def generate_layers(): neurons = Path('./neuron1024') for i in range(nneurons): l = Path('./neuron1024/n1024-l{}.tsv'.format(str(i + 1))) with l.open() as f: print('loading layer: ', i + 1) yield Matrix.from_tsv(f, lib.GrB_FP32, nneurons, nneurons)
def load_images(): images = Path('sparse-images-1024.tsv') with images.open() as i: print('loading images.') Y0 = Matrix.from_tsv(i, lib.GrB_FP32, nfeatures, nneurons) return Y0
def test_matrix_tsv_read(tmp_path): mmf = tmp_path / 'tsv_test.mm' mmf.touch() with mmf.open('w') as f: f.writelines(['3\t3\t3\n', '1\t1\t2\n', '2\t2\t3\n', '3\t3\t4\n']) with mmf.open() as f: n = Matrix.from_tsv(f, int, 3, 3) assert n.to_lists() == [[0, 1, 2], [0, 1, 2], [2, 3, 4]]
def load_layer(neurons, dest, i): fname = "{}/neuron{}/n{}-l{}.{}" binfile = fname.format(dest, neurons, neurons, str(i + 1), "ssb") if Path(binfile).exists(): return Matrix.from_binfile(binfile.encode("ascii")) l = Path(fname.format(dest, neurons, neurons, str(i + 1), "tsv")) with l.open() as f: m = Matrix.from_tsv(f, FP32, neurons, neurons) m.to_binfile(binfile.encode("ascii")) return m
def load_images(neurons, dest): fname = "{}/sparse-images-{}.{}" binfile = fname.format(dest, neurons, "ssb") if Path(binfile).exists(): return Matrix.from_binfile(binfile.encode("ascii")) images = Path(fname.format(dest, neurons, "tsv")) with images.open() as i: m = Matrix.from_tsv(i, FP32, NFEATURES, neurons) m.to_binfile(binfile.encode("ascii")) return m
def load_layer(i, dest): l = Path('{}/neuron{}/n{}-l{}.tsv'.format(dest, neurons, neurons, str(i+1))) with l.open() as f: return Matrix.from_tsv(f, lib.GrB_FP32, neurons, neurons)
def load_images(neurons, dest): images = Path('{}/sparse-images-{}.tsv'.format(dest, neurons)) with images.open() as i: return Matrix.from_tsv(i, lib.GrB_FP32, NFEATURES, neurons)