o Zh@s.ddlmZddlmZGdddejZdS))partialNcs$eZdZdZdZfddZZS)GradientCheckpointingLayeraBase class for layers with gradient checkpointing. This class enables gradient checkpointing functionality for a layer. By default, gradient checkpointing is disabled (`gradient_checkpointing = False`). When `model.set_gradient_checkpointing()` is called, gradient checkpointing is enabled by setting `gradient_checkpointing = True` and assigning a checkpointing function to `_gradient_checkpointing_func`. Important: When using gradient checkpointing with `use_reentrant=True`, inputs that require gradients (e.g. hidden states) must be passed as positional arguments (`*args`) rather than keyword arguments to properly propagate gradients. Example: ```python >>> # Correct - hidden_states passed as positional arg >>> out = self.layer(hidden_states, attention_mask=attention_mask) >>> # Incorrect - hidden_states passed as keyword arg >>> out = self.layer(hidden_states=hidden_states, attention_mask=attention_mask) ``` Fcs@|jr|jr|jttjfi|g|RStj|i|S)N)gradient_checkpointingZtrainingZ_gradient_checkpointing_funcrsuper__call__)selfargskwargs __class__K/var/www/auris/lib/python3.10/site-packages/transformers/modeling_layers.pyr-s "z#GradientCheckpointingLayer.__call__)__name__ __module__ __qualname____doc__rr __classcell__r r r r rsr) functoolsrZtorch.nnnnModulerr r r r s