`num_tpu_cores=8` does not work on kaggle
🐛 Bug
When I try to train a model on Kaggle TPU's with num_tpu_cores set to 8, I receive an error Exception: process 2 terminated with exit code 1 . Would be great if this worked on kaggle.
To Reproduce
Steps to reproduce the behavior:

Run this notebook:
https://www.kaggle.com/lezwon/pytorch-on-tpu-with-pytorch-lightning


---------------------------------------------------------------------------
Exception                                 Traceback (most recent call last)
<ipython-input-9-9251330963d1> in <module>
      3 # most basic trainer, uses good defaults (1 TPU)
      4 trainer = pl.Trainer(num_tpu_cores=8)
----> 5 trainer.fit(mnist_model)

/opt/conda/lib/python3.6/site-packages/pytorch_lightning/trainer/trainer.py in fit(self, model, train_dataloader, val_dataloaders, test_dataloaders)
    714 
    715             # train
--> 716             xmp.spawn(self.tpu_train, args=(model,), nprocs=self.num_tpu_cores, start_method=start_method)
    717 
    718             # load weights if not interrupted

/opt/conda/lib/python3.6/site-packages/torch_xla/distributed/xla_multiprocessing.py in spawn(fn, args, nprocs, join, daemon, start_method)
    180         join=join,
    181         daemon=daemon,
--> 182         start_method=start_method)

/opt/conda/lib/python3.6/site-packages/torch/multiprocessing/spawn.py in start_processes(fn, args, nprocs, join, daemon, start_method)
    156 
    157     # Loop on join until it returns True or raises an exception.
--> 158     while not context.join():
    159         pass
    160 

/opt/conda/lib/python3.6/site-packages/torch/multiprocessing/spawn.py in join(self, timeout)
    111                 raise Exception(
    112                     "process %d terminated with exit code %d" %
--> 113                     (error_index, exitcode)
    114                 )
    115 

Exception: process 3 terminated with exit code 1

Code sample
trainer = pl.Trainer(num_tpu_cores=8, precision=16) 
Expected behavior
Run the model utilizing all 8 TPU cores.
Environment
cuda:
	GPU:
	available:           False
	version:             None
packages:
	numpy:               1.18.2
	pyTorch_debug:       False
	pyTorch_version:     1.6.0a0+30e7055
	pytorch-lightning:   0.7.3
	tensorboard:         2.1.1
	tqdm:                4.42.0
system:
	OS:                  Linux
	architecture:
		64bit
		
	processor:           
	python:              3.6.6
	version:             #1 SMP Sat Apr 4 00:12:45 PDT 2020