Compute Library
 21.08
ConvolutionLayer.cpp
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2  * Copyright (c) 2017-2020 Arm Limited.
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24 #include "ConvolutionLayer.h"
25 
31 
33 
35 
36 namespace arm_compute
37 {
38 namespace test
39 {
40 namespace validation
41 {
42 namespace reference
43 {
44 template <typename T, typename TW, typename TB>
46  const Size2D &dilation, unsigned int num_groups)
47 {
48  ARM_COMPUTE_ERROR_ON((src.shape()[2] / num_groups) != weights.shape()[2]);
49 
50  // Compute reference
51  const int width_in = src.shape().x();
52  const int height_in = src.shape().y();
53  const int depth_in = src.shape().z();
54  const int width_out = dst.shape().x();
55  const int height_out = dst.shape().y();
56  const int depth_out = dst.shape().z();
57  const int width_weights = weights.shape().x();
58  const int height_weights = weights.shape().y();
59  const int depth_weights = weights.shape().z();
60  const int pad_left = info.pad_left();
61  const int pad_top = info.pad_top();
62  const int stride_xi = info.stride().first;
63  const int stride_yi = info.stride().second;
64 
65  auto output_wh = scaled_dimensions(width_in, height_in, width_weights, height_weights, info, dilation);
66 
67  const int start_xi = (dilation.x() * (width_weights - 1) + 1) / 2 - pad_left;
68  const int start_yi = (dilation.y() * (height_weights - 1) + 1) / 2 - pad_top;
69  const int end_xi = output_wh.first * stride_xi;
70  const int end_yi = output_wh.second * stride_yi;
71  const int num_batches = src.shape().total_size() / (width_in * height_in * depth_in);
72 
73 #if defined(_OPENMP) && !( defined(__arm__) && defined(__ANDROID__))
74  #pragma omp parallel for collapse(5)
75 #endif /* _OPENMP */
76  for(int r = 0; r < num_batches; ++r)
77  {
78  for(int yi = start_yi; yi < start_yi + end_yi; yi += stride_yi)
79  {
80  for(int xi = start_xi; xi < start_xi + end_xi; xi += stride_xi)
81  {
82  for(int group = 0; group < static_cast<int>(num_groups); ++group)
83  {
84  for(int ofm = 0; ofm < static_cast<int>(depth_out / num_groups); ++ofm)
85  {
86  // Compute input and output offsets
87  const int offset_in = r * width_in * height_in * depth_in + (group * (depth_in / num_groups) * width_in * height_in);
88  const int xo = (xi - start_xi) / stride_xi;
89  const int yo = (yi - start_yi) / stride_yi;
90  const int offset_out = xo + yo * width_out + ((ofm + group * (depth_out / num_groups)) * width_out * height_out) + (r * width_out * height_out * depth_out);
91  const int offset_w = (ofm + group * (depth_out / num_groups)) * width_weights * height_weights * depth_weights;
92  const int offset_b = (ofm + group * (depth_out / num_groups));
93 
94  ARM_COMPUTE_ASSERT(xo < width_out);
95  ARM_COMPUTE_ASSERT(yo < height_out);
96 
97  // Compute 3D convolution
98  convolution_3d::detail::convolution3d(src, weights, bias, dst,
99  offset_in, offset_w, offset_b, offset_out,
100  xi, yi,
101  width_in, height_in, (depth_in / num_groups),
102  width_weights, height_weights, dilation.x(), dilation.y(), ofm);
103  }
104  }
105  }
106  }
107  }
108  return dst;
109 }
110 template <typename T, typename TW, typename TB>
112  const Size2D &dilation, unsigned int num_groups, QuantizationInfo out_quant_info)
113 {
114  // if no explicit quantization has been set you the same as src
115  if(out_quant_info == QuantizationInfo())
116  {
117  out_quant_info = src.quantization_info();
118  }
119  // Create reference
120  SimpleTensor<T> dst{ output_shape, src.data_type(), 1, out_quant_info };
121 
122  return convolution_layer_nchw(src, weights, bias, dst, info, dilation, num_groups);
123 }
124 
126  const PadStrideInfo &info, const Size2D &dilation, unsigned int num_groups, QuantizationInfo out_quant_info);
127 template SimpleTensor<half> convolution_layer(const SimpleTensor<half> &src, const SimpleTensor<half> &weights, const SimpleTensor<half> &bias, const TensorShape &output_shape,
128  const PadStrideInfo &info, const Size2D &dilation, unsigned int num_groups, QuantizationInfo out_quant_info);
129 template SimpleTensor<uint8_t> convolution_layer(const SimpleTensor<uint8_t> &src, const SimpleTensor<uint8_t> &weights, const SimpleTensor<int32_t> &bias, const TensorShape &output_shape,
130  const PadStrideInfo &info, const Size2D &dilation, unsigned int num_groups, QuantizationInfo out_quant_info);
131 template SimpleTensor<uint8_t> convolution_layer(const SimpleTensor<uint8_t> &src, const SimpleTensor<int8_t> &weights, const SimpleTensor<int32_t> &bias, const TensorShape &output_shape,
132  const PadStrideInfo &info, const Size2D &dilation, unsigned int num_groups, QuantizationInfo out_quant_info);
133 template SimpleTensor<int8_t> convolution_layer(const SimpleTensor<int8_t> &src, const SimpleTensor<int8_t> &weights, const SimpleTensor<int32_t> &bias, const TensorShape &output_shape,
134  const PadStrideInfo &info, const Size2D &dilation, unsigned int num_groups, QuantizationInfo out_quant_info);
135 } // namespace reference
136 } // namespace validation
137 } // namespace test
138 } // namespace arm_compute
#define ARM_COMPUTE_ASSERT(cond)
Definition: Validate.h:37
Shape of a tensor.
Definition: TensorShape.h:39
DataType data_type() const override
Data type of the tensor.
Definition: SimpleTensor.h:357
#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
TensorShape shape() const override
Shape of the tensor.
Definition: SimpleTensor.h:320
size_t x() const
Semantic accessor for width as x.
Definition: Size2D.h:74
unsigned int pad_top() const
Get the top padding.
Definition: Types.h:731
SimpleTensor< float > src
Definition: DFT.cpp:155
Copyright (c) 2017-2021 Arm Limited.
std::pair< unsigned int, unsigned int > scaled_dimensions(int width, int height, int kernel_width, int kernel_height, const PadStrideInfo &pad_stride_info, const Size2D &dilation=Size2D(1U, 1U))
Returns expected width and height of output scaled tensor depending on dimensions rounding mode...
Definition: Utils.cpp:395
void convolution3d(const SimpleTensor< T > &in, const SimpleTensor< TW > &weights, const SimpleTensor< TB > &bias, SimpleTensor< T > &out, int i_offset, int w_offset, int b_offset, int o_offset, int xi, int yi, int width_in, int height_in, int depth_in, int width_weights, int height_weights, int dilation_x=1, int dilation_y=1, int filter_id=0)
Definition: Convolution3d.h:49
Quantization information.
const unsigned int num_groups
Definition: Im2Col.cpp:153
std::pair< unsigned int, unsigned int > stride() const
Get the stride.
Definition: Types.h:695
Padding and stride information class.
Definition: Types.h:647
size_t y() const
Semantic accessor for height as y.
Definition: Size2D.h:83
Simple tensor object that stores elements in a consecutive chunk of memory.
Definition: SimpleTensor.h:58
ScaleKernelInfo info(interpolation_policy, default_border_mode, PixelValue(), sampling_policy, false)
SimpleTensor< T > convolution_layer_nchw(const SimpleTensor< T > &src, const SimpleTensor< TW > &weights, const SimpleTensor< TB > &bias, SimpleTensor< T > &dst, const PadStrideInfo &info, const Size2D &dilation, unsigned int num_groups)
SimpleTensor< T > convolution_layer(const SimpleTensor< T > &src, const SimpleTensor< TW > &weights, const SimpleTensor< TB > &bias, const TensorShape &output_shape, const PadStrideInfo &info, const Size2D &dilation, unsigned int num_groups, QuantizationInfo out_quant_info)
Class for specifying the size of an image or rectangle.
Definition: Size2D.h:34
QuantizationInfo quantization_info() const override
Quantization info in case of asymmetric quantized type.
Definition: SimpleTensor.h:332
unsigned int pad_left() const
Get the left padding.
Definition: Types.h:721