Documentation enhancement: Specifying detailed shape requirements for pretrained models
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Description
📚 Documentation
In the documentation of PyTorch Model Zoo, it is suggested that:
H and W are expected to be at least 224.
Technically, for H/W < 224 it is also workable, but there might be some lower bound.
For example, the AlexNet model is able to consume a tensor of [3, 200, 200] but not applicable for that of [3, 62, 62].
Similar cases also apply to vgg* and densenet*. Therefore, I am wondering if it is necessary to specify the undefined behaviours of models in the documentation to help users better leverage the models. Thanks.
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Research direction
Start by reviewing the PyTorch Model Zoo documentation at https://pytorch.org/vision/stable/models.html and compare its H/W guidance with the stated AlexNet, vgg*, and densenet* examples. Document model-specific lower bounds or undefined behavior for smaller inputs, with the finished documentation making clear which tensor shapes are supported.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- computer-vision, documentation, machine-learning
- Issue type
- Documentation
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100