diff --git a/home/runner/work/TensorRT/TensorRT/cpp/include/torch_tensorrt/ptq.h b/tmp/changes.txt
index 50f63f8..3a05b3b 100644
--- a/home/runner/work/TensorRT/TensorRT/cpp/include/torch_tensorrt/ptq.h
+++ b/tmp/changes.txt
@@ -59,7 +59,7 @@ class Int8Calibrator : Algorithm {
   * calibration cache
   * @param use_cache : bool - Whether to use the cache (if it exists)
   */
-   Int8Calibrator(DataLoaderUniquePtr dataloader, const std::string& cache_file_path, bool use_cache)
+  Int8Calibrator(DataLoaderUniquePtr dataloader, const std::string& cache_file_path, bool use_cache)
      : dataloader_(dataloader.get()), cache_file_path_(cache_file_path), use_cache_(use_cache) {
    for (auto batch : *dataloader_) {
      batched_data_.push_back(batch.data);
@@ -309,11 +309,10 @@ class Int8CacheCalibrator : Algorithm {
 * @return Int8Calibrator<Algorithm, DataLoader>
 */
template <typename Algorithm = nvinfer1::IInt8EntropyCalibrator2, typename DataLoader>
-[[deprecated("Int8 PTQ Calibrator has been deprecated by TensorRT, please plan on porting to a NVIDIA Model Optimizer Toolkit based workflow. See: https://pytorch.org/TensorRT/tutorials/_rendered_examples/dynamo/vgg16_ptq.html for more details")]]
-inline Int8Calibrator<Algorithm, DataLoader> make_int8_calibrator(
-    DataLoader dataloader,
-    const std::string& cache_file_path,
-    bool use_cache) {
+[[deprecated("Int8 PTQ Calibrator has been deprecated by TensorRT, please plan on porting to a NVIDIA Model Optimizer Toolkit based workflow. See: https://pytorch.org/TensorRT/tutorials/_rendered_examples/dynamo/vgg16_ptq.html for more details")]] inline Int8Calibrator<
+    Algorithm,
+    DataLoader>
+make_int8_calibrator(DataLoader dataloader, const std::string& cache_file_path, bool use_cache) {
  return Int8Calibrator<Algorithm, DataLoader>(std::move(dataloader), cache_file_path, use_cache);
}

@@ -344,8 +343,9 @@ inline Int8Calibrator<Algorithm, DataLoader> make_int8_calibrator(
 * @return Int8CacheCalibrator<Algorithm>
 */
template <typename Algorithm = nvinfer1::IInt8EntropyCalibrator2>
-[[deprecated("Int8 PTQ Calibrator has been deprecated by TensorRT, please plan on porting to a NVIDIA Model Optimizer Toolkit based workflow. See: https://pytorch.org/TensorRT/tutorials/_rendered_examples/dynamo/vgg16_ptq.html for more details")]]
-inline Int8CacheCalibrator<Algorithm> make_int8_cache_calibrator(const std::string& cache_file_path) {
+[[deprecated("Int8 PTQ Calibrator has been deprecated by TensorRT, please plan on porting to a NVIDIA Model Optimizer Toolkit based workflow. See: https://pytorch.org/TensorRT/tutorials/_rendered_examples/dynamo/vgg16_ptq.html for more details")]] inline Int8CacheCalibrator<
+    Algorithm>
+make_int8_cache_calibrator(const std::string& cache_file_path) {
  return Int8CacheCalibrator<Algorithm>(cache_file_path);
}

ERROR: Some files do not conform to style guidelines

diff --git a/home/runner/work/TensorRT/TensorRT/cpp/include/torch_tensorrt/ptq.h b/tmp/changes.txt
index ae8aa07..a2f8234 100644
--- a/home/runner/work/TensorRT/TensorRT/cpp/include/torch_tensorrt/ptq.h
+++ b/tmp/changes.txt
@@ -59,7 +59,7 @@ class Int8Calibrator : Algorithm {
   * calibration cache
   * @param use_cache : bool - Whether to use the cache (if it exists)
   */
-   Int8Calibrator(DataLoaderUniquePtr dataloader, const std::string& cache_file_path, bool use_cache)
+  Int8Calibrator(DataLoaderUniquePtr dataloader, const std::string& cache_file_path, bool use_cache)
      : dataloader_(dataloader.get()), cache_file_path_(cache_file_path), use_cache_(use_cache) {
    for (auto batch : *dataloader_) {
      batched_data_.push_back(batch.data);
@@ -343,7 +343,8 @@ TORCH_TENSORRT_PTQ_DEPRECATION inline Int8Calibrator<Algorithm, DataLoader> make
 * @return Int8CacheCalibrator<Algorithm>
 */
template <typename Algorithm = nvinfer1::IInt8EntropyCalibrator2>
-TORCH_TENSORRT_PTQ_DEPRECATION inline Int8CacheCalibrator<Algorithm> make_int8_cache_calibrator(const std::string& cache_file_path) {
+TORCH_TENSORRT_PTQ_DEPRECATION inline Int8CacheCalibrator<Algorithm> make_int8_cache_calibrator(
+    const std::string& cache_file_path) {
  return Int8CacheCalibrator<Algorithm>(cache_file_path);
}

diff --git a/home/runner/work/TensorRT/TensorRT/cpp/include/torch_tensorrt/macros.h b/tmp/changes.txt
index 5fce518..bdc25f6 100644
--- a/home/runner/work/TensorRT/TensorRT/cpp/include/torch_tensorrt/macros.h
+++ b/tmp/changes.txt
@@ -30,7 +30,9 @@
  STR(TORCH_TENSORRT_MAJOR_VERSION) \
  "." STR(TORCH_TENSORRT_MINOR_VERSION) "." STR(TORCH_TENSORRT_PATCH_VERSION)

-#define TORCH_TENSORRT_PTQ_DEPRECATION [[deprecated("Int8 PTQ Calibrator has been deprecated by TensorRT, please plan on porting to a NVIDIA Model Optimizer Toolkit based workflow. See: https://pytorch.org/TensorRT/tutorials/_rendered_examples/dynamo/vgg16_ptq.html for more details")]]
+#define TORCH_TENSORRT_PTQ_DEPRECATION \
+  [[deprecated(                        \
+      "Int8 PTQ Calibrator has been deprecated by TensorRT, please plan on porting to a NVIDIA Model Optimizer Toolkit based workflow. See: https://pytorch.org/TensorRT/tutorials/_rendered_examples/dynamo/vgg16_ptq.html for more details")]]
// Setup namespace aliases for ease of use
namespace torch_tensorrt {
namespace torchscript {}
ERROR: Some files do not conform to style guidelines

--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/ts/_compiler.py	2025-01-31 19:46:47.225172+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/ts/_compiler.py	2025-01-31 19:47:11.147582+00:00
@@ -104,11 +104,11 @@
    """

    warnings.warn(
        'The torchscript frontend for Torch-TensorRT has been deprecated, please plan on porting to the dynamo frontend (torch_tensorrt.compile(..., ir="dynamo"). Torchscript will continue to be a supported deployment format via post compilation torchscript tracing, see: https://pytorch.org/TensorRT/user_guide/saving_models.html for more details',
        DeprecationWarning,
-        stacklevel=2
+        stacklevel=2,
    )

    input_list = list(inputs) if inputs is not None else []
    enabled_precisions_set = (
        enabled_precisions if enabled_precisions is not None else set()
@@ -248,11 +248,11 @@
        bytes: Serialized TensorRT engine, can either be saved to a file or deserialized via TensorRT APIs
    """
    warnings.warn(
        'The torchscript frontend for Torch-TensorRT has been deprecated, please plan on porting to the dynamo frontend (torch_tensorrt.convert_method_to_trt_engine(..., ir="dynamo"). Torchscript will continue to be a supported deployment format via post compilation torchscript tracing, see: https://pytorch.org/TensorRT/user_guide/saving_models.html for more details',
        DeprecationWarning,
-        stacklevel=2
+        stacklevel=2,
    )

    input_list = list(inputs) if inputs is not None else []
    enabled_precisions_set = (
        enabled_precisions if enabled_precisions is not None else {torch.float}
--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/ts/ptq.py	2025-01-31 19:46:47.225172+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/ts/ptq.py	2025-01-31 19:47:11.237116+00:00
@@ -91,11 +91,11 @@

    def __new__(cls, *args: Any, **kwargs: Any) -> Self:
        warnings.warn(
            "Int8 PTQ Calibrator has been deprecated by TensorRT, please plan on porting to a NVIDIA Model Optimizer Toolkit based workflow. See: https://pytorch.org/TensorRT/tutorials/_rendered_examples/dynamo/vgg16_ptq.html for more details",
            DeprecationWarning,
-            stacklevel=2
+            stacklevel=2,
        )
        dataloader = args[0]
        algo_type = kwargs.get("algo_type", CalibrationAlgo.ENTROPY_CALIBRATION_2)
        cache_file = kwargs.get("cache_file", None)
        use_cache = kwargs.get("use_cache", False)
@@ -183,11 +183,11 @@

    def __new__(cls, *args: Any, **kwargs: Any) -> Self:
        warnings.warn(
            "Int8 PTQ Calibrator has been deprecated by TensorRT, please plan on porting to a NVIDIA Model Optimizer Toolkit based workflow. See: https://pytorch.org/TensorRT/tutorials/_rendered_examples/dynamo/vgg16_ptq.html for more details",
            DeprecationWarning,
-            stacklevel=2
+            stacklevel=2,
        )
        cache_file = args[0]
        algo_type = kwargs.get("algo_type", CalibrationAlgo.ENTROPY_CALIBRATION_2)

        if os.path.isfile(cache_file):