Compute Library
 21.08
qsymm16.cpp
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26 #include "arm_compute/core/Types.h"
30 
31 namespace arm_compute
32 {
33 namespace cpu
34 {
35 void sub_qsymm16_neon(const ITensor *src0, const ITensor *src1, ITensor *dst, const ConvertPolicy &policy, const Window &window)
36 {
37  ARM_COMPUTE_UNUSED(policy);
38 
39  // Create input windows
40  Window input1_win = window.broadcast_if_dimension_le_one(src0->info()->tensor_shape());
41  Window input2_win = window.broadcast_if_dimension_le_one(src1->info()->tensor_shape());
42 
43  // Clear X Dimension on execution window as we handle manually
44  Window win = window;
45  win.set(Window::DimX, Window::Dimension(0, 1, 1));
46 
47  const int window_step_x = 8;
48  const auto window_start_x = static_cast<int>(window.x().start());
49  const auto window_end_x = static_cast<int>(window.x().end());
50  const bool is_broadcast_across_x = src0->info()->tensor_shape().x() != src1->info()->tensor_shape().x();
51 
52  const UniformQuantizationInfo iq1_info = src0->info()->quantization_info().uniform();
53  const UniformQuantizationInfo iq2_info = src1->info()->quantization_info().uniform();
54  const UniformQuantizationInfo oq_info = dst->info()->quantization_info().uniform();
55 
56  const float32x4_t vscale1 = vdupq_n_f32(iq1_info.scale);
57  const float32x4_t vscale2 = vdupq_n_f32(iq2_info.scale);
58  const float32x4_t invvscaleo = vdupq_n_f32(1.f / oq_info.scale);
59 
60  if(is_broadcast_across_x)
61  {
62  const bool is_broadcast_input_2 = input2_win.x().step() == 0;
63  Window broadcast_win = is_broadcast_input_2 ? input2_win : input1_win;
64  Window non_broadcast_win = !is_broadcast_input_2 ? input2_win : input1_win;
65  const ITensor *broadcast_tensor = is_broadcast_input_2 ? src1 : src0;
66  const ITensor *non_broadcast_tensor = !is_broadcast_input_2 ? src1 : src0;
67  const UniformQuantizationInfo broadcast_qinfo = broadcast_tensor->info()->quantization_info().uniform();
68  const UniformQuantizationInfo non_broadcast_qinfo = non_broadcast_tensor->info()->quantization_info().uniform();
69 
70  // Clear X Dimension on execution window as we handle manually
71  non_broadcast_win.set(Window::DimX, Window::Dimension(0, 1, 1));
72 
73  Iterator broadcast_input(broadcast_tensor, broadcast_win);
74  Iterator non_broadcast_input(non_broadcast_tensor, non_broadcast_win);
75  Iterator output(dst, win);
76 
77  execute_window_loop(win, [&](const Coordinates &)
78  {
79  const auto non_broadcast_input_ptr = reinterpret_cast<const int16_t *>(non_broadcast_input.ptr());
80  const auto output_ptr = reinterpret_cast<int16_t *>(output.ptr());
81 
82  const int16_t broadcast_value = *reinterpret_cast<const int16_t *>(broadcast_input.ptr());
83  const int16x8_t broadcast_value_vec = vdupq_n_s16(broadcast_value);
84 
85  const float32x4x2_t bf =
86  {
87  {
88  vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_low_s16(broadcast_value_vec))), vscale2),
89  vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_high_s16(broadcast_value_vec))), vscale2),
90  }
91  };
92  const float bfs = static_cast<int32_t>(broadcast_value) * broadcast_qinfo.scale;
93 
94  // Compute S elements per iteration
95  int x = window_start_x;
96  for(; x <= (window_end_x - window_step_x); x += window_step_x)
97  {
98  const int16x8_t a = vld1q_s16(non_broadcast_input_ptr + x);
99  const float32x4x2_t af =
100  {
101  {
102  vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_low_s16(a))), vscale1),
103  vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_high_s16(a))), vscale1),
104  }
105  };
106 
107  const int32x4x4_t rf =
108  {
109  {
110 #ifdef __aarch64__
111  vcvtnq_s32_f32(vmulq_f32(is_broadcast_input_2 ? vsubq_f32(bf.val[0], af.val[0]) : vsubq_f32(af.val[0], bf.val[0]), invvscaleo)),
112  vcvtnq_s32_f32(vmulq_f32(is_broadcast_input_2 ? vsubq_f32(bf.val[1], af.val[1]) : vsubq_f32(af.val[1], bf.val[1]), invvscaleo)),
113 #else //__aarch64__
114  vcvtq_s32_f32(vmulq_f32(is_broadcast_input_2 ? vsubq_f32(bf.val[0], af.val[0]) : vsubq_f32(af.val[0], bf.val[0]), invvscaleo)),
115  vcvtq_s32_f32(vmulq_f32(is_broadcast_input_2 ? vsubq_f32(bf.val[1], af.val[1]) : vsubq_f32(af.val[1], bf.val[1]), invvscaleo)),
116 #endif //__aarch64__
117  }
118  };
119 
120  const int16x8_t pa = vcombine_s16(vqmovn_s32(rf.val[0]), vqmovn_s32(rf.val[1]));
121  vst1q_s16(output_ptr + x, pa);
122  }
123 
124  // Compute left-over elements
125  for(; x < window_end_x; ++x)
126  {
127  const float afs = static_cast<int32_t>(*(non_broadcast_input_ptr + x)) * non_broadcast_qinfo.scale;
128  *(output_ptr + x) = quantize_qsymm16(is_broadcast_input_2 ? (bfs - afs) : (afs - bfs), oq_info);
129  }
130  },
131  broadcast_input, non_broadcast_input, output);
132  }
133  else
134  {
135  // Clear X Dimension on execution window as we handle manually
136  input1_win.set(Window::DimX, Window::Dimension(0, 1, 1));
137  input2_win.set(Window::DimX, Window::Dimension(0, 1, 1));
138 
139  Iterator input1(src0, input1_win);
140  Iterator input2(src1, input2_win);
141  Iterator output(dst, win);
142 
143  execute_window_loop(win, [&](const Coordinates &)
144  {
145  const auto input1_ptr = reinterpret_cast<const int16_t *>(input1.ptr());
146  const auto input2_ptr = reinterpret_cast<const int16_t *>(input2.ptr());
147  const auto output_ptr = reinterpret_cast<int16_t *>(output.ptr());
148 
149  // Compute S elements per iteration
150  int x = window_start_x;
151  for(; x <= (window_end_x - window_step_x); x += window_step_x)
152  {
153  const int16x8_t a = vld1q_s16(input1_ptr + x);
154  const int16x8_t b = vld1q_s16(input2_ptr + x);
155 
156  const float32x4x2_t af =
157  {
158  {
159  vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_low_s16(a))), vscale1),
160  vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_high_s16(a))), vscale1),
161  }
162  };
163 
164  const float32x4x2_t bf =
165  {
166  {
167  vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_low_s16(b))), vscale2),
168  vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_high_s16(b))), vscale2),
169  }
170  };
171 
172  const int32x4x2_t rf =
173  {
174  {
175 #ifdef __aarch64__
176  vcvtnq_s32_f32(vmulq_f32(vsubq_f32(af.val[0], bf.val[0]), invvscaleo)),
177  vcvtnq_s32_f32(vmulq_f32(vsubq_f32(af.val[1], bf.val[1]), invvscaleo)),
178 #else //__aarch64__
179  vcvtq_s32_f32(vmulq_f32(vsubq_f32(af.val[0], bf.val[0]), invvscaleo)),
180  vcvtq_s32_f32(vmulq_f32(vsubq_f32(af.val[1], bf.val[1]), invvscaleo)),
181 #endif //__aarch64__
182  }
183  };
184 
185  const int16x8_t pa = vcombine_s16(vqmovn_s32(rf.val[0]), vqmovn_s32(rf.val[1]));
186  vst1q_s16(output_ptr + x, pa);
187  }
188 
189  // Compute left-over elements
190  for(; x < window_end_x; ++x)
191  {
192  const float afs = static_cast<int32_t>((*(input1_ptr + x))) * iq1_info.scale;
193  const float bfs = static_cast<int32_t>((*(input2_ptr + x))) * iq2_info.scale;
194  *(output_ptr + x) = quantize_qsymm16((afs - bfs), dst->info()->quantization_info());
195  }
196  },
197  input1, input2, output);
198  }
199 }
200 } // namespace cpu
201 } // namespace arm_compute
int16_t quantize_qsymm16(float value, const UniformQuantizationInfo &qinfo, RoundingPolicy rounding_policy=RoundingPolicy::TO_NEAREST_UP)
Quantize a value given a 16-bit symmetric quantization scheme.
SimpleTensor< float > b
Definition: DFT.cpp:157
constexpr int step() const
Return the step of the dimension.
Definition: Window.h:104
Quantization info when assuming per layer quantization.
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.
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
#define ARM_COMPUTE_UNUSED(...)
To avoid unused variables warnings.
Definition: Error.h:152
virtual const TensorShape & tensor_shape() const =0
Size for each dimension of the tensor.
Coordinates of an item.
Definition: Coordinates.h:37
UniformQuantizationInfo uniform() const
Return per layer quantization info.
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
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
virtual QuantizationInfo quantization_info() const =0
Get the quantization settings (scale and offset) of the tensor.
void sub_qsymm16_neon(const ITensor *src0, const ITensor *src1, ITensor *dst, const ConvertPolicy &policy, const Window &window)
Definition: qsymm16.cpp:35
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
std::vector< NodeID > bfs(Graph &g)
Breadth first search traversal.
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
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 overflow.
Definition: Types.h:382
constexpr const Dimension & x() const
Alias to access the first dimension of the window.
Definition: Window.h:145