COMPMID-811 Add NHWC data format support for CL depthwise convolution QASYMM8

Change-Id: I89de432f3fbcba7abf9e1d4f8396a4334b4fa2c2
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/118324
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>

1 files changed, 306 insertions, 0 deletions

diff --git a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.cpp b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.cpp
new file mode 100644
index 0000000000..de68ceda11
--- /dev/null
+++ b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.cpp
@@ -0,0 +1,306 @@
+/*
+ * Copyright (c) 2018 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#include "arm_compute/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.h"
+
+#include "arm_compute/core/AccessWindowStatic.h"
+#include "arm_compute/core/CL/CLHelpers.h"
+#include "arm_compute/core/CL/CLKernelLibrary.h"
+#include "arm_compute/core/CL/ICLKernel.h"
+#include "arm_compute/core/CL/ICLTensor.h"
+#include "arm_compute/core/Error.h"
+#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/TensorInfo.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/core/Utils.h"
+#include "arm_compute/core/utils/misc/ShapeCalculator.h"
+#include "arm_compute/core/utils/quantization/AsymmHelpers.h"
+
+using namespace arm_compute;
+using namespace arm_compute::misc::shape_calculator;
+
+CLDepthwiseConvolutionLayer3x3NCHWKernel::CLDepthwiseConvolutionLayer3x3NCHWKernel()
+    : _conv_stride_x(0), _conv_pad_top(0)
+{
+}
+
+BorderSize CLDepthwiseConvolutionLayer3x3NCHWKernel::border_size() const
+{
+    return _border_size;
+}
+
+void CLDepthwiseConvolutionLayer3x3NCHWKernel::configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info,
+                                                         ActivationLayerInfo act_info)
+{
+    ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F16, DataType::F32);
+    ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights);
+    ARM_COMPUTE_ERROR_ON(weights->info()->dimension(0) != 3 || weights->info()->dimension(1) != 3);
+
+    bool is_qasymm = is_data_type_quantized_asymmetric(input->info()->data_type());
+
+    if(biases != nullptr)
+    {
+        if(is_qasymm)
+        {
+            ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(biases, 1, DataType::S32);
+        }
+        else
+        {
+            ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(weights, biases);
+        }
+        ARM_COMPUTE_ERROR_ON(biases->info()->dimension(0) != weights->info()->dimension(2));
+        ARM_COMPUTE_ERROR_ON(biases->info()->num_dimensions() > 1);
+    }
+
+    // Get convolved dimensions
+    const TensorShape output_shape = compute_depthwise_convolution_shape(*input->info(), *weights->info(), conv_info);
+
+    // Output auto inizialitation if not yet initialized
+    auto_init_if_empty(*output->info(),
+                       output_shape,
+                       1,
+                       input->info()->data_type(),
+                       input->info()->fixed_point_position(),
+                       input->info()->quantization_info());
+
+    ARM_COMPUTE_ERROR_ON_MISMATCHING_DIMENSIONS(output->info()->tensor_shape(), output_shape);
+
+    _input         = input;
+    _output        = output;
+    _weights       = weights;
+    _biases        = biases;
+    _conv_stride_x = conv_info.stride().first;
+    _conv_stride_y = conv_info.stride().second;
+    _conv_pad_left = conv_info.pad_left();
+    _conv_pad_top  = conv_info.pad_top();
+    _border_size   = BorderSize(_conv_pad_top, conv_info.pad_right(), conv_info.pad_bottom(), _conv_pad_left);
+
+    // Set build options
+    ARM_COMPUTE_ERROR_ON(_conv_stride_x < 1 || _conv_stride_x > 3);
+    CLBuildOptions build_opts;
+    build_opts.add_option("-DCONV_STRIDE_X=" + support::cpp11::to_string(_conv_stride_x));
+    build_opts.add_option_if(_biases != nullptr, "-DHAS_BIAS");
+
+    if(is_qasymm)
+    {
+        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("-DCONV_STRIDE_Y=" + support::cpp11::to_string(_conv_stride_y));
+        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 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)
+            {
+                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));
+                }
+            }
+        }
+    }
+
+    const GPUTarget gpu_target = get_target();
+    const bool      is_bifrost = gpu_target_is_in(gpu_target, GPUTarget::G71, GPUTarget::G72, GPUTarget::G51, GPUTarget::G51BIG, GPUTarget::G51LIT, GPUTarget::TNOX);
+
+    // Configure kernel window
+    unsigned int num_elems_read_per_iteration_x    = 0;
+    unsigned int num_elems_read_per_iteration_y    = 0;
+    unsigned int num_elems_written_per_iteration_x = 0;
+    unsigned int num_elems_written_per_iteration_y = 0;
+
+    // Create kernel
+    std::string kernel_name;
+
+    if(input->info()->data_type() == DataType::F16)
+    {
+        kernel_name                       = "depthwise_convolution_3x3_f16";
+        num_elems_written_per_iteration_x = 8 / data_size_from_type(input->info()->data_type());
+        num_elems_written_per_iteration_y = 1;
+        num_elems_read_per_iteration_y    = 3;
+        switch(_conv_stride_x)
+        {
+            case 1:
+                num_elems_read_per_iteration_x = 8;
+                break;
+            case 2:
+                num_elems_read_per_iteration_x = 9;
+                break;
+            case 3:
+                num_elems_read_per_iteration_x = 16;
+                break;
+            default:
+                num_elems_read_per_iteration_x = 3 + (num_elems_written_per_iteration_x - 1) * _conv_stride_x;
+                break;
+        }
+        if(is_bifrost)
+        {
+            if(_conv_stride_x == 1 && _conv_stride_y == 1)
+            {
+                kernel_name                       = "depthwise_convolution_3x3_stridex1_stridey1_bifrost_f16";
+                num_elems_read_per_iteration_x    = 8;
+                num_elems_written_per_iteration_x = 4;
+                num_elems_read_per_iteration_y    = 6;
+                num_elems_written_per_iteration_y = 4;
+            }
+            else if(_conv_stride_x == 2 && _conv_stride_y == 2)
+            {
+                kernel_name                       = "depthwise_convolution_3x3_stridex2_stridey2_bifrost_f16";
+                num_elems_read_per_iteration_x    = 10;
+                num_elems_written_per_iteration_x = 4;
+                num_elems_read_per_iteration_y    = 5;
+                num_elems_written_per_iteration_y = 2;
+            }
+        }
+    }
+    else if(input->info()->data_type() == DataType::F32 && is_bifrost)
+    {
+        if(_conv_stride_x == 1 && _conv_stride_y == 1)
+        {
+            kernel_name                       = "depthwise_convolution_3x3_stridex1_stridey1_bifrost_f32";
+            num_elems_read_per_iteration_x    = 4;
+            num_elems_read_per_iteration_y    = 6;
+            num_elems_written_per_iteration_x = 2;
+            num_elems_written_per_iteration_y = 4;
+        }
+        else if(_conv_stride_x == 2 && _conv_stride_y == 2)
+        {
+            kernel_name                       = "depthwise_convolution_3x3_stridex2_stridey2_bifrost_f32";
+            num_elems_read_per_iteration_x    = 6;
+            num_elems_read_per_iteration_y    = 5;
+            num_elems_written_per_iteration_x = 2;
+            num_elems_written_per_iteration_y = 2;
+        }
+        else
+        {
+            kernel_name                       = "depthwise_convolution_3x3";
+            num_elems_written_per_iteration_x = 8 / data_size_from_type(input->info()->data_type());
+            num_elems_written_per_iteration_y = 1;
+            num_elems_read_per_iteration_x    = 3 + (num_elems_written_per_iteration_x - 1) * _conv_stride_x;
+            num_elems_read_per_iteration_y    = 3;
+        }
+    }
+    else
+    {
+        kernel_name                       = is_qasymm ? "depthwise_convolution_3x3_quantized_nchw" : "depthwise_convolution_3x3";
+        num_elems_written_per_iteration_x = 8 / data_size_from_type(input->info()->data_type());
+        num_elems_written_per_iteration_y = (is_qasymm && _conv_stride_y < 3) ? (2 / _conv_stride_y) : 1;
+        num_elems_read_per_iteration_x    = 3 + (num_elems_written_per_iteration_x - 1) * _conv_stride_x;
+        num_elems_read_per_iteration_y    = num_elems_written_per_iteration_y + 2;
+    }
+
+    // Create window and update padding
+    Window win = calculate_max_window(*output->info(), Steps(num_elems_written_per_iteration_x, num_elems_written_per_iteration_y));
+
+    AccessWindowRectangle input_access(input->info(), -_conv_pad_left, -_conv_pad_top,
+                                       num_elems_read_per_iteration_x, num_elems_read_per_iteration_y,
+                                       _conv_stride_x, _conv_stride_y);
+    AccessWindowStatic    weights_access(weights->info(), 0, 0, 3, 3);
+    AccessWindowRectangle output_access(output->info(), 0, 0, num_elems_written_per_iteration_x, num_elems_written_per_iteration_y);
+
+    update_window_and_padding(win, input_access, weights_access, output_access);
+
+    output_access.set_valid_region(win, ValidRegion(Coordinates(), output->info()->tensor_shape()));
+
+    ICLKernel::configure(win);
+
+    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+
+    // Set config_id for enabling LWS tuning
+    _config_id = kernel_name;
+    _config_id += "_";
+    _config_id += lower_string(string_from_data_type(input->info()->data_type()));
+    _config_id += "_";
+    _config_id += support::cpp11::to_string(input->info()->dimension(0));
+    _config_id += "_";
+    _config_id += support::cpp11::to_string(input->info()->dimension(1));
+    _config_id += "_";
+    _config_id += support::cpp11::to_string(input->info()->dimension(2));
+    _config_id += "_";
+    _config_id += support::cpp11::to_string(output->info()->dimension(0));
+    _config_id += "_";
+    _config_id += support::cpp11::to_string(output->info()->dimension(1));
+}
+
+void CLDepthwiseConvolutionLayer3x3NCHWKernel::run(const Window &window, cl::CommandQueue &queue)
+{
+    ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
+    ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);
+
+    // Create input window and adjust
+    Window win_in = window;
+    win_in.adjust(Window::DimX, -_conv_pad_left, true);
+    win_in.adjust(Window::DimY, -_conv_pad_top, true);
+    win_in.set_dimension_step(Window::DimX, window.x().step() * _conv_stride_x);
+    win_in.set_dimension_step(Window::DimY, window.y().step() * _conv_stride_y);
+
+    Window slice_in      = win_in.first_slice_window_3D();
+    Window slice_out     = window.first_slice_window_3D();
+    Window slice_weights = window.first_slice_window_3D();
+    slice_weights.set_dimension_step(Window::DimX, 0);
+    slice_weights.set_dimension_step(Window::DimY, 0);
+
+    // Set biases
+    if(_biases != nullptr)
+    {
+        unsigned int idx = 3 * num_arguments_per_3D_tensor();
+        Window       slice_biases;
+        slice_biases.use_tensor_dimensions(_biases->info()->tensor_shape());
+        add_1D_tensor_argument(idx, _biases, slice_biases);
+    }
+
+    do
+    {
+        unsigned int idx = 0;
+        add_3D_tensor_argument(idx, _input, slice_in);
+        add_3D_tensor_argument(idx, _output, slice_out);
+        add_3D_tensor_argument(idx, _weights, slice_weights);
+
+        enqueue(queue, *this, slice_out, _lws_hint);
+    }
+    while(window.slide_window_slice_3D(slice_out) && win_in.slide_window_slice_3D(slice_in));
+}