[P] Generating text with character embeddings and RNN in pure Numpy
I’ve implemented a seq2seq generative character model in pure Numpy on top of CS231n’s assignment code. It’s nothing fancy but I think being able to see things in matrix multiplication level gives good intuitions about concepts in machine learning. Thus this repository contains reference implementations for
- CharRNN (Sequence to Sequence RNN to produce characters with temperature)
- Unit tests with numerical gradients to check implementations
- Character Embedding
- Recurrent Neural Networks
- Temporal Affine Layer
- Temporal Softmax
- Adam optimizer
- Solver (Run training loop, update weights, save model, record logs, etc.)
- Data loading, character mapping, masking non-frequent characters
Hope it will be useful for others, as well!
Repo
submitted by /u/kirbiyik
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