!7238 [DynamicShape] Add dyanmic shape CI test case

Merge pull request !7238 from caifubi/dynamic_shape

mindspore/ccsrc/backend/session/executor.cc

@@ -39,6 +39,13 @@ void UpdateOutputTensors(const VectorRef *outputs,
         auto &output_index = iter->second.second;
         auto address = AnfAlgo::GetMutableOutputAddr(node, output_index);
         tensor->set_device_address(address);
+
+        if (AnfAlgo::IsDynamicShape(node)) {
+          auto updated_shape = AnfAlgo::GetOutputInferShape(node, output_index);
+          ShapeVector int_shape;
+          std::transform(updated_shape.begin(), updated_shape.end(), std::back_inserter(int_shape), SizeToInt);
+          tensor->set_shape(int_shape);
+        }
       }
       if (tensor->NeedSyncDeviceToHostImmediately()) {
         tensor->data_sync(false);

tests/st/ops/ascend/dynamic_shape/test_unique.py

@@ -0,0 +1,44 @@
+# 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.
+# ============================================================================
+import numpy as np
+import pytest
+import mindspore.context as context
+import mindspore.nn as nn
+from mindspore import Tensor
+import mindspore.common.dtype as mstype
+from mindspore.ops import operations as P
+
+context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
+
+class Net(nn.Cell):
+    def __init__(self):
+        super(Net, self).__init__()
+        self.unique = P.Unique()
+
+    def construct(self, x):
+        return self.unique(x)
+
+@pytest.mark.level0
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.env_onecard
+def test_unqiue():
+    x = Tensor(np.array([1, 1, 2, 2, 3, 3]), mstype.int32)
+    unique = Net()
+    output = unique(x)
+    expect1 = np.array([1, 2, 3])
+    expect2 = np.array([0, 0, 1, 1, 2, 2])
+    assert (output[0].asnumpy() == expect1).all()
+    assert (output[1].asnumpy() == expect2).all()