enable dilated deconvolution

Since the underlying routines are shared, we need only upgrade
compute_output_shape.

src/caffe/layers/base_conv_layer.cpp

@@ -105,9 +105,6 @@ void BaseConvolutionLayer<Dtype>::LayerSetUp(const vector<Blob<Dtype>*>& bottom,
   for (int i = 0; i < num_spatial_axes_; ++i) {
     dilation_data[i] = (num_dilation_dims == 0) ? kDefaultDilation :
                        conv_param.dilation((num_dilation_dims == 1) ? 0 : i);
-    if (reverse_dimensions()) {
-      CHECK_EQ(dilation_data[i], 1) << "Deconvolution doesn't support dilation";
-    }
   }
   // Special case: im2col is the identity for 1x1 convolution with stride 1
   // and no padding, so flag for skipping the buffer and transformation.

src/caffe/layers/deconv_layer.cpp

@@ -9,12 +9,14 @@ void DeconvolutionLayer<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) {
     // 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 = stride_data[i] * (input_dim - 1)
-        + kernel_shape_data[i] - 2 * pad_data[i];
+        + kernel_extent - 2 * pad_data[i];
     this->output_shape_.push_back(output_dim);
   }
 }