use select implement tensor in list

mindspore/ops/composite/multitype_ops/_compile_utils.py

@@ -618,8 +618,8 @@ def tensor_setitem_by_ellipsis_with_tensor(data, index, value):
 
 def tensor_in_sequence(x, y):
     """Assigns whether a sequence contains the given tensor"""
+    result = const_utils.scalar_to_tensor(False)
     for i in y:
         if isinstance(i, mstype.tensor) and x.shape == i.shape and x.dtype == i.dtype:
-            if F.equal(x, i).all():
-                return const_utils.scalar_to_tensor(True)
-    return const_utils.scalar_to_tensor(False)
+            result = F.logical_or(F.equal(x, i).all(), result)
+    return result

tests/st/control/test_tensor_in_list.py

@@ -0,0 +1,58 @@
+# Copyright 2020 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_tensor_in_list """
+import pytest
+from mindspore import nn, Tensor, context
+from mindspore import dtype as mstype
+
+
+def setup_module():
+    context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
+
+
+class Net(nn.Cell):
+    def __init__(self):
+        super(Net, self).__init__()
+        self.list = [Tensor([1], mstype.int32), Tensor([2], mstype.int32), Tensor([3], mstype.int32)]
+
+    def construct(self, c):
+        if c in self.list:
+            out = c + c
+        else:
+            out = c + 0
+        return out
+
+
+@pytest.mark.level0
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.env_onecard
+def test_tensor_in_list():
+    net = Net()
+    output = net(Tensor([1], mstype.int32))
+    expect = Tensor([2], mstype.int32)
+    assert output == expect
+
+    output = net(Tensor([2], mstype.int32))
+    expect = Tensor([4], mstype.int32)
+    assert output == expect
+
+    output = net(Tensor([3], mstype.int32))
+    expect = Tensor([6], mstype.int32)
+    assert output == expect
+
+    output = net(Tensor([4], mstype.int32))
+    expect = Tensor([4], mstype.int32)
+    assert output == expect