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Merge pull request #2217 from jeffdonahue/ssafar-reshape-rebase
Rebase @ssafar's ReshapeLayer
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,95 @@ | ||
| #include <vector> | ||
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| #include "caffe/common_layers.hpp" | ||
| #include "caffe/layer.hpp" | ||
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| namespace caffe { | ||
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| template <typename Dtype> | ||
| void ReshapeLayer<Dtype>::LayerSetUp(const vector<Blob<Dtype>*>& bottom, | ||
| const vector<Blob<Dtype>*>& top) { | ||
| inferred_axis_ = -1; | ||
| copy_axes_.clear(); | ||
| const BlobShape& top_blob_shape = this->layer_param_.reshape_param().shape(); | ||
| const int top_num_axes = top_blob_shape.dim_size(); | ||
| constant_count_ = 1; | ||
| for (int i = 0; i < top_num_axes; ++i) { | ||
| const int top_dim = top_blob_shape.dim(i); | ||
| if (top_dim == 0) { | ||
| copy_axes_.push_back(i); | ||
| } else if (top_dim == -1) { | ||
| CHECK_EQ(inferred_axis_, -1) << "new shape contains multiple " | ||
| << "-1 dims; at most a single (1) value of -1 may be specified"; | ||
| inferred_axis_ = i; | ||
| } else { | ||
| constant_count_ *= top_dim; | ||
| } | ||
| } | ||
| } | ||
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| template <typename Dtype> | ||
| void ReshapeLayer<Dtype>::Reshape(const vector<Blob<Dtype>*>& bottom, | ||
| const vector<Blob<Dtype>*>& top) { | ||
| const int input_start_axis = this->layer_param_.reshape_param().axis(); | ||
| const int start_axis = (input_start_axis >= 0) ? input_start_axis : | ||
| bottom[0]->num_axes() + input_start_axis + 1; | ||
| CHECK_GE(start_axis, 0) << "axis " << input_start_axis << " out of range"; | ||
| CHECK_LE(start_axis, bottom[0]->num_axes()) << "axis " << input_start_axis | ||
| << " out of range for " << bottom[0]->num_axes() << "-D input blob"; | ||
| const int num_axes = this->layer_param_.reshape_param().num_axes(); | ||
| CHECK_GE(num_axes, -1) << "num_axes must be >= 0, or -1 for all"; | ||
| const int end_axis = | ||
| (num_axes == -1) ? bottom[0]->num_axes() : (start_axis + num_axes); | ||
| CHECK_LE(end_axis, bottom[0]->num_axes()) | ||
| << "end_axis = axis + num_axes is out of range"; | ||
| const int num_axes_replaced = end_axis - start_axis; | ||
| const int num_axes_retained = bottom[0]->num_axes() - num_axes_replaced; | ||
| const BlobShape& top_blob_shape = this->layer_param_.reshape_param().shape(); | ||
| const int num_new_axes = top_blob_shape.dim_size(); | ||
| vector<int> top_shape(num_axes_retained + num_new_axes); | ||
| int top_shape_index = 0; | ||
| for (int i = 0; i < start_axis; ++i) { | ||
| top_shape[top_shape_index++] = bottom[0]->shape(i); | ||
| } | ||
| for (int i = 0; i < num_new_axes; ++i) { | ||
| top_shape[top_shape_index++] = top_blob_shape.dim(i); | ||
| } | ||
| for (int i = end_axis; i < bottom[0]->num_axes(); ++i) { | ||
| top_shape[top_shape_index++] = bottom[0]->shape(i); | ||
| } | ||
| CHECK_EQ(top_shape_index, top_shape.size()); | ||
| for (int i = 0; i < copy_axes_.size(); ++i) { | ||
| const int copy_axis_index = copy_axes_[i]; | ||
| CHECK_GT(bottom[0]->num_axes(), start_axis + copy_axis_index) | ||
| << "new shape contains a 0, but there was no corresponding bottom axis " | ||
| << "to copy"; | ||
| top_shape[start_axis + copy_axis_index] = | ||
| bottom[0]->shape(start_axis + copy_axis_index); | ||
| } | ||
| if (inferred_axis_ >= 0) { | ||
| // A -1 dim was specified; infer the correct dimension by computing the | ||
| // product of the other dimensions. | ||
| int explicit_count = constant_count_; | ||
| explicit_count *= bottom[0]->count(0, start_axis); | ||
| explicit_count *= bottom[0]->count(end_axis); | ||
| for (int i = 0; i < copy_axes_.size(); ++i) { | ||
| const int copy_axis_index = copy_axes_[i]; | ||
| explicit_count *= top_shape[start_axis + copy_axis_index]; | ||
| } | ||
| CHECK_EQ(0, bottom[0]->count() % explicit_count) << "bottom count (" | ||
| << bottom[0]->count() << ") must be divisible by the product of " | ||
| << "the specified dimensions (" << explicit_count << ")"; | ||
| const int inferred_dim = bottom[0]->count() / explicit_count; | ||
| top_shape[start_axis + inferred_axis_] = inferred_dim; | ||
| } | ||
| top[0]->Reshape(top_shape); | ||
| CHECK_EQ(top[0]->count(), bottom[0]->count()) | ||
| << "output count must match input count"; | ||
| top[0]->ShareData(*bottom[0]); | ||
| top[0]->ShareDiff(*bottom[0]); | ||
| } | ||
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| INSTANTIATE_CLASS(ReshapeLayer); | ||
| REGISTER_LAYER_CLASS(Reshape); | ||
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| } // namespace caffe |
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