!3048 support use valuelist or valuetuple of primitives

Merge pull request !3048 from amongo/SupportPrimitiveList

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

@@ -168,15 +168,15 @@ bool ResolveObjectToNode(const FuncGraphPtr &func_graph, const py::object &obj,
   return true;
 }
 
-bool IsAllGraphInValueSequence(const std::vector<ValuePtr> &value_vec) {
+bool IsAllFuncInValueSequence(const std::vector<ValuePtr> &value_vec) {
   for (auto &elem : value_vec) {
     if (elem->isa<ValueTuple>() || elem->isa<ValueList>()) {
       const auto &vec = GetValue<std::vector<ValuePtr>>(elem);
-      auto is_graph = IsAllGraphInValueSequence(vec);
+      auto is_graph = IsAllFuncInValueSequence(vec);
       if (!is_graph) {
         return false;
       }
-    } else if (!elem->isa<FuncGraph>()) {
+    } else if (!elem->isa<FuncGraph>() && !elem->isa<Primitive>()) {
       return false;
     }
   }
@@ -196,6 +196,8 @@ AnfNodePtr TransformToMakeTupleNodes(const FuncGraphManagerPtr &manager, const F
       FuncGraphPtr new_fg = elem->cast<FuncGraphPtr>();
       manager->AddFuncGraph(new_fg);
       node = NewValueNode(new_fg);
+    } else if (elem->isa<Primitive>()) {
+      node = NewValueNode(elem);
     } else {
       MS_LOG(EXCEPTION) << "TransformToMakeTupleNodes error, expect funcgraph, got " << elem->ToString();
     }
@@ -205,19 +207,21 @@ AnfNodePtr TransformToMakeTupleNodes(const FuncGraphManagerPtr &manager, const F
   return cnode;
 }
 
-// transform the ValueTuple or ValueList of graph node to make tuple of const graph node
+// transform the ValueTuple or ValueList of graph/primitve node to make tuple of const graph/primitve node
-bool TransformVectorGraphValueNode(const FuncGraphManagerPtr &manager, const FuncGraphPtr &func_graph,
+bool TransformVectorFuncValueNode(const FuncGraphManagerPtr &manager, const FuncGraphPtr &func_graph,
-                                   const ValueNodePtr &value_node, AnfNodePtr *const transformed) {
+                                  const ValueNodePtr &value_node, AnfNodePtr *const transformed) {
   MS_EXCEPTION_IF_NULL(value_node);
   const auto &value_vec = GetValue<std::vector<ValuePtr>>(value_node->value());
-  if (!IsAllGraphInValueSequence(value_vec)) {
+  if (!IsAllFuncInValueSequence(value_vec)) {
     return false;
   }
 
-  // The celllist or ordered_cell will be parsed as valuetuple of const graph in it,
+  // (1) The celllist or ordered_cell will be parsed as valuetuple of const graph in it,
   // So if has graph in list, try to replace the node with make tuple of graph value node.
   // we do this because the graphmanger won't investigate the graph inside valuetuple,
-  // change the vector of graph to be make_tuple of graph value node
+  // change the vector of graph to be make_tuple of graph value node.
+  // (2) the primitve valuetuple or valuelist may encounter to abstract error, make it all
+  // independent nodes.
   auto node_tuple_graphs = TransformToMakeTupleNodes(manager, func_graph, value_vec);
   // replace the ret ptr to be make tuple of graph value node
   *transformed = node_tuple_graphs;
@@ -251,8 +255,8 @@ AnfNodePtr ResolveSymbol(const FuncGraphManagerPtr &manager, const NameSpacePtr
 
   // if the constant node is constant of vector of graph ,add graph to manager
   if (IsValueNode<ValueTuple>(resolved_node) || IsValueNode<ValueList>(resolved_node)) {
-    (void)TransformVectorGraphValueNode(manager, node->func_graph(), resolved_node->cast<ValueNodePtr>(),
+    (void)TransformVectorFuncValueNode(manager, node->func_graph(), resolved_node->cast<ValueNodePtr>(),
-                                        &resolved_node);
+                                       &resolved_node);
   }
 
   TraceManager::EndTrace();

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

@@ -17,6 +17,9 @@ from dataclasses import dataclass
 import numpy as np
 
 from mindspore import Tensor, Model, context
+from mindspore.ops import operations as P
+from mindspore.ops import composite as C
+from mindspore.ops import functional as F
 from mindspore.nn import Cell
 from mindspore.nn import ReLU
 from ...ut_filter import non_graph_engine
@@ -66,3 +69,58 @@ def function_access_base(number):
 def test_access_0040():
     """ test_access_0040 """
     function_access_base(2)
+
+
+class OpSeqNet(Cell):
+    def __init__(self, loop_count=1):
+        super().__init__()
+        self.loop_count = loop_count
+        self.op_seq = (P.Sqrt(), P.Reciprocal(), P.Square())
+
+    def construct(self, x):
+        t = x
+        for op in self.op_seq:
+            t = op(t)
+        return t
+
+
+def test_op_seq_test():
+    context.set_context(mode=context.GRAPH_MODE)
+    net = OpSeqNet()
+    input_np = np.random.randn(2, 3, 4, 5).astype(np.float32)
+    input_me = Tensor(input_np)
+    net(input_me)
+
+
+_grad_fusion = C.MultitypeFuncGraph("grad_fushion")
+
+
+@_grad_fusion.register("Tensor", "Function")
+def tensor_grad_scale(x, op):
+    return op(x)
+
+
+class AllReduceTest(Cell):
+    def __init__(self, loop_count=1):
+        super().__init__()
+        self.op_list = ()
+        self.fushion_flag = [0, 1, 1, 0, 1, 0]
+        for i in self.fushion_flag:
+            op = P.AllReduce().add_prim_attr('fusion', i)
+            self.op_list = self.op_list + (op,)
+        self.hyper_map = C.HyperMap()
+
+    def construct(self, x):
+        ret = ()
+        for _ in self.fushion_flag:
+            ret = ret + (x,)
+        fushion_res = self.hyper_map(F.partial(_grad_fusion), ret, self.op_list)
+        return fushion_res
+
+
+def test_allreduce_fushio_test():
+    context.set_context(mode=context.GRAPH_MODE)
+    net = AllReduceTest()
+    input_np = np.random.randn(2, 3, 4, 5).astype(np.float32)
+    input_me = Tensor(input_np)
+    net(input_me)