Comments (2)
In the original MANN paper, query key vector 'k' are used in both reading (eq 17) and writing (eq 23). You can set k_strategy='summary' if you want this way. However, in the NTM paper they are separated. If you set k_strategy='separate', the controller will generate a new add vector 'a' to replace the query vector 'k' in eq 23.
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Oh yes in MANN the k we are using is the same output from the controller which used to do content-based addressing as in the "summery" strategy.
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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
- Using MANN in A3C (reinforcement learning model) HOT 3
- 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
- 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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