dainis-boumber

import os
import re
import string
import numpy as np

from sklearn.feature_extraction.text import CountVectorizer

import torch
from torch import nn

dainis-boumber

from torch.optim.optimizer import Optimizer, required

class LARS(Optimizer):

    def __init__(self, params, lr=required, momentum=0, dampening=0,
                 weight_decay=0, nesterov=False, eta=0.001):
        if lr is not required and lr < 0.0:
            raise ValueError("Invalid learning rate: {}".format(lr))
        if momentum < 0.0:
            raise ValueError("Invalid momentum value: {}".format(momentum))