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import ot
import numpy as np
import time
import pytest
try: # test if cudamat installed
import ot.gpu
nogpu = False
except ImportError:
nogpu = True
@pytest.mark.skipif(nogpu, reason="No GPU available")
def test_gpu_sinkhorn():
np.random.seed(0)
def describeRes(r):
print("min:{:.3E}, max::{:.3E}, mean::{:.3E}, std::{:.3E}".format(
np.min(r), np.max(r), np.mean(r), np.std(r)))
for n in [50, 100, 500, 1000]:
print(n)
a = np.random.rand(n // 4, 100)
b = np.random.rand(n, 100)
time1 = time.time()
transport = ot.da.OTDA_sinkhorn()
transport.fit(a, b)
G1 = transport.G
time2 = time.time()
transport = ot.gpu.da.OTDA_sinkhorn()
transport.fit(a, b)
G2 = transport.G
time3 = time.time()
print("Normal sinkhorn, time: {:6.2f} sec ".format(time2 - time1))
describeRes(G1)
print(" GPU sinkhorn, time: {:6.2f} sec ".format(time3 - time2))
describeRes(G2)
assert np.allclose(G1, G2, rtol=1e-5, atol=1e-5)
@pytest.mark.skipif(nogpu, reason="No GPU available")
def test_gpu_sinkhorn_lpl1():
np.random.seed(0)
def describeRes(r):
print("min:{:.3E}, max:{:.3E}, mean:{:.3E}, std:{:.3E}"
.format(np.min(r), np.max(r), np.mean(r), np.std(r)))
for n in [50, 100, 500]:
print(n)
a = np.random.rand(n // 4, 100)
labels_a = np.random.randint(10, size=(n // 4))
b = np.random.rand(n, 100)
time1 = time.time()
transport = ot.da.OTDA_lpl1()
transport.fit(a, labels_a, b)
G1 = transport.G
time2 = time.time()
transport = ot.gpu.da.OTDA_lpl1()
transport.fit(a, labels_a, b)
G2 = transport.G
time3 = time.time()
print("Normal sinkhorn lpl1, time: {:6.2f} sec ".format(
time2 - time1))
describeRes(G1)
print(" GPU sinkhorn lpl1, time: {:6.2f} sec ".format(
time3 - time2))
describeRes(G2)
assert np.allclose(G1, G2, rtol=1e-5, atol=1e-5)
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