Enable multi-dimensional list value assignment

mindspore/ccsrc/pipeline/jit/parse/parse.cc

@@ -1501,7 +1501,7 @@ void Parser::HandleAssignSubscript(const FunctionBlockPtr &block, const py::obje
   AnfNodePtr slice_node = ParseExprNode(block, slice_obj);
   CNodePtr setitem_app = block->func_graph()->NewCNode({op_setitem, value_node, slice_node, assigned_node});
   // getitem apply should return the sequence data structure itself
-  std::string var_name = "";
+  std::string var_name;
   if (ast_->IsClassMember(value_obj)) {
     std::string attr_name = value_obj.attr("attr").cast<std::string>();
     var_name = "self." + attr_name;
@@ -1515,9 +1515,18 @@ void Parser::HandleAssignSubscript(const FunctionBlockPtr &block, const py::obje
                               << py::str(obj).cast<std::string>() << "' with type '"
                               << py::str(obj_type).cast<std::string>() << "'.";
     }
-  } else {
-    var_name = value_obj.attr("id").cast<std::string>();
+    block->WriteVariable(var_name, setitem_app);
+    return;
+  }
+  if (AstSubType(py::cast<int32_t>(ast_->CallParserObjMethod(PYTHON_PARSE_GET_AST_TYPE, value_obj))) ==
+      AST_SUB_TYPE_SUBSCRIPT) {
+    HandleAssignSubscript(block, value_obj, setitem_app);
+    return;
+  }
+  if (!py::hasattr(value_obj, "id")) {
+    MS_EXCEPTION(TypeError) << "Attribute id not found in " << py::str(value_obj).cast<std::string>();
   }
+  var_name = value_obj.attr("id").cast<std::string>();
   block->WriteVariable(var_name, setitem_app);
 }
 

tests/ut/python/ops/test_tensor_slice.py

@@ -672,14 +672,14 @@ def test_tensor_assign_bool_index():
     with pytest.raises(ValueError):
         net2(Ta, u_tensor_error)
     net3 = TensorAssignWithBoolTensorIndexError()
-    with pytest.raises(AttributeError):
+    with pytest.raises(IndexError):
         net3(Ta, Tb, Tc, u_tensor)
-    with pytest.raises(AttributeError):
+    with pytest.raises(IndexError):
         net3(Ta, Tb, Tc, Tensor(u_scalar, mstype.int32))
     net4 = TensorAssignWithBoolTensorIndex2Error()
-    with pytest.raises(AttributeError):
+    with pytest.raises(IndexError):
         net4(Ta, u_tensor)
-    with pytest.raises(AttributeError):
+    with pytest.raises(IndexError):
         net4(Ta, Tensor(u_scalar, mstype.int32))
 
 

tests/ut/python/pipeline/parse/test_sequence_assign.py

@@ -0,0 +1,116 @@
+# 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 enumerate"""
+import mindspore.nn as nn
+from mindspore import Tensor
+from mindspore import context
+
+context.set_context(mode=context.GRAPH_MODE)
+
+
+def test_list_index_1D():
+    class Net(nn.Cell):
+        def __init__(self):
+            super(Net, self).__init__()
+
+        def construct(self):
+            list_ = [[1], [2, 2], [3, 3, 3]]
+            list_[0] = [100]
+            return list_
+
+    net = Net()
+    out = net()
+    assert out[0] == [100]
+    assert out[1] == [2, 2]
+    assert out[2] == [3, 3, 3]
+
+
+def test_list_index_2D():
+    class Net(nn.Cell):
+        def __init__(self):
+            super(Net, self).__init__()
+
+        def construct(self):
+            list_ = [[1], [2, 2], [3, 3, 3]]
+            list_[1][0] = 200
+            list_[1][1] = 201
+            return list_
+
+    net = Net()
+    out = net()
+    assert out[0] == [1]
+    assert out[1] == [200, 201]
+    assert out[2] == [3, 3, 3]
+
+
+def test_list_index_3D():
+    class Net(nn.Cell):
+        def __init__(self):
+            super(Net, self).__init__()
+
+        def construct(self):
+            list_ = [[1], [2, 2], [[3, 3, 3]]]
+            list_[2][0][0] = 300
+            list_[2][0][1] = 301
+            list_[2][0][2] = 302
+            return list_
+
+    net = Net()
+    out = net()
+    assert out[0] == [1]
+    assert out[1] == [2, 2]
+    assert out[2] == [[300, 301, 302]]
+
+
+def test_list_index_1D_parameter():
+    class Net(nn.Cell):
+        def __init__(self):
+            super(Net, self).__init__()
+
+        def construct(self, x):
+            list_ = [x]
+            list_[0] = 100
+            return list_
+
+    net = Net()
+    net(Tensor(0))
+
+
+def test_list_index_2D_parameter():
+    class Net(nn.Cell):
+        def __init__(self):
+            super(Net, self).__init__()
+
+        def construct(self, x):
+            list_ = [[x, x]]
+            list_[0][0] = 100
+            return list_
+
+    net = Net()
+    net(Tensor(0))
+
+
+def test_list_index_3D_parameter():
+    class Net(nn.Cell):
+        def __init__(self):
+            super(Net, self).__init__()
+
+        def construct(self, x):
+            list_ = [[[x, x]]]
+            list_[0][0][0] = 100
+            return list_
+
+    net = Net()
+    net(Tensor(0))