improve the way passing ags of partial

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

@@ -915,7 +915,7 @@ AnfNodePtr Parser::ParseTuple(const FunctionBlockPtr &block, const py::object &n
 AnfNodePtr Parser::ParseList(const FunctionBlockPtr &block, const py::object &node) {
   MS_LOG(DEBUG) << "Process ast List";
   MS_EXCEPTION_IF_NULL(block);
-  py::tuple elts = python_adapter::GetPyObjAttr(node, "elts");
+  py::list elts = python_adapter::GetPyObjAttr(node, "elts");
   if (elts.size() == 0) {
     auto empty_list = std::vector<ValuePtr>();
     return NewValueNode(std::make_shared<ValueList>(empty_list));

mindspore/core/ir/func_graph_extends.cc

@@ -126,6 +126,7 @@ void FuncGraph::GenerateKwParams(const FuncGraphPtr &specialized_graph,
   std::vector<AnfNodePtr> kwarg_keys_tuple_nodes = {NewValueNode(prim::kPrimMakeTuple)};
   std::vector<AnfNodePtr> kwarg_values_tuple_nodes = {NewValueNode(prim::kPrimMakeTuple)};
 
+  std::set<AnfNodePtr> key_ward_para_nodes;
   for (const auto &kwarg : kwarg_list) {
     MS_EXCEPTION_IF_NULL(kwarg);
     std::string kw_param_name = kwarg->get_key();
@@ -146,7 +147,7 @@ void FuncGraph::GenerateKwParams(const FuncGraphPtr &specialized_graph,
                                                  return param != nullptr && param->name() == param_name;
                                                });
         if (find_kw_arg_in_list) {
-          MS_LOG(EXCEPTION) << "Multiply values for keyword argument:" << kw_param_name;
+          MS_EXCEPTION(TypeError) << "Multiply values for keyword argument: " << kw_param_name;
         }
         p->set_name(param_name);
         p->debug_info()->set_name(param_name);
@@ -159,12 +160,14 @@ void FuncGraph::GenerateKwParams(const FuncGraphPtr &specialized_graph,
     } else {
       auto node_itr = std::find(specialized_parameter_list->begin(), specialized_parameter_list->end(), param_node);
       // multiply values found given for parameter
-      if (node_itr != specialized_parameter_list->end()) {
-        MS_LOG(EXCEPTION) << "Multiply values for specific argument:" << kw_param_name;
+      if (node_itr != specialized_parameter_list->end() &&
+          key_ward_para_nodes.find(param_node) == key_ward_para_nodes.end()) {
+        MS_EXCEPTION(TypeError) << "Multiply values for specific argument: " << kw_param_name;
       } else {
         specialized_parameter_list->push_back(param_node);
         auto extract_node = specialized_graph->NewCNode(
           {NewValueNode(prim::kPrimExtractKeywordArg), NewValueNode(kw_param_name), param_node});
+        key_ward_para_nodes.insert(param_node);
         (void)repl_nodes->emplace(param_node, extract_node);
       }
     }
@@ -199,10 +202,7 @@ bool FuncGraph::NeedGenerate(const std::vector<abstract::AbstractKeywordArgPtr>
   }
 
   // if the graph is generated for specific input, do not need to generate again
-  if (is_generated()) {
-    return false;
-  }
-  return true;
+  return !is_generated();
 }
 
 void FuncGraph::GenerateDefaultValue(const FuncGraphPtr &specialized_graph,
@@ -232,20 +232,23 @@ void FuncGraph::GenerateDefaultValue(const FuncGraphPtr &specialized_graph,
 
 FuncGraphPtr FuncGraph::GenerateGraph(const AbstractBasePtrList &args_spec_list) {
   std::vector<abstract::AbstractKeywordArgPtr> kwarg_list;
+  std::vector<size_t> pos_arg_indexes;
   size_t arguments_count = args_spec_list.size();
-  for (const auto &arg : args_spec_list) {
-    // if it is a keyword argument
-    MS_EXCEPTION_IF_NULL(arg);
-    if (arg->isa<abstract::AbstractKeywordArg>()) {
-      kwarg_list.push_back(dyn_cast<abstract::AbstractKeywordArg>(arg));
+  for (size_t i = 0; i < arguments_count - hyper_param_count_; i++) {
+    MS_EXCEPTION_IF_NULL(args_spec_list[i]);
+    if (args_spec_list[i]->isa<abstract::AbstractKeywordArg>()) {
+      kwarg_list.push_back(args_spec_list[i]->cast<abstract::AbstractKeywordArgPtr>());
+    } else {
+      pos_arg_indexes.push_back(i);
     }
   }
+
   if (!NeedGenerate(kwarg_list)) {
     return shared_from_base<FuncGraph>();
   }
   FuncGraphPtr specialized_graph = BasicClone(shared_from_base<FuncGraph>());
   size_t kwarg_count = kwarg_list.size();
-  int pos_args_input_count = SizeToInt(arguments_count - kwarg_count - hyper_param_count());
+  int pos_args_input_count = SizeToInt(arguments_count - kwarg_count - hyper_param_count_);
   int pos_args_count = std::min(pos_args_input_count, this->GetPositionalArgsCount());
   int variable_args_count = pos_args_input_count - pos_args_count;
   std::vector<AnfNodePtr> specialized_parameter_list;
@@ -265,8 +268,14 @@ FuncGraphPtr FuncGraph::GenerateGraph(const AbstractBasePtrList &args_spec_list)
   // append hyper parameter to specialized_parameter_list
   MS_EXCEPTION_IF_NULL(specialized_graph);
   auto params = specialized_graph->parameters();
-  (void)std::transform(params.end() - SizeToInt(hyper_param_count()), params.end(),
-                       std::back_inserter(specialized_parameter_list), [](const AnfNodePtr &node) { return node; });
+  specialized_parameter_list.insert(specialized_parameter_list.end(), params.end() - SizeToInt(hyper_param_count_),
+                                    params.end());
+  std::vector<AnfNodePtr> specialized_parameter_list_update(specialized_parameter_list.begin() + pos_arg_indexes.size(),
+                                                            specialized_parameter_list.end());
+  for (size_t i = 0; i < pos_arg_indexes.size(); i++) {
+    specialized_parameter_list_update.insert(specialized_parameter_list_update.begin() + pos_arg_indexes[i],
+                                             specialized_parameter_list[i]);
+  }
 
   std::shared_ptr<mindspore::FuncGraphManager> manager = mindspore::Manage(specialized_graph, false);
   auto tr = manager->Transact();
@@ -275,7 +284,7 @@ FuncGraphPtr FuncGraph::GenerateGraph(const AbstractBasePtrList &args_spec_list)
                   << node_pair.second->DebugString();
     (void)tr.Replace(node_pair.first, node_pair.second);
   }
-  tr.SetParameters(specialized_graph, specialized_parameter_list);
+  tr.SetParameters(specialized_graph, specialized_parameter_list_update);
   tr.Commit();
   specialized_graph->set_has_kwarg(false);
   specialized_graph->set_has_vararg(false);

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

@@ -0,0 +1,223 @@
+# 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 partial"""
+from functools import partial
+
+import numpy as np
+import pytest
+
+from mindspore import nn, Tensor, context
+
+context.set_context(mode=context.GRAPH_MODE)
+
+def test_partial_pos_arg():
+    class Net(nn.Cell):
+        def __init__(self):
+            super(Net, self).__init__()
+
+        def show(self, x, y, z):
+            return x, y, z
+
+        def construct(self, x, y, z):
+            f = partial(self.show, x)
+            ret = f(y, z)
+            return ret
+
+    x = Tensor(np.arange(3).reshape((3,)).astype(np.float32))
+    y = Tensor(np.arange(3 * 4).reshape((3, 4)).astype(np.float32))
+    z = Tensor(np.arange(3 * 4 * 5).reshape((3, 4, 5)).astype(np.float32))
+    net = Net()
+    net(x, y, z)
+
+def test_partial_key_ward_arg():
+    class Net(nn.Cell):
+        def __init__(self):
+            super(Net, self).__init__()
+
+        def show(self, x, y, z):
+            return x, y, z
+
+        def construct(self, x, y, z):
+            f = partial(self.show, x=x)
+            ret = f(y=y, z=z)
+            return ret
+
+    x = Tensor(np.arange(3).reshape((3,)).astype(np.float32))
+    y = Tensor(np.arange(3 * 4).reshape((3, 4)).astype(np.float32))
+    z = Tensor(np.arange(3 * 4 * 5).reshape((3, 4, 5)).astype(np.float32))
+    net = Net()
+    net(x, y, z)
+
+def test_partial_key_ward_arg_update():
+    class Net(nn.Cell):
+        def __init__(self):
+            super(Net, self).__init__()
+
+        def show(self, x, y, z):
+            return x, y, z
+
+        def construct(self, x, y, z):
+            f = partial(self.show, x=x, y=y)
+            ret = f(y=y, z=z)
+            return ret
+
+    x = Tensor(np.arange(3).reshape((3,)).astype(np.float32))
+    y = Tensor(np.arange(3 * 4).reshape((3, 4)).astype(np.float32))
+    z = Tensor(np.arange(3 * 4 * 5).reshape((3, 4, 5)).astype(np.float32))
+    net = Net()
+    net(x, y, z)
+
+
+def test_partial_key_ward_arg_and_pos_arg():
+    class Net(nn.Cell):
+        def __init__(self):
+            super(Net, self).__init__()
+
+        def show(self, x, y, z):
+            return x, y, z
+
+        def construct(self, x, y, z):
+            f = partial(self.show, y=y)
+            ret = f(2, z=z)
+            return ret
+
+    x = Tensor(np.arange(3).reshape((3,)).astype(np.float32))
+    y = Tensor(np.arange(3 * 4).reshape((3, 4)).astype(np.float32))
+    z = Tensor(np.arange(3 * 4 * 5).reshape((3, 4, 5)).astype(np.float32))
+    net = Net()
+    net(x, y, z)
+
+
+def test_partial_pos_arg_const():
+    class Net(nn.Cell):
+        def __init__(self):
+            super(Net, self).__init__()
+
+        def show(self, x, y, z):
+            return x, y, z
+
+        def construct(self):
+            f = partial(self.show, 1)
+            ret = f(2, 3)
+            return ret
+
+    net = Net()
+    assert net() == (1, 2, 3)
+
+def test_partial_key_ward_arg_const():
+    class Net(nn.Cell):
+        def __init__(self):
+            super(Net, self).__init__()
+
+        def show(self, x, y, z):
+            return x, y, z
+
+        def construct(self):
+            f = partial(self.show, x=1)
+            ret = f(y=2, z=3)
+            return ret
+
+    net = Net()
+    assert net() == (1, 2, 3)
+
+def test_partial_key_ward_arg_update_const():
+    class Net(nn.Cell):
+        def __init__(self):
+            super(Net, self).__init__()
+
+        def show(self, x, y, z):
+            return x, y, z
+
+        def construct(self):
+            f = partial(self.show, x=1, y=2)
+            ret = f(y=3, z=4)
+            return ret
+
+    net = Net()
+    assert net() == (1, 3, 4)
+
+
+def test_partial_key_ward_arg_and_pos_arg_const():
+    class Net(nn.Cell):
+        def __init__(self):
+            super(Net, self).__init__()
+
+        def show(self, x, y, z):
+            return x, y, z
+
+        def construct(self):
+            f = partial(self.show, y=2)
+            ret = f(1, z=3)
+            return ret
+
+    net = Net()
+    assert net() == (1, 2, 3)
+
+
+def test_partial_key_ward_arg_and_pos_arg_const_multi_assign_x():
+    class Net(nn.Cell):
+        def __init__(self):
+            super(Net, self).__init__()
+
+        def show(self, x, y, z):
+            return x, y, z
+
+        def construct(self):
+            f = partial(self.show, x=1)
+            ret = f(1, 2, 3)
+            return ret
+
+    net = Net()
+    with pytest.raises(TypeError) as ex:
+        net()
+    assert "Multiply values for specific argument: x" in str(ex.value)
+
+
+def test_partial_key_ward_arg_and_pos_arg_const_multi_assign_y():
+    class Net(nn.Cell):
+        def __init__(self):
+            super(Net, self).__init__()
+
+        def show(self, x, y, z):
+            return x, y, z
+
+        def construct(self):
+            f = partial(self.show, y=2)
+            ret = f(1, 2, z=3)
+            return ret
+
+    net = Net()
+    with pytest.raises(TypeError) as ex:
+        net()
+    assert "Multiply values for specific argument: y" in str(ex.value)
+
+
+def test_partial_key_ward_arg_and_pos_arg_const_multi_assign_z():
+    class Net(nn.Cell):
+        def __init__(self):
+            super(Net, self).__init__()
+
+        def show(self, x, y, z):
+            return x, y, z
+
+        def construct(self):
+            f = partial(self.show, z=1)
+            ret = f(1, 2, 3)
+            return ret
+
+    net = Net()
+    with pytest.raises(TypeError) as ex:
+        net()
+    assert "Multiply values for specific argument: z" in str(ex.value)