Buckets:
| # SGD | |
| Stochastic gradient descent (SGD) is a basic gradient descent optimizer to minimize loss given a set of model parameters and updates the parameters in the opposite direction of the gradient. The update is performed on a randomly sampled mini-batch of data from the dataset. | |
| bitsandbytes also supports momentum and Nesterov momentum to accelerate SGD by adding a weighted average of past gradients to the current gradient. | |
| ## SGD[[api-class]][[bitsandbytes.optim.SGD]] | |
| #### bitsandbytes.optim.SGD[[bitsandbytes.optim.SGD]] | |
| ```python | |
| bitsandbytes.optim.SGD(params, lr, momentum = 0, dampening = 0, weight_decay = 0, nesterov = False, optim_bits = 32, args = None, min_8bit_size = 4096) | |
| ``` | |
| [Source](https://github.com/bitsandbytes-foundation/bitsandbytes/blob/vr_2038/bitsandbytes/optim/sgd.py#L8) | |
| #### __init__[[bitsandbytes.optim.SGD.__init__]] | |
| ```python | |
| __init__(params, lr, momentum = 0, dampening = 0, weight_decay = 0, nesterov = False, optim_bits = 32, args = None, min_8bit_size = 4096) | |
| ``` | |
| [Source](https://github.com/bitsandbytes-foundation/bitsandbytes/blob/vr_2038/bitsandbytes/optim/sgd.py#L9) | |
| **Parameters:** | |
| params (`torch.tensor`) : The input parameters to optimize. | |
| lr (`float`) : The learning rate. | |
| momentum (`float`, defaults to 0) : The momentum value speeds up the optimizer by taking bigger steps. | |
| dampening (`float`, defaults to 0) : The dampening value reduces the momentum of the optimizer. | |
| weight_decay (`float`, defaults to 0.0) : The weight decay value for the optimizer. | |
| nesterov (`bool`, defaults to `False`) : Whether to use Nesterov momentum. | |
| optim_bits (`int`, defaults to 32) : The number of bits of the optimizer state. | |
| args (`object`, defaults to `None`) : An object with additional arguments. | |
| min_8bit_size (`int`, defaults to 4096) : The minimum number of elements of the parameter tensors for 8-bit optimization. | |
| Base SGD optimizer. | |
| ## SGD8bit[[bitsandbytes.optim.SGD8bit]] | |
| #### bitsandbytes.optim.SGD8bit[[bitsandbytes.optim.SGD8bit]] | |
| ```python | |
| bitsandbytes.optim.SGD8bit(params, lr, momentum = 0, dampening = 0, weight_decay = 0, nesterov = False, args = None, min_8bit_size = 4096) | |
| ``` | |
| [Source](https://github.com/bitsandbytes-foundation/bitsandbytes/blob/vr_2038/bitsandbytes/optim/sgd.py#L59) | |
| #### __init__[[bitsandbytes.optim.SGD8bit.__init__]] | |
| ```python | |
| __init__(params, lr, momentum = 0, dampening = 0, weight_decay = 0, nesterov = False, args = None, min_8bit_size = 4096) | |
| ``` | |
| [Source](https://github.com/bitsandbytes-foundation/bitsandbytes/blob/vr_2038/bitsandbytes/optim/sgd.py#L60) | |
| **Parameters:** | |
| params (`torch.tensor`) : The input parameters to optimize. | |
| lr (`float`) : The learning rate. | |
| momentum (`float`, defaults to 0) : The momentum value speeds up the optimizer by taking bigger steps. | |
| dampening (`float`, defaults to 0) : The dampening value reduces the momentum of the optimizer. | |
| weight_decay (`float`, defaults to 0.0) : The weight decay value for the optimizer. | |
| nesterov (`bool`, defaults to `False`) : Whether to use Nesterov momentum. | |
| args (`object`, defaults to `None`) : An object with additional arguments. | |
| min_8bit_size (`int`, defaults to 4096) : The minimum number of elements of the parameter tensors for 8-bit optimization. | |
| 8-bit SGD optimizer. | |
| ## SGD32bit[[bitsandbytes.optim.SGD32bit]] | |
| #### bitsandbytes.optim.SGD32bit[[bitsandbytes.optim.SGD32bit]] | |
| ```python | |
| bitsandbytes.optim.SGD32bit(params, lr, momentum = 0, dampening = 0, weight_decay = 0, nesterov = False, args = None, min_8bit_size = 4096) | |
| ``` | |
| [Source](https://github.com/bitsandbytes-foundation/bitsandbytes/blob/vr_2038/bitsandbytes/optim/sgd.py#L107) | |
| #### __init__[[bitsandbytes.optim.SGD32bit.__init__]] | |
| ```python | |
| __init__(params, lr, momentum = 0, dampening = 0, weight_decay = 0, nesterov = False, args = None, min_8bit_size = 4096) | |
| ``` | |
| [Source](https://github.com/bitsandbytes-foundation/bitsandbytes/blob/vr_2038/bitsandbytes/optim/sgd.py#L108) | |
| **Parameters:** | |
| params (`torch.tensor`) : The input parameters to optimize. | |
| lr (`float`) : The learning rate. | |
| momentum (`float`, defaults to 0) : The momentum value speeds up the optimizer by taking bigger steps. | |
| dampening (`float`, defaults to 0) : The dampening value reduces the momentum of the optimizer. | |
| weight_decay (`float`, defaults to 0.0) : The weight decay value for the optimizer. | |
| nesterov (`bool`, defaults to `False`) : Whether to use Nesterov momentum. | |
| args (`object`, defaults to `None`) : An object with additional arguments. | |
| min_8bit_size (`int`, defaults to 4096) : The minimum number of elements of the parameter tensors for 8-bit optimization. | |
| 32-bit SGD optimizer. | |
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