COMPMID-2805: Add QASYMM8_SIGNED support in NEGEMMLowpOutputStage

Add support from requantizing down from S32 to Int8 with fixed point
requantization. This involves the following:
- Compute fixed point multiplication between each entry of input by
  result_fixedpoint_multiplier
- Add bias to final result if bias tensor is not a nullptr
- Round to nearest division by a power-of-two using result_shift
- Add offset to each result
- Clamp the value between the specified min and max bounds
- Cast to int8 data type

Change-Id: I641b3fac0833c568d8565ccb859bbc561a24c17d
Signed-off-by: Georgios Pinitas <georgios.pinitas@arm.com>
Reviewed-on: https://review.mlplatform.org/c/2340
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>

1 files changed, 246 insertions, 0 deletions

diff --git a/src/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel.cpp b/src/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel.cpp
new file mode 100644
index 0000000000..d24089d615
--- /dev/null
+++ b/src/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel.cpp
@@ -0,0 +1,246 @@
+/*
+ * Copyright (c) 2019 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/NEON/kernels/NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel.h"
+
+#include "arm_compute/core/AccessWindowStatic.h"
+#include "arm_compute/core/Error.h"
+#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/ITensor.h"
+#include "arm_compute/core/NEON/NEAsymm.h"
+#include "arm_compute/core/TensorInfo.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/core/Utils.h"
+#include "arm_compute/core/Validate.h"
+#include "arm_compute/core/Window.h"
+#include "arm_compute/core/utils/misc/ShapeCalculator.h"
+
+#include <arm_neon.h>
+#include <cstddef>
+#include <cstdint>
+
+namespace arm_compute
+{
+namespace
+{
+Status validate_arguments(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, int min, int max)
+{
+    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::S32);
+    ARM_COMPUTE_RETURN_ERROR_ON(max > 127);
+    ARM_COMPUTE_RETURN_ERROR_ON(min < -128 || min > max);
+
+    // Check biases if exist
+    if(bias != nullptr)
+    {
+        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, bias);
+        ARM_COMPUTE_RETURN_ERROR_ON(bias->num_dimensions() > 1);
+        ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(0) != bias->dimension(0));
+    }
+
+    if(output->total_size() != 0)
+    {
+        ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::QASYMM8_SIGNED);
+        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(output, input);
+    }
+
+    return Status{};
+}
+
+std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output)
+{
+    // Output auto initialization if not yet initialized
+    auto_init_if_empty(*output, input->clone()->set_data_type(DataType::QASYMM8_SIGNED));
+
+    // Configure kernel window
+    Window win = calculate_max_window(*input, Steps());
+
+    // NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel doesn't need padding so update_window_and_padding() can be skipped
+    Coordinates coord;
+    coord.set_num_dimensions(output->num_dimensions());
+    output->set_valid_region(ValidRegion(coord, output->tensor_shape()));
+
+    return std::make_pair(Status{}, win);
+}
+} // namespace
+
+template <bool is_bounded_relu>
+void NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel::run(const Window &window)
+{
+    const int32x4_t result_offset_after_shift_s32 = vdupq_n_s32(_result_offset_after_shift);
+    const int8x16_t min_s8                        = vdupq_n_s8(static_cast<int8_t>(_min));
+    const int8x16_t max_s8                        = vdupq_n_s8(static_cast<int8_t>(_max));
+
+    ARM_COMPUTE_UNUSED(min_s8, max_s8);
+
+    const int  window_step_x  = 16;
+    const auto window_start_x = static_cast<int>(window.x().start());
+    const auto window_end_x   = static_cast<int>(window.x().end());
+
+    Window win_collapsed = window.collapse_if_possible(window, Window::DimZ);
+    win_collapsed.set(Window::DimX, Window::Dimension(0, 1, 1));
+
+    Iterator in(_input, win_collapsed);
+    Iterator out(_output, win_collapsed);
+    if(_bias != nullptr)
+    {
+        Window win_biases;
+        win_biases.set(Window::DimX, Window::Dimension(0, 1, 1));
+        win_biases.set(Window::DimY, Window::Dimension(0, 1, 1));
+
+        Iterator bias(_bias, win_biases);
+        execute_window_loop(win_collapsed, [&](const Coordinates &)
+        {
+            // Compute 16 elements per iteration
+            int x = window_start_x;
+            for(; x <= (window_end_x - window_step_x); x += window_step_x)
+            {
+                int32x4x4_t in_s32 =
+                {
+                    {
+                        vld1q_s32(reinterpret_cast<const int32_t *>(in.ptr()) + x + 0),
+                        vld1q_s32(reinterpret_cast<const int32_t *>(in.ptr()) + x + 4),
+                        vld1q_s32(reinterpret_cast<const int32_t *>(in.ptr()) + x + 8),
+                        vld1q_s32(reinterpret_cast<const int32_t *>(in.ptr()) + x + 12)
+                    }
+                };
+
+                const int32x4x4_t bias_s32 =
+                {
+                    {
+                        vld1q_s32(reinterpret_cast<const int32_t *>(bias.ptr()) + x + 0),
+                        vld1q_s32(reinterpret_cast<const int32_t *>(bias.ptr()) + x + 4),
+                        vld1q_s32(reinterpret_cast<const int32_t *>(bias.ptr()) + x + 8),
+                        vld1q_s32(reinterpret_cast<const int32_t *>(bias.ptr()) + x + 12)
+                    }
+                };
+
+                // Add the bias to GEMM's result
+                in_s32.val[0] = vaddq_s32(in_s32.val[0], bias_s32.val[0]);
+                in_s32.val[1] = vaddq_s32(in_s32.val[1], bias_s32.val[1]);
+                in_s32.val[2] = vaddq_s32(in_s32.val[2], bias_s32.val[2]);
+                in_s32.val[3] = vaddq_s32(in_s32.val[3], bias_s32.val[3]);
+
+                vst1q_s8(reinterpret_cast<int8_t *>(out.ptr() + x),
+                         finalize_quantization<is_bounded_relu>(in_s32, _result_fixedpoint_multiplier, _result_shift, result_offset_after_shift_s32, min_s8, max_s8));
+            }
+
+            // Compute left-over elements
+            for(; x < window_end_x; ++x)
+            {
+                const int32_t bias_value = *(reinterpret_cast<const int32_t *>(bias.ptr()) + x);
+                int32_t       in_value   = *(reinterpret_cast<const int32_t *>(in.ptr()) + x);
+
+                // Add bias
+                in_value += bias_value;
+                // Finalize and store the result
+                *reinterpret_cast<int8_t *>(out.ptr() + x) = finalize_quantization<is_bounded_relu>(in_value, _result_fixedpoint_multiplier, _result_shift, _result_offset_after_shift,
+                                                                                                    static_cast<int8_t>(_min), static_cast<int8_t>(_max));
+            }
+        },
+        in, out, bias);
+    }
+    else
+    {
+        execute_window_loop(win_collapsed, [&](const Coordinates &)
+        {
+            // Compute 16 elements per iteration
+            int x = window_start_x;
+            for(; x <= (window_end_x - window_step_x); x += window_step_x)
+            {
+                int32x4x4_t in_s32 =
+                {
+                    {
+                        vld1q_s32(reinterpret_cast<const int32_t *>(in.ptr()) + x + 0),
+                        vld1q_s32(reinterpret_cast<const int32_t *>(in.ptr()) + x + 4),
+                        vld1q_s32(reinterpret_cast<const int32_t *>(in.ptr()) + x + 8),
+                        vld1q_s32(reinterpret_cast<const int32_t *>(in.ptr()) + x + 12)
+                    }
+                };
+
+                vst1q_s8(reinterpret_cast<int8_t *>(out.ptr() + x),
+                         finalize_quantization<is_bounded_relu>(in_s32, _result_fixedpoint_multiplier, _result_shift, result_offset_after_shift_s32, min_s8, max_s8));
+            }
+
+            // Compute left-over elements
+            for(; x < window_end_x; ++x)
+            {
+                const int32_t in_value = *(reinterpret_cast<const int32_t *>(in.ptr()) + x);
+
+                // Finalize and store the result
+                *reinterpret_cast<int8_t *>(out.ptr() + x) = finalize_quantization<is_bounded_relu>(in_value, _result_fixedpoint_multiplier, _result_shift, _result_offset_after_shift,
+                                                                                                    static_cast<int8_t>(_min), static_cast<int8_t>(_max));
+            }
+        },
+        in, out);
+    }
+}
+
+NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel::NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel()
+    : _func(nullptr), _input(nullptr), _bias(nullptr), _output(nullptr), _result_fixedpoint_multiplier(0), _result_shift(0), _result_offset_after_shift(0), _min(0), _max(0)
+{
+}
+
+void NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel::configure(const ITensor *input, const ITensor *bias, ITensor *output, int result_fixedpoint_multiplier, int result_shift,
+                                                                         int result_offset_after_shift, int min, int max)
+{
+    // Perform validate step
+    ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
+    ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), (bias != nullptr) ? bias->info() : nullptr, output->info(), min, max));
+
+    _input                        = input;
+    _bias                         = bias;
+    _output                       = output;
+    _result_fixedpoint_multiplier = result_fixedpoint_multiplier;
+    _result_shift                 = result_shift;
+    _result_offset_after_shift    = result_offset_after_shift;
+    _min                          = min;
+    _max                          = max;
+
+    // Configure kernel window
+    auto win_config = validate_and_configure_window(input->info(), output->info());
+    ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
+    INEKernel::configure(win_config.second);
+
+    // Check if we need to clamp the result using min and max
+    const bool is_bounded_relu = ((min != max) && !(min == -128 && max == 127));
+    _func                      = is_bounded_relu ? &NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel::run<true> : &NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel::run<false>;
+}
+
+Status NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel::validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, int min, int max)
+{
+    ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
+    ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, bias, output, min, max));
+    ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get()).first);
+
+    return Status{};
+}
+
+void NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel::run(const Window &window, const ThreadInfo &info)
+{
+    ARM_COMPUTE_UNUSED(info);
+    ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
+    ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);
+
+    (this->*_func)(window);
+}
+} // namespace arm_compute
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