diff --git a/tests/ut/python/fallback/test_graph_fallback_numpy.py b/tests/ut/python/fallback/test_graph_fallback_numpy.py
new file mode 100644
index 00000000000..7773965a548
--- /dev/null
+++ b/tests/ut/python/fallback/test_graph_fallback_numpy.py
@@ -0,0 +1,492 @@
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ============================================================================
+""" test graph fallback """
+import pytest
+import numpy as np
+from mindspore import ms_function, context
+
+context.set_context(mode=context.GRAPH_MODE)
+
+
+@pytest.mark.skip(reason='Not support graph fallback feature yet')
+def test_np_array_1():
+    """
+    Feature: JIT Fallback
+    Description: Test numpy with ndarray in graph mode.
+    Expectation: No exception.
+    """
+    @ms_function
+    def np_array_1():
+        a = np.array([1, 2, 3])
+        return a
+    res = np_array_1()
+    assert res == (1, 2, 3)
+
+
+@pytest.mark.skip(reason='Not support graph fallback feature yet')
+def test_np_array_2():
+    """
+    Feature: JIT Fallback
+    Description: Test numpy with ndarray in graph mode.
+    Expectation: No exception.
+    """
+    @ms_function
+    def np_array_2():
+        a = np.array([[1, 2], [3, 4]])
+        return a
+    res = np_array_2()
+    assert res == ([1, 2], [3, 4])
+
+
+@pytest.mark.skip(reason='Not support graph fallback feature yet')
+def test_np_array_3():
+    """
+    Feature: JIT Fallback
+    Description: Test numpy with ndarray in graph mode.
+    Expectation: No exception.
+    """
+    @ms_function
+    def np_array_3():
+        a = np.array([1, 2, 3, 4, 5], ndmin=2)
+        return a
+    res = np_array_3()
+    assert res == ([1, 2, 3, 4, 5],)
+
+
+@pytest.mark.skip(reason='Not support graph fallback feature yet')
+def test_np_array_4():
+    """
+    Feature: JIT Fallback
+    Description: Test numpy with ndarray in graph mode.
+    Expectation: No exception.
+    """
+    @ms_function
+    def np_array_4():
+        a = np.array([1, 2, 3], dtype=complex)
+        return a
+    res = np_array_4()
+    assert res == ((1+0j), (2+0j), (3+0j))
+
+
+@pytest.mark.skip(reason='Not support graph fallback feature yet')
+def test_np_dtype_1():
+    """
+    Feature: JIT Fallback
+    Description: Test numpy with dtype in graph mode.
+    Expectation: No exception.
+    """
+    @ms_function
+    def np_dtype_1():
+        t = np.dtype(np.int32)
+        return t
+    res = np_dtype_1()
+    print("res:", res)
+
+
+@pytest.mark.skip(reason='Not support graph fallback feature yet')
+def test_np_dtype_2():
+    """
+    Feature: JIT Fallback
+    Description: Test numpy with dtype in graph mode.
+    Expectation: No exception.
+    """
+    @ms_function
+    def np_dtype_2():
+        t = np.dtype('i4')
+        return t
+    res = np_dtype_2()
+    print("res:", res)
+
+
+@pytest.mark.skip(reason='Not support graph fallback feature yet')
+def test_np_dtype_3():
+    """
+    Feature: JIT Fallback
+    Description: Test numpy with dtype in graph mode.
+    Expectation: No exception.
+    """
+    @ms_function
+    def np_dtype_3():
+        t = np.dtype([('age', np.int8)])
+        return t
+    res = np_dtype_3()
+    print("res:", res)
+
+
+@pytest.mark.skip(reason='Not support graph fallback feature yet')
+def test_np_dtype_4():
+    """
+    Feature: JIT Fallback
+    Description: Test numpy with dtype in graph mode.
+    Expectation: No exception.
+    """
+    @ms_function
+    def np_dtype_4():
+        student = np.dtype([('name', 'S20'), ('age', 'i1'), ('marks', 'f4')])
+        a = np.array([('abc', 21, 50), ('xyz', 18, 75)], dtype=student)
+        return a
+    res = np_dtype_4()
+    print("res:", res)
+
+
+@pytest.mark.skip(reason='Not support graph fallback feature yet')
+def test_np_array_ndim():
+    """
+    Feature: JIT Fallback
+    Description: Test numpy with array ndim in graph mode.
+    Expectation: No exception.
+    """
+    @ms_function
+    def np_array_ndim():
+        a = np.arange(24)
+        return a.ndim
+    res = np_array_ndim()
+    print("res:", res)
+
+
+@pytest.mark.skip(reason='Not support graph fallback feature yet')
+def test_np_array_reshape_1():
+    """
+    Feature: JIT Fallback
+    Description: Test numpy with array reshape in graph mode.
+    Expectation: No exception.
+    """
+    @ms_function
+    def np_array_reshape_1():
+        a = np.array([[1, 2, 3], [4, 5, 6]])
+        b = a.reshape(3, 2)
+        return b.ndim
+    res = np_array_reshape_1()
+    print("res:", res)
+
+
+@pytest.mark.skip(reason='Not support graph fallback feature yet')
+def test_np_array_reshape_2():
+    """
+    Feature: JIT Fallback
+    Description: Test numpy with array reshape in graph mode.
+    Expectation: No exception.
+    """
+    @ms_function
+    def np_array_reshape_2():
+        a = np.array([[1, 2, 3], [4, 5, 6]])
+        a.shape = (3, 2)
+        return a
+    res = np_array_reshape_2()
+    print("res:", res)
+
+
+@pytest.mark.skip(reason='Not support graph fallback feature yet')
+def test_np_array_itemsize():
+    """
+    Feature: JIT Fallback
+    Description: Test numpy with array reshape in graph mode.
+    Expectation: No exception.
+    """
+    @ms_function
+    def np_array_itemsize():
+        a = np.array([1, 2, 3, 4, 5], dtype=np.int8)
+        return a.itemsize
+    res = np_array_itemsize()
+    print("res:", res)
+
+
+@pytest.mark.skip(reason='Not support graph fallback feature yet')
+def test_np_array_flags():
+    """
+    Feature: JIT Fallback
+    Description: Test numpy with array flags in graph mode.
+    Expectation: No exception.
+    """
+    @ms_function
+    def np_array_flags():
+        a = np.array([1, 2, 3, 4, 5])
+        return a.flags
+    res = np_array_flags()
+    print("res:", res)
+
+
+@pytest.mark.skip(reason='Not support graph fallback feature yet')
+def test_np_empty_zeros_ones():
+    """
+    Feature: JIT Fallback
+    Description: Test numpy with array empty, zeros, ones in graph mode.
+    Expectation: No exception.
+    """
+    @ms_function
+    def np_empty_zeros_ones():
+        x = np.empty([3, 2], dtype=np.int)
+        y = np.zeros(x.shape, dtype=np.int)
+        z = np.ones(x.shape, dtype=np.int)
+        return y + z
+    res = np_empty_zeros_ones()
+    print("res:", res)
+
+
+@pytest.mark.skip(reason='Not support graph fallback feature yet')
+def test_np_asarray_list():
+    """
+    Feature: JIT Fallback
+    Description: Test numpy with list to array in graph mode.
+    Expectation: No exception.
+    """
+    @ms_function
+    def np_asarray_list():
+        x = [1, 2, 3]
+        y = np.asarray(x)
+        return y
+    res = np_asarray_list()
+    print("res:", res)
+
+
+@pytest.mark.skip(reason='Not support graph fallback feature yet')
+def test_np_asarray_tuple():
+    """
+    Feature: JIT Fallback
+    Description: Test numpy with tuple to array in graph mode.
+    Expectation: No exception.
+    """
+    @ms_function
+    def np_asarray_tuple():
+        x = (1, 2, 3)
+        y = np.asarray(x)
+        return y
+    res = np_asarray_tuple()
+    print("res:", res)
+
+
+@pytest.mark.skip(reason='Not support graph fallback feature yet')
+def test_np_asarray_tuple_list():
+    """
+    Feature: JIT Fallback
+    Description: Test numpy with tuple list to array in graph mode.
+    Expectation: No exception.
+    """
+    @ms_function
+    def np_asarray_tuple_list():
+        x = [(1, 2, 3), (4, 5)]
+        y = np.asarray(x)
+        return y
+    res = np_asarray_tuple_list()
+    print("res:", res)
+
+
+@pytest.mark.skip(reason='Not support graph fallback feature yet')
+def test_np_frombuffer():
+    """
+    Feature: JIT Fallback
+    Description: Test numpy with frombuffer in graph mode.
+    Expectation: No exception.
+    """
+    @ms_function
+    def np_frombuffer():
+        s = b'Hello World'
+        a = np.frombuffer(s, dtype='S1')
+        return a
+    res = np_frombuffer()
+    print("res:", res)
+
+
+@pytest.mark.skip(reason='Not support graph fallback feature yet')
+def test_np_fromiter():
+    """
+    Feature: JIT Fallback
+    Description: Test numpy with fromiter in graph mode.
+    Expectation: No exception.
+    """
+    @ms_function
+    def np_fromiter():
+        l = range(5)
+        it = iter(l)
+        x = np.fromiter(it, dtype=float)
+        return x
+    res = np_fromiter()
+    print("res:", res)
+
+
+@pytest.mark.skip(reason='Not support graph fallback feature yet')
+def test_np_arange():
+    """
+    Feature: JIT Fallback
+    Description: Test numpy with arange in graph mode.
+    Expectation: No exception.
+    """
+    @ms_function
+    def np_arange():
+        x = np.arange(5, dtype=float)
+        y = np.arange(10, 20, 2)
+        return x, y
+    res1, res2 = np_arange()
+    print("res1:", res1)
+    print("res2:", res2)
+
+
+@pytest.mark.skip(reason='Not support graph fallback feature yet')
+def test_np_linspace():
+    """
+    Feature: JIT Fallback
+    Description: Test numpy with linspace in graph mode.
+    Expectation: No exception.
+    """
+    @ms_function
+    def np_linspace():
+        a = np.linspace(1, 10, 10)
+        b = np.linspace(1, 1, 10)
+        c = np.linspace(10, 20, 5, endpoint=False)
+        d = np.linspace(10, 20, 5, endpoint=True)
+        e = np.linspace(1, 10, 10, retstep=True)
+        f = np.linspace(1, 10, 10).reshape([10, 1])
+        return a, b, c, d, e, f
+    a, b, c, d, e, f = np_linspace()
+    print("a:", a)
+    print("b:", b)
+    print("c:", c)
+    print("d:", d)
+    print("e:", e)
+    print("f:", f)
+
+
+@pytest.mark.skip(reason='Not support graph fallback feature yet')
+def test_np_logspace():
+    """
+    Feature: JIT Fallback
+    Description: Test numpy with logspace in graph mode.
+    Expectation: No exception.
+    """
+    @ms_function
+    def np_logspace():
+        a = np.logspace(1.0, 2.0, num=10)
+        b = np.logspace(0, 9, 10, base=2)
+        return a, b
+    a, b = np_logspace()
+    print("a:", a)
+    print("b:", b)
+
+
+@pytest.mark.skip(reason='Not support graph fallback feature yet')
+def test_np_arange_slice_1():
+    """
+    Feature: JIT Fallback
+    Description: Test numpy with arange slice in graph mode.
+    Expectation: No exception.
+    """
+    @ms_function
+    def np_arange_slice_1():
+        x = np.arange(10)
+        index = slice(2, 7, 2)
+        a = x[index]
+        b = x[2:7:2]
+        c = x[5]
+        d = x[2:]
+        e = x[2:5]
+        return a, b, c, d, e
+    a, b, c, d, e = np_arange_slice_1()
+    print("a:", a)
+    print("b:", b)
+    print("c:", c)
+    print("d:", d)
+    print("e:", e)
+
+
+@pytest.mark.skip(reason='Not support graph fallback feature yet')
+def test_np_arange_slice_2():
+    """
+    Feature: JIT Fallback
+    Description: Test numpy with arange slice in graph mode.
+    Expectation: No exception.
+    """
+    @ms_function
+    def np_arange_slice_2():
+        x = np.array([[1, 2, 3], [3, 4, 5], [4, 5, 6]])
+        a = x[1:]
+        b = x[..., 1]
+        c = x[1, ...]
+        d = x[..., 1:]
+        return a, b, c, d
+    a, b, c, d = np_arange_slice_2()
+    print("a:", a)
+    print("b:", b)
+    print("c:", c)
+    print("d:", d)
+
+
+@pytest.mark.skip(reason='Not support graph fallback feature yet')
+def test_np_array_advanced_index_1():
+    """
+    Feature: JIT Fallback
+    Description: Test numpy with array advanced index in graph mode.
+    Expectation: No exception.
+    """
+    @ms_function
+    def np_array_advanced_index_1():
+        x = np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8], [9, 10, 11]])
+        a = x[[0, 1, 2], [0, 1, 0]]
+        rows = np.array([[0, 0], [3, 3]])
+        cols = np.array([[0, 2], [0, 2]])
+        b = x[rows, cols]
+        c = x[1:3, 1:3]
+        d = x[1:3, [1, 2]]
+        e = x[..., 1:]
+        return a, b, c, d, e
+    a, b, c, d, e = np_array_advanced_index_1()
+    print("a:", a)
+    print("b:", b)
+    print("c:", c)
+    print("d:", d)
+    print("e:", e)
+
+
+@pytest.mark.skip(reason='Not support graph fallback feature yet')
+def test_np_array_advanced_index_2():
+    """
+    Feature: JIT Fallback
+    Description: Test numpy with array advanced index in graph mode.
+    Expectation: No exception.
+    """
+    @ms_function
+    def np_array_advanced_index_2():
+        x = np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8], [9, 10, 11]])
+        y = np.array([np.nan, 1, 2, np.nan, 3, 4, 5])
+        z = np.array([1, 2 + 6j, 5, 3.5 + 5j])
+        a = x[x > 5]
+        b = y[~np.isnan(y)]
+        c = z[np.iscomplex(z)]
+        return a, b, c
+    a, b, c = np_array_advanced_index_2()
+    print("a:", a)
+    print("b:", b)
+    print("c:", c)
+
+
+@pytest.mark.skip(reason='Not support graph fallback feature yet')
+def test_np_array_advanced_index_3():
+    """
+    Feature: JIT Fallback
+    Description: Test numpy with array advanced index in graph mode.
+    Expectation: No exception.
+    """
+    @ms_function
+    def np_array_advanced_index_3():
+        x = np.arange(32).reshape((8, 4))
+        a = x[[4, 2, 1, 7]]
+        y = np.arange(32).reshape((8, 4))
+        b = y[[-4, -2, -1, -7]]
+        z = np.arange(32).reshape((8, 4))
+        c = z[np.ix_([1, 5, 7, 2], [0, 3, 1, 2])]
+        return a, b, c
+    a, b, c = np_array_advanced_index_3()
+    print("a:", a)
+    print("b:", b)
+    print("c:", c)