Comments (2)
This is standard behavior of JAX. A function that's wrapped in jit will be compiled the first time it runs. Then the compiled version will be cached. Thus, if the jitted function is called with arguments of the same sizes and types, then it will use the cached version. Otherwise it needs to recompile. Every function in python has associated state (i.e., jax.jit returns a function which is a closure), so references to the compiled computation graph are stored in the state associated with the function.
In the future, this kind of question might be a better fit for a the JAX repository, as this behavior isn't specific to TAP/TAPIR.
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Thanks @cdoersch , i will pay close attention to where i post issues to. Thank you for your explanations on it, clear and concise.
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Related Issues (20)
- Re: architecture of ResNet used for track initialization HOT 2
- _pickle.UnpicklingError: Failed to interpret file '../checkpoint/checkpoint.npy' as a pickle HOT 2
- is there an open version of control code of robotap HOT 1
- OnnxExporterError: Unsupported: ONNX export of operator GridSample with 5D volumetric input. HOT 5
- ValueError: All `hk.Module`s must be initialized inside an `hk.transform` HOT 12
- ValueError: converting frame count is not supported. HOT 8
- robotap's query points selection question HOT 5
- Torchscript compatibility HOT 6
- Has anyone implemented it with tensorrt? HOT 1
- None of the algorithms provided by cuDNN heuristics worked; trying fallback algorithms HOT 2
- Pytorch <2.1.0 can't load the checkpoints correctly HOT 1
- Pretrained Weights for Pytorch Version of Online Tapir/BootsTapir HOT 2
- IndexError: boolean index did not match indexed array along dimension 1; dimension is 256 but corresponding boolean dimension is 990 HOT 2
- Training TAPIR PyTorch version script? HOT 7
- BootsTAP Training Dataset HOT 1
- `plot_tracks_v2` has bug when plotting with `trackgroup` argument. HOT 2
- KeyError: 'global_step' When I load the weight of TAPIR HOT 5
- CUDA out of memory issue when using PyTorch weights instead of JAX weights. HOT 2
- pytorch version TAPIR 's training file HOT 1
- Annotation Tool for TAP-VID HOT 2
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