Error occurred during model training.

[XLOXL]

Hello, I didn't encounter any errors when training small amounts of data, but when I tried to train several Gs worth of data, I received the following error. Could you please advise me on how to fix it? Error：tensorflow.python.framework.errors_impl.InvalidArgumentError: len(seq_lens) != input.dims(0), (22 vs. 32) [[node token_lstm/bidirectional_rnn/bw/ReverseSequence (defined at /anaconda3/envs/DeepMicrobes-master/lib/python3.6/site-packages/tensorflow_core/python/framework/ops.py:1748) ]]

[MicrobeLab]

Hi, sorry I did not encounter such errors before and have no idea how to fix it.

[XLOXL]

Okay, thank you!

[XLOXL]

Hello, I have another question. The default batch size for training is 32, while the default batch size for prediction is 8192. I'm wondering what the difference is between the two and why the values are so different.

[MicrobeLab]

For prediction, the batch size has no effect on the results, so I tend to use the largest batch size that fits into memory. For training, batch size is an important hyper-parameter that users should carefully tune.

[XLOXL]

Okay, thank you!

[XLOXL]

Hello, have you encountered a similar error during prediction before? I have modified my num_classes, vocab_size, and k-mer. Error：Assign requires shapes of both tensors to match. lhs shape= [2505] rhs shape= [1] [[node save/Assign_7 (defined at /anaconda3/envs/DeepMicrobes-master/lib/python3.6/site-packages/tensorflow_core/python/framework/ops.py:1748) ]]

[MicrobeLab]

Hi, I have not encountered a similar error. It seems that the number of classes was left as the default 2505. Not sure why.

[XLOXL]

Okay, thank you very much for your patient response.