linear and one-dimensional pseudos

test/basis.json

@@ -3,7 +3,7 @@
     "degree": 1,
     "pseudo": [0, 0.25, 0.5, 0.75, 1],
     "kernel_size": [5],
-    "is_open_spline": [0],
+    "is_open_spline": [1],
     "expected_basis": [[0, 1], [0, 1], [0, 1], [0, 1], [0, 1]],
     "expected_index": [[1, 0], [2, 1], [3, 2], [4, 3], [0, 4]]
   }

torch_spline_conv/functions/utils.py

@@ -3,7 +3,7 @@ from torch.autograd import Function
 
 from .._ext import ffi
 
-degrees = {1: 'linear', 2: 'quadric', 3: 'cubic'}
+implemented_degrees = {1: 'linear', 2: 'quadric', 3: 'cubic'}
 
 
 def get_func(name, tensor):
@@ -19,7 +19,7 @@ def spline_basis(degree, pseudo, kernel_size, is_open_spline, K):
     basis = pseudo.new(pseudo.size(0), s)
     weight_index = kernel_size.new(pseudo.size(0), s)
 
-    degree = degrees.get(degree)
+    degree = implemented_degrees.get(degree)
     if degree is None:
         raise NotImplementedError('Basis computation not implemented for '
                                   'specified B-spline degree')

torch_spline_conv/src/generic/cpu.c

@@ -3,30 +3,41 @@
 #else
 
 void spline_(basis_linear)(THTensor *basis, THLongTensor *weight_index, THTensor *pseudo, THTensor *kernel_size, THByteTensor *is_open_spline, int K) {
+  int64_t *kernel_size_data = kernel_size->storage->data + kernel_size->storageOffset;
+  uint8_t *is_open_spline_data = is_open_spline->storage->data + is_open_spline->storageOffset;
+
   int64_t k, s, S, d, D;
   real value;
   D = THTensor_(size)(pseudo, 1);
   S = THLongTensor_size(weight_index, 1);
-  /* TH_TENSOR_DIM_APPLY3(real, basis, int64_t, weight_index, real, pseudo, 1, TH_TENSOR_DIM_APPLY3_SIZE_EX_EXCEPT_DIM, */
-  /*   for (s = 0; s < S; s++) { */
+  TH_TENSOR_DIM_APPLY3(real, basis, int64_t, weight_index, real, pseudo, 1, TH_TENSOR_DIM_APPLY3_SIZE_EQ_EXCEPT_DIM,
+    for (s = 0; s < S; s++) {
   /*     /1* k = K; *1/ */
-  /*     /1* b = 1; i = 0; *1/ */
+      real b = 1; int64_t i = 0;
 
-  /*     for (d = 0; d < D; d++) { */
+      for (d = 0; d < D; d++) {
   /*       /1* k /= kernel_size[d]; *1/ */
 
 
 
 
-  /*       /1* value = *(pseudo_data + d * pseudo_stride) * (kernel_size[d] - is_open_spline[d]); *1/ */
+        value = *(pseudo_data + d * pseudo_stride) * (kernel_size_data[d] - is_open_spline_data[d]);
+        int64_t bot = ((int64_t) value) % kernel_size_data[d];
+        int64_t top = ((int64_t) (value + 1)) % kernel_size_data[d];
+        value -= floor(value);
+
+        int mod = s % 2;
+        b *= (1 - mod) * value + mod * (1 - value);
+        i += (1 - mod) * top + mod * bot;
+
 
   /*       /1* int bot = int64_t(value); *1/ */
   /*       /1* int top = (bot + 1) % kernel_size[d]; *1/ */
   /*       /1* bot %= kernel_size[d]; *1/ */
-  /*     } */
-  /*     basis_data[s * basis_stride] = 1; */
-  /*     weight_index_data[s * weight_index_stride] = 2; */
-    /* }) */
+      }
+      basis_data[s * basis_stride] = b;
+      weight_index_data[s * weight_index_stride] = i;
+    })
 }