From 76075c0b36cc7295b5489660b5400c1b633bf624 Mon Sep 17 00:00:00 2001
From: yuchaojie <yuchaojie1@huawei.com>
Date: Thu, 1 Jul 2021 17:33:14 +0800
Subject: [PATCH] SliceGrad unify mindir adpation for Cangjie frontend

---
 .../ascend/mindir/slice_grad_unify_mindir.cc  | 32 +++++++++++++------
 1 file changed, 23 insertions(+), 9 deletions(-)

diff --git a/mindspore/ccsrc/backend/optimizer/ascend/mindir/slice_grad_unify_mindir.cc b/mindspore/ccsrc/backend/optimizer/ascend/mindir/slice_grad_unify_mindir.cc
index fd56fa17127..f02871bf52a 100644
--- a/mindspore/ccsrc/backend/optimizer/ascend/mindir/slice_grad_unify_mindir.cc
+++ b/mindspore/ccsrc/backend/optimizer/ascend/mindir/slice_grad_unify_mindir.cc
@@ -31,6 +31,7 @@ namespace mindspore {
 namespace opt {
 namespace {
 constexpr size_t kSliceGradInputTensorNum = 4;
+constexpr size_t kSliceGradCangjieInputTensorNum = 2;
 
 std::vector<int64_t> GetInputXShape(const AnfNodePtr &node) {
   MS_EXCEPTION_IF_NULL(node);
@@ -50,11 +51,8 @@ std::vector<int64_t> GetTupleValue(const AnfNodePtr &node) {
 }  // namespace
 
 const BaseRef SliceGradUnifyMindIR::DefinePattern() const {
-  VarPtr X1 = std::make_shared<Var>();
-  VarPtr X2 = std::make_shared<Var>();
-  VarPtr X3 = std::make_shared<Var>();
-  VarPtr X4 = std::make_shared<Var>();
-  VectorRef slice_grad({std::make_shared<Primitive>("SliceGrad"), X1, X2, X3, X4});
+  VarPtr Xs = std::make_shared<SeqVar>();
+  VectorRef slice_grad({std::make_shared<Primitive>("SliceGrad"), Xs});
   return slice_grad;
 }
 
@@ -63,8 +61,16 @@ const AnfNodePtr SliceGradUnifyMindIR::Process(const FuncGraphPtr &graph, const
   MS_EXCEPTION_IF_NULL(graph);
   MS_EXCEPTION_IF_NULL(node);
 
-  auto slice_grad = CheckAnfNodeIfCNodeAndInputSize(node, kSliceGradInputTensorNum);
-  std::vector<AnfNodePtr> pad_inputs = {NewValueNode(std::make_shared<Primitive>(kPadOpName)), slice_grad->input(1)};
+  auto slice_grad = node->cast<CNodePtr>();
+  MS_EXCEPTION_IF_NULL(slice_grad);
+  auto input_num = AnfAlgo::GetInputTensorNum(slice_grad);
+  if (input_num != kSliceGradInputTensorNum && input_num != kSliceGradCangjieInputTensorNum) {
+    MS_LOG(EXCEPTION) << "The input tensor size[" << input_num
+                      << "] of node " + slice_grad->DebugString() + " is not equal to " << kSliceGradInputTensorNum
+                      << " or " << kSliceGradCangjieInputTensorNum;
+  }
+  std::vector<AnfNodePtr> pad_inputs = {NewValueNode(std::make_shared<Primitive>(kPadOpName)),
+                                        slice_grad->input(kIndex1)};
   auto pad = graph->NewCNode(pad_inputs);
   MS_EXCEPTION_IF_NULL(pad);
   pad->set_scope(slice_grad->scope());
@@ -72,8 +78,16 @@ const AnfNodePtr SliceGradUnifyMindIR::Process(const FuncGraphPtr &graph, const
 
   // set attr paddings
   auto x_shape = GetInputXShape(slice_grad);
-  auto begins = GetTupleValue(slice_grad->input(kIndex3));
-  auto sizes = GetTupleValue(slice_grad->input(kIndex4));
+  std::vector<int64_t> begins;
+  std::vector<int64_t> sizes;
+  if (input_num == kSliceGradInputTensorNum) {
+    begins = GetTupleValue(slice_grad->input(kIndex3));
+    sizes = GetTupleValue(slice_grad->input(kIndex4));
+  } else {
+    // if frontend is Cangjie and mode is pynative, input 2, 3 is already converted to attr
+    begins = AnfAlgo::GetNodeAttr<std::vector<int64_t>>(slice_grad, kAttrBegin);
+    sizes = AnfAlgo::GetNodeAttr<std::vector<int64_t>>(slice_grad, kAttrSize);
+  }
   if (x_shape.size() != begins.size() || begins.size() != sizes.size()) {
     MS_LOG(EXCEPTION) << "For SliceGrad, x's shape dim number should be equal to len(begin) and len(size).";
   }