!12852 Change maketuple in coreops

From: @liangzhibo
Reviewed-by: 
Signed-off-by:

mindspore/_extends/graph_kernel/model/model.py

@@ -176,7 +176,7 @@ class PrimLib:
         'ReduceSum': Prim(REDUCE),
         'ReduceMax': Prim(REDUCE),
         'ReduceMin': Prim(REDUCE),
-        'make_tuple': Prim(CONTROL),
+        'MakeTuple': Prim(CONTROL),
         'ControlDepend': Prim(CONTROL),
         'Assign': Prim(ELEMWISE),
         'Tanh': Prim(ELEMWISE),

mindspore/_extends/parse/resources.py

@@ -121,7 +121,7 @@ convert_object_map = {
     T.next:         M.ms_next,
     T.hasnext:      M.hasnext,
 
-    T.make_tuple:   F.make_tuple,
+    T.MakeTuple:   F.make_tuple,
     T.make_dict:    F.make_dict,
     T.make_list:    F.make_list,
     T.make_slice:   F.make_slice,

mindspore/_extends/parse/trope.py

@@ -48,7 +48,7 @@ __all__ = ['add', 'sub', 'mul', 'truediv', 'floordiv', 'mod', 'eq', 'ne', 'lt',
            'exp', 'log', 'sin', 'cos', 'tan']
 
 
-def make_tuple(*elts):  # pragma: no cover
+def MakeTuple(*elts):  # pragma: no cover
     """Tuple builder."""
     raise RuntimeError('This operation is not meant to be called directly.')
 

mindspore/ccsrc/debug/anf_ir_utils.cc

@@ -2153,7 +2153,7 @@ class IrParser {
 
     std::vector<ValuePtr> elems;
     std::vector<AnfNodePtr> nodes;
-    nodes.push_back(std::make_shared<ValueNode>(std::make_shared<Primitive>("make_tuple")));
+    nodes.push_back(std::make_shared<ValueNode>(std::make_shared<Primitive>("MakeTuple")));
     ValuePtr elem = nullptr;
     AnfNodePtr node = nullptr;
     bool node_is_valid = false;

mindspore/ccsrc/frontend/parallel/ops_info/ops_utils.h

@@ -327,7 +327,7 @@ constexpr char UNIQUE[] = "Unique";
 
 // Parallel don't care
 constexpr char STRING_EQUAL[] = "string_equal";
-constexpr char MAKE_TUPLE[] = "make_tuple";
+constexpr char MAKE_TUPLE[] = "MakeTuple";
 constexpr char MAKE_LIST[] = "make_list";
 constexpr char MAKE_DICT[] = "make_dict";
 constexpr char MAKE_SLICE[] = "make_slice";

mindspore/ccsrc/pipeline/jit/parse/parse_base.h

@@ -118,7 +118,7 @@ const char NAMED_PRIMITIVE_GETITEM[] = "getitem";
 const char NAMED_PRIMITIVE_SETITEM[] = "setitem";
 const char NAMED_PRIMITIVE_HASNEXT[] = "hasnext";
 const char NAMED_PRIMITIVE_BOOL[] = "bool_";  // bool: P.identity
-const char NAMED_PRIMITIVE_MAKETUPLE[] = "make_tuple";
+const char NAMED_PRIMITIVE_MAKETUPLE[] = "MakeTuple";
 const char NAMED_PRIMITIVE_MAKELIST[] = "make_list";
 const char NAMED_PRIMITIVE_MAKESLICE[] = "make_slice";
 const char NAMED_PRIMITIVE_MAKEDICT[] = "make_dict";

mindspore/ccsrc/pipeline/jit/static_analysis/prim.cc

@@ -47,7 +47,7 @@ namespace abstract {
 using mindspore::parse::PyObjectWrapper;
 
 std::unordered_set<std::string> prims_to_skip_undetermined_infer{
-  "make_tuple", "make_list", "switch", "env_setitem", "env_getitem", "Load", "UpdateState"};
+  "MakeTuple", "make_list", "switch", "env_setitem", "env_getitem", "Load", "UpdateState"};
 
 EvalResultPtr DoSignatureEvaluator::Run(AnalysisEnginePtr engine, const ConfigPtrList &args_conf_list,
                                         AnfNodeConfigPtr out_conf) {

mindspore/ccsrc/transform/graph_ir/convert.cc

@@ -625,7 +625,7 @@ void DfGraphConvertor::TraceOutput(const AnfNodePtr node) {
     name = GetCNodeTargetFuncName(c);
   }
 
-  if (name == "make_tuple") {
+  if (name == "MakeTuple") {
     for (unsigned int i = 1; i < c->inputs().size(); i++) {
       TraceOutput(c->input(i));
     }

mindspore/core/base/core_ops.h

@@ -264,7 +264,7 @@ inline const PrimitivePtr kPrimMomentum = std::make_shared<Primitive>("Momentum"
 inline const PrimitivePtr kPrimApplyMomentum = std::make_shared<Primitive>("ApplyMomentum");
 inline const PrimitivePtr kPrimApplyFtrl = std::make_shared<Primitive>("ApplyFtrl");
 inline const PrimitivePtr kPrimLayerNorm = std::make_shared<Primitive>("LayerNorm");
-inline const PrimitivePtr kPrimLrn = std::make_shared<Primitive>("Lrn");
+inline const PrimitivePtr kPrimLrn = std::make_shared<Primitive>("LRN");
 inline const PrimitivePtr kPrimLayerNormGrad = std::make_shared<Primitive>("LayerNormGrad");
 inline const PrimitivePtr kPrimLayerNormXBackprop = std::make_shared<Primitive>("LayerNormXBackprop");
 inline const PrimitivePtr kPrimLayerNormBetaGammaBackprop = std::make_shared<Primitive>("LayerNormBetaGammaBackprop");
@@ -411,7 +411,7 @@ inline const PrimitivePtr kPrimAssignSub = std::make_shared<Primitive>("AssignSu
 inline const PrimitivePtr kPrimSelect = std::make_shared<Primitive>("Select");
 inline const PrimitivePtr kPrimCall = std::make_shared<Primitive>("call");
 
-inline const PrimitivePtr kPrimMakeTuple = std::make_shared<Primitive>("make_tuple");
+inline const PrimitivePtr kPrimMakeTuple = std::make_shared<Primitive>("MakeTuple");
 inline const PrimitivePtr kPrimMakeSlice = std::make_shared<Primitive>("make_slice");
 inline const PrimitivePtr kPrimTupleGetItem = std::make_shared<Primitive>(kTupleGetItem);
 inline const PrimitivePtr kPrimArrayGetItem = std::make_shared<Primitive>("array_getitem");

mindspore/core/ops/lrn.h

@@ -26,7 +26,7 @@
 
 namespace mindspore {
 namespace ops {
-constexpr auto kNameLRN = "Lrn";
+constexpr auto kNameLRN = "LRN";
 class LRN : public PrimitiveC {
  public:
   LRN() : PrimitiveC(kNameLRN) { InitIOName({"x"}, {"y"}); }

mindspore/ops/functional.py

@@ -132,7 +132,7 @@ tuple_len = Primitive("tuple_len")
 list_len = Primitive("list_len")
 tuple_reversed = Primitive("tuple_reversed")
 make_range = Primitive("make_range")
-make_tuple = Primitive('make_tuple')
+make_tuple = Primitive('MakeTuple')
 make_dict = Primitive('make_dict')
 make_list = Primitive('make_list')
 make_slice = Primitive('make_slice')

tests/st/graph_kernel/model/test_split.py

@@ -38,7 +38,7 @@ def first_connected(sp, space):
         nodes = [sp.nodes[i] for i in cand[0]]
         graphs = sp.resolve_connnected_graphs(nodes)
         if len(graphs) != 1:
-            print("connect check faied: ", nodes)
+            print("connect check failed: ", nodes)
             return False
     return True
 
@@ -245,7 +245,7 @@ def graph_pat_7():
         a1 = gb.tensor([1024, 1024], "float32", name="a1")
         a = gb.emit("Abs", a0, 'a')
         b = gb.emit("Abs", a1, 'b')
-        c = gb.emit("make_tuple", [a, b], 'c')
+        c = gb.emit("MakeTuple", [a, b], 'c')
         d = gb.tensor([1024, 1024], "float32", name="d")
         gb.op("AddN", d, [c])
         gb.emit("Abs", d, 'f')

tests/ut/cpp/operator/ops_test.cc

@@ -173,7 +173,7 @@ TEST_F(TestOps, HasTypeTest) {
 
 // Data structures
 TEST_F(TestOps, MakeTupleTest) {
-  auto prim = std::make_shared<Primitive>("make_tuple");
+  auto prim = std::make_shared<Primitive>("MakeTuple");
   ASSERT_EQ(prim->name(), kPrimMakeTuple->name());
 }
 

tests/ut/cpp/python_input/gtest_input/optimizer/opt_test.py

@@ -579,7 +579,7 @@ def test_elim_sum_shape_one(tag):
 def test_tuple_getitem(tag):
     """ test_tuple_getitem """
     fns = FnDict()
-    make_tuple = Primitive('make_tuple')
+    make_tuple = Primitive('MakeTuple')
 
     @fns
     def make_get_0(x, y):
@@ -603,7 +603,7 @@ def test_tuple_getitem(tag):
 def test_tuple_setitem(tag):
     """ test_tuple_setitem """
     fns = FnDict()
-    make_tuple = Primitive('make_tuple')
+    make_tuple = Primitive('MakeTuple')
     tuple_setitem = Primitive('tuple_setitem')
 
     @fns
@@ -924,7 +924,7 @@ def test_convert_switch_ops(tag):
     add = Primitive(Constants.kScalarAdd)
     neg = Primitive('Neg')
     tuple_getitem = Primitive(Constants.kTupleGetItem)
-    make_tuple = Primitive('make_tuple')
+    make_tuple = Primitive('MakeTuple')
 
     @fns
     def before(cond, x, y):
@@ -1032,7 +1032,7 @@ def test_reducesum_one(tag):
 def test_print_tuple_wrapper(tag):
     fns = FnDict()
     print_ = Primitive('Print')
-    make_tuple = Primitive('make_tuple')
+    make_tuple = Primitive('MakeTuple')
 
     @fns
     def before1(x, y):

tests/ut/cpp/python_input/gtest_input/pre_activate/adam_apply_one_fusion_test.py

@@ -25,7 +25,7 @@ RealDiv = P.RealDiv()
 Sqrt = P.Sqrt()
 Square = P.Square()
 Assign = P.Assign()
-make_tuple = Primitive('make_tuple')
+make_tuple = Primitive('MakeTuple')
 tuple_getitem = Primitive(Constants.kTupleGetItem)
 AdamApplyOne = Primitive('AdamApplyOne')
 AdamApplyOneAssign = Primitive('AdamApplyOneAssign')

tests/ut/cpp/python_input/gtest_input/pre_activate/adam_apply_one_with_decay_rule.py

@@ -25,7 +25,7 @@ sqrt = P.Sqrt()
 real_div = P.RealDiv()
 sub = P.Sub()
 Assign = P.Assign()
-make_tuple = Primitive('make_tuple')
+make_tuple = Primitive('MakeTuple')
 tuple_getitem = Primitive(Constants.kTupleGetItem)
 adam_apply_one_with_decay = Primitive('AdamApplyOneWithDecay')
 adam_apply_one_with_decay_assign = Primitive('AdamApplyOneWithDecayAssign')

tests/ut/cpp/python_input/gtest_input/pre_activate/addn_fission_test.py

@@ -17,7 +17,7 @@ from mindspore.ops import Primitive
 from mindspore.ops import operations as P
 
 addn = P.AddN()
-make_tuple = Primitive('make_tuple')
+make_tuple = Primitive('MakeTuple')
 
 
 class FnDict:

tests/ut/cpp/python_input/gtest_input/pre_activate/batch_norm_bert_fission_test.py

@@ -16,7 +16,7 @@ from mindspore.ops import Primitive
 from mindspore.ops import operations as P
 from mindspore.ops import _constants as Constants
 
-make_tuple = Primitive('make_tuple')
+make_tuple = Primitive('MakeTuple')
 tuple_getitem = Primitive(Constants.kTupleGetItem)
 BatchNorm = P.BatchNorm()
 BNTrainingReduce = Primitive('BNTrainingReduce')

tests/ut/cpp/python_input/gtest_input/pre_activate/batch_norm_grad_infer_fission_test.py

@@ -16,7 +16,7 @@ from mindspore.ops import Primitive
 from mindspore.ops.operations import _grad_ops as G
 from mindspore.ops import _constants as Constants
 
-make_tuple = Primitive('make_tuple')
+make_tuple = Primitive('MakeTuple')
 tuple_getitem = Primitive(Constants.kTupleGetItem)
 BatchNormGradTraining = G.BatchNormGrad(is_training=True)
 BatchNormGradInfer = G.BatchNormGrad(is_training=False)

tests/ut/cpp/python_input/gtest_input/pre_activate/batch_norm_grad_split.py

@@ -20,7 +20,7 @@ from mindspore.ops import _constants as Constants
 batch_norm_grad = G.BatchNormGrad(is_training=True)
 bn_training_update_grad = Primitive('BNTrainingUpdateGrad')
 bn_training_reduce_grad = Primitive('BNTrainingReduceGrad')
-make_tuple = Primitive('make_tuple')
+make_tuple = Primitive('MakeTuple')
 tuple_getitem = Primitive(Constants.kTupleGetItem)
 
 

tests/ut/cpp/python_input/gtest_input/pre_activate/batchnorm_to_bninfer.py

@@ -19,7 +19,7 @@ from mindspore.ops import _constants as Constants
 
 batch_norm = P.BatchNorm(is_training=False)
 bn_infer = Primitive('BNInfer')
-make_tuple = Primitive('make_tuple')
+make_tuple = Primitive('MakeTuple')
 tuple_getitem = Primitive(Constants.kTupleGetItem)
 
 

tests/ut/cpp/python_input/gtest_input/pre_activate/batchnormgrad_to_bninfergrad.py

@@ -19,7 +19,7 @@ from mindspore.ops import _constants as Constants
 
 batch_norm_grad = G.BatchNormGrad(is_training=False)
 bn_infer_grad = Primitive('BNInferGrad')
-make_tuple = Primitive('make_tuple')
+make_tuple = Primitive('MakeTuple')
 tuple_getitem = Primitive(Constants.kTupleGetItem)
 
 

tests/ut/cpp/python_input/gtest_input/pre_activate/bn_grad_split.py

@@ -19,7 +19,7 @@ from mindspore.ops import _constants as Constants
 from mindspore.common.tensor import Tensor
 import mindspore.common.dtype as mstype
 
-make_tuple = Primitive('make_tuple')
+make_tuple = Primitive('MakeTuple')
 tuple_getitem = Primitive(Constants.kTupleGetItem)
 bn_grad = G.BatchNormGrad(is_training=True)
 sync_bn_grad = G.SyncBatchNormGrad()

tests/ut/cpp/python_input/gtest_input/pre_activate/bn_split.py

@@ -20,7 +20,7 @@ from mindspore.ops import _constants as Constants
 from mindspore.common.tensor import Tensor
 import mindspore.common.dtype as mstype
 
-make_tuple = Primitive('make_tuple')
+make_tuple = Primitive('MakeTuple')
 tuple_getitem = Primitive(Constants.kTupleGetItem)
 bn = P.BatchNorm(is_training=True)
 sync_bn = inner.SyncBatchNorm()

tests/ut/cpp/python_input/gtest_input/pre_activate/buffer_fusion_test.py

@@ -33,7 +33,7 @@ Fusion_matmul_relu = Primitive('FusionOp_MatMul_ReLU')
 
 Add = P.Add()
 Sub = P.Sub()
-make_tuple = Primitive('make_tuple')
+make_tuple = Primitive('MakeTuple')
 
 
 class FnDict: