[RELEASE ONLY CHANGES] Finalize 1.4 release dependencies and version - #21563
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[RELEASE ONLY CHANGES] Finalize 1.4 release dependencies and version#21563JacobSzwejbka wants to merge 5 commits into
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/21563
Note: Links to docs will display an error until the docs builds have been completed. ⏳ 272 Pending, 1 Unrelated FailureAs of commit 3592c81 with merge base cd380e7 ( FLAKY - The following job failed but was likely due to flakiness present on trunk:
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…V-cache The torchao bump pulls in pytorch/ao#4466, which preserves mutable buffer inputs during pt2e prepare. The static KV cache is now a genuine fp32 mutable buffer feeding index_put instead of a folded quantized constant. An INT-only TOSA delegate boundary must be quantized, so the Arm backend cannot delegate index_put on the fp32 buffer; the node is dropped from the partition and the cache read-modify-write forms a dependency cycle. This is the same underlying gap as the already-xfailed static-cache tests (MLETORCH-1971), and a proper Arm-side fix is being investigated separately. Mark the test xfail so the torchao pin bump can land. This change was authored with Claude Code.
pytorch/ao#4466 preserves mutable buffer inputs during pt2e prepare, so the llama KV cache stays an fp32 mutable buffer instead of being folded into a quantized constant. The Arm INT backend has no handling for that yet, and it breaks on both sides of the cache: test_llama_tosa_INT hits the same partition dependency cycle as the already-xfailed static-cache tests when writing the cache via index_put, and test_llama_vgf_quant fails in attention because the cache is read as float32 while the query is int8, which MATMUL rejects. Both tests only run in the trunk stories110M jobs, which pass --llama_inputs and --use_kv_cache. Mark them xfail so the torchao pin bump can land for the 1.4 release; the Arm-side fix is being investigated separately under MLETORCH-1971. This change was authored with Claude Code.
test_model.sh exports yolo26 via examples.portable.scripts.export, but yolo26's model imports ultralytics, which was never installed -- the CI job failed with ModuleNotFoundError: No module named 'ultralytics'. Install examples/models/yolo26/requirements.txt before the export, matching the per-model dep handling already used for llava/edsr/mb. torch/torchvision are already installed and satisfy ultralytics, so --upgrade-strategy only-if-needed leaves them untouched and no pytorch extra-index-url is needed. Authored with Claude assistance.
Keep the shared DS-CNN example input contiguous for portable execution, while forcing 4D Cortex-M inputs to channels-last and returning the converted tuple for BundleIO. This handles singleton-channel tensors whose contiguity predicate is ambiguous.\n\nAuthored with Codex assistance.
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Release-only changes. Do not merge to main.
Finalizes the ExecuTorch 1.4 release metadata and released dependency pins:
1.4.0.v0.18.0.v1.4.0.0.15.0CPU wheels.Test plan:
git diff --checkpy_compilebash -non all modified shell scriptssetup.py --namemetadata smoke testsv0.18.0andv1.4.0(490, 490, 10, 1)to channels-last strides(490, 1, 10, 1)Authored with Codex.