tvalentyn commented on code in PR #39922:
URL: https://github.com/apache/beam/pull/39922#discussion_r4020064657


##########
sdks/python/apache_beam/examples/inference/README.md:
##########
@@ -83,13 +83,19 @@ pip install torch==1.10.0
 ### TensorRT dependencies
 
 The RunInference API supports TensorRT SDK for high-performance deep learning 
inference with NVIDIA GPUs.
-To use TensorRT locally, we suggest an environment with TensorRT >= 8.0.1. 
Install TensorRT as per the
+To use TensorRT locally, we suggest an environment with TensorRT >= 10.0. 
Install TensorRT as per the
 [TensorRT Install 
Guide](https://docs.nvidia.com/deeplearning/tensorrt/install-guide/index.html). 
You
 will need to make sure the Python bindings for TensorRT are also installed 
correctly, these are available by installing the python3-libnvinfer and 
python3-libnvinfer-dev packages on your TensorRT download.
 
+TensorRT 10 or later is required. Note that a serialized TensorRT engine can 
only
+be deserialized by the TensorRT major version that built it, so an engine built
+with TensorRT 8.x must be rebuilt. TensorRT 10 and later also require a GPU 
with
+compute capability 7.5 or higher, which excludes NVIDIA Pascal and Volta GPUs

Review Comment:
   ```suggestion
   compute capability 7.5 or higher, for example, T4, L4, A100. The NVIDIA 
Pascal and Volta GPUs
   ```



##########
sdks/python/apache_beam/examples/inference/README.md:
##########
@@ -83,13 +83,19 @@ pip install torch==1.10.0
 ### TensorRT dependencies
 
 The RunInference API supports TensorRT SDK for high-performance deep learning 
inference with NVIDIA GPUs.
-To use TensorRT locally, we suggest an environment with TensorRT >= 8.0.1. 
Install TensorRT as per the
+To use TensorRT locally, we suggest an environment with TensorRT >= 10.0. 
Install TensorRT as per the
 [TensorRT Install 
Guide](https://docs.nvidia.com/deeplearning/tensorrt/install-guide/index.html). 
You
 will need to make sure the Python bindings for TensorRT are also installed 
correctly, these are available by installing the python3-libnvinfer and 
python3-libnvinfer-dev packages on your TensorRT download.
 
+TensorRT 10 or later is required. Note that a serialized TensorRT engine can 
only
+be deserialized by the TensorRT major version that built it, so an engine built
+with TensorRT 8.x must be rebuilt. TensorRT 10 and later also require a GPU 
with
+compute capability 7.5 or higher, which excludes NVIDIA Pascal and Volta GPUs
+such as the Tesla P4, P100 and V100.

Review Comment:
   ```suggestion
   such as the Tesla P4, P100 and V100 are no longer supported.
   ```



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