wayveai / mile

PyTorch code for the paper "Model-Based Imitation Learning for Urban Driving".
MIT License
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Confused about the observation dropout #32

Open wzn0828 opened 8 months ago

wzn0828 commented 8 months ago

Through the paper, I learned the working mechanism of observation dropout. But, during training, when decoding the h and s to the output, why not use the observation dropout ?

image

anthonyhu commented 8 months ago

Hello,

The observation dropout is only used to drop the input observation fed to the posterior. There is no need to additionally dropout when feeding the state to the policy.

wzn0828 commented 8 months ago

Hello,

The observation dropout is only used to drop the input observation fed to the posterior. There is no need to additionally dropout when feeding the state to the policy.

However, In the screenshot, you always use the posterior sample to decoder action and BEV. That's to say, you do not use the dropout when action decoding and BEV decoding, you just use it for the input of GRU.

anthonyhu commented 8 months ago

That's correct, dropout is only used for the input of the GRU. During training, the action and BEV output are predicted from the posterior.