diff --git a/mindspore/core/ops/conv2d.cc b/mindspore/core/ops/conv2d.cc
index 720b83ae3c2..3dcabeeb98c 100644
--- a/mindspore/core/ops/conv2d.cc
+++ b/mindspore/core/ops/conv2d.cc
@@ -30,6 +30,11 @@ using mindspore::abstract::Shape;
 namespace mindspore {
 namespace ops {
 namespace {
+constexpr size_t top_padding = 0;
+constexpr size_t bottom_padding = 1;
+constexpr size_t left_padding = 2;
+constexpr size_t right_padding = 3;
+
 // check functions
 void CheckShapeAnyAndPositive(const std::string &op, const ShapeVector &shape) {
   for (size_t i = 0; i < shape.size(); ++i) {
@@ -148,12 +153,30 @@ void Conv2DPadFunction(std::vector<int64_t> *output_hw, std::vector<int64_t> *pa
   }
 }
 
-abstract::ShapePtr Conv2dInferShape(const PrimitivePtr &primitive, const std::vector<AbstractBasePtr> &input_args) {
-  MS_EXCEPTION_IF_NULL(primitive);
-  auto prim_name = primitive->name();
-  for (const auto &item : input_args) {
-    MS_EXCEPTION_IF_NULL(item);
+bool CheckConv2dShape(const std::string &prim_name, const std::vector<AbstractBasePtr> &input_args,
+                      const std::vector<int64_t> &x_shape, const std::vector<int64_t> &w_shape,
+                      const std::vector<int64_t> &padding, int64_t pad_mode, uint64_t w_axis, uint64_t h_axis) {
+  auto x_shape_ptr = CheckAndConvertUtils::GetTensorInputShape(prim_name, input_args, 0);
+  auto w_shape_ptr = CheckAndConvertUtils::GetTensorInputShape(prim_name, input_args, 1);
+  if (x_shape_ptr->IsDynamic() || w_shape_ptr->IsDynamic()) {
+    return true;
   }
+  if (w_shape[w_axis] != Shape::SHP_ANY && pad_mode != PadMode::SAME) {
+    int64_t input_height = x_shape[h_axis];
+    int64_t input_width = x_shape[w_axis];
+    if (pad_mode == PadMode::PAD) {
+      input_height += padding[left_padding] + padding[right_padding];
+      input_width += padding[top_padding] + padding[bottom_padding];
+    }
+    if (input_height < w_shape[h_axis] || input_width < w_shape[w_axis]) {
+      return false;
+    }
+  }
+  return true;
+}
+
+abstract::ShapePtr Conv2dInferShape(const PrimitivePtr &primitive, const std::vector<AbstractBasePtr> &input_args) {
+  auto prim_name = primitive->name();
   auto x_shape_map = CheckAndConvertUtils::ConvertShapePtrToShapeMap(input_args[0]->BuildShape());
   auto w_shape_map = CheckAndConvertUtils::ConvertShapePtrToShapeMap(input_args[1]->BuildShape());
   auto x_shape = x_shape_map[kShape];
@@ -216,6 +239,10 @@ abstract::ShapePtr Conv2dInferShape(const PrimitivePtr &primitive, const std::ve
   std::vector<int64_t> padding = CheckAttrIntOrTuple(primitive->GetAttr("pad"), 0, padding_num);
   int64_t pad_mode;
   CheckAndConvertUtils::GetPadModEnumValue(primitive->GetAttr("pad_mode"), &pad_mode);
+  if (!CheckConv2dShape(prim_name, input_args, x_shape, w_shape, padding, pad_mode, w_axis, h_axis)) {
+    MS_LOG(EXCEPTION)
+      << "Shape error for Conv2d, input shape's h and w after padding is less than kernel_size's h and w dims.";
+  }
   std::vector<int64_t> output_hw;
   std::vector<int64_t> pad_list;
   std::vector<int64_t> output_hw_min;
@@ -371,6 +398,7 @@ Format Conv2D::get_format() const {
 
 AbstractBasePtr Conv2dInfer(const abstract::AnalysisEnginePtr &, const PrimitivePtr &primitive,
                             const std::vector<AbstractBasePtr> &input_args) {
+  MS_EXCEPTION_IF_NULL(primitive);
   for (auto item : input_args) {
     MS_EXCEPTION_IF_NULL(item);
   }