Deprecate torchscript frontend #3373
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There are some changes that do not conform to C++ style guidelines:
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
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There was a problem hiding this comment.
There are some changes that do not conform to C++ 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
There was a problem hiding this comment.
There are some changes that do not conform to Python 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):
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Description
Deprecate the TS frontend, Dynamo can be used in conjunction with TorchScript to get the same deployment feature set + the extra operator support.
Fixes # (issue)
Type of change
Please delete options that are not relevant and/or add your own.
Checklist: