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Comments (12)

reidmcy avatar reidmcy commented on June 12, 2024

Your providing a list in the yaml, it's expecting a string

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CallOn84 avatar CallOn84 commented on June 12, 2024

Your providing a list in the yaml, it's expecting a string

The yaml for maia_config is in a list, so I don't get it.

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reidmcy avatar reidmcy commented on June 12, 2024

Please check again, here this is the relevant line. I'm not sure which config you are using there

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CallOn84 avatar CallOn84 commented on June 12, 2024

Please check again, here this is the relevant line. I'm not sure which config you are using there

Ah, thanks. It works now. However, when it goes through the training games, it comes back as 0 chunks total. I don't know why that happening when there's the data there.

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reidmcy avatar reidmcy commented on June 12, 2024

It's not looking for the the directory to the files, did you read the comment in the yaml?

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CallOn84 avatar CallOn84 commented on June 12, 2024

It's not looking for the the directory to the files, did you read the comment in the yaml?

I did read the comments of the YAML and followed it to the tea. Still detecting zero chunks.

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reidmcy avatar reidmcy commented on June 12, 2024

Then you are putting in the wrong path, glob.glob() will produce [] when nothing is found

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CallOn84 avatar CallOn84 commented on June 12, 2024

Then you are putting in the wrong path, glob.glob() will produce [] when nothing is found

I've replicated the same path as the final config in the configuration file, and it's still giving me no chunks.

This is literally my config file:

%YAML 1.2
---
gpu: 0

dataset:
  input_train: '/trainingdata/elo_ranges/2500/train/*/*'
  input_test: '/trainingdata/elo_ranges/2500/test/*/*'

training:
    precision: 'half'
    batch_size: 1024
    num_batch_splits: 1
    test_steps: 2000
    train_avg_report_steps: 50
    total_steps: 400000
    checkpoint_steps: 10000
    shuffle_size: 250000
    lr_values:
        - 0.1
        - 0.01
        - 0.001
        - 0.0001
    lr_boundaries:
        - 80000
        - 200000
        - 360000
    policy_loss_weight: 1.0            # weight of policy loss
    value_loss_weight: 1.0             # weight of value loss

model:
  filters: 64
  residual_blocks: 6
  se_ratio: 8
...

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reidmcy avatar reidmcy commented on June 12, 2024

You're on Windows, that's almost certainly not a valid path on your OS. Where are your datafiles? The paths should point to them. The code we provide is intended for replication, it is not meant to be a turnkey run code and it just works, it's intended for other researches to replicate our work.

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CallOn84 avatar CallOn84 commented on June 12, 2024

You're on Windows, that's almost certainly not a valid path on your OS. Where are your datafiles? The paths should point to them. The code we provide is intended for replication, it is not meant to be a turnkey run code and it just works, it's intended for other researches to replicate our work.

Ah, okay. That makes sense. I just assumed the training was similar to that of when you train Leela Chess Zero using supervised learning, which I have done before.

As for data files, I'm not sure what you mean by that.

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reidmcy avatar reidmcy commented on June 12, 2024

Did you do steps 1 and 2 of the instructions? That's for generating the training data, those are converted to the training/validation data files in step 2.

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CallOn84 avatar CallOn84 commented on June 12, 2024

Did you do steps 1 and 2 of the instructions? That's for generating the training data, those are converted to the training/validation data files in step 2.

After fiddling about for hours on Windows, trying to get it to work, I got train_maia.py working! I'm going to start training Maia to be rated at around 2500.

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