I recently discovered Google Colab and I uploaded my Pytorch project related to training models for processing audio. I got it training models using google’s TPUs, but I noticed that the models were less accurate than the ones I trained on my local machine. It turns out the the state dict weights and biases have about half the decimal places as the locally trained model. After some searching I read that Colab uses float16 By default instead of float32 precision to increase speed, but since the audio I’m training is in float32, it really needs to train in float32 precision. Is there a way to change this in Colab? Or is there a way to change my pytorch model to ensure float32 precision is kept? My model uses a stack of 1d convolutional layers, if that matters.