[Failing Test]: Fix and re-enable the TensorRT integration test

[jrmccluskey]

What happened?

The TensorRT integration test went red when the workflow was moved from a base container with Python 3.8 to Python 3.10 as part of the 3.8 support deprecation. The problem is that the model engine staged at gs://apache-beam-ml/models/ssd_mobilenet_v2_320x320_coco17_tpu-8.trt (based on a TF Model Garden config) was built with TensorRT 8.x, and Python 3.10 containers use TensorRT 10.x. Unfortunately the documentation around loading the model from the TF side is somewhat out of date or not necessarily what we need; additionally, we need to convert the model from a TF format to a TensorRT format since we do not use the ONNX route in the test.

The gradle task for the test is :sdks:python:test-suites:dataflow:py310:tensorRTtests and is defined here:

beam/sdks/python/test-suites/dataflow/common.gradle

Line 444 in 2488ca1

def tensorRTTests = tasks.create("tensorRTtests") {

.

When testing the workflow ensure that you're running on dataflow or on a machine with a GPU, as the workflow will fail with CUDA error 35 if there isn't a GPU present.

Issue Failure

Failure: Test is continually failing

Issue Priority

Priority: 2 (backlog / disabled test but we think the product is healthy)

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