fix(imperative): allow rng op infer shape fallible

GitOrigin-RevId: 687844500cc2cab18de576b1484215c72329e4b8

imperative/python/test/unit/functional/test_functional.py

@@ -71,6 +71,7 @@ def test_dropout():
         with gm:
             out = F.nn.dropout(data, rate, training=True)
             gm.backward(out, tensor(np.ones(shape, dtype=np.float32)))
+            if len(shape) != 0:
                 assert not out.numpy().all()
             np.testing.assert_allclose(out.numpy(), data.grad.numpy(), 1e-7, 1e-7)
 
@@ -99,6 +100,7 @@ def test_dropout():
         out4 = F.nn.dropout(data, rate, training=True)
         assert not (out1.numpy() == out4.numpy()).all()
 
+    test_dropout_with_shape([], 0.4)
     test_dropout_with_shape([13, 17, 63, 21], 0.4)
     test_dropout_with_shape([16, 32, 64], 0.3)
     test_multiple_dropout([1024], 0.2)

imperative/src/impl/ops/rng.cpp

@@ -559,25 +559,33 @@ std::tuple<SmallVector<LogicalTensorDesc>, bool> infer_output_attrs_fallible(
     }
     dest.comp_node = inputs[0].comp_node;
     dest.layout = _InferLayout<rng_with_shape>::do_infer(inputs[0], xxx_rng_def);
-    return {{dest}, true};
+    return {{dest}, inputs[0].layout.ndim != 0};
 }
 
 template <>
 std::tuple<SmallVector<LogicalTensorDesc>, bool> infer_output_attrs_fallible<
         ShuffleRNG>(const OpDef& def, const SmallVector<LogicalTensorDesc>& inputs) {
+    bool success = inputs[0].layout.ndim != 0;
+
     SmallVector<LogicalTensorDesc> dests(2);
     dests[0].comp_node = inputs[0].comp_node;
     dests[0].layout = TensorLayout(inputs[0].layout);
     dests[0].layout.dtype = inputs[0].layout.dtype;
     dests[1].comp_node = inputs[0].comp_node;
+    if (success) {
         dests[1].layout =
                 TensorLayout(TensorShape({inputs[0].layout.shape[0]}), dtype::Int32());
-    return {dests, true};
+    } else {
+        dests[1].layout = TensorLayout(dtype::Int32());
+    }
+    return {dests, success};
 }
 
 template <>
 std::tuple<SmallVector<LogicalTensorDesc>, bool> infer_output_attrs_fallible<Dropout>(
         const OpDef& op, const SmallVector<LogicalTensorDesc>& inputs) {
+    bool success = inputs[0].layout.ndim != 0;
+
     SmallVector<LogicalTensorDesc> dests(2);
     auto cn = inputs[0].comp_node;
     dests[0].comp_node = cn;
@@ -590,8 +598,13 @@ std::tuple<SmallVector<LogicalTensorDesc>, bool> infer_output_attrs_fallible<Dro
                 inputs[0].layout);
     };
     dests[1].comp_node = cn;
+    if (success) {
         dests[1].layout = TensorLayout(TensorShape({get_mask_size()}), dtype::Byte());
-    return {dests, true};
+    } else {
+        dests[1].layout = TensorLayout(dtype::Byte());
+    }
+
+    return {dests, success};
 }
 
 template <typename Op>