COMPMID-344 Updated doxygen

Change-Id: I32f7b84daa560e460b77216add529c8fa8b327ae

1 files changed, 302 insertions, 0 deletions

diff --git a/src/core/NEON/kernels/NEActivationLayerKernel.cpp b/src/core/NEON/kernels/NEActivationLayerKernel.cpp
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+++ b/src/core/NEON/kernels/NEActivationLayerKernel.cpp
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+/*
+ * Copyright (c) 2017 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/NEActivationLayerKernel.h"
+
+#include "arm_compute/core/FixedPoint.h"
+#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/ITensor.h"
+#include "arm_compute/core/NEON/NEFixedPoint.h"
+#include "arm_compute/core/NEON/NEMath.h"
+#include "arm_compute/core/TensorInfo.h"
+#include "arm_compute/core/Utils.h"
+#include "arm_compute/core/Validate.h"
+#include "arm_compute/core/Window.h"
+
+#include <arm_neon.h>
+#include <array>
+#include <cmath>
+#include <map>
+
+using namespace arm_compute;
+
+NEActivationLayerKernel::NEActivationLayerKernel()
+    : _func(nullptr), _act_info(ActivationFunction::LOGISTIC)
+{
+}
+
+void NEActivationLayerKernel::configure(const ITensor *input, ITensor *output, ActivationLayerInfo activation_info)
+{
+    ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32, DataType::QS8);
+    ARM_COMPUTE_ERROR_ON_NULLPTR(output);
+
+    // Output auto inizialitation if not yet initialized
+    auto_init_if_empty(*output->info(), input->info()->tensor_shape(), 1, input->info()->data_type(), input->info()->fixed_point_position());
+
+    ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(input, output);
+    ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
+    ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT(input, output);
+
+    // Activation functions : FP32
+    static std::map<ActivationFunction, ActivationFunctionExecutorPtr> act_map_f32 =
+    {
+        { ActivationFunction::ABS, &NEActivationLayerKernel::activation<ActivationFunction::ABS, float> },
+        { ActivationFunction::LINEAR, &NEActivationLayerKernel::activation<ActivationFunction::LINEAR, float> },
+        { ActivationFunction::LOGISTIC, &NEActivationLayerKernel::activation<ActivationFunction::LOGISTIC, float> },
+        { ActivationFunction::RELU, &NEActivationLayerKernel::activation<ActivationFunction::RELU, float> },
+        { ActivationFunction::BOUNDED_RELU, &NEActivationLayerKernel::activation<ActivationFunction::BOUNDED_RELU, float> },
+        { ActivationFunction::SOFT_RELU, &NEActivationLayerKernel::activation<ActivationFunction::SOFT_RELU, float> },
+        { ActivationFunction::SQRT, &NEActivationLayerKernel::activation<ActivationFunction::SQRT, float> },
+        { ActivationFunction::SQUARE, &NEActivationLayerKernel::activation<ActivationFunction::SQUARE, float> },
+        { ActivationFunction::TANH, &NEActivationLayerKernel::activation<ActivationFunction::TANH, float> },
+    };
+
+    // Activation functions : QS8
+    static std::map<ActivationFunction, ActivationFunctionExecutorPtr> act_map_qs8 =
+    {
+        { ActivationFunction::ABS, &NEActivationLayerKernel::activation<ActivationFunction::ABS, qint8_t> },
+        { ActivationFunction::LINEAR, &NEActivationLayerKernel::activation<ActivationFunction::LINEAR, qint8_t> },
+        { ActivationFunction::LOGISTIC, &NEActivationLayerKernel::activation<ActivationFunction::LOGISTIC, qint8_t> },
+        { ActivationFunction::RELU, &NEActivationLayerKernel::activation<ActivationFunction::RELU, qint8_t> },
+        { ActivationFunction::BOUNDED_RELU, &NEActivationLayerKernel::activation<ActivationFunction::BOUNDED_RELU, qint8_t> },
+        { ActivationFunction::SOFT_RELU, &NEActivationLayerKernel::activation<ActivationFunction::SOFT_RELU, qint8_t> },
+        { ActivationFunction::SQRT, &NEActivationLayerKernel::activation<ActivationFunction::SQRT, qint8_t> },
+        { ActivationFunction::SQUARE, &NEActivationLayerKernel::activation<ActivationFunction::SQUARE, qint8_t> },
+        { ActivationFunction::TANH, &NEActivationLayerKernel::activation<ActivationFunction::TANH, qint8_t> },
+    };
+
+    _input    = input;
+    _output   = output;
+    _act_info = activation_info;
+    switch(input->info()->data_type())
+    {
+        case DataType::F32:
+            _func = act_map_f32[activation_info.activation()];
+            break;
+        case DataType::QS8:
+            _func = act_map_qs8[activation_info.activation()];
+            break;
+        default:
+            ARM_COMPUTE_ERROR("Unsupported data type.");
+    }
+
+    constexpr unsigned int num_elems_processed_per_iteration = 16;
+
+    INESimpleKernel::configure(_input, _output, num_elems_processed_per_iteration);
+}
+
+template <ActivationLayerInfo::ActivationFunction F, typename T>
+typename std::enable_if<std::is_same<T, float>::value, void>::type NEActivationLayerKernel::activation(const Window &window)
+{
+    Iterator input(_input, window);
+    Iterator output(_output, window);
+
+    static const float32x4_t CONST_1 = vdupq_n_f32(1.f);
+    static const float32x4_t CONST_0 = vdupq_n_f32(0.f);
+    const float32x4_t        a       = vdupq_n_f32(_act_info.a());
+    const float32x4_t        b       = vdupq_n_f32(_act_info.b());
+
+    execute_window_loop(window, [&](const Coordinates & id)
+    {
+        const auto input_ptr  = reinterpret_cast<const float *>(input.ptr());
+        const auto output_ptr = reinterpret_cast<float *>(output.ptr());
+
+        const float32x4x4_t in  = vld4q_f32(input_ptr);
+        float32x4x4_t       tmp = { {} };
+
+        switch(F)
+        {
+            case ActivationFunction::ABS:
+                tmp =
+                {
+                    {
+                        vabsq_f32(in.val[0]),
+                        vabsq_f32(in.val[1]),
+                        vabsq_f32(in.val[2]),
+                        vabsq_f32(in.val[3]),
+                    }
+                };
+                break;
+            case ActivationFunction::BOUNDED_RELU:
+                tmp =
+                {
+                    {
+                        vminq_f32(a, vmaxq_f32(CONST_0, in.val[0])),
+                        vminq_f32(a, vmaxq_f32(CONST_0, in.val[1])),
+                        vminq_f32(a, vmaxq_f32(CONST_0, in.val[2])),
+                        vminq_f32(a, vmaxq_f32(CONST_0, in.val[3])),
+                    }
+                };
+                break;
+            case ActivationFunction::LINEAR:
+                tmp =
+                {
+                    {
+                        vmlaq_f32(b, a, in.val[0]),
+                        vmlaq_f32(b, a, in.val[1]),
+                        vmlaq_f32(b, a, in.val[2]),
+                        vmlaq_f32(b, a, in.val[3]),
+                    }
+                };
+                break;
+            case ActivationFunction::LOGISTIC:
+                tmp =
+                {
+                    {
+                        vinvq_f32(vaddq_f32(CONST_1, vexpq_f32(vnegq_f32(in.val[0])))),
+                        vinvq_f32(vaddq_f32(CONST_1, vexpq_f32(vnegq_f32(in.val[1])))),
+                        vinvq_f32(vaddq_f32(CONST_1, vexpq_f32(vnegq_f32(in.val[2])))),
+                        vinvq_f32(vaddq_f32(CONST_1, vexpq_f32(vnegq_f32(in.val[3])))),
+                    }
+                };
+                break;
+            case ActivationFunction::RELU:
+                tmp =
+                {
+                    {
+                        vmaxq_f32(CONST_0, in.val[0]),
+                        vmaxq_f32(CONST_0, in.val[1]),
+                        vmaxq_f32(CONST_0, in.val[2]),
+                        vmaxq_f32(CONST_0, in.val[3]),
+                    }
+                };
+                break;
+            case ActivationFunction::SOFT_RELU:
+                tmp =
+                {
+                    {
+                        vlogq_f32(vaddq_f32(CONST_1, vexpq_f32(in.val[0]))),
+                        vlogq_f32(vaddq_f32(CONST_1, vexpq_f32(in.val[1]))),
+                        vlogq_f32(vaddq_f32(CONST_1, vexpq_f32(in.val[2]))),
+                        vlogq_f32(vaddq_f32(CONST_1, vexpq_f32(in.val[3]))),
+                    }
+                };
+                break;
+            case ActivationFunction::SQRT:
+                tmp =
+                {
+                    {
+                        vinvq_f32(vinvsqrtq_f32(in.val[0])),
+                        vinvq_f32(vinvsqrtq_f32(in.val[1])),
+                        vinvq_f32(vinvsqrtq_f32(in.val[2])),
+                        vinvq_f32(vinvsqrtq_f32(in.val[3])),
+                    }
+                };
+                break;
+            case ActivationFunction::SQUARE:
+                tmp =
+                {
+                    {
+                        vmulq_f32(in.val[0], in.val[0]),
+                        vmulq_f32(in.val[1], in.val[1]),
+                        vmulq_f32(in.val[2], in.val[2]),
+                        vmulq_f32(in.val[3], in.val[3]),
+                    }
+                };
+                break;
+            case ActivationFunction::TANH:
+                tmp =
+                {
+                    {
+                        vmulq_f32(a, vtanhq_f32(vmulq_f32(b, in.val[0]))),
+                        vmulq_f32(a, vtanhq_f32(vmulq_f32(b, in.val[1]))),
+                        vmulq_f32(a, vtanhq_f32(vmulq_f32(b, in.val[2]))),
+                        vmulq_f32(a, vtanhq_f32(vmulq_f32(b, in.val[3]))),
+                    }
+                };
+                break;
+            default:
+                break;
+        }
+
+        vst4q_f32(output_ptr, tmp);
+    },
+    input, output);
+}
+
+template <ActivationLayerInfo::ActivationFunction F, typename T>
+typename std::enable_if<std::is_same<T, int8_t>::value, void>::type NEActivationLayerKernel::activation(const Window &window)
+{
+    Iterator input(_input, window);
+    Iterator output(_output, window);
+    int      fixed_point_position = _input->info()->fixed_point_position();
+
+    static const qint8x16_t CONST_0 = vdupq_n_qs8(0);
+    const qint8x16_t        CONST_1 = vdupq_n_qs8(scvt_qs8_f32(1.f, fixed_point_position));
+    const qint8x16_t        a       = vdupq_n_qs8(scvt_qs8_f32(_act_info.a(), fixed_point_position));
+    const qint8x16_t        b       = vdupq_n_qs8(scvt_qs8_f32(_act_info.b(), fixed_point_position));
+
+    execute_window_loop(window, [&](const Coordinates & id)
+    {
+        const auto input_ptr  = reinterpret_cast<const int8_t *>(input.ptr());
+        const auto output_ptr = reinterpret_cast<int8_t *>(output.ptr());
+
+        const qint8x16_t in  = vld1q_qs8(input_ptr);
+        qint8x16_t       tmp = {};
+
+        switch(F)
+        {
+            case ActivationFunction::ABS:
+                tmp = vqabsq_qs8(in);
+                break;
+            case ActivationFunction::BOUNDED_RELU:
+                tmp = vminq_qs8(a, vmaxq_qs8(CONST_0, in));
+                break;
+            case ActivationFunction::LINEAR:
+                tmp = vqmlaq_qs8(b, a, in, fixed_point_position);
+                break;
+            case ActivationFunction::LOGISTIC:
+                tmp = vrecipq_qs8(vqaddq_qs8(CONST_1, vqexpq_qs8(vnegq_s8(in), fixed_point_position)), fixed_point_position);
+                break;
+            case ActivationFunction::RELU:
+                tmp = vmaxq_qs8(CONST_0, in);
+                break;
+            case ActivationFunction::SOFT_RELU:
+                tmp = vlogq_qs8(vqaddq_qs8(CONST_1, vqexpq_qs8(in, fixed_point_position)), fixed_point_position);
+                break;
+            case ActivationFunction::SQRT:
+                tmp = vrecipq_qs8(vinvsqrtq_qs8(in, fixed_point_position), fixed_point_position);
+                break;
+            case ActivationFunction::SQUARE:
+                tmp = vqmulq_qs8(in, in, fixed_point_position);
+                break;
+            case ActivationFunction::TANH:
+                tmp = vtanhq_qs8(in, fixed_point_position);
+                break;
+            default:
+                break;
+        }
+
+        vst1q_qs8(output_ptr, tmp);
+    },
+    input, output);
+}
+
+void NEActivationLayerKernel::run(const Window &window)
+{
+    ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
+    ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INESimpleKernel::window(), window);
+    ARM_COMPUTE_ERROR_ON(_func == nullptr);
+
+    (this->*_func)(window);
+}