fn_out = dir_out + fn
def gmm_objective_wrapper(params, x, wishart_gamma, wishart_m):
return gmm.gmm_objective(params[0], params[1], params[2], x, wishart_gamma,
wishart_m)
alphas, means, icf, x, wishart_gamma, wishart_m = gmm_io.read_gmm_instance(
fn_in + ".txt", replicate_point)
tf = utils.timer(gmm.gmm_objective,
(alphas, means, icf, x, wishart_gamma, wishart_m),
nruns=nruns_f,
limit=time_limit)
name = "Autograd"
if nruns_J > 0:
# k = alphas.size
grad_gmm_objective_wrapper = value_and_grad(gmm_objective_wrapper)
tJ, grad = utils.timer(grad_gmm_objective_wrapper,
((alphas, means, icf), x, wishart_gamma, wishart_m),
nruns=nruns_J,
limit=time_limit,
ret_val=True)
gmm_io.write_J(fn_out + "_J_" + name + ".txt", grad[1])
else:
tJ = 0
utils.write_times(fn_out + "_times_" + name + ".txt", tf, tJ)
nruns_J = int(sys.argv[argv_idx + 4])
fn_in = dir_in + fn
fn_out = dir_out + fn
alphas, means, icf, x, wishart_gamma, wishart_m = gmm_io.read_gmm_instance(
fn_in + ".txt", replicate_point)
tf, err = utils.timer(f, (alphas, means, icf, x, wishart_gamma, wishart_m),
nruns=nruns_f,
limit=time_limit,
ret_val=True)
print("err:")
print(err)
name = "Theano"
if nruns_J > 0:
tJ, J = utils.timer(fgrad,
(alphas, means, icf, x, wishart_gamma, wishart_m),
nruns=nruns_J,
limit=time_limit,
ret_val=True)
tJ += tf # !!!!!!!!! adding this because no function value is returned by fgrad
gmm_io.write_J(fn_out + "_J_" + name + ".txt", J)
else:
tJ = 0
utils.write_times(fn_out + "_times_" + name + ".txt", tf, tJ)
from python_common import gmm_io
import torch_wrapper
import gmm_objective as gmm
dir_in = sys.argv[1]
dir_out = sys.argv[2]
fn = sys.argv[3]
nruns_f = int(sys.argv[4])
nruns_J = int(sys.argv[5])
time_limit = int(sys.argv[6]) if len(sys.argv) >= 7 else float("inf")
replicate_point = (len(sys.argv) >= 8 and sys.argv[7] == "-rep")
fn_in = dir_in + fn
fn_out = dir_out + fn
alphas, means, icf, x, wishart_gamma, wishart_m = gmm_io.read_gmm_instance(fn_in + ".txt", replicate_point)
tf = utils.timer(torch_wrapper.torch_func, (gmm.gmm_objective, (alphas, means, icf), (x, wishart_gamma, wishart_m), False), nruns=nruns_f, limit=time_limit)
name = "PyTorch"
if nruns_J > 0:
# k = alphas.size
tJ, res = utils.timer(torch_wrapper.torch_func, (gmm.gmm_objective, (alphas, means, icf), (x, wishart_gamma, wishart_m), True), nruns=nruns_J, limit=time_limit, ret_val=True)
gmm_io.write_J(fn_out + "_J_" + name + ".txt", res[1])
else:
tJ = 0
utils.write_times(fn_out + "_times_" + name + ".txt", tf, tJ)