Comments (2)
Aha, found it
RecurrentAttentionLayer have no memory_lengths argument
But RecurrentTransformerDecoderLayer try to pass it
from fast-transformers.
Nevermind, didnt realize where is RecurrentCrossAttentionLayer also.
Kind of complicated honestly.
from fast-transformers.
Related Issues (20)
- Windows installation - Building wheel HOT 3
- Training Language Model HOT 2
- Parallel complexity of Linear Attention is O(N)? HOT 1
- how causal mask constructed in training batch model with linear causal attention?
- Runtime error on causal_product_cpu on GCC/G++ 11 HOT 3
- Casual attention is cheating by looking in the future HOT 1
- Installing error on linux HOT 4
- Any decoder example? HOT 1
- Can't officially save Linear Attention model HOT 2
- can offer built code for linus?
- Speed of recurrent model HOT 2
- Cuda version HOT 1
- Example for NLP
- Understanding how to define key, query and value for the cross attention calculation
- Detailed implementation of `clustered_sparse_dot_product`
- Windows installation - building wheel error HOT 27
- Got different result for the same batch HOT 1
- Error about `causal_product_cpu.cpython-38-darwin.so` on Mac HOT 2
- `.causal_product_cuda` missing in pip installed version on linux HOT 4
- Provenance of algorithms
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from fast-transformers.