nan metric breaking ModelCheckpoint
🐛 Bug
Comparing any numbers to float('nan') is False in Python so as a result if a non-loss metric score is nan initially in training, then callback cannot checkpoint any scores after.
Expected behavior
Ignore a nan metric score. This is orthogonal to when grad or weights become nan.
Environment

PyTorch Version (e.g., 1.0): 1.5.0
OS (e.g., Linux): Linux
How you installed PyTorch (conda, pip, source): pip
Build command you used (if compiling from source):
Python version: 3.6
CUDA/cuDNN version: 10.0
GPU models and configuration: Tesla V100

Additional context
Previous issue wasn't addressed completely #1008