End-to-end EfficientNet one-click benchmark

[szalpal]

This PR introdces a one-button benchmark for the EfficientNet use case.

This use case is an inference task, which combines DALI data preprocessing and EfficientNet classification on the server side.

Information about running the benchmark and explanation of some of the terms and parameters is included in the README file.

The automatization of this benchmark comprises the following actions:

1. Obtaining the EfficientNet checkpoint. This part is conducted via DeepLearningExamples repository and its torch.hub configuration.
2. Patching the DeepLearningExamples repository, so that Model Navigator can work with it.
3. Converting the EfficientNet checkpoint from PyTorch format to the TRT, using Model Navigator.
4. Creating a model_repository from the output of Model Navigator conversion and some regex-analysis on config.pbtxt.in pattern files.
5. Running tritonserver in the background.
6. Running perf_analyzer and benchmarking the solution.
7. Combining results into a single csv file.

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