Comments (3)
Generally speaking, MANN is not so easy to get converged as other RNN models are, and a blind combination can result in severe instability of training. I take a lot of time to finally get it converged on the omniglot dataset demonstrated in the original paper. So please prepare enough time and patience, and you may need to adjust the model to fit your task. Good luck!
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Thanks so much for replying!
You're absolutely correct. RL by itself can already go horribly wrong under various (and usually unknown) circumstances. I couldn't find any working implementation of memory-augmented RL models (open-sourced or from authors of original papers) so I have to do it myself. Naively combining memory net to RL is not technically a well-motivated approach but I'm still implementing it as baseline for my research.
If you don't mind keeping this issue thread open, I would like to continue this discussion here.
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I have 1 operation tf.nn.dynamic_rnn in my computation graph. I'm thinking of replacing that op with tf.while_loop whose body is the MANN operations. Do you think this approach makes sense?
I'm aware that you used 'for' loop in your model so I will try both and see which works. Either way, I need to find a way to terminate the loop, i.e. define a condition for tf.while_loop or a sequence length for 'for' loop.
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Related Issues (20)
- Can You please upload the link to the data set(MANN) ? HOT 1
- Can you please explain about the accuracy mechanism in the model ? HOT 1
- Converging of the network for different data sets? HOT 6
- copy_task.py stopped with NotFoundError HOT 3
- small correction about argument parsing in copy_task.py HOT 1
- No model_checkpoint_path error when copy_task.py --mode test HOT 1
- data folder for one_shot_learning.py ?
- num_parameters_per_head confused? HOT 3
- How to use model for Inference HOT 7
- What is key vector? HOT 2
- Memory tends to be the same? And the confusion about MANN
- instance
- recurrence through the state dictionary HOT 2
- Training the Model HOT 1
- Initialization regarding the addressing and memory matrix . HOT 4
- can you explain about the plotting read vectors ? HOT 3
- How did you calculate the number of controller output parameters in MANN cell ? HOT 2
- confusion when calculating the least used weight vector in MANN HOT 6
- Why we need to set the least used memory location to zero in the memory matrix HOT 2
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