diff --git a/torch_npu/csrc/aten/ops/LogSumExpKernelNpu.cpp b/torch_npu/csrc/aten/ops/LogSumExpKernelNpu.cpp
index 6f9eaa480c106a32cd6a9df06e6cdcd927fccc50..a14ddfbb4ad38bd29d2e83cae119f43b9c6ee7e5 100644
--- a/torch_npu/csrc/aten/ops/LogSumExpKernelNpu.cpp
+++ b/torch_npu/csrc/aten/ops/LogSumExpKernelNpu.cpp
@@ -45,7 +45,7 @@ at::Tensor& NPUNativeFunctions::logsumexp_out(const at::Tensor& self, at::IntArr
 
 at::Tensor NPUNativeFunctions::logsumexp(const at::Tensor& self, at::IntArrayRef dims, bool keepdim) {
   auto outputSize = logsumexp_npu_output_size(self, dims, keepdim);
-  at::Tensor result =  OpPreparation::ApplyTensorWithSizes(outputSize, self.options());
+  at::Tensor result =  OpPreparation::ApplyTensor(self, outputSize);
   return logsumexp_out_nocheck(self, dims, keepdim, result);
 }
 
diff --git a/torch_npu/csrc/aten/ops/QuantizePerChannelKernelNpu.cpp b/torch_npu/csrc/aten/ops/QuantizePerChannelKernelNpu.cpp
index e7248a57b5beace3a103c563e4c5c7f1c2b783b7..2ce7443defd8c7a368077895a5d79bcd6f315f2a 100644
--- a/torch_npu/csrc/aten/ops/QuantizePerChannelKernelNpu.cpp
+++ b/torch_npu/csrc/aten/ops/QuantizePerChannelKernelNpu.cpp
@@ -83,9 +83,10 @@ at::Tensor NPUNativeFunctions::quantize_per_channel(
   } else if (dtype == at::ScalarType::QInt32) {
     outputDtype = at::kInt;
   }
-  at::Tensor result = OpPreparation::ApplyTensorWithSizes(
+  at::Tensor result = OpPreparation::ApplyTensorWithFormat(
       outputSize,
-      self.options().dtype(outputDtype));
+      self.options().dtype(outputDtype),
+      CalcuOpUtil::get_tensor_npu_format(self));
   quantize_per_channel_out_nocheck(result, self, scales, zero_points, axis, dtype);
   return result;
 }
diff --git a/torch_npu/csrc/aten/ops/QuantizePerTensorKernelNpu.cpp b/torch_npu/csrc/aten/ops/QuantizePerTensorKernelNpu.cpp
index ce83ad715fb29a4bf1686281e9dede99b0ff4b14..c2afae426b244a1278c13f1f28bc16f29c6447a0 100644
--- a/torch_npu/csrc/aten/ops/QuantizePerTensorKernelNpu.cpp
+++ b/torch_npu/csrc/aten/ops/QuantizePerTensorKernelNpu.cpp
@@ -59,17 +59,20 @@ at::Tensor NPUNativeFunctions::quantize_per_tensor(
   } else if (dtype == at::ScalarType::QInt32) {
     outputDtype = at::kInt;
   }
-  at::Tensor scaleTensor = OpPreparation::ApplyTensorWithSizes(
+  at::Tensor scaleTensor = OpPreparation::ApplyTensorWithFormat(
       {1},
-      self.options().dtype(at::kFloat));
+      self.options().dtype(at::kFloat),
+      CalcuOpUtil::get_tensor_npu_format(self));
   scaleTensor[0] = scaleFloat;
-  at::Tensor zpTensor = OpPreparation::ApplyTensorWithSizes(
+  at::Tensor zpTensor = OpPreparation::ApplyTensorWithFormat(
       {1},
-      self.options().dtype(at::kInt));
+      self.options().dtype(at::kInt),
+      CalcuOpUtil::get_tensor_npu_format(self));
   zpTensor[0] = zero_point;
-  at::Tensor result = OpPreparation::ApplyTensorWithSizes(
+  at::Tensor result = OpPreparation::ApplyTensorWithFormat(
       outputSize,
-      self.options().dtype(outputDtype));
+      self.options().dtype(outputDtype),
+      CalcuOpUtil::get_tensor_npu_format(self));
   quantize_per_tensor_out_nocheck(result, self, scaleTensor, zpTensor, dtype);
   return result;
 }
diff --git a/torch_npu/csrc/aten/ops/RenormKernelNpu.cpp b/torch_npu/csrc/aten/ops/RenormKernelNpu.cpp
index 96572651f5ed279ebfd33409e1936cf44cdf216f..3ec5d26a4c1751e92ca5a858b4226d21c7abad2e 100644
--- a/torch_npu/csrc/aten/ops/RenormKernelNpu.cpp
+++ b/torch_npu/csrc/aten/ops/RenormKernelNpu.cpp
@@ -68,9 +68,10 @@ at::Tensor& renorm_out_nocheck(
   }
   dim = CalcuOpUtil::make_wrap_dim(dim, self.dim());
   auto outputSize = renorm_npu_output_size(self, dim);
-  at::Tensor result_bak = OpPreparation::ApplyTensorWithSizes(
+  at::Tensor result_bak = OpPreparation::ApplyTensorWithFormat(
       outputSize,
-      self.options().dtype(at::kFloat));
+      self.options().dtype(at::kFloat),
+      CalcuOpUtil::get_tensor_npu_format(self));
   if(ori_type == c10::ScalarType::Half) {
     at::Tensor self_no_name = self.rename(c10::nullopt);
     at::Tensor result_no_name = result.rename(c10::nullopt);
@@ -131,9 +132,7 @@ at::Tensor& NPUNativeFunctions::renorm_out(
 at::Tensor NPUNativeFunctions::renorm(const at::Tensor& self, at::Scalar p, int64_t dim, at::Scalar maxnorm) {
   // calculate the output size
   auto outputSize = input_same_output_size(self);
-  at::Tensor result = OpPreparation::ApplyTensorWithSizes(
-      outputSize,
-      self.options());
+  at::Tensor result = OpPreparation::ApplyTensor(self);
 
   return renorm_out_nocheck(result, self, p, dim, maxnorm);
 }
diff --git a/torch_npu/csrc/aten/ops/RepeatInterLeaveKernelNpu.cpp b/torch_npu/csrc/aten/ops/RepeatInterLeaveKernelNpu.cpp
index db0f0d80f9d524b198649177ea1fd50ebbd09be3..acb1e1494ee18c0732d32cdd80d337f884048604 100644
--- a/torch_npu/csrc/aten/ops/RepeatInterLeaveKernelNpu.cpp
+++ b/torch_npu/csrc/aten/ops/RepeatInterLeaveKernelNpu.cpp
@@ -48,9 +48,7 @@ at::Tensor NPUNativeFunctions::repeat_interleave(
   }
 
   auto outputSize = repeat_interleave_npu_output_size(selfTensor, repeats, realDim);
-  at::Tensor result = OpPreparation::ApplyTensorWithSizes(
-      outputSize,
-      selfTensor.options());
+  at::Tensor result = OpPreparation::ApplyTensor(selfTensor, outputSize);
   repeat_interleave_out_npu(result, selfTensor, repeats, realDim);
 
   return result;