Base SGD optimizer. Arguments: params (`torch.tensor`): The input parameters to optimize. lr (`float`): The learning rate. momentum (`float`, defaults to 0): The momentum value speeds up the optimiz
(
self,
params,
lr,
momentum=0,
dampening=0,
weight_decay=0,
nesterov=False,
optim_bits=32,
args=None,
min_8bit_size=4096,
)
| 7 | |
| 8 | class SGD(Optimizer1State): |
| 9 | def __init__( |
| 10 | self, |
| 11 | params, |
| 12 | lr, |
| 13 | momentum=0, |
| 14 | dampening=0, |
| 15 | weight_decay=0, |
| 16 | nesterov=False, |
| 17 | optim_bits=32, |
| 18 | args=None, |
| 19 | min_8bit_size=4096, |
| 20 | ): |
| 21 | """ |
| 22 | Base SGD optimizer. |
| 23 | |
| 24 | Arguments: |
| 25 | params (`torch.tensor`): |
| 26 | The input parameters to optimize. |
| 27 | lr (`float`): |
| 28 | The learning rate. |
| 29 | momentum (`float`, defaults to 0): |
| 30 | The momentum value speeds up the optimizer by taking bigger steps. |
| 31 | dampening (`float`, defaults to 0): |
| 32 | The dampening value reduces the momentum of the optimizer. |
| 33 | weight_decay (`float`, defaults to 0.0): |
| 34 | The weight decay value for the optimizer. |
| 35 | nesterov (`bool`, defaults to `False`): |
| 36 | Whether to use Nesterov momentum. |
| 37 | optim_bits (`int`, defaults to 32): |
| 38 | The number of bits of the optimizer state. |
| 39 | args (`object`, defaults to `None`): |
| 40 | An object with additional arguments. |
| 41 | min_8bit_size (`int`, defaults to 4096): |
| 42 | The minimum number of elements of the parameter tensors for 8-bit optimization. |
| 43 | """ |
| 44 | if momentum == 0: |
| 45 | raise NotImplementedError("SGD without momentum is not supported!") |
| 46 | super().__init__( |
| 47 | "momentum", |
| 48 | params, |
| 49 | lr, |
| 50 | (momentum, dampening), |
| 51 | 0.0, |
| 52 | weight_decay, |
| 53 | optim_bits, |
| 54 | args, |
| 55 | min_8bit_size, |
| 56 | ) |
| 57 | |
| 58 | |
| 59 | class SGD8bit(Optimizer1State): |