Relaxing type requirements for reshape_like op

src/operator/tensor/elemwise_unary_op_basic.cc

@@ -481,7 +481,16 @@ Negative indices are supported, and `None` can be used for either `lhs_end` or `
     [](const NodeAttrs& attrs) { return std::vector<uint32_t>(1, 1); })
 .set_attr<FCompute>("FCompute<cpu>", UnaryOp::IdentityCompute<cpu>)
 .set_attr<mxnet::FInferShape>("FInferShape", ReshapeLikeShapeCompute)
-.set_attr<nnvm::FInferType>("FInferType", ElemwiseType<2, 1>)
+.set_attr<nnvm::FInferType>("FInferType", [](const nnvm::NodeAttrs& attrs,
+                                             std::vector<int> *in_attrs,
+                                             std::vector<int> *out_attrs) {
+    CHECK_EQ(in_attrs->size(), 2) << " in operator " << attrs.name;
+    std::vector<int> checked_in_attrs = { (*in_attrs)[0] };
+    bool ret = !type_is_none((*in_attrs)[1]) &&
+               ElemwiseType<1, 1>(attrs, &checked_in_attrs, out_attrs);
+    (*in_attrs)[0] = checked_in_attrs[0];
+    return ret;
+  })
 .set_attr<nnvm::FGradient>(
     "FGradient",  [](const nnvm::NodePtr& n,
                      const std::vector<nnvm::NodeEntry>& ograds) {

tests/python/unittest/test_operator.py

@@ -2529,6 +2529,16 @@ def test_slice_like_different_types():
     z = mx.nd.slice_like(x, y)
     assert_allclose(z.asnumpy(), [[1,2,3],[5,6,7]])
 
+@with_seed()
+def test_reshape_like_different_types():
+    x = mx.nd.zeros((2, 3))
+
+    y = mx.nd.array([[1, 2], [3, 4], [5, 6]])
+
+    y = mx.nd.array(y).astype('int32')
+    z = mx.nd.reshape_like(x, y)
+    assert_allclose(z.asnumpy(), [[0,0],[0,0],[0,0]])
+
 @with_seed()
 def test_flip():
     for ndim in range(1, 6):