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Diffstat (limited to 'src/caffe/layers/base_conv_layer.cpp')
-rw-r--r--src/caffe/layers/base_conv_layer.cpp10
1 files changed, 2 insertions, 8 deletions
diff --git a/src/caffe/layers/base_conv_layer.cpp b/src/caffe/layers/base_conv_layer.cpp
index a5b90a54..c6b47550 100644
--- a/src/caffe/layers/base_conv_layer.cpp
+++ b/src/caffe/layers/base_conv_layer.cpp
@@ -20,13 +20,7 @@ void BaseConvolutionLayer<Dtype>::LayerSetUp(const vector<Blob<Dtype>*>& bottom,
const int num_axes = bottom[0]->num_axes();
num_spatial_axes_ = num_axes - first_spatial_axis;
CHECK_GE(num_spatial_axes_, 0);
- // Setup input dimensions (input_shape_).
vector<int> bottom_dim_blob_shape(1, num_spatial_axes_ + 1);
- input_shape_.Reshape(bottom_dim_blob_shape);
- int* input_shape_data = input_shape_.mutable_cpu_data();
- for (int i = 0; i < num_spatial_axes_ + 1; ++i) {
- input_shape_data[i] = bottom[0]->shape(channel_axis_ + i);
- }
vector<int> spatial_dim_blob_shape(1, std::max(num_spatial_axes_, 1));
// Setup filter kernel dimensions (kernel_shape_).
kernel_shape_.Reshape(spatial_dim_blob_shape);
@@ -190,6 +184,7 @@ void BaseConvolutionLayer<Dtype>::Reshape(const vector<Blob<Dtype>*>& bottom,
<< "All inputs must have the same shape.";
}
// Shape the tops.
+ bottom_shape_ = &bottom[0]->shape();
compute_output_shape();
vector<int> top_shape(bottom[0]->shape().begin(),
bottom[0]->shape().begin() + channel_axis_);
@@ -223,10 +218,9 @@ void BaseConvolutionLayer<Dtype>::Reshape(const vector<Blob<Dtype>*>& bottom,
// it goes lazily unused to save memory.
col_buffer_shape_.clear();
col_buffer_shape_.push_back(kernel_dim_ * group_);
- const int* input_shape_data = input_shape_.cpu_data() + 1;
for (int i = 0; i < num_spatial_axes_; ++i) {
if (reverse_dimensions()) {
- col_buffer_shape_.push_back(input_shape_data[i]);
+ col_buffer_shape_.push_back(input_shape(i + 1));
} else {
col_buffer_shape_.push_back(output_shape_[i]);
}