def run_legion(N):
from legion import Client
client = Client()
alpha = 0.5
beta = 0.5
big_matrix = generate_big_matrix(N)
current_inv_approx = np.eye(N)
client.create_if_not_already_created("current_inv_approx", current_inv_approx)
current_inv_approx = client.pull_full("current_inv_approx")
#print "type(current_inv_approx)"
#print type(current_inv_approx)
current_error = get_error(current_inv_approx, big_matrix)
original_noise = 0.001
current_noise = original_noise
last_index_with_good_proposal = 0
for i in range(1000):
(status, current_inv_approx, current_error) = try_one_guess(current_inv_approx, big_matrix, current_noise, current_error)
#print "update %s, current_error %0.4f" % (status, current_error)
time.sleep(1)
if status == 'success':
client.push_full("current_inv_approx", current_inv_approx, alpha, beta)
print "Pushed current_inv_approx with error %0.12f to server." % current_error
current_inv_approx = client.pull_full("current_inv_approx")
last_index_with_good_proposal = i
current_noise = original_noise
else:
current_noise = 0.9 * current_noise
if last_index_with_good_proposal == i or 25 < last_index_with_good_proposal - i:
current_inv_approx = client.pull_full("current_inv_approx")
current_error = get_error(current_inv_approx, big_matrix)
print "Pulled current_inv_approx with error %0.12f from server." % current_error
"""
def main():
leg = Client()
test = -np.ones((10, 20, 30))
test[2:5, 2:5, 2:5] = np.zeros((3, 3, 3))
# We create the value on the server. If we try to create it from different clients at once,
# it will only take the first value it receives, and send it back to the other clients so they know which one was picked.
test = leg.create_if_not_already_created("test", test)
test *= 2
comp_test0 = leg.pull_full("test")
leg.push_as_part("test", test, [[0], [1, 4], [1, 6]], 0.5, 0.5)
comp_test1 = leg.pull_full("test")
print comp_test0
print comp_test1
