Edouard360

import numpy as np
import scipy.sparse as sp
import torch
import torch.nn as nn
from torch.utils.data import DataLoader, Dataset


def one_hot(index, n_cat):
    onehot = torch.zeros(index.size(0), n_cat, device=index.device)
    onehot.scatter_(1, index.type(torch.long), 1)

Edouard360

import torch
import scipy.sparse as sp
def test_sparse_tensor():
    # That is sparse for sure
    data = np.random.binomial(1, 0.01, size=(128, 27000))
    csr_matrix = sp.csr_matrix(data)

    indptr = csr_matrix.indptr
    indices = csr_matrix.indices
    i = torch.LongTensor(np.array([[l, j] for l, i in enumerate(range(len(indptr) - 1))

Edouard360

import re

import numpy as np
import torch

from scvi.dataset.dataset import GeneExpressionDataset
from scvi.dataset.synthetic import SyntheticDataset


class NamedDataset1(GeneExpressionDataset):