(exp_avg_sq, grad, beta2)
| 85 | |
| 86 | # Functions to update the different optimizer states |
| 87 | def update_exp_avg_sq(exp_avg_sq, grad, beta2): |
| 88 | return exp_avg_sq.mul(beta2).addcmul(grad, grad, value=1 - beta2) |
| 89 | |
| 90 | def update_param(param, step, exp_avg, exp_avg_sq, beta1, beta2, lr, eps): |
| 91 | bias_correction1 = 1 - torch.pow(beta1, step) |
nothing calls this directly
no outgoing calls
no test coverage detected