examples/llama: lower to Core ML with to_edge_transform_and_lower

[msluszniak]

Summary

Fixes #19634.

The Core ML branch of _to_edge_and_lower_llama() still used the deprecated export_to_edge() + to_backend() split, and CoreMLPartitioner logs a deprecation warning about it on every invocation.

The split matters beyond the warning. It decomposes the graph before the partitioner runs, so the ops Core ML has its own implementations for are already broken into primitives by the time it sees them. CoreMLPartitioner.ops_to_not_decompose() asks to keep every op Core ML supports, and only to_edge_transform_and_lower honours that request.

This adds _to_edge_and_lower_llama_coreml(), matching the existing xnnpack and mlx helpers, and routes to it when Core ML is the only backend enabled.

Scope

Enabling Core ML together with Vulkan, MPS or QNN still takes the old combined path, which builds a single partitioner list. QNN in particular needs the edge manager for its pass pipeline and model sharding, so it is left alone; migrating it is a separate piece of work.

Etrecord generation comes along for free: to_edge_transform_and_lower takes generate_etrecord directly, so the helper does not need the deepcopy of the edge manager the old path used.

Results

LFM2.5 350M, fp32, max_seq_length=512, ios: 18, compute_units: cpu_and_ne:

	subgraphs	delegated nodes	non-delegated	deprecation warnings
before	1	1156	13	1
after	1	893	13	0

Same partitioning, 263 fewer nodes for Core ML to reassemble. expand_copy drops from 133 to 49 and unsqueeze_copy from 375 to 99.

A note on the original report

The issue also reported a SpecViolationError ("Mutation node aten_index_put_default_N is neither a buffer nor a user input") from the split path on LFM2 hybrid models, where the short-conv conv_state.copy_() decomposes to slice_copy + index_put and only one of the two is recorded as the mutation source. That no longer reproduces on main: the same export now completes on both the old and the new path. Only the deprecation and the extra decomposition remain, which is what this PR addresses.

Test plan

Adds examples/models/lfm2/config/lfm2_coreml_fp32.yaml alongside the existing lfm2_xnnpack_fp32.yaml and lfm2_mlx_4w.yaml, so the Core ML path has a config to run:

python -m extension.llm.export.export_llm \
  --config examples/models/lfm2/config/lfm2_coreml_fp32.yaml \
  +base.model_class=lfm2_5_350m \
  +base.params=examples/models/lfm2/config/lfm2_5_350m_config.json \
  +export.max_seq_length=512 \
  +export.max_context_length=512 \
  +export.output_name=lfm2_coreml.pte

[pytorch-bot]

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⚠️ 20 Awaiting Approval

As of commit de8e0bc with merge base fbd4bbf ():

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