!1878 fix tuple args issue in pynative mode

Merge pull request !1878 from wangqiuliang/fix-tuple-args-issue-in-pynative

mindspore/ccsrc/pynative/pynative_execute.cc

@@ -661,6 +661,20 @@ AnfNodePtr PynativeExecutor::GetInput(const py::object &obj, const py::object &o
     // out = op(cell1(x, y))
     // out = op(cell1(x, y)[0])
     node = GetObjNode(obj);
+  } else if (py::isinstance<py::tuple>(obj)) {
+    // out = op((x, y))
+    // out = cell((x, y))
+    std::vector<AnfNodePtr> args;
+    args.push_back(NewValueNode(prim::kPrimMakeTuple));
+
+    auto tuple = obj.cast<py::tuple>();
+    auto tuple_size = static_cast<int>(tuple.size());
+    for (int i = 0; i < tuple_size; i++) {
+      args.push_back(GetInput(tuple[i], py::object()));
+    }
+    auto cnode = curr_g_->NewCNode(args);
+    set_obj_node_map(curr_g_, GetId(obj), cnode);
+    node = cnode;
   } else {
     // out = op(x, 1)
     ValuePtr converted_ret = nullptr;
@@ -728,6 +742,13 @@ void PynativeExecutor::EndGraph(const py::object &cell, const py::object &out, c
     }
     auto out_cnode = curr_g_->NewCNode(inputs);
     set_pyobj(curr_g_, GetId(cell));
+    if (py::isinstance<py::tuple>(out)) {
+      auto out_list = py::cast<py::tuple>(out);
+      auto out_size = static_cast<int>(out_list.size());
+      for (int i = 0; i < out_size; i++) {
+        set_obj_node_map(curr_g_, GetId(out_list[i]), out_cnode, i);
+      }
+    }
     set_obj_node_map(curr_g_, GetId(out), out_cnode);
   } else {
     parse::ResolveFuncGraph(newfg, resource_);

mindspore/common/tensor.py

@@ -19,6 +19,7 @@ from .._c_expression import Tensor as Tensor_
 from .._c_expression import MetaTensor
 from .._checkparam import check_type, check_typename
 from . import dtype as mstype
+from .. import context
 from ._register_for_tensor import tensor_operator_registry
 
 __all__ = ['Tensor', 'MetaTensor']
@@ -77,6 +78,8 @@ class Tensor(Tensor_):
     def __eq__(self, other):
         if not isinstance(other, Tensor):
             return False
+        if context.get_context("enable_ge") or self.dtype() == mstype.bool_ or other.dtype() == mstype.bool_:
+            return Tensor(np.array(self.asnumpy() == other.asnumpy()))
         return tensor_operator_registry.get('__eq__')(self, other)
 
     def __ne__(self, other):

mindspore/ops/operations/array_ops.py

@@ -145,8 +145,8 @@ class SameTypeShape(PrimitiveWithInfer):
 
     def __call__(self, x, y):
         """run in PyNative mode"""
-        validator.check_subclass('x', x.dtype(), mstype.tensor, self.name)
-        validator.check_subclass('y', y.dtype(), mstype.tensor, self.name)
+        validator.check_value_type("x", x, Tensor, self.name)
+        validator.check_value_type("y", y, Tensor, self.name)
         validator.check('x dtype', x.dtype(), 'y dtype', y.dtype(), Rel.EQ, self.name, TypeError)
         validator.check('x shape', x.shape(), 'y shape', y.shape(), Rel.EQ, self.name)
         return x