Question Warning when using LSTM

I have tried adding memory to my agent while using PPO and when the first ONNX model checkpoint is made this error is written to the console:


UserWarning: Exporting a model to ONNX with a batch_size other than 1, with a variable length with LSTM can cause an error when running the ONNX model with a different batch size. Make sure to save the model with a batch size of 1, or define the initial states (h0/c0) as inputs of the model.

I'm not quite sure how to interpret this so if anybody can give any insight that would be greatly appreciated

Here is my YAML config file:
behaviors:
SkripsieFighter:
trainer_type: ppo
hyperparameters:
batch_size: 512
buffer_size: 10240
learning_rate: 1.0e-4
beta: 5.0e-3
epsilon: 0.2
lambd: 0.9
num_epoch: 3
learning_rate_schedule: linear
network_settings:
normalize: false
hidden_units: 512
num_layers: 2
memory:
memory_size: 128
sequence_length: 64
reward_signals:
extrinsic:
gamma: 1.0
strength: 1.0
max_steps: 50000000
time_horizon: 1024
summary_freq: 50000
self_play:
save_steps: 100000
team_change: 500000
swap_steps: 50000
window: 30
play_against_latest_model_ratio: 0.5

 

It would be nice to have an official confirmation, but it seems this error is a false alarm and the outputted neural network is valid: https://github.com/pytorch/pytorch/issues/45653

 

On some days I see this warning message very often. On some days I never see it at all. On rare occasions ML Agents training crashes immediately after this error. When that happens I just resume the training run with the --resume flag

However the models train perfectly fine whether I see this warning message or not. Meaning zero impact on training.

In terms of the output OMNZ file that is also perfectly fine. Meaning zero impact on the final trained model either.