I have a very sparse dataset that is organized as a scipy sparse csr_matrix and it is too large to convert it to a single dense numpy array. For now, I can only extract part of it and convert that part to an numpy array, then to a tensor and forward the tensor.  But the csr_matrix to numpy array step is still awfully time-consuming. I wonder whether there is a better method to feed the sparse matrix.