added backward

torch_spline_conv/functions/utils.py

@@ -36,8 +36,8 @@ def spline_weighting_forward(x, weight, basis, weight_index):
 
 
 def spline_weighting_backward(grad_output, x, weight, basis, weight_index):
-    grad_input = x.new(x.size(0), weight.size(1))
-    grad_weight = x.new(weight)
+    grad_input = x.new(x.size(0), weight.size(1)).fill_(0)
+    grad_weight = x.new(weight).fill_(0)
     func = get_func('weighting_backward', x)
     func(grad_input, grad_weight, grad_output, x, weight, basis, weight_index)
     return grad_input, grad_weight

torch_spline_conv/src/generic/cpu.c

@@ -73,7 +73,27 @@ void spline_(weighting_forward)(THTensor *output, THTensor *input, THTensor *wei
 }
 
 void spline_(weighting_backward)(THTensor *grad_input, THTensor *grad_weight, THTensor *grad_output, THTensor *input, THTensor *weight, THTensor *basis, THLongTensor *weight_index) {
+  real *weight_data = weight->storage->data + weight->storageOffset;
+  real *grad_weight_data = grad_weight->storage->data + grad_weight->storageOffset;
+  int64_t M_out = THTensor_(size)(grad_input, 1);
+  int64_t M_in = THTensor_(size)(input, 1);
+  int64_t S = THLongTensor_size(weight_index, 1);
+  int64_t m_out, m_in, s, i, w_idx; real g, b;
+
   TH_TENSOR_DIM_APPLY5(real, grad_input, real, grad_output, real, input, real, basis, int64_t, weight_index, 1,
+    for (m_out = 0; m_out < M_out; m_out++) {
+      g = *(grad_output_data + m_out * grad_output_stride);
+      for (s = 0; s < S; s++) {
+        b = *(basis_data + s * basis_stride);
+        i = *(weight_index_data + s * weight_index_stride);
+        for (m_in = 0; m_in < M_in; m_in++) {
+          w_idx = i * M_in * M_out + m_in * M_out + m_out;
+          grad_input_data[m_in] += b * g * *(weight_data + w_idx);
+          grad_weight_data[w_idx] += b * g * *(input_data + m_in * input_stride);
+
+        }
+      }
+    }
   )
 }