movefast

class Seq2SeqAttnRNN(nn.Module):
    def __init__(self, vecs_enc, itos_enc, em_sz_enc, vecs_dec, itos_dec, em_sz_dec, nh, out_sl, nl=2):
        super().__init__()
        self.emb_enc = create_emb(vecs_enc, itos_enc, em_sz_enc)
        self.nl,self.nh,self.out_sl = nl,nh,out_sl
        self.gru_enc = nn.GRU(em_sz_enc, nh, num_layers=nl, dropout=0.25)
        self.out_enc = nn.Linear(nh, em_sz_dec, bias=False)
        self.emb_dec = create_emb(vecs_dec, itos_dec, em_sz_dec)
        self.gru_dec = nn.GRU(em_sz_dec, em_sz_dec, num_layers=nl, dropout=0.1)
        self.emb_enc_drop = nn.Dropout(0.15)

movefast

from torch.utils.data.sampler import Sampler
from torch.utils.data.sampler import RandomSampler

class WeightedLossSampler(Sampler, Callback):
    
    def __init__(self, data_source, replacement=True, bs=64, init_fac=1, ls_init_fac=1e-2):
        self.num_samples = len(data_source)
        self.weights = to_gpu(torch.ones(self.num_samples)*init_fac)
        self.replacement = replacement
        self.i = 0

movefast

# you have ctags but it does not work...
$ ctags -R --exclude=.git --exclude=log *
ctags: illegal option -- R
usage: ctags [-BFadtuwvx] [-f tagsfile] file ...

#you need to get new ctags, i recommend homebrew but anything will work
$ brew install ctags

#alias ctags if you used homebrew
$ alias ctags="`brew --prefix`/bin/ctags"

movefast

public class Solution {
    public static int uniquePathsWithObstacles(int[][] obstacleGrid) {
        if(obstacleGrid.length == 0 || obstacleGrid[0].length == 0) return 0;
        int[][] res = new int[obstacleGrid.length][obstacleGrid[0].length];
        for(int i = 0; i < obstacleGrid.length; i++) {
            for(int j = 0; j < obstacleGrid[0].length;j++) {
                if(obstacleGrid[i][j] == 1) res[i][j] = 0;
                else if(i == 0 && j == 0) res[0][0] = 1;
                else if (i == 0) res[i][j] = res[i][j-1];
                else if (j == 0) res[i][j] = res[i-1][j];