Thanks for the code snippet.
I cannot reproduce the error using your model and this code:
model = SpeedChallengeModel1()
model = model.float()

mse_full = nn.MSELoss(reduction="none")
batch_datas = torch.randn(2, 3, 66, 220)
batch_labels = torch.randn(2)
                
# predict speed
pred = model(batch_datas)            
loss_each = mse_full( pred.flatten(), batch_labels )
loss_all = torch.mean(loss_each)
loss_all.backward()