r""" Registers a chat template. To add the following chat template: ``` [HUMAN]: user prompt here [AI]: model response he

r""" Returns a logger with the specified name. It it not supposed to be accessed externally.

r""" Gets element by id. Example: top.lang, train.dataset

r""" Forms a list of slots according to the inputs to encode.

r""" Gets the path to saved model checkpoints.

r""" Validates if this model accepts the input modalities.

r""" Loads pretrained tokenizer and optionally loads processor. Note: including inplace operation of model_args.

r""" Loads pretrained model.

r""" Gets chat template and fixes the tokenizer.

r""" Processes visual inputs. Returns: (llava and paligemma) pixel_values: tensor with shape (B, C, H, W) Return

r""" Returns a single pair of token ids representing prompt and response respectively.

r""" Adds elements to manager.

r""" Gets the train dataset and optionally gets the evaluation dataset.

r""" Pre-processes input messages before tokenization for VLMs.

r""" Saves model checkpoint. Subclass and override to inject custom behavior.

r""" Gets the current available device.

r""" Casts a torch tensor or a numpy array to a numpy array.

r""" Plots loss curves and saves the image.

r""" Pre-processes token ids after tokenization for VLMs.

r""" Collects GPU or NPU memory.

r""" Computes the real sequence length after truncation by the cutoff_len.

r""" Loads user config if exists.

r""" Gets the number of available GPU or NPU devices.

r""" Returns the list of all elements.