[dnn/shift] bugfix in wgrad

examples/python/tensorflow/run.py

@@ -56,7 +56,7 @@ def blocksparse_matmul_grad(op, dy):
     return (dx, dw)
 
 def run_shift():
-    B, C, H, W = 1, 16, 8, 8
+    B, C, H, W = 1, 32, 8, 6
     R, S, F = 3, 3, 16
     np.random.seed(2)
     a = tf.placeholder(tf.float32, shape=[C, H, W, B])
@@ -76,8 +76,8 @@ def run_shift():
     sess = tf.InteractiveSession()
     grads = tf.test.compute_gradient([a, b], [(C, H, W, B), (C, F)], c, (F, H, W, B),
                                     extra_feed_dict={a: ha, b: hb})
-    dx_t, dx_n = grads[0]
     dw_t, dw_n = grads[1]
+    dx_t, dx_n = grads[0]
     print(np.max(np.abs(dw_t - dw_n)))
     print(np.max(np.abs(dx_t - dx_n)))
     # Run