def test_lite_optimizer_state_dict():
"""Test that the LiteOptimizer calls into the strategy to collect the state."""
optimizer = Mock()
strategy = Mock()
lite_optimizer = _LiteOptimizer(optimizer=optimizer, strategy=strategy)
lite_optimizer.state_dict()
strategy.optimizer_state.assert_called_with(optimizer)
def test_lite_optimizer_wraps():
"""Test that the LiteOptimizer fully wraps the optimizer."""
optimizer_cls = torch.optim.SGD
optimizer = Mock(spec=optimizer_cls)
lite_optimizer = _LiteOptimizer(optimizer, Mock())
assert lite_optimizer.optimizer is optimizer
assert isinstance(lite_optimizer, optimizer_cls)
def setup(
self,
model: nn.Module,
*optimizers: Optimizer,
move_to_device: bool = True,
) -> Any: # no specific return because the way we want our API to look does not play well with mypy
"""Setup a model and its optimizers for accelerated training.
Args:
model: A model to setup
*optimizers: The optimizer(s) to setup (no optimizers is also possible)
move_to_device: If set ``True`` (default), moves the model to the correct device. Set this to ``False``
and alternatively use :meth:`to_device` manually.
Returns:
The tuple of the wrapped model and list of optimizers, in the same order they were passed in.
"""
self._validate_setup(model, optimizers)
if move_to_device:
model = self._move_model_to_device(model=model, optimizers=list(optimizers))
# Let accelerator/plugin wrap and connect the models and optimizers
model, optimizers = self._strategy._setup_model_and_optimizers(model, list(optimizers))
model = _LiteModule(model, self._precision_plugin)
optimizers = [_LiteOptimizer(optimizer=optimizer, strategy=self._strategy) for optimizer in optimizers]
self._models_setup += 1
if optimizers:
# join both types in a list for API convenience
return [model] + optimizers # type: ignore
return model
def test_lite_optimizer_steps():
"""Test that the LiteOptimizer forwards the step() and zero_grad() calls to the wrapped optimizer."""
optimizer = Mock()
strategy = Mock()
lite_optimizer = _LiteOptimizer(optimizer=optimizer, strategy=strategy)
lite_optimizer.step()
strategy.optimizer_step.assert_called_once()
strategy.optimizer_step.assert_called_with(optimizer,
opt_idx=0,
closure=ANY,
model=strategy.model)
