`num_training_batches` can be 0 if `train_percent_check` is too small
🐛 Bug
if train_percent_check is set to a tiny value, then num_training_batches can be 0. Then no training happens, and no validation either, but no warning is raised and epochs are normally iterated over.
To Reproduce
Train on any dataset using limit sufficiently small (eg 0.01).
Code sample
I think there is a simple fix, in data_loading.py, adding a line after l. 171
            (l.171) self.num_training_batches = int(self.num_training_batches * self.train_percent_check)
            self.num_training_batches = max(1, self.num_training_batches)

Expected behavior
Training at least on 1 batch to have a quick check.
Environment

CUDA:
- GPU:
- available:         False
- version:           None
Packages:
- numpy:             1.18.4
- pyTorch_debug:     False
- pyTorch_version:   1.5.0
- pytorch-lightning: 0.7.6rc3
- tensorboard:       2.2.1
- tqdm:              4.46.0
System:
- OS:                Linux
- architecture:
- 64bit
- ELF
- processor:         x86_64
- python:            3.8.2
- version:           #864-Microsoft Thu Nov 07 15:22:00 PST 2019