respond to review comments. Thanks @siju-samuel

python/tvm/relay/op/dyn/_transform.py

@@ -102,5 +102,5 @@ def tile_shape_func(attrs, inputs, _):
     """
     ndim = len(inputs[0].shape)
     rdim = inputs[1].shape[0].value
-    assert ndim == rdim, "tile data and res ranks don't match"
+    assert ndim == rdim, "tile data and reps ranks don't match"
     return [_tile_shape_func(inputs[0], inputs[1], convert(ndim))]

tests/python/relay/dyn/test_dynamic_op_level3.py

@@ -79,9 +79,6 @@ def verify_tile(dshape, reps):
         func = relay.Function([x, r], z)
         x_data = np.random.uniform(low=-1, high=1, size=dshape).astype("float32")
         ref_res = np.tile(x_data, reps=reps)
-        print (ref_res.shape)
-        print(x_data.shape)
-        print(np.array(reps).shape)
         verify_func(func, [x_data, np.array(reps).astype("float32")], ref_res)
     verify_tile((2, 3, 4), (3, 2, 1))
     verify_tile((2, 3, 4), (1, 2, 1))

topi/include/topi/transform.h

@@ -1020,7 +1020,7 @@ inline Tensor tile(const Tensor& x, Array<Integer> reps, std::string name = "T_t
  * \brief Creates an operation to tile elements of an array
  *
  * \param x The input tensor
- * \param reps The number of times for repeating the tensor
+ * \param new_shape The shape of the output after tiling
  * \param name The name of the operation
  * \param tag The tag to mark the operation
  *
@@ -1029,8 +1029,6 @@ inline Tensor tile(const Tensor& x, Array<Integer> reps, std::string name = "T_t
 inline Tensor dyn_tile(const Tensor& x, Array<PrimExpr> new_shape, std::string name = "T_tile",
                        std::string tag = kBroadcast) {
   size_t ndim = x->shape.size();
-  std::cout << ndim << std::endl;
-  std::cout << new_shape << std::endl;
   if (is_empty_shape(new_shape)) {
     return compute(
         new_shape, [&](const Array<Var>& indices) { return tvm::cast(x->dtype, 0); }, name, tag);