def gmm_learn(v, k, nt=1, niter=30, seed=0, redo=1, use_weights=True):
_check_row_float32(v)
n, d = v.shape
flags = 0
if use_weights: flags |= yael.GMM_FLAGS_W
gmm = yael.gmm_learn(d, n, k, niter, fvec_ref(v), nt, seed, redo, flags)
gmm_npy = _gmm_to_numpy(gmm)
yael.gmm_delete(gmm)
return gmm_npy
def gmm_learn(v, k, nt=1, niter=30, seed=0, redo=1, use_weights=True):
_check_row_float32(v)
n, d = v.shape
flags = 0
if use_weights:
flags |= yael.GMM_FLAGS_W
gmm = yael.gmm_learn(d, n, k, niter, yael.numpy_to_fvec_ref(v), nt, seed, redo, flags)
gmm_npy = _gmm_to_numpy(gmm)
yael.gmm_delete(gmm)
return gmm_npy
#! /usr/bin/env python
import sys
import argparse
import numpy as np
import yael
parser = argparse.ArgumentParser()
parser.add_argument('--gmm_ncomponents', type=int, required=True)
parser.add_argument('--vocab', nargs=2, required=True)
args = parser.parse_args()
cutFrom, cutTo = map(int, args.vocab[0].split('-'))
data = np.loadtxt(sys.stdin,
dtype=np.float32,
usecols=range(cutFrom, 1 + cutTo))
npoints, nfeatures = data.shape
niter = 50
nthreads = 1
seed = 0
redo = 1
flags = yael.GMM_FLAGS_W
gmm = yael.gmm_learn(nfeatures, npoints, args.gmm_ncomponents, niter,
yael.FloatArray.acquirepointer(yael.numpy_to_fvec(data)),
nthreads, seed, redo, flags)
yael.gmm_write(gmm, open(args.vocab[1], 'w'))
#! /usr/bin/env python
import sys
import argparse
import numpy as np
import yael
parser = argparse.ArgumentParser()
parser.add_argument('--gmm_ncomponents', type = int, required = True)
parser.add_argument('--vocab', nargs = 2, required = True)
args = parser.parse_args()
cutFrom, cutTo = map(int, args.vocab[0].split('-'))
data = np.loadtxt(sys.stdin, dtype = np.float32, usecols = range(cutFrom, 1 + cutTo))
npoints, nfeatures = data.shape
niter = 50
nthreads = 1
seed = 0
redo = 1
flags = yael.GMM_FLAGS_W
gmm = yael.gmm_learn(nfeatures, npoints, args.gmm_ncomponents, niter, yael.FloatArray.acquirepointer(yael.numpy_to_fvec(data)), nthreads, seed, redo, flags)
yael.gmm_write(gmm, open(args.vocab[1], 'w'))
