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hub / github.com/OpenPTrack/open_ptrack_v2 / Reshape

Method Reshape

rtpose_wrapper/src/caffe/layers/reshape_layer.cpp:32–91  ·  view source on GitHub ↗

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30
31template <typename Dtype>
32void ReshapeLayer<Dtype>::Reshape(const vector<Blob<Dtype>*>& bottom,
33 const vector<Blob<Dtype>*>& top) {
34 const int input_start_axis = this->layer_param_.reshape_param().axis();
35 const int start_axis = (input_start_axis >= 0) ? input_start_axis :
36 bottom[0]->num_axes() + input_start_axis + 1;
37 CHECK_GE(start_axis, 0) << "axis " << input_start_axis << " out of range";
38 CHECK_LE(start_axis, bottom[0]->num_axes()) << "axis " << input_start_axis
39 << " out of range for " << bottom[0]->num_axes() << "-D input blob";
40 const int num_axes = this->layer_param_.reshape_param().num_axes();
41 CHECK_GE(num_axes, -1) << "num_axes must be >= 0, or -1 for all";
42 const int end_axis =
43 (num_axes == -1) ? bottom[0]->num_axes() : (start_axis + num_axes);
44 CHECK_LE(end_axis, bottom[0]->num_axes())
45 << "end_axis = axis + num_axes is out of range";
46 const int num_axes_replaced = end_axis - start_axis;
47 const int num_axes_retained = bottom[0]->num_axes() - num_axes_replaced;
48 const BlobShape& top_blob_shape = this->layer_param_.reshape_param().shape();
49 const int num_new_axes = top_blob_shape.dim_size();
50 vector<int> top_shape(num_axes_retained + num_new_axes);
51 int top_shape_index = 0;
52 for (int i = 0; i < start_axis; ++i) {
53 top_shape[top_shape_index++] = bottom[0]->shape(i);
54 }
55 for (int i = 0; i < num_new_axes; ++i) {
56 top_shape[top_shape_index++] = top_blob_shape.dim(i);
57 }
58 for (int i = end_axis; i < bottom[0]->num_axes(); ++i) {
59 top_shape[top_shape_index++] = bottom[0]->shape(i);
60 }
61 CHECK_EQ(top_shape_index, top_shape.size());
62 for (int i = 0; i < copy_axes_.size(); ++i) {
63 const int copy_axis_index = copy_axes_[i];
64 CHECK_GT(bottom[0]->num_axes(), start_axis + copy_axis_index)
65 << "new shape contains a 0, but there was no corresponding bottom axis "
66 << "to copy";
67 top_shape[start_axis + copy_axis_index] =
68 bottom[0]->shape(start_axis + copy_axis_index);
69 }
70 if (inferred_axis_ >= 0) {
71 // A -1 dim was specified; infer the correct dimension by computing the
72 // product of the other dimensions.
73 int explicit_count = constant_count_;
74 explicit_count *= bottom[0]->count(0, start_axis);
75 explicit_count *= bottom[0]->count(end_axis);
76 for (int i = 0; i < copy_axes_.size(); ++i) {
77 const int copy_axis_index = copy_axes_[i];
78 explicit_count *= top_shape[start_axis + copy_axis_index];
79 }
80 CHECK_EQ(0, bottom[0]->count() % explicit_count) << "bottom count ("
81 << bottom[0]->count() << ") must be divisible by the product of "
82 << "the specified dimensions (" << explicit_count << ")";
83 const int inferred_dim = bottom[0]->count() / explicit_count;
84 top_shape[start_axis + inferred_axis_] = inferred_dim;
85 }
86 top[0]->Reshape(top_shape);
87 CHECK_EQ(top[0]->count(), bottom[0]->count())
88 << "output count must match input count";
89 top[0]->ShareData(*bottom[0]);

Callers

nothing calls this directly

Calls 6

num_axesMethod · 0.80
shapeMethod · 0.80
countMethod · 0.80
ShareDataMethod · 0.80
ShareDiffMethod · 0.80
sizeMethod · 0.45

Tested by

no test coverage detected