Add some fallback testcases

tests/ut/python/fallback/test_graph_fallback.py

@@ -29,11 +29,13 @@ context.set_context(mode=context.GRAPH_MODE)
 def add_func(x, y):
     return x + y
 
+
 @ms_function
 def do_increment(i):
     add_1 = F.partial(add_func, 1)
     return add_1(i)
 
+
 def test_increment():
     a = do_increment(9)
     assert a == 10
@@ -45,6 +47,7 @@ def use_monad(x, y):
     res = F.depend(res, monad.U)
     return res
 
+
 def test_use_monad():
     x = Tensor(1.0, mstype.float32)
     y = Tensor(1.0, mstype.float32)
@@ -62,6 +65,7 @@ class Net(nn.Cell):
             print(i)
         return x_len
 
+
 def test_builtins_len():
     net = Net()
     net()
@@ -75,6 +79,7 @@ def np_fallback_func():
     me_x = me_x + me_x
     return me_x
 
+
 @pytest.mark.skip(reason='Not support graph fallback feature yet')
 def test_np_fallback_func():
     print(np_fallback_func())
@@ -88,6 +93,7 @@ def div_mod_func1():
     a = divmod(x, y)
     return Tensor(a)
 
+
 @pytest.mark.skip(reason='Not support graph fallback feature yet')
 def test_div_mod_func1():
     print(div_mod_func1())  # (2, 2)
@@ -99,6 +105,7 @@ def div_mod_func2(x, y):
     a = divmod(x, y)
     return Tensor(a)
 
+
 @pytest.mark.skip(reason='Not support graph fallback feature yet')
 def test_div_mod_func2_scalar():
     """
@@ -108,6 +115,7 @@ def test_div_mod_func2_scalar():
     """
     print(div_mod_func2(8, 3))  # (2, 2)
 
+
 @pytest.mark.skip(reason='Not support graph fallback feature yet')
 def test_div_mod_func2_tensor():
     """
@@ -129,6 +137,7 @@ def select_func(cond, x, y):
         output = x
     return output
 
+
 def test_select_func():
     cond = Tensor([True, False])
     x = Tensor([2, 3], mstype.float32)
@@ -147,6 +156,7 @@ def select_func2(cond, x, y):
         output = x
     return output
 
+
 def test_select_func2():
     cond = Tensor([True, False])
     x = Tensor([2, 3], mstype.float32)
@@ -160,7 +170,62 @@ def slice_func(a, b):
     a[1:3, ::] = b
     return a
 
+
 def test_slice_func():
     a = Tensor(np.arange(60).reshape(3, 4, 5), dtype=mstype.float32)
     b = Tensor([1], dtype=mstype.float32)
     print(slice_func(a, b))
+
+
+@ms_function
+def np_fallback_func_tensor_index(x):
+    array_x = tuple([2, 3, 4, 5])
+    np_x = np.array(array_x).astype(np.float32)
+    me_x = Tensor(np_x)
+    me_x = me_x + me_x
+    return me_x[x]
+
+
+@pytest.mark.skip(reason='Not support graph fallback feature yet')
+def test_np_fallback_func_tensor_index():
+    """
+    Feature: Fallback feature: support Tensor index.
+    Description: Fallback feature: support Tensor index.
+    Expectation: Fallback feature: support Tensor index.
+    """
+    x = Tensor(1, mstype.int32)
+    output = np_fallback_func_tensor_index(x)
+    output_expect = Tensor(6, mstype.float32)
+    assert output == output_expect
+
+
+class ControlNet(nn.Cell):
+    def __init__(self):
+        super(ControlNet, self).__init__()
+
+    def inner_function_1(self, a, b):
+        return a + b
+
+    def inner_function_2(self, a, b):
+        return a - b
+
+    def construct(self, x):
+        a = Tensor(np.array(4), mstype.int32)
+        b = Tensor(np.array(5), mstype.int32)
+        if a + b > x:
+            return self.inner_function_1(a, b)
+        return self.inner_function_2(a, b)
+
+
+@pytest.mark.skip(reason='Not support graph fallback feature yet')
+def test_fallback_control_sink_tensor():
+    """
+    Feature: Fallback feature: support define Tensor in Class construct.
+    Description: Fallback feature: support define Tensor in Class construct.
+    Expectation: Fallback feature: support define Tensor in Class construct.
+    """
+    x = Tensor(np.array(1), mstype.int32)
+    net = ControlNet()
+    output = net(x)
+    output_expect = Tensor(9, mstype.int32)
+    assert output == output_expect