precision parameter in Trainer does not accept "16" passed as str

[pkubik]

Bug description

When you try to create Trainer with wrong value for precision it provides correct values as:

MisconfigurationException("Precision '<wrong value>' is invalid. Allowed precision values: ('16', '32', '64', 'bf16')")

This indicate that the values are supposed to be string. However, later when I pass "16" as a value. It fails with:

RuntimeError('No precision set')

Only value 16 passed as an integer works right now. It causes problems with some configuration frameworks or hyperparam optimization libraries. They often do not work with unions.

How to reproduce the bug

import pytorch_lightning as pl
pl.Trainer(precision="16")

Error messages and logs

File ~/myenv/python3.9/site-packages/pytorch_lightning/trainer/connectors/accelerator_connector.py:226, in AcceleratorConnector.__init__(self, devices, num_nodes, accelerator, strategy, plugins, precision, amp_type, amp_level, sync_batchnorm, benchmark, replace_sampler_ddp, deterministic, auto_select_gpus, num_processes, tpu_cores, ipus, gpus)
    223 self._init_strategy()
    225 # 5. Instantiate Precision Plugin
--> 226 self.precision_plugin = self._check_and_init_precision()
    228 # 6. Instantiate Strategy - Part 2
    229 self._lazy_init_strategy()

File ~/myenv/python3.9/site-packages/pytorch_lightning/trainer/connectors/accelerator_connector.py:735, in AcceleratorConnector._check_and_init_precision(self)
    732         self._amp_level_flag = self._amp_level_flag or "O2"
    733         return ApexMixedPrecisionPlugin(self._amp_level_flag)
--> 735 raise RuntimeError("No precision set")

RuntimeError: No precision set

Environment

• CUDA:
  • GPU: None
  • available: False
  • version: None
• Lightning:
  • lightning-utilities: 0.3.0
  • pytorch-lightning: 1.8.3.post1
  • torch: 1.13.0
  • torchaudio: 0.13.0
  • torchmetrics: 0.10.3
  • torchvision: 0.14.0
• System:
  • OS: Darwin
  • architecture:
    • 64bit
  • processor: arm
  • python: 3.9.15
  • version: Darwin Kernel Version 21.6.0

More info

Also checked on newest pytorch_lightning pytorch_lightning-1.8.4.post0.

Works fine for following snippet:

import pytorch_lightning as pl
pl.Trainer(precision=16)

cc @Borda @carmocca @justusschock @awaelchli

[pkubik]

I guess this is due to this line:
https://github.com/Lightning-AI/lightning/blob/6aaac8b910e6c101ea3d62e3f2a5576c07a214b6/src/pytorch_lightning/trainer/connectors/accelerator_connector.py#L708

if self._precision_flag in (16, "bf16"):

It should probably be something like:

if str(self._precision_flag) in ("16", "bf16"):

[awaelchli]

Hi @pkubik
The intended type is indeed int. String was not meant to be supported. The addition of "bf16" was added at a later time when it was introduced in PyTorch.

The error message can be misleading, I agree. We can consider to change it to remove the quotes.
We can also consider adding the string values as accepted types. In fact, we wanted to do this in Lightning Lite already. cc @carmocca

It causes problems with some configuration frameworks or hyperparam optimization libraries. They often do not work with unions.

What library are you working with?

Another related issue that proposes an overhaul: #9956

[Borda]

for consistency I would extend support for int and str 🦦

[pkubik]

What library are you working with?

We actually tried to use this with hydra with schema defined in a dataclass. We probably could find some nasty workaround.

I do not claim that my case is sufficient justification to make a decision here :). I just saw this inconsistency with the error message and thought that accepting str was expected here.

[carmocca]

We can also consider adding the string values as accepted types. In fact, we wanted to do this in Lightning Lite already. cc @carmocca

Yes. A contribution is welcome!