Shortcuts

LambdaCallback

class pytorch_lightning.callbacks.LambdaCallback(on_before_accelerator_backend_setup=None, setup=None, on_configure_sharded_model=None, teardown=None, on_init_start=None, on_init_end=None, on_fit_start=None, on_fit_end=None, on_sanity_check_start=None, on_sanity_check_end=None, on_train_batch_start=None, on_train_batch_end=None, on_train_epoch_start=None, on_train_epoch_end=None, on_validation_epoch_start=None, on_validation_epoch_end=None, on_test_epoch_start=None, on_test_epoch_end=None, on_epoch_start=None, on_epoch_end=None, on_batch_start=None, on_validation_batch_start=None, on_validation_batch_end=None, on_test_batch_start=None, on_test_batch_end=None, on_batch_end=None, on_train_start=None, on_train_end=None, on_pretrain_routine_start=None, on_pretrain_routine_end=None, on_validation_start=None, on_validation_end=None, on_test_start=None, on_test_end=None, on_keyboard_interrupt=None, on_save_checkpoint=None, on_load_checkpoint=None, on_after_backward=None, on_before_zero_grad=None)[source]

Bases: pytorch_lightning.callbacks.base.Callback

Create a simple callback on the fly using lambda functions.

Parameters

**kwargs – hooks supported by Callback

Example:

>>> from pytorch_lightning import Trainer
>>> from pytorch_lightning.callbacks import LambdaCallback
>>> trainer = Trainer(callbacks=[LambdaCallback(setup=lambda *args: print('setup'))])
Read the Docs v: latest
Versions
latest
stable
1.2.7
1.2.6
1.2.5
1.2.4
1.2.3
1.2.2
1.2.1
1.2.0
1.1.8
1.1.7
1.1.6
1.1.5
1.1.4
1.1.3
1.1.2
1.1.1
1.1.0
1.0.8
1.0.7
1.0.6
1.0.5
1.0.4
1.0.3
1.0.2
1.0.1
1.0.0
0.10.0
0.9.0
0.8.5
0.8.4
0.8.3
0.8.2
0.8.1
0.8.0
0.7.6
0.7.5
0.7.4
0.7.3
0.7.2
0.7.1
0.7.0
0.6.0
0.5.3
0.4.9
docs-robots
Downloads
pdf
html
On Read the Docs
Project Home
Builds

Free document hosting provided by Read the Docs.