chore(deps): update dependency timm to v1 #1267
Open
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
This PR contains the following updates:
==0.9.16
->==1.0.9
Release Notes
huggingface/pytorch-image-models (timm)
v1.0.9
Compare Source
Aug 21, 2024
Add SAM2 (HieraDet) backbone arch & weight loading support
Add Hiera Small weights trained w/ abswin pos embed on in12k & fine-tuned on 1k
Aug 8, 2024
v1.0.8
Compare Source
July 28, 2024
mobilenet_edgetpu_v2_m
weights w/ra4
mnv4-small based recipe. 80.1% top-1 @ 224 and 80.7 @ 256.July 26, 2024
set_input_size()
added to vit and swin v1/v2 models to allow changing image size, patch size, window size after model creation.set_input_size
,always_partition
andstrict_img_size
args have been added to__init__
to allow more flexible input size constraintstiny
< .5M param models for testing that are actually trained on ImageNet-1kJune 24, 2024
v1.0.7
Compare Source
June 12, 2024
timm
trained weights added:v1.0.3
Compare Source
May 14, 2024
normalize=
flag for transorms, return non-normalized torch.Tensor with original dytpe (forchug
)May 11, 2024
Searching for Better ViT Baselines (For the GPU Poor)
weights and vit variants released. Exploring model shapes between Tiny and Base.timm
models. See example in https://github.com/huggingface/pytorch-image-models/discussions/1232#discussioncomment-9320949forward_intermediates()
API refined and added to more models including some ConvNets that have other extraction methods.features_only=True
feature extraction. Remaining 34 architectures can be supported but based on priority requests.April 11, 2024
features_only=True
support for ViT models with flat hidden states or non-std module layouts (so far covering'vit_*', 'twins_*', 'deit*', 'beit*', 'mvitv2*', 'eva*', 'samvit_*', 'flexivit*'
)forward_intermediates()
API that can be used with a feature wrapping module or direclty.Configuration
📅 Schedule: Branch creation - At any time (no schedule defined), Automerge - At any time (no schedule defined).
🚦 Automerge: Disabled by config. Please merge this manually once you are satisfied.
♻ Rebasing: Whenever PR becomes conflicted, or you tick the rebase/retry checkbox.
🔕 Ignore: Close this PR and you won't be reminded about this update again.
This PR was generated by Mend Renovate. View the repository job log.