Comments (6)
Hey, can you please test after reverting d7b3840?
from pytorch-ntm.
it seems that change does not helpy
from pytorch-ntm.
Interesting, perhaps it's related to the seed (initialization and random training samples). Can you please test using a different seed? My test involved averaging 4 different seeds. I'll try to reproduce with seed=10 as well.
from pytorch-ntm.
It's seems to be a seed issue, I attached plots for the training of the copy task with seed=1000. Results may vary based on the seed as it controls the initialization and the training examples as well (which are random sequences of bits).
from pytorch-ntm.
Could u please list a detailed param setting? Thanks a lot.
from pytorch-ntm.
Hi, sure.
It appears in the copy notebook, at the beginning.
from pytorch-ntm.
Related Issues (16)
- register_buffer HOT 1
- Why to create a new tensor? HOT 2
- Convergence is really slow with copy task when sequence length is smaller HOT 2
- Different results between testing in the mid terms of training and at the end of training HOT 3
- It would be nice if you can add the cuda option HOT 1
- What's the meaning of using memory? HOT 1
- How to change code when each sequence length is different HOT 1
- Why use vague storage
- error in copy-task-plots.ipynb HOT 2
- Cannot reproduce README.md graphs/results on copy task [Commit: 5c5ce66] HOT 1
- Why it runs so slowly?
- Why did each batch has a memory? HOT 1
- How could u write down beta, gamma in your source code? HOT 1
- How to visual the training process and draw these animation? HOT 1
- why need to initialize read vector and memory? HOT 1
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