lightning/docs/source-pytorch/model/build_model_intermediate.rst

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###################################
Supercharge training (intermediate)
###################################
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Enable training features
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Enable advanced training features using Trainer arguments. These are SOTA techniques that are automatically integrated into your training loop without changes to your code.
.. code::
# train 1T+ parameter models with DeepSpeed/FSDP
trainer = Trainer(
devices=4,
accelerator="gpu",
strategy="deepspeed_stage_2",
precision="16-mixed",
)
# 20+ helpful arguments for rapid idea iteration
trainer = Trainer(
max_epochs=10,
min_epochs=5,
overfit_batches=1
)
# access the latest state of the art techniques
trainer = Trainer(callbacks=[StochasticWeightAveraging(...)])
----
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Extend the Trainer
******************
.. video:: https://pl-public-data.s3.amazonaws.com/assets_lightning/cb.mp4
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If you have multiple lines of code with similar functionalities, you can use *callbacks* to easily group them together and toggle all of those lines on or off at the same time.
.. code::
trainer = Trainer(callbacks=[AWSCheckpoints()])