Replace space ' ' with explicit SPACE='_' vocab token to disambiguate
padding from real spaces, and rewrite forward_step to take a single
character plus rolling state string instead of a reconstructed vc matrix,
producing predictions one character at a time per unit.
- Increase H_SIZE to 128, lr to 0.2, disable Rao-Blackwell
- Expand VOCAB to include lowercase and hyphen/period
- Fix batch_delay to always use delay=1 per unit
- forward_step now returns (vc, text) with predicted char per unit step
- Collect and print generated text in main inference loop
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Switch TEXT to "HALLO MAUSI! SUPER HASE!", H_SIZE to 64, lr to 0.1
- Extract v2char() helper from vc2char()
- Fix shift_left to use vocab_size() step instead of 1
- Re-enable model.train() and model.save() in main
- Clean up dead prediction loop code
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Add batch_delay() to shift visible input per unit index
- Unify forward_step() to work with combined vc matrix
- Fix split() to always slice on axis=1
- Add index param to Entity for readable naming
- Rename test_xor.py to xor.py, replace Mat with np.array
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- reduce WIN to 3 and H_SIZE to 32 for faster iteration
- increase NUM_EPOCHS to 1000 and collapse NUM_ITERATIONS to a single pass
- add README_JayRnn.md with algorithm description and ASCII architecture diagrams
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
jens
