Compute Library
 23.11
ConcatenateLayer.cpp
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1 /*
2  * Copyright (c) 2019 Arm Limited.
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24 #include "ConcatenateLayer.h"
25 
28 
29 namespace arm_compute
30 {
31 namespace test
32 {
33 namespace validation
34 {
35 namespace reference
36 {
37 namespace
38 {
39 template <typename T>
40 SimpleTensor<T> widthconcatenate_layer(const std::vector<SimpleTensor<T>> &srcs, SimpleTensor<T> &dst)
41 {
42  // Create reference
43  std::vector<TensorShape> shapes;
44  shapes.reserve(srcs.size());
45  for(const auto &src : srcs)
46  {
47  shapes.emplace_back(src.shape());
48  }
49  // Compute reference
50  int width_offset = 0;
51  const int width_out = dst.shape().x();
52  // Set output tensor to 0
53  std::fill_n(dst.data(), dst.num_elements(), 0);
54  for(const auto &src : srcs)
55  {
56  ARM_COMPUTE_ERROR_ON(width_offset >= width_out);
57 
58  const int width = src.shape().x();
59  const int height = src.shape().y();
60  const int depth = src.shape().z();
61  const int upper_dims = src.shape().total_size() / (width * height * depth);
62 
63  const T *src_ptr = src.data();
64  T *dst_ptr = dst.data();
65 
66  for(int u = 0; u < upper_dims; ++u)
67  {
68  for(int d = 0; d < depth; ++d)
69  {
70  for(int r = 0; r < height; ++r)
71  {
72  const int offset = u * height * depth + d * height + r;
73  if(is_data_type_quantized(src.data_type()) && src.quantization_info() != dst.quantization_info())
74  {
75  const UniformQuantizationInfo iq_info = src.quantization_info().uniform();
76  const UniformQuantizationInfo oq_info = dst.quantization_info().uniform();
77 
78  if(src.data_type() == DataType::QASYMM8)
79  {
80  std::transform(src_ptr, src_ptr + width, dst_ptr + width_offset + offset * width_out, [&](T t)
81  {
82  const float dequantized_input = dequantize_qasymm8(t, iq_info);
83  return quantize_qasymm8(dequantized_input, oq_info);
84  });
85  }
86  else
87  {
88  std::transform(src_ptr, src_ptr + width, dst_ptr + width_offset + offset * width_out, [&](T t)
89  {
90  const float dequantized_input = dequantize_qasymm8_signed(t, iq_info);
91  return quantize_qasymm8_signed(dequantized_input, oq_info);
92  });
93  }
94  src_ptr += width;
95  }
96  else
97  {
98  std::copy(src_ptr, src_ptr + width, dst_ptr + width_offset + offset * width_out);
99  src_ptr += width;
100  }
101  }
102  }
103  }
104  width_offset += width;
105  }
106  return dst;
107 }
108 
109 template SimpleTensor<float> widthconcatenate_layer(const std::vector<SimpleTensor<float>> &srcs, SimpleTensor<float> &dst);
110 template SimpleTensor<half> widthconcatenate_layer(const std::vector<SimpleTensor<half>> &srcs, SimpleTensor<half> &dst);
111 template SimpleTensor<uint8_t> widthconcatenate_layer(const std::vector<SimpleTensor<uint8_t>> &srcs, SimpleTensor<uint8_t> &dst);
112 template SimpleTensor<int8_t> widthconcatenate_layer(const std::vector<SimpleTensor<int8_t>> &srcs, SimpleTensor<int8_t> &dst);
113 } // namespace
114 
115 template <typename T>
116 SimpleTensor<T> concatenate_layer(std::vector<SimpleTensor<T>> &srcs, SimpleTensor<T> &dst, unsigned int axis)
117 {
118  switch(axis)
119  {
120  case Window::DimX:
121  {
122  return widthconcatenate_layer(srcs, dst);
123  }
124  case Window::DimY:
125  {
126  for(auto &t : srcs)
127  {
128  t = reference::permute<T>(t, PermutationVector(1U, 0U));
129  }
130  dst = reference::permute<T>(dst, PermutationVector(1U, 0U));
131  return reference::permute<T>(widthconcatenate_layer(srcs, dst), PermutationVector(1U, 0U));
132  }
133  case Window::DimZ:
134  {
135  for(auto &t : srcs)
136  {
137  t = reference::permute<T>(t, PermutationVector(2U, 1U, 0U));
138  }
139  dst = reference::permute<T>(dst, PermutationVector(2U, 1U, 0U));
140  return reference::permute<T>(widthconcatenate_layer(srcs, dst), PermutationVector(2U, 1U, 0U));
141  }
142  case 3:
143  {
144  for(auto &t : srcs)
145  {
146  t = reference::permute<T>(t, PermutationVector(3U, 2U, 1U, 0U));
147  }
148  dst = reference::permute<T>(dst, PermutationVector(3U, 2U, 1U, 0U));
149  auto ret = reference::permute<T>(widthconcatenate_layer(srcs, dst), PermutationVector(3U, 2U, 1U, 0U));
150  return ret;
151  }
152  default:
153  {
154  ARM_COMPUTE_ERROR("Not supported");
155  return dst;
156  }
157  }
158 }
159 
160 template SimpleTensor<float> concatenate_layer(std::vector<SimpleTensor<float>> &srcs, SimpleTensor<float> &dst, unsigned int axis);
161 template SimpleTensor<half> concatenate_layer(std::vector<SimpleTensor<half>> &srcs, SimpleTensor<half> &dst, unsigned int axis);
162 template SimpleTensor<uint8_t> concatenate_layer(std::vector<SimpleTensor<uint8_t>> &srcs, SimpleTensor<uint8_t> &dst, unsigned int axis);
163 template SimpleTensor<int8_t> concatenate_layer(std::vector<SimpleTensor<int8_t>> &srcs, SimpleTensor<int8_t> &dst, unsigned int axis);
164 } // namespace reference
165 } // namespace validation
166 } // namespace test
167 } // namespace arm_compute
arm_compute::dequantize_qasymm8
float dequantize_qasymm8(uint8_t value, const INFO_TYPE &qinfo)
Dequantize a value given an unsigned 8-bit asymmetric quantization scheme.
Definition: QuantizationInfo.h:353
arm_compute::test::validation::src
SimpleTensor< float > src
Definition: DFT.cpp:155
arm_compute::DataType::QASYMM8
@ QASYMM8
quantized, asymmetric fixed-point 8-bit number unsigned
arm_compute::test::validation::dst
auto dst
Definition: DFT.cpp:170
arm_compute::Window::DimX
static constexpr size_t DimX
Alias for dimension 0 also known as X dimension.
Definition: Window.h:43
arm_compute::quantize_qasymm8
uint8_t quantize_qasymm8(float value, const INFO_TYPE &qinfo, RoundingPolicy rounding_policy=RoundingPolicy::TO_NEAREST_UP)
Quantize a value given an unsigned 8-bit asymmetric quantization scheme.
Definition: QuantizationInfo.h:295
ARM_COMPUTE_ERROR
#define ARM_COMPUTE_ERROR(msg)
Print the given message then throw an std::runtime_error.
Definition: Error.h:354
Permute.h
arm_compute::utils::cast::U
U
Definition: SaturateCast.h:65
arm_compute::PermutationVector
Strides PermutationVector
Permutation vector.
Definition: CoreTypes.h:38
ARM_COMPUTE_ERROR_ON
#define ARM_COMPUTE_ERROR_ON(cond)
If the condition is true then an error message is printed and an exception thrown.
Definition: Error.h:466
arm_compute::quantize_qasymm8_signed
int8_t quantize_qasymm8_signed(float value, const INFO_TYPE &qinfo, RoundingPolicy rounding_policy=RoundingPolicy::TO_NEAREST_UP)
Quantize a value given a signed 8-bit asymmetric quantization scheme.
Definition: QuantizationInfo.h:309
offset
__global uchar * offset(const Image *img, int x, int y)
Get the pointer position of a Image.
Definition: helpers.h:1128
arm_compute::test::validation::reference::copy
SimpleTensor< T > copy(const SimpleTensor< T > &src, const TensorShape &output_shape)
Definition: Copy.cpp:37
ConcatenateLayer.h
arm_compute::Window::DimY
static constexpr size_t DimY
Alias for dimension 1 also known as Y dimension.
Definition: Window.h:45
arm_compute::test::SimpleTensor
Simple tensor object that stores elements in a consecutive chunk of memory.
Definition: SimpleTensor.h:58
arm_compute::dequantize_qasymm8_signed
float dequantize_qasymm8_signed(int8_t value, const INFO_TYPE &qinfo)
Dequantize a value given a signed 8-bit asymmetric quantization scheme.
Definition: QuantizationInfo.h:366
arm_compute
Copyright (c) 2017-2023 Arm Limited.
Definition: introduction.dox:24
arm_compute::Window::DimZ
static constexpr size_t DimZ
Alias for dimension 2 also known as Z dimension.
Definition: Window.h:47
arm_compute::is_data_type_quantized
bool is_data_type_quantized(DataType dt)
Check if a given data type is of quantized type.
Definition: DataTypeUtils.h:324
Helpers.h
arm_compute::test::validation::reference::concatenate_layer
SimpleTensor< T > concatenate_layer(std::vector< SimpleTensor< T >> &srcs, SimpleTensor< T > &dst, unsigned int axis)
Definition: ConcatenateLayer.cpp:116
tf_frozen_model_extractor.t
t
Definition: tf_frozen_model_extractor.py:49