Comments (1)
Thank you for the kind words. I'll use a notation close to the paper to make it easier to connect the dots, and set the number of projections to 3. In the first version of Hyena, you will have a different matrix for each channel. To visualize H(u)
for a target channel you'll need to materialize the following matrices:
- T_v: toeplitz matrix corresponding to the causal short 1d convolution applied to the target channel of the
v
projection - T_x1: same as above, but for a different projection
- T_x2: same as above, but for a different projection
- D_v: the L x L matrix with
v
at the given channel on the diagonal. Note this is also L x L - D_x1: same as above
- D_x2: same as above
- T: Toeplitz matrix corresponding to the long implicit convolution.
Once you have these matrices, you can multiply them in the same order you would apply them to v
, e.g,:
- H(u) := T_x2 D_x2 T T_x1 D_x1 T_v v
Once you have the matrix you can also check whether applying H(u)
gives you the same output via a direct matrix multiply. When you generate the Toeplitz matrices with the convolutional filters, be careful to take into account padding to keep all convolutions causal.
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Related Issues (20)
- RuntimeError: u must have shape (batch_size, H, L) HOT 3
- fftconv compiling issue HOT 3
- configs for Hyena Wikitext103 experiments HOT 10
- Downstream evaluation on SuperGLUE HOT 2
- Inconsistent between implementation and paper descriptions HOT 1
- Encoder decoder
- Does Hyena support BERT style LLM? HOT 3
- Bidirectional Hyena HOT 1
- low train accuracy (10% / 40%) on synthetic language modeling tasks for H3 HOT 2
- What is the suggested config for running LRA exps with Hyena?
- RWKV
- learn_ifft in long_conv.py HOT 1
- dropout_add_layer_norm is not installed HOT 1
- Hyena seems forward leakage? HOT 9
- Accuracy on CIFAR is not similar to that in the paper HOT 4
- Non-causal implementation of language model for synthetic datasets HOT 5
- Hyena
- About the squash operator of long convolution HOT 2
- How to reproduce the Hyena-Imagenet experiment result simillar with the paper? HOT 1
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