Script 'mail_helper' called by obssrc Hello community, here is the log from the commit of package python-timm for openSUSE:Factory checked in at 2026-08-25 13:20:01 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Comparing /work/SRC/openSUSE:Factory/python-timm (Old) and /work/SRC/openSUSE:Factory/.python-timm.new.1258 (New) ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Package is "python-timm" Tue Aug 25 13:20:01 2026 rev:2 rq:1373474 version:1.0.28 Changes: -------- --- /work/SRC/openSUSE:Factory/python-timm/python-timm.changes 2026-08-24 15:43:37.766732772 +0200 +++ /work/SRC/openSUSE:Factory/.python-timm.new.1258/python-timm.changes 2026-08-25 13:20:15.156302300 +0200 @@ -1,0 +2,31 @@ +Mon Aug 24 18:07:15 UTC 2026 - Martin Pluskal <[email protected]> + +- Update to 1.0.28: + * New models: DINOv3 ConvNeXt/ViT, Gemma4 ViT, TIPSv2, EUPE, + CSATv2, MobileCLIP-2 and MetaCLIP-2 encoders, SigLIP-2 + NaFlex weights + * Add the Muon optimizer plus AdaMuon/NAdaMuon variants, and + a cautious mode for AdamP and SGDP + * Add a lightweight task abstraction with logits, feature and + token distillation support (new timm.task subpackage) + * Add ROPE support to NaFlexViT and set_input_size() to EVA + models; extend NaFlexViT patch layout and forward_intermediates + * Add differential attention, coordinate attention and the + LsePlus/SimPool/PRR pooling modules + * Harden checkpoint loading: default weights_only=True and + address several pickle security concerns + * Support device/dtype factory kwargs and meta-device model + initialisation + * Fix LayerScale ignoring init_values, reg_token weight decay + grouping, Hiera SDPA dispatch and a ZeroDivisionError in + AverageMeter + * Remove APEX AMP support and reduce torch.jit usage ahead of + its deprecation + * Compat break: correct QKV vs MLP bias in ParallelScalingBlock + and DiffParallelScalingBlock; no shipped weights are affected + * Compat break: MobileNet-V5 gains a stem bias and uses the tanh + GELU approximation, breaking pre-1.0.17 weights +- Extend the %check smoke test with a forward pass and a guard for + the SigLIP ViT that python-sglang builds via timm.create_model() + +------------------------------------------------------------------- Old: ---- timm-1.0.16.tar.gz New: ---- timm-1.0.28.tar.gz ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Other differences: ------------------ ++++++ python-timm.spec ++++++ --- /var/tmp/diff_new_pack.gVWESU/_old 2026-08-25 13:20:16.362344884 +0200 +++ /var/tmp/diff_new_pack.gVWESU/_new 2026-08-25 13:20:16.371345202 +0200 @@ -18,7 +18,7 @@ %{?sle15_python_module_pythons} Name: python-timm -Version: 1.0.16 +Version: 1.0.28 Release: 0 Summary: PyTorch Image Models License: Apache-2.0 @@ -59,8 +59,18 @@ %check # Upstream pytest downloads pretrained weights and needs network. -# Smoke-test the import and model registry instead. -%python_expand PYTHONPATH=%{buildroot}%{$python_sitelib} $python -B -c "import timm; assert timm.__version__ == '%{version}', timm.__version__; assert timm.list_models()" +# Smoke-test import, the model registry and a real forward pass instead. +cat > smoke.py <<'EOF' +import timm, torch +assert timm.__version__ == "%{version}", timm.__version__ +assert timm.list_models() +# guard the SigLIP ViT that python-sglang builds via timm.create_model() +assert "vit_so400m_patch14_siglip_384" in timm.list_models() +m = timm.create_model("resnet18", pretrained=False, num_classes=10).eval() +with torch.no_grad(): + assert m(torch.randn(1, 3, 64, 64)).shape == (1, 10) +EOF +%python_expand PYTHONPATH=%{buildroot}%{$python_sitelib} $python -B smoke.py %files %{python_files} %license LICENSE ++++++ timm-1.0.16.tar.gz -> timm-1.0.28.tar.gz ++++++ ++++ 55072 lines of diff (skipped)
