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UPGRADING.md

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Upgrading from previous versions

I generally try to maintain code interface and especially model weight compability across many timm versions. Sometimes there are exceptions.

Checkpoint remapping

Pretrained weight remapping is handled by checkpoint_filter_fn in a model implementation module. This remaps old pretrained checkpoints to new, and also 3rd party (original) checkpoints to timm format if the model was modified when brough into timm.

The checkpoint_filter_fn is automatically called when loading pretrained weights via pretrained=True, but they can be called manually if you call the fn directly with the current model instance and old state dict.

Upgrading from 0.6 and earlier

Many changes were made since the 0.6.x stable releases. They were previewed in 0.8.x dev releases but not everyone transitioned.

  • timm.models.layers moved to timm.layers:
    • from timm.models.layers import name will still work via deprecation mapping (but please transition to timm.layers).
    • import timm.models.layers.module or from timm.models.layers.module import name needs to be changed now.
  • Builder, helper, non-model modules in timm.models have a _ prefix added, ie timm.models.helpers -> timm.models._helpers, there are temporary deprecation mapping files but those will be removed.
  • All models now support architecture.pretrained_tag naming (ex resnet50.rsb_a1).
    • The pretrained_tag is the specific weight variant (different head) for the architecture.
    • Using only architecture defaults to the first weights in the default_cfgs for that model architecture.
    • In adding pretrained tags, many model names that existed to differentiate were renamed to use the tag (ex: vit_base_patch16_224_in21k -> vit_base_patch16_224.augreg_in21k). There are deprecation mappings for these.
  • A number of models had their checkpoints remaped to match architecture changes needed to better support features_only=True, there are checkpoint_filter_fn methods in any model module that was remapped. These can be passed to timm.models.load_checkpoint(..., filter_fn=timm.models.swin_transformer_v2.checkpoint_filter_fn) to remap your existing checkpoint.
  • The Hugging Face Hub (https://huggingface.co/timm) is now the primary source for timm weights. Model cards include link to papers, original source, license.
  • Previous 0.6.x can be cloned from 0.6.x branch or installed via pip with version.