This proposed feature allows finetuning specific parameters from a given checkpoint. If finetuning is enabled, the trainer loads all matched parameters from the source ckpt when a new training task is started.

Need 4 new configuration keys:

• finetune_enabled: whether finetuning is enabled
• finetune_ckpt: path to the ckpt to be finetuned
• finetune_ignored_params: params (name prefixes) to be dropped from the ckpt before finetuning starts
• finetune_strict_shapes: if set to True, raise errors when tensor shapes mismatch; otherwise skip the mismatching parameters