Compute Library
 20.02.1
DeconvolutionLayer.cpp
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1 /*
2  * Copyright (c) 2017-2019 ARM Limited.
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24 #include "ConvolutionLayer.h"
25 
27 
28 namespace arm_compute
29 {
30 namespace test
31 {
32 namespace validation
33 {
34 namespace reference
35 {
36 template <typename T, typename TB>
38  const PadStrideInfo &info, QuantizationInfo out_qinfo)
39 {
40  // Create reference
41  const unsigned int pad_left = info.pad_left();
42  const unsigned int pad_right = info.pad_right();
43  const unsigned int pad_top = info.pad_top();
44  const unsigned int pad_bottom = info.pad_bottom();
45  const int stride_x = info.stride().first;
46  const int stride_y = info.stride().second;
47  const int weights_width = weights.shape().x();
48  const int weights_height = weights.shape().y();
49  const int weights_upper_dims = weights.shape().total_size() / (weights_width * weights_height);
50 
51  ARM_COMPUTE_ERROR_ON(pad_left > (weights.shape().x() - 1));
52  ARM_COMPUTE_ERROR_ON(pad_right > (weights.shape().x() - 1));
53  ARM_COMPUTE_ERROR_ON(pad_top > (weights.shape().y() - 1));
54  ARM_COMPUTE_ERROR_ON(pad_bottom > (weights.shape().y() - 1));
55 
56  // Find the upsampled dimensions
57  unsigned int out_x = (src.shape().x() - 1) * stride_x + 1;
58  unsigned int out_y = (src.shape().y() - 1) * stride_y + 1;
59 
60  // Find the padding needed for the convolution with stride 1 in order to match output shape
61  unsigned int deconv_pad_x = output_shape.x() - (out_x - weights_width + 1);
62  unsigned int deconv_pad_y = output_shape.y() - (out_y - weights_height + 1);
63  out_x += deconv_pad_x;
64  out_y += deconv_pad_y;
65 
66  unsigned int deconv_pad_left = pad_right > pad_left ? pad_right - pad_left : 0;
67  unsigned int deconv_pad_right = pad_left > pad_right ? pad_left - pad_right : 0;
68  deconv_pad_x -= deconv_pad_left + deconv_pad_right;
69  ARM_COMPUTE_ERROR_ON((deconv_pad_x % 2) != 0);
70  deconv_pad_left += deconv_pad_x / 2;
71  deconv_pad_right += deconv_pad_x / 2;
72 
73  unsigned int deconv_pad_top = pad_bottom > pad_top ? pad_bottom - pad_top : 0;
74  unsigned int deconv_pad_bottom = pad_top > pad_bottom ? pad_top - pad_bottom : 0;
75  deconv_pad_y -= deconv_pad_top + deconv_pad_bottom;
76  ARM_COMPUTE_ERROR_ON((deconv_pad_y % 2) != 0);
77  deconv_pad_top += deconv_pad_y / 2;
78  deconv_pad_bottom += deconv_pad_y / 2;
79 
80  TensorShape scaled_shape = src.shape();
81  scaled_shape.set(0, out_x);
82  scaled_shape.set(1, out_y);
83  SimpleTensor<T> scaled{ scaled_shape, src.data_type(), 1, src.quantization_info() };
84 
85  const int width_in = src.shape().x();
86  const int height_in = src.shape().y();
87  const int width_scaled = scaled.shape().x();
88  const int height_scaled = scaled.shape().y();
89  const int num_2d_slices = src.shape().total_size() / (width_in * height_in);
90 
91  if(src.data_type() == DataType::QASYMM8)
92  {
93  const uint8_t quantized_zero = src.quantization_info().uniform().offset;
94  std::fill_n(scaled.data(), scaled.num_elements(), quantized_zero);
95  }
96  else
97  {
98  std::fill_n(scaled.data(), scaled.num_elements(), T(0));
99  }
100 
101  // Flip weights by 180 degrees
102  SimpleTensor<T> weights_flipped{ weights.shape(), weights.data_type(), 1, weights.quantization_info() };
103  for(int ud = 0; ud < weights_upper_dims; ++ud)
104  {
105  const int offset = ud * weights_width * weights_height;
106  for(int y = 0; y < weights_height; ++y)
107  {
108  for(int x = 0; x < weights_width; ++x)
109  {
110  weights_flipped[offset + (weights_height - 1 - y) * weights_width + (weights_width - 1 - x)] = weights[offset + y * weights_width + x];
111  }
112  }
113  }
114 
115  for(int slice = 0; slice < num_2d_slices; ++slice)
116  {
117  const int offset_slice_in = slice * width_in * height_in;
118  const int offset_slice_out = slice * width_scaled * height_scaled;
119  const int start_x = deconv_pad_left;
120  const int start_y = deconv_pad_top;
121  const int end_x = width_scaled - deconv_pad_right;
122  const int end_y = height_scaled - deconv_pad_bottom;
123 
124  for(int yi = start_y, in_y = 0; yi < end_y; yi += stride_y, in_y++)
125  {
126  for(int xi = start_x, in_x = 0; xi < end_x; xi += stride_x, in_x++)
127  {
128  const T *in = src.data() + offset_slice_in + in_y * width_in + in_x;
129  T *out = scaled.data() + offset_slice_out + xi + yi * width_scaled;
130  *out = *in;
131  }
132  }
133  }
134 
135  const PadStrideInfo conv_info(1, 1, 0, 0, 0, 0, DimensionRoundingType::CEIL);
136  return convolution_layer(scaled, weights_flipped, bias, output_shape, conv_info, Size2D(1U, 1U), 1, out_qinfo);
137 }
138 
140  const PadStrideInfo &info, QuantizationInfo out_quant_info);
142  const PadStrideInfo &info, QuantizationInfo out_quant_info);
144  const PadStrideInfo &info, QuantizationInfo out_quant_info);
145 } // namespace reference
146 } // namespace validation
147 } // namespace test
148 } // namespace arm_compute
__global uchar * offset(const Image *img, int x, int y)
Get the pointer position of a Image.
Definition: helpers.h:510
Shape of a tensor.
Definition: TensorShape.h:39
SimpleTensor< T > deconvolution_layer(const SimpleTensor< T > &src, const SimpleTensor< T > &weights, const SimpleTensor< TB > &bias, const TensorShape &output_shape, const PadStrideInfo &info, QuantizationInfo out_qinfo)
Deconvolution reference implementation.
#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
Copyright (c) 2017-2020 ARM Limited.
Quantization information.
quantized, asymmetric fixed-point 8-bit number unsigned
Padding and stride information class.
Definition: Types.h:686
Simple tensor object that stores elements in a consecutive chunk of memory.
Definition: SimpleTensor.h:59
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
TensorShape & set(size_t dimension, size_t value, bool apply_dim_correction=true)
Accessor to set the value of one of the dimensions.
Definition: TensorShape.h:78
cast configure & src
Definition: Cast.cpp:169
SimpleTensor< T > slice(const SimpleTensor< T > &src, Coordinates starts, Coordinates ends)