D_tensor_argument(idx, _output_multipliers, slice); - add_1D_tensor_argument(idx, _output_shifts, slice); - } + unsigned int idx = 2 * num_arguments_per_4D_tensor() + num_arguments_per_3D_tensor(); if(_biases != nullptr) { @@ -401,62 +223,14 @@ void CLDepthwiseConvolutionLayer3x3NHWCKernel::run(const Window &window, cl::Com add_1D_tensor_argument(idx, _biases, win_biases); } - 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()->dimension(1) * _input->info()->dimension(2)) + (_input->info()->padding().bottom + _input->info()->padding().top) * (_input->info()->dimension( - 2) - 1)) * _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); add_4D_tensor_argument(idx, _output, slice); - if(_is_quantized) - { - add_2D_tensor_argument(idx, _weights, slice); - } - else - { - add_3D_tensor_argument(idx, _weights, slice); - } + add_3D_tensor_argument(idx, _weights, slice); + enqueue(queue, *this, slice, lws_hint()); } while(win.slide_window_slice_4D(slice)); |