'No TPU devices were found' continues to exist for v2-32.
🐛 Bug
The error is still similar to that previously, as described in #6778. I am running the check code with pytorch-lightning master branch.
All the 3 slaves show the same exception.
raceback (most recent call last):
  File "/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/pytorch_lightning/utilities/xla_device.py", line 31, in inner_f
    queue.put(func(*args, **kwargs))
  File "/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/pytorch_lightning/utilities/xla_device.py", line 70, in _is_device_tpu
    return len(xm.get_xla_supported_devices("TPU")) > 0
  File "/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/torch_xla/core/xla_model.py", line 136, in get_xla_supported_devices
    xla_devices = _DEVICES.value
  File "/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/torch_xla/utils/utils.py", line 32, in value
    self._value = self._gen_fn()
  File "/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/torch_xla/core/xla_model.py", line 18, in <lambda>
    _DEVICES = xu.LazyProperty(lambda: torch_xla._XLAC._xla_get_devices())
RuntimeError: tensorflow/compiler/xla/xla_client/xrt_computation_client.cc:258 : Check failed: default_device_target != options_.global_device_map.end() 
*** Begin stack trace ***
	tensorflow::CurrentStackTrace()
	xla::XrtComputationClient::XrtComputationClient(xla::XrtComputationClient::Options, std::unique_ptr<tensorflow::tpu::TopologyProto, std::default_delete<tensorflow::tpu::TopologyProto> >, xla::XrtLocalService*)
	xla::ComputationClient::Create()
	
	
	xla::ComputationClient::Get()
	
	
	_PyCFunction_FastCallDict
	
	_PyEval_EvalFrameDefault
	
	
	_PyEval_EvalFrameDefault
	PyEval_EvalCodeEx
	
	PyObject_Call
	
	_PyObject_GenericGetAttrWithDict
	_PyEval_EvalFrameDefault
	
	
	
	_PyEval_EvalFrameDefault
	PyEval_EvalCodeEx
	
	PyObject_Call
	_PyEval_EvalFrameDefault
	PyEval_EvalCodeEx
	
	PyObject_Call
	_PyEval_EvalFrameDefault
	
	
	_PyEval_EvalFrameDefault
	
	
	_PyEval_EvalFrameDefault
	
	
	_PyEval_EvalFrameDefault
	_PyFunction_FastCallDict
	_PyObject_FastCallDict
	_PyObject_Call_Prepend
	PyObject_Call
	
	
	_PyObject_FastCallDict
	
	_PyEval_EvalFrameDefault
	
	
	_PyEval_EvalFrameDefault
	
	
	_PyEval_EvalFrameDefault
	
	
	_PyEval_EvalFrameDefault
	
	
	
	_PyEval_EvalFrameDefault
	
	
	_PyEval_EvalFrameDefault
	PyEval_EvalCodeEx
	PyEval_EvalCode
	
	PyCFunction_Call
	_PyEval_EvalFrameDefault
	
	
	
	_PyEval_EvalFrameDefault
	
	
	_PyEval_EvalFrameDefault
	
	
	_PyEval_EvalFrameDefault
	
	
	_PyEval_EvalFrameDefault
	_PyFunction_FastCallDict
	_PyObject_FastCallDict
	_PyObject_CallMethodIdObjArgs
	PyImport_ImportModuleLevelObject
	_PyEval_EvalFrameDefault
	PyEval_EvalCodeEx
	PyEval_EvalCode
	
	PyCFunction_Call
	_PyEval_EvalFrameDefault
	
	
	
	_PyEval_EvalFrameDefault
	
	
	_PyEval_EvalFrameDefault
	
	
	_PyEval_EvalFrameDefault
	
	
	_PyEval_EvalFrameDefault
	_PyFunction_FastCallDict
	_PyObject_FastCallDict
	_PyObject_CallMethodIdObjArgs
	PyImport_ImportModuleLevelObject
	_PyEval_EvalFrameDefault
	PyEval_EvalCodeEx
	PyEval_EvalCode
	
	PyCFunction_Call
	_PyEval_EvalFrameDefault
	
	
	
	_PyEval_EvalFrameDefault
	
	
	_PyEval_EvalFrameDefault
	
	
	_PyEval_EvalFrameDefault
	
*** End stack trace ***

/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/pytorch_lightning/utilities/distributed.py:52: UserWarning: ModelCheckpoint(save_last=True, save_top_k=None, monitor=None) is a redundant configuration. You can save the last checkpoint with ModelCheckpoint(save_top_k=None, monitor=None).
  warnings.warn(*args, **kwargs)
Traceback (most recent call last):
  File "play.py", line 119, in <module>
    main()
  File "play.py", line 102, in main
    checkpoint_callback=checkpointer,
  File "/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/pytorch_lightning/trainer/connectors/env_vars_connector.py", line 40, in insert_env_defaults
    return fn(self, **kwargs)
  File "/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/pytorch_lightning/trainer/trainer.py", line 307, in __init__
    replace_sampler_ddp, deterministic, precision, amp_backend, amp_level, plugins
  File "/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/pytorch_lightning/trainer/connectors/accelerator_connector.py", line 97, in __init__
    self.tpu_cores = device_parser.parse_tpu_cores(tpu_cores)
  File "/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/pytorch_lightning/utilities/device_parser.py", line 113, in parse_tpu_cores
    raise MisconfigurationException('No TPU devices were found.')
pytorch_lightning.utilities.exceptions.MisconfigurationException: No TPU devices were found.

The master node looks ok:
GPU available: False, used: False
TPU available: True, using: 8 TPU cores

To Reproduce
the same as #6778