diff --git a/mindspore/core/ops/softmax.cc b/mindspore/core/ops/softmax.cc
index 7e76bf0872..0df32d9275 100644
--- a/mindspore/core/ops/softmax.cc
+++ b/mindspore/core/ops/softmax.cc
@@ -46,15 +46,24 @@ void Softmax::Init(const int64_t axis) {
 
 abstract::ShapePtr SoftMaxInferShape(const PrimitivePtr &primitive, const std::vector<AbstractBasePtr> &input_args) {
   MS_EXCEPTION_IF_NULL(primitive);
-  auto Softmax_prim = primitive->cast<PrimSoftmaxPtr>();
-  MS_EXCEPTION_IF_NULL(Softmax_prim);
-  auto op_name = Softmax_prim->name();
-  auto axis = Softmax_prim->get_axis();
-  auto in_shape = CheckAndConvertUtils::ConvertShapePtrToShape("input_shape", input_args[0]->GetShapeTrack(), op_name);
+  auto op_name = primitive->name();
+  auto axis = GetValue<std::vector<int64_t>>(primitive->GetAttr(kAxis));
+  (void)CheckAndConvertUtils::CheckValue<size_t>("length of axis", axis.size(), kGreaterEqual, 1, op_name);
+  auto shape_map = CheckAndConvertUtils::ConvertShapePtrToShapeMap(input_args[0]->BuildShape());
+  if (shape_map.empty()) {
+    // Scalar input, has no shape
+    return std::make_shared<abstract::Shape>(std::vector<int64_t>());
+  }
+  auto in_shape = shape_map[kShape];
+  auto min_shape = shape_map[kMinShape];
+  auto max_shape = shape_map[kMaxShape];
   auto rank = SizeToLong(in_shape.size());
   for (auto &item : axis) {
     CheckAndConvertUtils::CheckInRange<int64_t>("axis", item, kIncludeLeft, {-rank, rank}, op_name);
   }
+  if (min_shape.size() != 0 && max_shape.size() != 0) {
+    return std::make_shared<abstract::Shape>(in_shape, min_shape, max_shape);
+  }
   return std::make_shared<abstract::Shape>(in_shape);
 }
 
@@ -71,6 +80,7 @@ AbstractBasePtr SoftmaxInfer(const abstract::AnalysisEnginePtr &, const Primitiv
   return std::make_shared<abstract::AbstractTensor>(SoftMaxInferType(primitive, input_args),
                                                     SoftMaxInferShape(primitive, input_args)->shape());
 }
+REGISTER_PRIMITIVE_EVAL_IMPL(Softmax, prim::kPrimSoftmax, SoftmaxInfer, nullptr, true);
 REGISTER_PRIMITIVE_C(kNameSoftmax, Softmax);
 }  // namespace ops
 }  // namespace mindspore
diff --git a/mindspore/ops/operations/nn_ops.py b/mindspore/ops/operations/nn_ops.py
index 659c1a8c71..cd1f2239e6 100644
--- a/mindspore/ops/operations/nn_ops.py
+++ b/mindspore/ops/operations/nn_ops.py
@@ -177,17 +177,6 @@ class Softmax(PrimitiveWithInfer):
         for item in self.axis:
             validator.check_value_type("item of axis", item, [int], self.name)
 
-    def infer_shape(self, logits):
-        validator.check_int(len(self.axis), 1, Rel.GE, "length of axis", self.name)
-        rank = len(logits)
-        for axis_v in self.axis:
-            validator.check_int_range(axis_v, -rank, rank, Rel.INC_LEFT, "axis", self.name)
-        return logits
-
-    def infer_dtype(self, logits):
-        validator.check_tensor_dtype_valid("logits", logits, mstype.float_type, self.name)
-        return logits
-
 
 class LogSoftmax(PrimitiveWithInfer):
     r"""