Rename `gradient_checkpointing` to `activation_checkpointing` in the next major

What gets checkpointed is activations, not gradients: the forward keeps some of them and the backward recomputes the others. "Gradient checkpointing" comes from Chen et al. 2016 and OpenAI's gradient-checkpointing package, and transformers kept it. Most of the stack has since settled on "activation checkpointing":

Library	Name
PyTorch	activation checkpointing (torch.utils.checkpoint, apply_activation_checkpointing)
torchtitan	[activation_checkpoint]
DeepSpeed	activation_checkpointing config section
accelerate	fsdp_activation_checkpointing
Megatron-LM	activation recomputation (Korthikanti et al. 2022)
JAX	jax.checkpoint / jax.remat
transformers, PEFT	gradient_checkpointing

So a user moving between accelerate's FSDP plugin, DeepSpeed and transformers meets the same technique under two names.

The timing fits: gradient_checkpointing_enable just gained every_n_layers and offload, and selective checkpointing (saving the attention output) is next (huggingface/trl#7194). Better to settle the name before more options pile up under the old one.

Proposal

• TrainingArguments.activation_checkpointing / activation_checkpointing_kwargs, model.activation_checkpointing_enable() / _disable(), same arguments as today.
• The gradient_checkpointing* names stay for one major as aliases with a FutureWarning, then go.
• Internal names (supports_gradient_checkpointing, GradientCheckpointingLayer) are rarely user-facing: open question whether they move in the same major.
• PEFT, accelerate and TRL switch in the same release cycle.

[!IMPORTANT] This issue is not open to external contribs