Parameters of Gabor functions are NOT learnable
- Dominant language
- Python
- Stars
- 107
- Forks
- 28
- PR merge metrics
- No merged PRs in 30d
Description
GaborConv2d implementation does not change the filter parameters (freq, sigma, theta, etc.) during training.
Tested with torch 2.3.0+cu121
If you create a simple network with GaborConv2d first layer, and check the values and gradients for sigma, theta, etc. during training. Values of these parameters will not change, and their gradients will be None.
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Research direction
Locate the GaborConv2d implementation and reproduce the issue with a simple network using torch 2.3.0+cu121. Inspect how freq, sigma, theta, and related parameters are defined and used during training. Done means these parameters receive gradients and their values change after optimizer steps.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- computer-vision, machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 45/100