From 1b8485c4ce0ae2e887336fc9e3fad53475798888 Mon Sep 17 00:00:00 2001 From: Ross Wightman Date: Wed, 4 Jan 2023 22:23:28 -0800 Subject: [PATCH] Update README, fixing convnextv2 tests --- README.md | 7 +++++++ tests/test_models.py | 2 +- 2 files changed, 8 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index e78dd241..ce0d690a 100644 --- a/README.md +++ b/README.md @@ -28,6 +28,11 @@ For a few months now, `timm` has been part of the Hugging Face ecosystem. Yearly If you have a couple of minutes and want to participate in shaping the future of the ecosystem, please share your thoughts: [**hf.co/oss-survey**](https://hf.co/oss-survey) 🙏 +### Jan 5, 2023 +* ConvNeXt-V2 models and weights added to existing `convnext.py` + * Paper: [ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders](http://arxiv.org/abs/2301.00808) + * Reference impl: https://github.com/facebookresearch/ConvNeXt-V2 (NOTE: weights currently CC-BY-NC) + ### Dec 23, 2022 🎄☃ * Add FlexiViT models and weights from https://github.com/google-research/big_vision (check out paper at https://arxiv.org/abs/2212.08013) * NOTE currently resizing is static on model creation, on-the-fly dynamic / train patch size sampling is a WIP @@ -396,6 +401,7 @@ A full version of the list below with source links can be found in the [document * CoaT (Co-Scale Conv-Attentional Image Transformers) - https://arxiv.org/abs/2104.06399 * CoAtNet (Convolution and Attention) - https://arxiv.org/abs/2106.04803 * ConvNeXt - https://arxiv.org/abs/2201.03545 +* ConvNeXt-V2 - http://arxiv.org/abs/2301.00808 * ConViT (Soft Convolutional Inductive Biases Vision Transformers)- https://arxiv.org/abs/2103.10697 * CspNet (Cross-Stage Partial Networks) - https://arxiv.org/abs/1911.11929 * DeiT - https://arxiv.org/abs/2012.12877 @@ -418,6 +424,7 @@ A full version of the list below with source links can be found in the [document * Single-Path NAS - https://arxiv.org/abs/1904.02877 * TinyNet - https://arxiv.org/abs/2010.14819 * EVA - https://arxiv.org/abs/2211.07636 +* FlexiViT - https://arxiv.org/abs/2212.08013 * GCViT (Global Context Vision Transformer) - https://arxiv.org/abs/2206.09959 * GhostNet - https://arxiv.org/abs/1911.11907 * gMLP - https://arxiv.org/abs/2105.08050 diff --git a/tests/test_models.py b/tests/test_models.py index d0d15951..3e91d9a8 100644 --- a/tests/test_models.py +++ b/tests/test_models.py @@ -38,7 +38,7 @@ if 'GITHUB_ACTIONS' in os.environ: '*efficientnet_l2*', '*resnext101_32x48d', '*in21k', '*152x4_bitm', '*101x3_bitm', '*50x3_bitm', '*nfnet_f3*', '*nfnet_f4*', '*nfnet_f5*', '*nfnet_f6*', '*nfnet_f7*', '*efficientnetv2_xl*', '*resnetrs350*', '*resnetrs420*', 'xcit_large_24_p8*', 'vit_huge*', 'vit_gi*', 'swin*huge*', - 'swin*giant*'] + 'swin*giant*', 'convnextv2_huge*'] NON_STD_EXCLUDE_FILTERS = ['vit_huge*', 'vit_gi*', 'swin*giant*', 'eva_giant*'] else: EXCLUDE_FILTERS = []