From 4fc003bfaed69151ee37dab27072dd50f79ba14a Mon Sep 17 00:00:00 2001
From: yangruoqi713 <yangruoqi@huawei.com>
Date: Fri, 4 Dec 2020 15:47:50 +0800
Subject: [PATCH] [MSLITE][Develop] return RET_INFET_INVALID when infer_flag is
 false for op infershape

---
 mindspore/lite/src/ops/addn.cc                   | 2 +-
 mindspore/lite/src/ops/argmax.cc                 | 2 +-
 mindspore/lite/src/ops/argmin.cc                 | 2 +-
 mindspore/lite/src/ops/arithmetic.cc             | 2 +-
 mindspore/lite/src/ops/arithmetic_self.cc        | 2 +-
 mindspore/lite/src/ops/audio_spectrogram.cc      | 2 +-
 mindspore/lite/src/ops/batch_to_space.cc         | 2 +-
 mindspore/lite/src/ops/broadcast_to.cc           | 2 +-
 mindspore/lite/src/ops/cast.cc                   | 2 +-
 mindspore/lite/src/ops/concat.cc                 | 2 +-
 mindspore/lite/src/ops/constant_of_shape.cc      | 2 +-
 mindspore/lite/src/ops/conv2d.cc                 | 2 +-
 mindspore/lite/src/ops/crop.cc                   | 2 +-
 mindspore/lite/src/ops/deconv2d.cc               | 2 +-
 mindspore/lite/src/ops/dedepthwise_conv2d.cc     | 2 +-
 mindspore/lite/src/ops/depth_to_space.cc         | 2 +-
 mindspore/lite/src/ops/depthwise_conv2d.cc       | 2 +-
 mindspore/lite/src/ops/detection_post_process.cc | 2 +-
 mindspore/lite/src/ops/dropout.cc                | 2 +-
 mindspore/lite/src/ops/dropout_grad.cc           | 2 +-
 mindspore/lite/src/ops/embedding_lookup.cc       | 2 +-
 mindspore/lite/src/ops/expand_dims.cc            | 2 +-
 mindspore/lite/src/ops/fft_imag.cc               | 2 +-
 mindspore/lite/src/ops/fft_real.cc               | 2 +-
 mindspore/lite/src/ops/fill.cc                   | 2 +-
 mindspore/lite/src/ops/flatten.cc                | 2 +-
 mindspore/lite/src/ops/flatten_grad.cc           | 2 +-
 mindspore/lite/src/ops/full_connection.cc        | 2 +-
 mindspore/lite/src/ops/gather.cc                 | 2 +-
 mindspore/lite/src/ops/gather_nd.cc              | 2 +-
 mindspore/lite/src/ops/layer_norm.cc             | 2 +-
 mindspore/lite/src/ops/lstm.cc                   | 2 +-
 mindspore/lite/src/ops/matmul.cc                 | 2 +-
 mindspore/lite/src/ops/maximum_grad.cc           | 2 +-
 mindspore/lite/src/ops/mean.cc                   | 2 +-
 mindspore/lite/src/ops/mfcc.cc                   | 2 +-
 mindspore/lite/src/ops/nchw2nhwc.cc              | 2 +-
 mindspore/lite/src/ops/nhwc2nchw.cc              | 2 +-
 mindspore/lite/src/ops/one_hot.cc                | 2 +-
 mindspore/lite/src/ops/pad.cc                    | 2 +-
 mindspore/lite/src/ops/pooling.cc                | 2 +-
 mindspore/lite/src/ops/power.cc                  | 2 +-
 mindspore/lite/src/ops/prior_box.cc              | 2 +-
 mindspore/lite/src/ops/quant_dtype_cast.cc       | 2 +-
 mindspore/lite/src/ops/range.cc                  | 2 +-
 mindspore/lite/src/ops/rank.cc                   | 2 +-
 mindspore/lite/src/ops/reduce.cc                 | 2 +-
 mindspore/lite/src/ops/reshape.cc                | 2 +-
 mindspore/lite/src/ops/resize.cc                 | 2 +-
 mindspore/lite/src/ops/return.cc                 | 2 +-
 mindspore/lite/src/ops/reverse_sequence.cc       | 2 +-
 mindspore/lite/src/ops/rfft.cc                   | 2 +-
 mindspore/lite/src/ops/roi_pooling.cc            | 2 +-
 mindspore/lite/src/ops/scatter_nd.cc             | 2 +-
 mindspore/lite/src/ops/shape.cc                  | 2 +-
 mindspore/lite/src/ops/slice.cc                  | 2 +-
 mindspore/lite/src/ops/softmax.cc                | 2 +-
 mindspore/lite/src/ops/space_to_batch.cc         | 2 +-
 mindspore/lite/src/ops/space_to_batch_nd.cc      | 2 +-
 mindspore/lite/src/ops/space_to_depth.cc         | 2 +-
 mindspore/lite/src/ops/sparse_to_dense.cc        | 2 +-
 mindspore/lite/src/ops/split.cc                  | 2 +-
 mindspore/lite/src/ops/squeeze.cc                | 2 +-
 mindspore/lite/src/ops/stack.cc                  | 2 +-
 mindspore/lite/src/ops/tile.cc                   | 2 +-
 mindspore/lite/src/ops/topk.cc                   | 2 +-
 mindspore/lite/src/ops/transpose.cc              | 2 +-
 mindspore/lite/src/ops/unique.cc                 | 2 +-
 mindspore/lite/src/ops/unsqueeze.cc              | 2 +-
 mindspore/lite/src/ops/unstack.cc                | 2 +-
 mindspore/lite/src/ops/where.cc                  | 2 +-
 mindspore/lite/src/ops/zeros_like.cc             | 2 +-
 72 files changed, 72 insertions(+), 72 deletions(-)

diff --git a/mindspore/lite/src/ops/addn.cc b/mindspore/lite/src/ops/addn.cc
index d71e24bdcb..2391ffa2c6 100644
--- a/mindspore/lite/src/ops/addn.cc
+++ b/mindspore/lite/src/ops/addn.cc
@@ -86,7 +86,7 @@ int AddN::InferShape(std::vector<Tensor *> inputs, std::vector<Tensor *> outputs
   output->set_format(input->format());
   output->set_data_type(input->data_type());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   output->set_shape(input->shape());
 
diff --git a/mindspore/lite/src/ops/argmax.cc b/mindspore/lite/src/ops/argmax.cc
index cca4b0e11b..1e8af0ea8d 100644
--- a/mindspore/lite/src/ops/argmax.cc
+++ b/mindspore/lite/src/ops/argmax.cc
@@ -74,7 +74,7 @@ int ArgMax::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> outp
   output->set_format(input->format());
   output->set_data_type(input->data_type());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   std::vector<int> output_shape(input->shape());
   auto input_shape_size = input->shape().size();
diff --git a/mindspore/lite/src/ops/argmin.cc b/mindspore/lite/src/ops/argmin.cc
index 656a517065..acd6272ae8 100644
--- a/mindspore/lite/src/ops/argmin.cc
+++ b/mindspore/lite/src/ops/argmin.cc
@@ -72,7 +72,7 @@ int ArgMin::InferShape(std::vector<lite::Tensor *> inputs_, std::vector<lite::Te
   output->set_format(input->format());
   output->set_data_type(input->data_type());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   auto input_shape_size = input->shape().size();
   auto axis = GetAxis() < 0 ? GetAxis() + input_shape_size : GetAxis();
diff --git a/mindspore/lite/src/ops/arithmetic.cc b/mindspore/lite/src/ops/arithmetic.cc
index 755417716d..0c03bd6917 100644
--- a/mindspore/lite/src/ops/arithmetic.cc
+++ b/mindspore/lite/src/ops/arithmetic.cc
@@ -45,7 +45,7 @@ int Arithmetic::InferShape(std::vector<lite::Tensor *> inputs_, std::vector<lite
   output->set_format(format);
   output->set_data_type(input0->data_type());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   if (input_shape0.size() > 10 || input_shape1.size() > 10) {
     int wrong_dim = input_shape0.size() > input_shape1.size() ? input_shape0.size() : input_shape1.size();
diff --git a/mindspore/lite/src/ops/arithmetic_self.cc b/mindspore/lite/src/ops/arithmetic_self.cc
index 77187d269e..bc8c2a5831 100644
--- a/mindspore/lite/src/ops/arithmetic_self.cc
+++ b/mindspore/lite/src/ops/arithmetic_self.cc
@@ -33,7 +33,7 @@ int ArithmeticSelf::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor
   output->set_format(input->format());
   output->set_data_type(input->data_type());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   output->set_shape(input->shape());
   return RET_OK;
diff --git a/mindspore/lite/src/ops/audio_spectrogram.cc b/mindspore/lite/src/ops/audio_spectrogram.cc
index d3a19224b0..6adce58037 100644
--- a/mindspore/lite/src/ops/audio_spectrogram.cc
+++ b/mindspore/lite/src/ops/audio_spectrogram.cc
@@ -77,7 +77,7 @@ int AudioSpectrogram::InferShape(std::vector<Tensor *> inputs_, std::vector<Tens
   output->set_data_type(input->data_type());
   output->set_format(input->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   auto input_shape = input->shape();
   if (input_shape.size() != 2) {
diff --git a/mindspore/lite/src/ops/batch_to_space.cc b/mindspore/lite/src/ops/batch_to_space.cc
index 6156517f0c..34e03a67b5 100644
--- a/mindspore/lite/src/ops/batch_to_space.cc
+++ b/mindspore/lite/src/ops/batch_to_space.cc
@@ -98,7 +98,7 @@ int BatchToSpace::InferShape(std::vector<lite::Tensor *> inputs, std::vector<lit
   outputs[0]->set_format(input->format());
   outputs[0]->set_data_type(input->data_type());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   auto input_shape = input->shape();
   if (input_shape.size() != kDimension_4d) {
diff --git a/mindspore/lite/src/ops/broadcast_to.cc b/mindspore/lite/src/ops/broadcast_to.cc
index 252691712e..e5a891af84 100644
--- a/mindspore/lite/src/ops/broadcast_to.cc
+++ b/mindspore/lite/src/ops/broadcast_to.cc
@@ -80,7 +80,7 @@ int BroadcastTo::InferShape(std::vector<Tensor *> inputs, std::vector<Tensor *>
   outputs[0]->set_format(input->format());
   outputs[0]->set_data_type(input->data_type());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   std::vector<int32_t> dst_shape(GetDstShape());
   for (size_t i = 0; i < dst_shape.size(); ++i) {
diff --git a/mindspore/lite/src/ops/cast.cc b/mindspore/lite/src/ops/cast.cc
index 6dfe87d9d3..abebfe508e 100644
--- a/mindspore/lite/src/ops/cast.cc
+++ b/mindspore/lite/src/ops/cast.cc
@@ -93,7 +93,7 @@ int Cast::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> output
 
   output->set_data_type(static_cast<TypeId>(GetDstT()));
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
 
   if (GetSrcT() != 0 && input->data_type() != GetSrcT()) {
diff --git a/mindspore/lite/src/ops/concat.cc b/mindspore/lite/src/ops/concat.cc
index 24d9be51d3..3f8bfb5a55 100644
--- a/mindspore/lite/src/ops/concat.cc
+++ b/mindspore/lite/src/ops/concat.cc
@@ -98,7 +98,7 @@ int Concat::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> outp
   output->set_data_type(input0->data_type());
   output->set_format(input0->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
 
   auto input0_shape = inputs_.at(0)->shape();
diff --git a/mindspore/lite/src/ops/constant_of_shape.cc b/mindspore/lite/src/ops/constant_of_shape.cc
index 83babc623c..0e73effed6 100644
--- a/mindspore/lite/src/ops/constant_of_shape.cc
+++ b/mindspore/lite/src/ops/constant_of_shape.cc
@@ -83,7 +83,7 @@ int ConstantOfShape::InferShape(std::vector<Tensor *> inputs_, std::vector<Tenso
   out_tensor->set_data_type(static_cast<TypeId>(GetDataType()));
   out_tensor->set_format(in_tensor->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   auto in_data = reinterpret_cast<int *>(in_tensor->data_c());
   if (in_data == nullptr) {
diff --git a/mindspore/lite/src/ops/conv2d.cc b/mindspore/lite/src/ops/conv2d.cc
index f40699231d..28cb4fb252 100644
--- a/mindspore/lite/src/ops/conv2d.cc
+++ b/mindspore/lite/src/ops/conv2d.cc
@@ -391,7 +391,7 @@ int Conv2D::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> outp
   pad_r_ = GetPadRight();
 
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   auto in_shape = input_tensor->shape();
   int input_h = in_shape.at(1);
diff --git a/mindspore/lite/src/ops/crop.cc b/mindspore/lite/src/ops/crop.cc
index 15dbd2c00e..c568f8832b 100644
--- a/mindspore/lite/src/ops/crop.cc
+++ b/mindspore/lite/src/ops/crop.cc
@@ -71,7 +71,7 @@ int Crop::InferShape(std::vector<Tensor *> inputs, std::vector<Tensor *> outputs
   outputs[0]->set_format(inputs[0]->format());
   outputs[0]->set_data_type(inputs[0]->data_type());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   outputs[0]->set_shape(inputs[1]->shape());
   return RET_OK;
diff --git a/mindspore/lite/src/ops/deconv2d.cc b/mindspore/lite/src/ops/deconv2d.cc
index 722bc8ee57..c68dabbe3f 100644
--- a/mindspore/lite/src/ops/deconv2d.cc
+++ b/mindspore/lite/src/ops/deconv2d.cc
@@ -317,7 +317,7 @@ int DeConv2D::InferShape(std::vector<lite::Tensor *> inputs_, std::vector<lite::
   output->set_format(input->format());
   output->set_data_type(input->data_type());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   int32_t input_h = input->Height();
   int32_t input_w = input->Width();
diff --git a/mindspore/lite/src/ops/dedepthwise_conv2d.cc b/mindspore/lite/src/ops/dedepthwise_conv2d.cc
index 50c1baab6b..276c91cd5c 100644
--- a/mindspore/lite/src/ops/dedepthwise_conv2d.cc
+++ b/mindspore/lite/src/ops/dedepthwise_conv2d.cc
@@ -138,7 +138,7 @@ int DeDepthwiseConv2D::InferShape(std::vector<lite::Tensor *> inputs_, std::vect
   output->set_format(input->format());
   output->set_data_type(input->data_type());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   auto in_shape = input->shape();
   int input_h = in_shape.at(1);
diff --git a/mindspore/lite/src/ops/depth_to_space.cc b/mindspore/lite/src/ops/depth_to_space.cc
index 2ad62eb0fd..194e30d4ac 100644
--- a/mindspore/lite/src/ops/depth_to_space.cc
+++ b/mindspore/lite/src/ops/depth_to_space.cc
@@ -73,7 +73,7 @@ int DepthToSpace::InferShape(std::vector<lite::Tensor *> inputs, std::vector<lit
   outputs[0]->set_data_type(input->data_type());
   outputs[0]->set_format(input->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   auto input_shape = input->shape();
   if (input_shape.size() != kDimension_4d) {
diff --git a/mindspore/lite/src/ops/depthwise_conv2d.cc b/mindspore/lite/src/ops/depthwise_conv2d.cc
index 5ab48bfb4f..235f326c77 100644
--- a/mindspore/lite/src/ops/depthwise_conv2d.cc
+++ b/mindspore/lite/src/ops/depthwise_conv2d.cc
@@ -219,7 +219,7 @@ int DepthwiseConv2D::InferShape(std::vector<lite::Tensor *> inputs_, std::vector
   pad_r_ = GetPadRight();
 
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   auto in_shape = input->shape();
   int input_h = in_shape.at(1);
diff --git a/mindspore/lite/src/ops/detection_post_process.cc b/mindspore/lite/src/ops/detection_post_process.cc
index c96078747f..dc608ef40e 100644
--- a/mindspore/lite/src/ops/detection_post_process.cc
+++ b/mindspore/lite/src/ops/detection_post_process.cc
@@ -190,7 +190,7 @@ int DetectionPostProcess::InferShape(std::vector<lite::Tensor *> inputs_, std::v
   num_det->set_format(boxes->format());
   num_det->set_data_type(kNumberTypeFloat32);
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   const auto max_detections = GetMaxDetections();
   const auto max_classes_per_detection = GetMaxClassesPerDetection();
diff --git a/mindspore/lite/src/ops/dropout.cc b/mindspore/lite/src/ops/dropout.cc
index 32c6baa7a8..efe8534e31 100644
--- a/mindspore/lite/src/ops/dropout.cc
+++ b/mindspore/lite/src/ops/dropout.cc
@@ -84,7 +84,7 @@ int Dropout::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> out
   auto output0 = outputs_.front();
   MS_ASSERT(output0 != nullptr);
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   output0->set_shape(input->shape());
   output0->set_data_type(input->data_type());
diff --git a/mindspore/lite/src/ops/dropout_grad.cc b/mindspore/lite/src/ops/dropout_grad.cc
index e459dc65b3..8f046cd559 100644
--- a/mindspore/lite/src/ops/dropout_grad.cc
+++ b/mindspore/lite/src/ops/dropout_grad.cc
@@ -87,7 +87,7 @@ int DropoutGrad::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *>
   auto output = outputs_.front();
   MS_ASSERT(output != nullptr);
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   output->set_shape(input->shape());
   output->set_data_type(input->data_type());
diff --git a/mindspore/lite/src/ops/embedding_lookup.cc b/mindspore/lite/src/ops/embedding_lookup.cc
index 0ef4ba49e1..a0a3ee7a06 100644
--- a/mindspore/lite/src/ops/embedding_lookup.cc
+++ b/mindspore/lite/src/ops/embedding_lookup.cc
@@ -70,7 +70,7 @@ int EmbeddingLookup::InferShape(std::vector<Tensor *> inputs_, std::vector<Tenso
   output->set_format(params_->format());
   output->set_data_type(params_->data_type());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
 
   auto embedding_shape = params_->shape();
diff --git a/mindspore/lite/src/ops/expand_dims.cc b/mindspore/lite/src/ops/expand_dims.cc
index 419eed0744..4ca40f682b 100644
--- a/mindspore/lite/src/ops/expand_dims.cc
+++ b/mindspore/lite/src/ops/expand_dims.cc
@@ -103,7 +103,7 @@ int ExpandDims::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *>
   output->set_data_type(input->data_type());
   output->set_format(input->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   int dim = GetDim();
   if (dim < 0) {
diff --git a/mindspore/lite/src/ops/fft_imag.cc b/mindspore/lite/src/ops/fft_imag.cc
index 86bde09c86..73f9b9b60f 100644
--- a/mindspore/lite/src/ops/fft_imag.cc
+++ b/mindspore/lite/src/ops/fft_imag.cc
@@ -43,7 +43,7 @@ int FftImag::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> out
   output->set_data_type(TypeId::kNumberTypeFloat32);
   output->set_format(input->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   auto input_shape = input->shape();
   input_shape.pop_back();
diff --git a/mindspore/lite/src/ops/fft_real.cc b/mindspore/lite/src/ops/fft_real.cc
index fcf7dd5a43..5d65ce0f34 100644
--- a/mindspore/lite/src/ops/fft_real.cc
+++ b/mindspore/lite/src/ops/fft_real.cc
@@ -43,7 +43,7 @@ int FftReal::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> out
   output->set_data_type(TypeId::kNumberTypeFloat32);
   output->set_format(input->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   auto input_shape = input->shape();
   input_shape.pop_back();
diff --git a/mindspore/lite/src/ops/fill.cc b/mindspore/lite/src/ops/fill.cc
index 6fff1fe27e..607319f60f 100644
--- a/mindspore/lite/src/ops/fill.cc
+++ b/mindspore/lite/src/ops/fill.cc
@@ -71,7 +71,7 @@ int Fill::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> output
   output->set_data_type(input->data_type());
   output->set_format(input->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
 
   std::vector<int> output_shape;
diff --git a/mindspore/lite/src/ops/flatten.cc b/mindspore/lite/src/ops/flatten.cc
index ed123fab2c..06227a12d7 100644
--- a/mindspore/lite/src/ops/flatten.cc
+++ b/mindspore/lite/src/ops/flatten.cc
@@ -40,7 +40,7 @@ int Flatten::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> out
   output->set_data_type(input->data_type());
   output->set_format(input->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
 
   auto input_shape = input->shape();
diff --git a/mindspore/lite/src/ops/flatten_grad.cc b/mindspore/lite/src/ops/flatten_grad.cc
index 8821470f86..bb768b05c0 100644
--- a/mindspore/lite/src/ops/flatten_grad.cc
+++ b/mindspore/lite/src/ops/flatten_grad.cc
@@ -39,7 +39,7 @@ int FlattenGrad::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *>
   output->set_data_type(input->data_type());
   output->set_format(input->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
 
   auto input_shape = input->shape();
diff --git a/mindspore/lite/src/ops/full_connection.cc b/mindspore/lite/src/ops/full_connection.cc
index 6d50ff56af..f34ea6f660 100644
--- a/mindspore/lite/src/ops/full_connection.cc
+++ b/mindspore/lite/src/ops/full_connection.cc
@@ -70,7 +70,7 @@ int FullConnection::InferShape(std::vector<lite::Tensor *> inputs_, std::vector<
   auto output = outputs_.front();
   MS_ASSERT(output != nullptr);
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   if ((GetHasBias() && inputs_.size() != kMultiNum) || (!GetHasBias() && inputs_.size() != kDoubleNum)) {
     MS_LOG(ERROR) << "Input tensors num error";
diff --git a/mindspore/lite/src/ops/gather.cc b/mindspore/lite/src/ops/gather.cc
index 662062a3c5..027366c7cd 100644
--- a/mindspore/lite/src/ops/gather.cc
+++ b/mindspore/lite/src/ops/gather.cc
@@ -114,7 +114,7 @@ int Gather::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> outp
   output->set_data_type(input->data_type());
   output->set_format(input->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
 
   int axis = GetAxis();
diff --git a/mindspore/lite/src/ops/gather_nd.cc b/mindspore/lite/src/ops/gather_nd.cc
index 4f7523b0da..976c80d75a 100644
--- a/mindspore/lite/src/ops/gather_nd.cc
+++ b/mindspore/lite/src/ops/gather_nd.cc
@@ -66,7 +66,7 @@ int GatherNd::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> ou
   output->set_data_type(input->data_type());
   output->set_format(input->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   auto in_shape = input->shape();
   int in_rank = in_shape.size();
diff --git a/mindspore/lite/src/ops/layer_norm.cc b/mindspore/lite/src/ops/layer_norm.cc
index acce63150d..403048fd32 100644
--- a/mindspore/lite/src/ops/layer_norm.cc
+++ b/mindspore/lite/src/ops/layer_norm.cc
@@ -103,7 +103,7 @@ int LayerNorm::InferShape(std::vector<lite::Tensor *> inputs_, std::vector<lite:
     }
   }
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
 
   output->set_shape(input_shape);
diff --git a/mindspore/lite/src/ops/lstm.cc b/mindspore/lite/src/ops/lstm.cc
index b66c9bc22b..8963020915 100644
--- a/mindspore/lite/src/ops/lstm.cc
+++ b/mindspore/lite/src/ops/lstm.cc
@@ -68,7 +68,7 @@ int Lstm::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> output
     outputs_.at(i)->set_format(input->format());
   }
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
 
   std::vector<int> in_shape = input->shape();
diff --git a/mindspore/lite/src/ops/matmul.cc b/mindspore/lite/src/ops/matmul.cc
index a2d8fa0009..bd11e88fd8 100644
--- a/mindspore/lite/src/ops/matmul.cc
+++ b/mindspore/lite/src/ops/matmul.cc
@@ -101,7 +101,7 @@ int MatMul::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> outp
   output->set_data_type(input0->data_type());
   output->set_format(input0->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
 
   std::vector<int> a_shape = input0->shape();
diff --git a/mindspore/lite/src/ops/maximum_grad.cc b/mindspore/lite/src/ops/maximum_grad.cc
index 6a0cc672a1..8fc3a5385c 100644
--- a/mindspore/lite/src/ops/maximum_grad.cc
+++ b/mindspore/lite/src/ops/maximum_grad.cc
@@ -93,7 +93,7 @@ int MaximumGrad::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *>
   MS_ASSERT(dx1 != nullptr);
   MS_ASSERT(dx2 != nullptr);
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
 
   auto inShape0 = x1->shape();
diff --git a/mindspore/lite/src/ops/mean.cc b/mindspore/lite/src/ops/mean.cc
index 843157b6ce..4fac9e183c 100644
--- a/mindspore/lite/src/ops/mean.cc
+++ b/mindspore/lite/src/ops/mean.cc
@@ -77,7 +77,7 @@ int Mean::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> output
   output->set_data_type(input->data_type());
   output->set_format(input->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   if (this->primitive_ == nullptr) {
     return RET_NULL_PTR;
diff --git a/mindspore/lite/src/ops/mfcc.cc b/mindspore/lite/src/ops/mfcc.cc
index c7e5d023f0..511e1cfc95 100644
--- a/mindspore/lite/src/ops/mfcc.cc
+++ b/mindspore/lite/src/ops/mfcc.cc
@@ -59,7 +59,7 @@ int Mfcc::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> output
   output->set_data_type(input->data_type());
   output->set_format(input->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   auto input_shape = input->shape();
   if (input_shape.size() != 3) {
diff --git a/mindspore/lite/src/ops/nchw2nhwc.cc b/mindspore/lite/src/ops/nchw2nhwc.cc
index b73db62e82..ff80c7aba8 100644
--- a/mindspore/lite/src/ops/nchw2nhwc.cc
+++ b/mindspore/lite/src/ops/nchw2nhwc.cc
@@ -48,7 +48,7 @@ int Nchw2Nhwc::InferShape(std::vector<lite::Tensor *> inputs_, std::vector<lite:
   output->set_format(schema::Format::Format_NHWC);
   output->set_data_type(input->data_type());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   std::vector<int> nchw_shape = input->shape();
   if (nchw_shape.size() != 4) {
diff --git a/mindspore/lite/src/ops/nhwc2nchw.cc b/mindspore/lite/src/ops/nhwc2nchw.cc
index dfe27f5269..9e7648be72 100644
--- a/mindspore/lite/src/ops/nhwc2nchw.cc
+++ b/mindspore/lite/src/ops/nhwc2nchw.cc
@@ -49,7 +49,7 @@ int Nhwc2Nchw::InferShape(std::vector<lite::Tensor *> inputs_, std::vector<lite:
   output->set_format(schema::Format::Format_NCHW);
   output->set_data_type(input->data_type());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   std::vector<int> nhwc_shape = input->shape();
   if (nhwc_shape.size() != 4) {
diff --git a/mindspore/lite/src/ops/one_hot.cc b/mindspore/lite/src/ops/one_hot.cc
index f6efcbfdf7..2917ca4900 100644
--- a/mindspore/lite/src/ops/one_hot.cc
+++ b/mindspore/lite/src/ops/one_hot.cc
@@ -117,7 +117,7 @@ int OneHot::InferShape(std::vector<Tensor *> inputs, std::vector<Tensor *> outpu
   output->set_data_type(on_value->data_type());
   output->set_format(on_value->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   const auto input_shape = input->shape();
   int input_rank = static_cast<int>(input_shape.size());
diff --git a/mindspore/lite/src/ops/pad.cc b/mindspore/lite/src/ops/pad.cc
index 5a3c7145dc..f9ac5ae519 100644
--- a/mindspore/lite/src/ops/pad.cc
+++ b/mindspore/lite/src/ops/pad.cc
@@ -83,7 +83,7 @@ int Pad::InferShape(std::vector<Tensor *> inputs, std::vector<Tensor *> outputs)
   output->set_format(input->format());
   output->set_data_type(input->data_type());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
 
   std::vector<int> paddings;
diff --git a/mindspore/lite/src/ops/pooling.cc b/mindspore/lite/src/ops/pooling.cc
index 57b4de165b..6e5cd459ac 100644
--- a/mindspore/lite/src/ops/pooling.cc
+++ b/mindspore/lite/src/ops/pooling.cc
@@ -181,7 +181,7 @@ int Pooling::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> out
   output->set_data_type(input->data_type());
   output->set_format(schema::Format::Format_NHWC);
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   int input_h = input->shape().at(1);
   int input_w = input->shape().at(2);
diff --git a/mindspore/lite/src/ops/power.cc b/mindspore/lite/src/ops/power.cc
index 17d85424f4..492b2ff37f 100644
--- a/mindspore/lite/src/ops/power.cc
+++ b/mindspore/lite/src/ops/power.cc
@@ -115,7 +115,7 @@ int Power::InferShape(std::vector<Tensor *> inputs, std::vector<Tensor *> output
   output_tensor->set_data_type(x_tensor->data_type());
   output_tensor->set_format(x_tensor->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   if (exp_tensor != nullptr) {
     if ((exp_tensor->shape().size() > 1 && exp_tensor->shape() != x_tensor->shape()) ||
diff --git a/mindspore/lite/src/ops/prior_box.cc b/mindspore/lite/src/ops/prior_box.cc
index 0be455d5d0..1d70ad4edf 100644
--- a/mindspore/lite/src/ops/prior_box.cc
+++ b/mindspore/lite/src/ops/prior_box.cc
@@ -140,7 +140,7 @@ int PriorBox::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> ou
   output->set_data_type(kNumberTypeFloat32);
   output->set_format(input->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   std::vector<float> different_aspect_ratios{1.0f};
   auto aspect_ratios = GetAspectRatios();
diff --git a/mindspore/lite/src/ops/quant_dtype_cast.cc b/mindspore/lite/src/ops/quant_dtype_cast.cc
index e70d087280..e7fa5a97c1 100644
--- a/mindspore/lite/src/ops/quant_dtype_cast.cc
+++ b/mindspore/lite/src/ops/quant_dtype_cast.cc
@@ -63,7 +63,7 @@ int QuantDTypeCast::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor
   output->set_data_type(static_cast<TypeId>(GetDstT()));
   output->set_format(input->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   output->set_shape(input->shape());
   return RET_OK;
diff --git a/mindspore/lite/src/ops/range.cc b/mindspore/lite/src/ops/range.cc
index baaa1c9956..29f4d4644a 100644
--- a/mindspore/lite/src/ops/range.cc
+++ b/mindspore/lite/src/ops/range.cc
@@ -71,7 +71,7 @@ int Range::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> outpu
   }
   output->set_format(input->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
 
   int shape_size = 0;
diff --git a/mindspore/lite/src/ops/rank.cc b/mindspore/lite/src/ops/rank.cc
index 1ef39d11c9..c0633e2d92 100644
--- a/mindspore/lite/src/ops/rank.cc
+++ b/mindspore/lite/src/ops/rank.cc
@@ -45,7 +45,7 @@ int Rank::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> output
   output->set_data_type(input->data_type());
   output->set_format(input->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   std::vector<int> in_shape(1, 1);
   output->set_shape(in_shape);
diff --git a/mindspore/lite/src/ops/reduce.cc b/mindspore/lite/src/ops/reduce.cc
index f23535146d..ac016dc0fb 100644
--- a/mindspore/lite/src/ops/reduce.cc
+++ b/mindspore/lite/src/ops/reduce.cc
@@ -157,7 +157,7 @@ int Reduce::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> outp
   output->set_data_type(input->data_type());
   output->set_format(input->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   if (this->primitive_ == nullptr) {
     return RET_NULL_PTR;
diff --git a/mindspore/lite/src/ops/reshape.cc b/mindspore/lite/src/ops/reshape.cc
index 2456c8ff0f..c6d91d2884 100644
--- a/mindspore/lite/src/ops/reshape.cc
+++ b/mindspore/lite/src/ops/reshape.cc
@@ -173,7 +173,7 @@ int Reshape::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> out
   output->set_data_type(input->data_type());
   output->set_format(input->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
 
   std::vector<int> out_shape;
diff --git a/mindspore/lite/src/ops/resize.cc b/mindspore/lite/src/ops/resize.cc
index 12f57ba512..0bb5ea3681 100644
--- a/mindspore/lite/src/ops/resize.cc
+++ b/mindspore/lite/src/ops/resize.cc
@@ -131,7 +131,7 @@ int Resize::InferShape(std::vector<lite::Tensor *> inputs_, std::vector<lite::Te
   output->set_data_type(input->data_type());
   output->set_format(input->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
 
   std::vector<int> output_shape;
diff --git a/mindspore/lite/src/ops/return.cc b/mindspore/lite/src/ops/return.cc
index d7120104b3..401c886001 100644
--- a/mindspore/lite/src/ops/return.cc
+++ b/mindspore/lite/src/ops/return.cc
@@ -72,7 +72,7 @@ int Return::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> outp
   output->set_data_type(input->data_type());
   output->set_format(input->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   if (this->primitive_ == nullptr) {
     return RET_NULL_PTR;
diff --git a/mindspore/lite/src/ops/reverse_sequence.cc b/mindspore/lite/src/ops/reverse_sequence.cc
index 42b908b875..08c52ebcd4 100644
--- a/mindspore/lite/src/ops/reverse_sequence.cc
+++ b/mindspore/lite/src/ops/reverse_sequence.cc
@@ -66,7 +66,7 @@ int ReverseSequence::InferShape(std::vector<Tensor *> inputs, std::vector<Tensor
   output->set_data_type(input->data_type());
   output->set_format(input->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   output->set_shape(input->shape());
   return RET_OK;
diff --git a/mindspore/lite/src/ops/rfft.cc b/mindspore/lite/src/ops/rfft.cc
index 09378f2470..559f25e9b9 100644
--- a/mindspore/lite/src/ops/rfft.cc
+++ b/mindspore/lite/src/ops/rfft.cc
@@ -54,7 +54,7 @@ int Rfft::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> output
   output->set_data_type(TypeId::kNumberTypeComplex64);
   output->set_format(input->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   auto input_shape = input->shape();
   input_shape[input_shape.size() - 1] = GetFftLength() / 2 + 1;
diff --git a/mindspore/lite/src/ops/roi_pooling.cc b/mindspore/lite/src/ops/roi_pooling.cc
index 260da92804..6a0704392e 100644
--- a/mindspore/lite/src/ops/roi_pooling.cc
+++ b/mindspore/lite/src/ops/roi_pooling.cc
@@ -79,7 +79,7 @@ int ROIPooling::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *>
   output->set_data_type(input->data_type());
   output->set_format(input->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
 
   auto new_h = GetPooledH();
diff --git a/mindspore/lite/src/ops/scatter_nd.cc b/mindspore/lite/src/ops/scatter_nd.cc
index 0767d19a70..fb5239fdd0 100644
--- a/mindspore/lite/src/ops/scatter_nd.cc
+++ b/mindspore/lite/src/ops/scatter_nd.cc
@@ -62,7 +62,7 @@ int ScatterND::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> o
   output->set_data_type(update->data_type());
   output->set_format(update->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   auto shape_data = reinterpret_cast<int *>(shape->MutableData());
   std::vector<int> out_shape(shape_data, shape_data + shape->ElementsNum());
diff --git a/mindspore/lite/src/ops/shape.cc b/mindspore/lite/src/ops/shape.cc
index ebd976b98c..f98c3604bf 100644
--- a/mindspore/lite/src/ops/shape.cc
+++ b/mindspore/lite/src/ops/shape.cc
@@ -44,7 +44,7 @@ int Shape::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> outpu
   out_tensor->set_data_type(kNumberTypeInt32);
   out_tensor->set_format(schema::Format::Format_NHWC);
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   std::vector<int> out_shape;
   out_shape.push_back(static_cast<int>(in_tensor->shape().size()));
diff --git a/mindspore/lite/src/ops/slice.cc b/mindspore/lite/src/ops/slice.cc
index d25e4d6d80..378bbfa653 100644
--- a/mindspore/lite/src/ops/slice.cc
+++ b/mindspore/lite/src/ops/slice.cc
@@ -175,7 +175,7 @@ int Slice::InferShape(std::vector<lite::Tensor *> inputs, std::vector<lite::Tens
   outputs[0]->set_data_type(input->data_type());
   outputs[0]->set_format(input->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   auto input_shape = input->shape();
   std::vector<int32_t> slice_begin(GetBegin());
diff --git a/mindspore/lite/src/ops/softmax.cc b/mindspore/lite/src/ops/softmax.cc
index 62adaada57..e8ae684939 100644
--- a/mindspore/lite/src/ops/softmax.cc
+++ b/mindspore/lite/src/ops/softmax.cc
@@ -86,7 +86,7 @@ int SoftMax::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> out
   output->set_data_type(input->data_type());
   output->set_format(input->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   if (input->shape().size() > 5) {
     MS_LOG(ERROR) << "Softmax input dim must be less than 5, get " << input->shape().size();
diff --git a/mindspore/lite/src/ops/space_to_batch.cc b/mindspore/lite/src/ops/space_to_batch.cc
index 205db3e855..4c13eea799 100644
--- a/mindspore/lite/src/ops/space_to_batch.cc
+++ b/mindspore/lite/src/ops/space_to_batch.cc
@@ -97,7 +97,7 @@ int SpaceToBatch::InferShape(std::vector<lite::Tensor *> inputs, std::vector<lit
   outputs[0]->set_data_type(input->data_type());
   outputs[0]->set_format(input->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   auto input_shape = input->shape();
   if (input_shape.size() != kDimension_4d) {
diff --git a/mindspore/lite/src/ops/space_to_batch_nd.cc b/mindspore/lite/src/ops/space_to_batch_nd.cc
index a64e9b1160..68b24ebf5b 100644
--- a/mindspore/lite/src/ops/space_to_batch_nd.cc
+++ b/mindspore/lite/src/ops/space_to_batch_nd.cc
@@ -99,7 +99,7 @@ int SpaceToBatchND::InferShape(std::vector<lite::Tensor *> inputs, std::vector<l
   outputs[0]->set_data_type(input->data_type());
   outputs[0]->set_format(input->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   auto input_shape = input->shape();
   if (input_shape.size() != kDimension_4d) {
diff --git a/mindspore/lite/src/ops/space_to_depth.cc b/mindspore/lite/src/ops/space_to_depth.cc
index b98be02b2e..23bdf22a50 100644
--- a/mindspore/lite/src/ops/space_to_depth.cc
+++ b/mindspore/lite/src/ops/space_to_depth.cc
@@ -74,7 +74,7 @@ int SpaceToDepth::InferShape(std::vector<lite::Tensor *> inputs, std::vector<lit
   outputs[0]->set_format(input->format());
   outputs[0]->set_data_type(input->data_type());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   auto input_shape = input->shape();
   if (input_shape.size() != kDimension_4d) {
diff --git a/mindspore/lite/src/ops/sparse_to_dense.cc b/mindspore/lite/src/ops/sparse_to_dense.cc
index 6c9a4cd340..4332fb3d15 100644
--- a/mindspore/lite/src/ops/sparse_to_dense.cc
+++ b/mindspore/lite/src/ops/sparse_to_dense.cc
@@ -64,7 +64,7 @@ int SparseToDense::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor
   outputs_[0]->set_format(input2->format());
 
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   if (this->primitive_ == nullptr) {
     return RET_NULL_PTR;
diff --git a/mindspore/lite/src/ops/split.cc b/mindspore/lite/src/ops/split.cc
index ad2e8ecb41..795b7a33d2 100644
--- a/mindspore/lite/src/ops/split.cc
+++ b/mindspore/lite/src/ops/split.cc
@@ -123,7 +123,7 @@ int Split::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> outpu
     outputs_[i]->set_format(input->format());
   }
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   size_t split_dim = GetSplitDim() == -1 ? input->shape().size() - 1 : GetSplitDim();
   std::vector<int> input_shape = input->shape();
diff --git a/mindspore/lite/src/ops/squeeze.cc b/mindspore/lite/src/ops/squeeze.cc
index 3cf4435d02..1a4836fb01 100644
--- a/mindspore/lite/src/ops/squeeze.cc
+++ b/mindspore/lite/src/ops/squeeze.cc
@@ -105,7 +105,7 @@ int Squeeze::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> out
   outputs_.front()->set_data_type(in_tensor->data_type());
   outputs_.front()->set_format(in_tensor->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   auto in_shape = in_tensor->shape();
   std::vector<int> out_shape;
diff --git a/mindspore/lite/src/ops/stack.cc b/mindspore/lite/src/ops/stack.cc
index f6bee87c56..81f8cae669 100644
--- a/mindspore/lite/src/ops/stack.cc
+++ b/mindspore/lite/src/ops/stack.cc
@@ -83,7 +83,7 @@ int Stack::InferShape(std::vector<Tensor *> inputs, std::vector<Tensor *> output
   outputs[0]->set_data_type(input0_data_type);
   outputs[0]->set_format(input->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   auto input_shape = input->shape();
 
diff --git a/mindspore/lite/src/ops/tile.cc b/mindspore/lite/src/ops/tile.cc
index 5dd481cbc2..9f42d0006b 100644
--- a/mindspore/lite/src/ops/tile.cc
+++ b/mindspore/lite/src/ops/tile.cc
@@ -135,7 +135,7 @@ int Tile::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> output
   output->set_data_type(input->data_type());
   output->set_format(input->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
 
   std::vector<int> out_shape;
diff --git a/mindspore/lite/src/ops/topk.cc b/mindspore/lite/src/ops/topk.cc
index 07e71a31de..1bb8816197 100644
--- a/mindspore/lite/src/ops/topk.cc
+++ b/mindspore/lite/src/ops/topk.cc
@@ -69,7 +69,7 @@ int TopK::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> output
   output1->set_data_type(kNumberTypeInt32);
   output1->set_format(input->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   auto out_shape = input->shape();
   out_shape[out_shape.size() - 1] = GetK();
diff --git a/mindspore/lite/src/ops/transpose.cc b/mindspore/lite/src/ops/transpose.cc
index f6ef25a9f9..7ebd8752bb 100644
--- a/mindspore/lite/src/ops/transpose.cc
+++ b/mindspore/lite/src/ops/transpose.cc
@@ -122,7 +122,7 @@ int Transpose::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> o
   output->set_data_type(input->data_type());
   output->set_format(input->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   MS_ASSERT(inputs_.size() == kSingleNum || inputs_.size() == kDoubleNum);
   MS_ASSERT(outputs_.size() == kSingleNum);
diff --git a/mindspore/lite/src/ops/unique.cc b/mindspore/lite/src/ops/unique.cc
index 69dff48528..367364552d 100644
--- a/mindspore/lite/src/ops/unique.cc
+++ b/mindspore/lite/src/ops/unique.cc
@@ -65,7 +65,7 @@ int Unique::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> outp
   output1->set_format(input->format());
   output0->set_format(input->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   output0->set_shape(input->shape());
   output1->set_shape(input->shape());
diff --git a/mindspore/lite/src/ops/unsqueeze.cc b/mindspore/lite/src/ops/unsqueeze.cc
index 930feba040..8a3f1770ab 100644
--- a/mindspore/lite/src/ops/unsqueeze.cc
+++ b/mindspore/lite/src/ops/unsqueeze.cc
@@ -78,7 +78,7 @@ int Unsqueeze::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> o
   output->set_data_type(input->data_type());
   output->set_format(input->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
 
   auto dims = GetAxis();
diff --git a/mindspore/lite/src/ops/unstack.cc b/mindspore/lite/src/ops/unstack.cc
index 0e2954ecd7..52deeafabb 100644
--- a/mindspore/lite/src/ops/unstack.cc
+++ b/mindspore/lite/src/ops/unstack.cc
@@ -66,7 +66,7 @@ int Unstack::InferShape(std::vector<Tensor *> inputs, std::vector<Tensor *> outp
     out->set_format(input->format());
   }
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   std::vector<int> output_shape;
   for (size_t i = 0; i < input_shape.size(); ++i) {
diff --git a/mindspore/lite/src/ops/where.cc b/mindspore/lite/src/ops/where.cc
index cc85c95b89..915c7ee132 100644
--- a/mindspore/lite/src/ops/where.cc
+++ b/mindspore/lite/src/ops/where.cc
@@ -81,7 +81,7 @@ int Where::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> outpu
   output->set_data_type(input->data_type());
   output->set_format(input->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   int num = input0->ElementsNum();
   int num1 = input1->ElementsNum();
diff --git a/mindspore/lite/src/ops/zeros_like.cc b/mindspore/lite/src/ops/zeros_like.cc
index 2fe8b52634..9e1b656ffc 100644
--- a/mindspore/lite/src/ops/zeros_like.cc
+++ b/mindspore/lite/src/ops/zeros_like.cc
@@ -56,7 +56,7 @@ int ZerosLike::InferShape(std::vector<lite::Tensor *> inputs_, std::vector<lite:
   output->set_data_type(input->data_type());
   output->set_format(input->format());
   if (!infer_flag()) {
-    return RET_OK;
+    return RET_INFER_INVALID;
   }
   output->set_shape(input->shape());
   return RET_OK;