.. testsetup:: *

    from pytorch_lightning.trainer.trainer import Trainer


Training Tricks
================
Lightning implements various tricks to help during training

Accumulate gradients
-------------------------------------
Accumulated gradients runs K small batches of size N before doing a backwards pass.
The effect is a large effective batch size of size KxN.

.. seealso:: :class:`~pytorch_lightning.trainer.trainer.Trainer`

.. testcode::

    # DEFAULT (ie: no accumulated grads)
    trainer = Trainer(accumulate_grad_batches=1)


Gradient Clipping
-------------------------------------
Gradient clipping may be enabled to avoid exploding gradients. Specifically, this will `clip the gradient
norm <https://pytorch.org/docs/stable/nn.html#torch.nn.utils.clip_grad_norm_>`_ computed over all model parameters together.

.. seealso:: :class:`~pytorch_lightning.trainer.trainer.Trainer`

.. testcode::

    # DEFAULT (ie: don't clip)
    trainer = Trainer(gradient_clip_val=0)

    # clip gradients with norm above 0.5
    trainer = Trainer(gradient_clip_val=0.5)