[BUG] AvgOnnxLatency blows up if you have installed multiple Onnx RuntimeProviders

[lovettchris]

Describe the bug

The AvgOnnLatency evaluator creates an OnnxRuntime InferenceSession and InferenceSession requires that you specify the runtime provider when multiple are available, otherwise it throws an error.

To Reproduce
Steps to reproduce the behavior:

1. Install multiple OnnxRuntime providers (eg. CPU and CUDA).
2. Run this code:

import onnxruntime as rt
onnx_session = rt.InferenceSession('model.onnx')

3. See error

ValueError: This ORT build has ['TensorrtExecutionProvider', 'CUDAExecutionProvider', 'CPUExecutionProvider'] enabled. Since ORT 1.9, you are required to explicitly set the providers parameter when instantiating InferenceSession. For example, onnxruntime.InferenceSession(..., providers=['TensorrtExecutionProvider', 'CUDAExecutionProvider', 'CPUExecutionProvider'], ...)

Expected behavior

AvgOnnLatency should allow me to specify which device to use like this: e = AvgOnnLatency(device='gpu').

Screenshots
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Desktop (please complete the following information):

• OS: [e.g. Ubuntu Linux]
• Virtual Environment [e.g. conda, venv]
• Python Version [e.g. 3.7]

Additional context
Add any other context about the problem here.