Stuck on an issue?

Lightrun Answers was designed to reduce the constant googling that comes with debugging 3rd party libraries. It collects links to all the places you might be looking at while hunting down a tough bug.

And, if you’re still stuck at the end, we’re happy to hop on a call to see how we can help out.

optimizer = Ranger21(params=model.parameters(), lr=learning_rate) File "/mnt/Drive1/florian/msblob/Ranger21/ranger21/ranger21.py", line 179, in init self.total_iterations = num_epochs * num_batches_per_epoch TypeError: unsupported operand type(s) for *: 'NoneType' and 'NoneType'

See original GitHub issue

I get the following error when starting my training:

Traceback (most recent call last):
  File "tr_baseline.py", line 75, in <module>
    optimizer = Ranger21(params=model.parameters(), lr=learning_rate)
  File "/mnt/Drive1/florian/msblob/Ranger21/ranger21/ranger21.py", line 179, in __init__
    self.total_iterations = num_epochs * num_batches_per_epoch
TypeError: unsupported operand type(s) for *: 'NoneType' and 'NoneType'

initializing ranger with:

# ranger:
optimizer = Ranger21(params=model.parameters(), lr=learning_rate)

Issue Analytics

State:
Created 2 years ago
Comments:6 (2 by maintainers)

Top GitHub Comments

1reaction

saruarlivecommented, Jun 28, 2021

Well, have you tried as shown below,

from ranger21 import Ranger21 
optimizer = Ranger21(model.parameters(), lr = 1e-02, num_epochs = epochs, num_batches_per_epoch = len(train_loader))

0reactions

neuronflowcommented, Jul 6, 2021

One further question, I have a training where I use multiple training data loaders with different batch length…is it possible to apply ranger21 in this context?