Compute Library
 21.11
list.h
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24 #ifndef SRC_CORE_NEON_KERNELS_ADD_LIST_H
25 #define SRC_CORE_NEON_KERNELS_ADD_LIST_H
26 
27 #include "arm_compute/core/Types.h"
30 
31 namespace arm_compute
32 {
33 namespace cpu
34 {
35 #define DECLARE_ADD_KERNEL(func_name) \
36  void func_name(const ITensor *src0, const ITensor *src1, ITensor *dst, const ConvertPolicy &policy, const Window &window)
37 
41 
42 #undef DECLARE_ADD_KERNEL
43 
44 template <typename ScalarType>
45 void add_same_neon(const ITensor *src0, const ITensor *src1, ITensor *dst, const ConvertPolicy &policy, const Window &window)
46 {
47  /** SIMD vector tag type. */
49 
50  // Create input windows
51  Window input1_win = window.broadcast_if_dimension_le_one(src0->info()->tensor_shape());
52  Window input2_win = window.broadcast_if_dimension_le_one(src1->info()->tensor_shape());
53 
54  // Clear X Dimension on execution window as we handle manually
55  Window win = window;
56  win.set(Window::DimX, Window::Dimension(0, 1, 1));
57 
58  constexpr int window_step_x = 16 / sizeof(ScalarType);
59  const auto window_start_x = static_cast<int>(window.x().start());
60  const auto window_end_x = static_cast<int>(window.x().end());
61  const bool is_broadcast_across_x = src0->info()->tensor_shape().x() != src1->info()->tensor_shape().x();
62 
63  if(is_broadcast_across_x)
64  {
65  const bool is_broadcast_input_2 = input2_win.x().step() == 0;
66  Window broadcast_win = is_broadcast_input_2 ? input2_win : input1_win;
67  Window non_broadcast_win = !is_broadcast_input_2 ? input2_win : input1_win;
68  const ITensor *broadcast_tensor = is_broadcast_input_2 ? src1 : src0;
69  const ITensor *non_broadcast_tensor = !is_broadcast_input_2 ? src1 : src0;
70 
71  // Clear X Dimension on execution window as we handle manually
72  non_broadcast_win.set(Window::DimX, Window::Dimension(0, 1, 1));
73 
74  Iterator broadcast_input(broadcast_tensor, broadcast_win);
75  Iterator non_broadcast_input(non_broadcast_tensor, non_broadcast_win);
76  Iterator output(dst, win);
77 
78  execute_window_loop(win, [&](const Coordinates &)
79  {
80  const auto non_broadcast_input_ptr = reinterpret_cast<const ScalarType *>(non_broadcast_input.ptr());
81  const auto output_ptr = reinterpret_cast<ScalarType *>(output.ptr());
82 
83  const ScalarType broadcast_value = *reinterpret_cast<const ScalarType *>(broadcast_input.ptr());
84  const auto broadcast_value_vec = wrapper::vdup_n(broadcast_value, ExactTagType{});
85 
86  // Compute S elements per iteration
87  int x = window_start_x;
88  for(; x <= (window_end_x - window_step_x); x += window_step_x)
89  {
90  const auto non_broadcast_v = wrapper::vloadq(non_broadcast_input_ptr + x);
91  const auto res = (policy == ConvertPolicy::SATURATE) ? wrapper::vqadd(broadcast_value_vec, non_broadcast_v) : wrapper::vadd(broadcast_value_vec, non_broadcast_v);
92  wrapper::vstore(output_ptr + x, res);
93  }
94 
95  // Compute left-over elements
96  for(; x < window_end_x; ++x)
97  {
98  const auto non_broadcast_v = *(non_broadcast_input_ptr + x);
99  *(output_ptr + x) = (policy == ConvertPolicy::SATURATE) ? wrapper::add_sat(broadcast_value, non_broadcast_v) : broadcast_value + non_broadcast_v;
100  }
101  },
102  broadcast_input, non_broadcast_input, output);
103  }
104  else
105  {
106  // Clear X Dimension on execution window as we handle manually
107  input1_win.set(Window::DimX, Window::Dimension(0, 1, 1));
108  input2_win.set(Window::DimX, Window::Dimension(0, 1, 1));
109 
110  Iterator input1(src0, input1_win);
111  Iterator input2(src1, input2_win);
112  Iterator output(dst, win);
113 
114  execute_window_loop(win, [&](const Coordinates &)
115  {
116  const auto input1_ptr = reinterpret_cast<const ScalarType *>(input1.ptr());
117  const auto input2_ptr = reinterpret_cast<const ScalarType *>(input2.ptr());
118  const auto output_ptr = reinterpret_cast<ScalarType *>(output.ptr());
119 
120  // Compute S elements per iteration
121  int x = window_start_x;
122  for(; x <= (window_end_x - window_step_x); x += window_step_x)
123  {
124  const auto val1 = wrapper::vloadq(input1_ptr + x);
125  const auto val2 = wrapper::vloadq(input2_ptr + x);
126  const auto res = (policy == ConvertPolicy::SATURATE) ? wrapper::vqadd(val1, val2) : wrapper::vadd(val1, val2);
127  wrapper::vstore(output_ptr + x, res);
128  }
129 
130  // Compute left-over elements
131  for(; x < window_end_x; ++x)
132  {
133  const auto val1 = *(input1_ptr + x);
134  const auto val2 = *(input2_ptr + x);
135  *(output_ptr + x) = (policy == ConvertPolicy::SATURATE) ? wrapper::add_sat(val1, val2) : val1 + val2;
136  }
137  },
138  input1, input2, output);
139  }
140 }
141 } // namespace cpu
142 } // namespace arm_compute
143 #endif // SRC_CORE_NEON_KERNELS_ADD_LIST_H
constexpr int step() const
Return the step of the dimension.
Definition: Window.h:104
uint8x16_t vloadq(const uint8_t *ptr)
Definition: load.h:58
uint8x8_t vadd(const uint8x8_t &a, const uint8x8_t &b)
Definition: add.h:39
Describe one of the image&#39;s dimensions with a start, end and step.
Definition: Window.h:77
Interface for CPU tensor.
Definition: ITensor.h:36
Copyright (c) 2017-2021 Arm Limited.
void add_qsymm16_neon(const ITensor *src0, const ITensor *src1, ITensor *dst, const ConvertPolicy &policy, const Window &window)
Definition: qsymm16.cpp:35
void add_qasymm8_neon(const ITensor *src0, const ITensor *src1, ITensor *dst, const ConvertPolicy &policy, const Window &window)
Definition: qasymm8.cpp:35
typename neon_bitvector< T, BW >::tag_type neon_bitvector_tag_t
Helper type template to get the tag type of a neon vector.
Definition: traits.h:132
T x() const
Alias to access the size of the first dimension.
Definition: Dimensions.h:87
static constexpr size_t DimX
Alias for dimension 0 also known as X dimension.
Definition: Window.h:43
virtual const TensorShape & tensor_shape() const =0
Size for each dimension of the tensor.
Coordinates of an item.
Definition: Coordinates.h:37
uint8_t add_sat(const uint8_t &a, const uint8_t &b)
Definition: add.h:33
virtual ITensorInfo * info() const =0
Interface to be implemented by the child class to return the tensor&#39;s metadata.
constexpr uint8_t * ptr() const
Return a pointer to the current pixel.
Definition: Helpers.inl:139
uint8x8_t vqadd(const uint8x8_t &a, const uint8x8_t &b)
Definition: add.h:73
#define DECLARE_ADD_KERNEL(func_name)
Definition: list.h:35
void set(size_t dimension, const Dimension &dim)
Set the values of a given dimension.
Definition: Window.inl:49
Window broadcast_if_dimension_le_one(const TensorShape &shape) const
Don&#39;t advance in the dimension where shape is less equal to 1.
Definition: Window.inl:120
void add_qasymm8_signed_neon(const ITensor *src0, const ITensor *src1, ITensor *dst, const ConvertPolicy &policy, const Window &window)
void vstore(uint8_t *ptr, uint8x8_t val)
Definition: store.h:39
uint8x8_t vdup_n(uint8_t value, traits::vector_64_tag)
Definition: dup_n.h:41
void execute_window_loop(const Window &w, L &&lambda_function, Ts &&... iterators)
Iterate through the passed window, automatically adjusting the iterators and calling the lambda_funct...
Definition: Helpers.inl:77
Includes all wrapper headers at once.
constexpr int end() const
Return the end of the dimension.
Definition: Window.h:99
Iterator updated by execute_window_loop for each window element.
Definition: Helpers.h:46
void add_same_neon(const ITensor *src0, const ITensor *src1, ITensor *dst, const ConvertPolicy &policy, const Window &window)
Definition: list.h:45
constexpr int start() const
Return the start of the dimension.
Definition: Window.h:94
Describe a multidimensional execution window.
Definition: Window.h:39
ConvertPolicy
Policy to handle integer overflow.
Definition: Types.h:391
constexpr const Dimension & x() const
Alias to access the first dimension of the window.
Definition: Window.h:145