!2996 Add test case for switch_layer

Merge pull request !2996 from fanglei/add_testcase_switchlayer

mindspore/ccsrc/vm/transform.cc

@@ -199,7 +199,6 @@ bool IsSubGraph(const AnfNodePtr &node) {
     }
 
     AnfNodePtr fn = inputs[0];
-    MS_EXCEPTION_IF_NULL(fn);
     if (!IsValueNode<Primitive>(fn)) {
       return false;
     }
@@ -239,7 +238,6 @@ bool CompileGraph::IsCut(const AnfNodePtr &node) {
     }
 
     AnfNodePtr fn = inputs[0];
-    MS_EXCEPTION_IF_NULL(fn);
     if (IsValueNode<FuncGraph>(fn)) {
       auto fg = GetValueNode<FuncGraphPtr>(fn);
       if (fg->has_attr(FUNC_GRAPH_ATTR_GRAPH_KERNEL)) {

mindspore/ccsrc/vm/vm.cc

@@ -503,7 +503,8 @@ void FinalVM::InstSwitchLayer(const VectorRef &args) {
     idx_value += size;
   }
   if (idx_value < 0 || idx_value >= size) {
-    MS_LOG(EXCEPTION) << __FUNCTION__ << " given index " << idx_value << " out of range.";
+    MS_LOG(EXCEPTION) << __FUNCTION__ << " given index " << idx_value << " out of range. Please make sure the value "
+                      << "of index in [" << -size << ", " << size << "), and the type is int32.";
   }
   Push(branches[idx_value]);
   MS_LOG(DEBUG) << "End";

tests/st/control/test_switch_layer.py

+# 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
+from mindspore import Tensor, nn
+from mindspore.common import dtype as mstype
+
+
+class CaseNet(nn.Cell):
+    def __init__(self):
+        super(CaseNet, self).__init__()
+        self.conv = nn.Conv2d(1, 3, 3)
+        self.relu = nn.ReLU()
+        self.softmax = nn.Softmax()
+        self.layers1 = (self.relu, self.softmax)
+        self.layers2 = (self.conv, self.relu)
+
+    def construct(self, x, index1, index2):
+        x = self.layers1[index1](x)
+        x = self.layers2[index2](x)
+        return x
+
+
+@pytest.mark.level0
+@pytest.mark.platform_x86_gpu_training
+@pytest.mark.env_onecard
+def test_switch_layer():
+    context.set_context(mode=context.GRAPH_MODE)
+    net = CaseNet()
+    data = Tensor(np.ones((1, 1, 224, 224)), mstype.float32)
+    idx = Tensor(0, mstype.int32)
+    idx2 = Tensor(-1, mstype.int32)
+    value = net(data, idx, idx2)
+    relu = nn.ReLU()
+    true_value = relu(data)
+    ret = np.allclose(value.asnumpy(), true_value.asnumpy())
+    assert ret
+
+    idx3 = Tensor(3, mstype.int32)
+    with pytest.raises(RuntimeError):
+        value = net(data, idx3, idx2)