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NativeMixedPrecisionPlugin

class pytorch_lightning.plugins.precision.NativeMixedPrecisionPlugin(precision, device, scaler=None)[source]

Bases: pytorch_lightning.plugins.precision.precision_plugin.PrecisionPlugin

Plugin for Native Mixed Precision (AMP) training with torch.autocast.

Parameters
clip_gradients(optimizer, clip_val=0.0, gradient_clip_algorithm=GradClipAlgorithmType.NORM)[source]

Clips the gradients.

Return type

None

forward_context()[source]

Enable autocast context.

Return type

Generator[None, None, None]

load_state_dict(state_dict)[source]

Called when loading a checkpoint, implement to reload precision plugin state given precision plugin state_dict.

Parameters

state_dict (Dict[str, Any]) – the precision plugin state returned by state_dict.

Return type

None

optimizer_step(optimizer, model, optimizer_idx, closure, **kwargs)[source]

Hook to run the optimizer step.

Return type

Any

pre_backward(tensor, module)[source]

Runs before precision plugin executes backward.

Parameters
  • tensor (Tensor) – The tensor that will be used for backpropagation

  • module (LightningModule) – The module that was involved in producing the tensor and whose parameters need the gradients

Return type

Tensor

state_dict()[source]

Called when saving a checkpoint, implement to generate precision plugin state_dict.

Return type

Dict[str, Any]

Returns

A dictionary containing precision plugin state.

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