Pedro Augusto 2780bc459a sparse/config: probe flex_gemm on MPS, soft-fall-back to pytorch backend ... The default Darwin path used to be a try/except ImportError, which only catches build failures. With the mtlgemm round 1 fixes shipped, the more common failure mode for end users will be running an *older* mtlgemm that still returns CPU tensors from MPS calls — that doesn't fail import, it fails with a cryptic LayerNorm crash inside the model on the first conv. The new probe runs a tiny SparseConv3d on MPS and checks the output device. If anything breaks (import, build, dispatch, return-device), fall back to the pure-PyTorch backend rather than crashing inside the model. Tensors in the probe are built on CPU then moved to MPS because some PyTorch builds lack int/fp16 torch.zeros kernels on MPS — that's a PyTorch issue, separate from anything we control here. Plus: end-to-end smoke test (test_flex_gemm_integration.py) that exercises both Algorithm.IMPLICIT_GEMM and Algorithm.MASKED_IMPLICIT_GEMM through a real SparseConv3d → F.layer_norm chain on MPS. Confirms both algorithms return MPS tensors of the right dtype and produce equivalent output. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>		2026-07-17 07:51:05 +03:00
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attention	Init Release	2025-12-16 19:00:42 +00:00
sparse	sparse/config: probe flex_gemm on MPS, soft-fall-back to pytorch backend	2026-07-17 07:51:05 +03:00
transformer	Init Release	2025-12-16 19:00:42 +00:00
image_feature_extractor.py	add mlx backend for apple silicon with metal gpu acceleration	2026-07-17 07:51:05 +03:00
norm.py	Init Release	2025-12-16 19:00:42 +00:00
spatial.py	Init Release	2025-12-16 19:00:42 +00:00
utils.py	Init Release	2025-12-16 19:00:42 +00:00