caffe源码阅读
1. base_conv_layer:
void ConvolutionLayer<Dtype>::compute_output_shape() { const int* kernel_shape_data = this->kernel_shape_.cpu_data(); const int* stride_data = this->stride_.cpu_data(); const int* pad_data = this->pad_.cpu_data(); const int* dilation_data = this->dilation_.cpu_data(); this->output_shape_.clear(); for (int i = 0; i < this->num_spatial_axes_; ++i) { //追溯到LayerSetUp里,可以看到通常num_spatial_axes_=2 // i + 1 to skip channel axis const int input_dim = this->input_shape(i + 1); const int kernel_extent = dilation_data[i] * (kernel_shape_data[i] - 1) + 1; const int output_dim = (input_dim + 2 * pad_data[i] - kernel_extent)/ stride_data[i] + 1; this->output_shape_.push_back(output_dim); } }