Fix ModelPruning iterative reuse RuntimeError on non-leaf tensors

[Priyanshu-byte-coder]

What does this PR fix?

Fixes #8542.

When ModelPruning(use_lottery_ticket_hypothesis=True) is reused across multiple trainer.fit() calls (iterative pruning), the second and subsequent calls to setup() raise:

RuntimeError: Only Tensors created explicitly by the user (graph leaves) support the deepcopy protocol at the moment

Root cause: After the first training pass, apply_lottery_ticket_hypothesis() calls _copy_param() which does dst.data = src.data.to(dst.device). This in-place data assignment makes the model parameters non-leaf tensors. When setup() is called again on the next trainer.fit(), deepcopy(module) fails.

Changes

src/lightning/pytorch/callbacks/pruning.py

• Added _deepcopy_for_pruning(module) static helper: temporarily replaces non-leaf parameters with detach().clone() copies, deepcopies, then restores originals
• Updated setup() to use _deepcopy_for_pruning instead of bare deepcopy(module)
• In setup(), set self._original_layers = None before re-populating to release previous-run tensor references

tests/tests_pytorch/callbacks/test_pruning.py

• Added test_iterative_pruning_no_runtime_error: runs 3 consecutive trainer.fit() calls with the same pruning callback and verifies no RuntimeError is raised

Reproduction

model = BoringModel()
pruning_callback = ModelPruning("l1_unstructured", use_lottery_ticket_hypothesis=True, amount=0.2)
for _ in range(2):
    trainer = Trainer(max_epochs=1, accelerator="cpu", callbacks=[pruning_callback])
    trainer.fit(model)  # RuntimeError on second iteration (before fix)

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📚 Documentation preview 📚: https://pytorch-lightning--21717.org.readthedocs.build/en/21717/

[Priyanshu-byte-coder]

Pinging for review — all CI checks are green (triage, pre-commit, GitGuardian, ReadTheDocs all pass).

@justusschock @tchaton could one of you take a look when you get a chance? The fix is in _deepcopy_for_pruning in pruning.py — patches module.__dict__ instead of module._parameters to handle the non-leaf tensor that PyTorch's pruning forward pre-hook stores there.