The -1 is multiplied to the gradient, so the loss term contains it negatively. The 1 is probably not needed, but we all copied it from the DCGAN in the pytorch examples or the WGAN code.
For DCGAN and plain WGAN I can see the advantage over adding loss components (memory consumption), fir WGAN-GP its probably just copy-paste without thinking, at least that is the case for me.
Best regards
Thomas