Files
pytorch-lightning/tests/base/eval_model_train_steps.py
T
William FalconandJ. Borovec 3431c62d41 Remove error when test dataloader used in test (#1495)
* remove error when test dataloader used in test

* remove error when test dataloader used in test

* remove error when test dataloader used in test

* remove error when test dataloader used in test

* remove error when test dataloader used in test

* remove error when test dataloader used in test

* fix lost model reference

* remove error when test dataloader used in test

* fix lost model reference

* moved optimizer types

* moved optimizer types

* moved optimizer types

* moved optimizer types

* moved optimizer types

* moved optimizer types

* moved optimizer types

* moved optimizer types

* added tests for warning

* fix lost model reference

* fix lost model reference

* added tests for warning

* added tests for warning

* refactoring

* refactoring

* fix imports

* refactoring

* fix imports

* refactoring

* fix tests

* fix mnist

* flake8

* review

Co-authored-by: J. Borovec <jirka.borovec@seznam.cz>
2020-04-15 22:16:40 -04:00

31 lines
852 B
Python

from abc import ABC
from collections import OrderedDict
class TrainingStepVariations(ABC):
"""
Houses all variations of training steps
"""
def training_step(self, batch, batch_idx, optimizer_idx=None):
"""Lightning calls this inside the training loop"""
# forward pass
x, y = batch
x = x.view(x.size(0), -1)
y_hat = self(x)
# calculate loss
loss_val = self.loss(y, y_hat)
# alternate possible outputs to test
if self.trainer.batch_idx % 1 == 0:
output = OrderedDict({
'loss': loss_val,
'progress_bar': {'some_val': loss_val * loss_val},
'log': {'train_some_val': loss_val * loss_val},
})
return output
if self.trainer.batch_idx % 2 == 0:
return loss_val