class TestGPU(object):
def setup(self):
from neon.backends.mgpu import MGPU, MGPUTensor
# this code gets called prior to each test
try:
self.be = MGPU(rng_seed=0, num_dev=2)
except AssertionError:
# likely that only one GPU device is available
self.be = MGPU(rng_seed=0, num_dev=1)
self.gpt = MGPUTensor
def reduction_test(self):
nr = self.be.num_dev
if nr == 1: # This shouldn't be supported
return
# create a numpy array as the test-bed
asize = 9
# round up to the nearest multiple of num_dev
bsize = -(-asize // nr) * nr
h_a = np.random.randn(asize * nr).reshape(
(nr, asize)).astype(self.be.default_dtype)
h_result = np.sum(h_a, axis=0, keepdims=True)
d_a = self.be.empty((1, asize))
u_a = self.be.empty((1, bsize))
self.be.scatter(h_a, d_a)
self.be.reduce(d_a, u_a)
print(h_result)
print(d_a.tlist[0].asnumpyarray())
for i in range(nr):
np.testing.assert_allclose(d_a.tlist[i].asnumpyarray(),
h_result,
atol=1e-6,
rtol=0)
def memset_test(self):
# create a numpy array as the test-bed
asize = 9
h_result = np.zeros((1, asize))
d_a = self.be.zeros((1, asize))
for i in range(self.be.num_dev):
np.testing.assert_allclose(d_a.tlist[i].asnumpyarray(),
h_result,
atol=1e-6,
rtol=0)
def frag2rep_test(self):
nr = self.be.num_dev
if nr == 1: # This shouldn't be supported
return
np.random.seed(0)
# create a numpy array as the test-bed
(rows, cols) = (24, 128)
indim = rows * cols
odim = indim * nr
# h_frags has the data in the order we expect on the device
h_frags_t = np.random.randn(odim).reshape(
(nr * cols, rows)).astype(self.be.default_dtype)
h_frags = h_frags_t.transpose().astype(self.be.default_dtype,
order='C')
d_frags = self.be.empty((rows, cols))
d_frags_t = self.be.empty((cols, rows))
d_reps = self.be.empty((rows, cols * nr))
d_reps_t = self.be.empty((cols * nr, rows))
self.be.scatter(h_frags_t, d_frags_t)
self.be.transpose(d_frags_t, d_frags)
np.testing.assert_allclose(d_frags.asnumpyarray(),
h_frags,
atol=1e-5,
rtol=0)
self.be.fragment_to_replica(d_frags_t, d_reps_t)
self.be.transpose(d_reps_t, d_reps)
for i in range(nr):
np.testing.assert_allclose(d_frags.asnumpyarray(),
d_reps.tlist[i].asnumpyarray(),
atol=1e-5,
rtol=0)
print("Frag2Rep OK")
d_frags_t.fill(0)
self.be.replica_to_fragment(d_reps_t, d_frags_t)
self.be.transpose(d_frags_t, d_frags)
for i in range(nr):
np.testing.assert_allclose(d_frags.asnumpyarray(),
d_reps.tlist[i].asnumpyarray(),
atol=1e-5,
rtol=0)
print("Rep2Frag OK")
class TestGPU(object):
def setup(self):
from neon.backends.mgpu import MGPU, MGPUTensor
# this code gets called prior to each test
try:
self.be = MGPU(rng_seed=0, num_dev=2)
except AssertionError:
# likely that only one GPU device is available
self.be = MGPU(rng_seed=0, num_dev=1)
self.gpt = MGPUTensor
def reduction_test(self):
nr = self.be.num_dev
if nr == 1: # This shouldn't be supported
return
# create a numpy array as the test-bed
asize = 9
# round up to the nearest multiple of num_dev
bsize = -(-asize // nr) * nr
h_a = np.random.randn(asize * nr).reshape(
(nr, asize)).astype(self.be.default_dtype)
h_result = np.sum(h_a, axis=0, keepdims=True)
d_a = self.be.empty((1, asize))
u_a = self.be.empty((1, bsize))
self.be.scatter(h_a, d_a)
self.be.reduce(d_a, u_a)
print(h_result)
print(d_a.tlist[0].asnumpyarray())
for i in range(nr):
np.testing.assert_allclose(d_a.tlist[i].asnumpyarray(),
h_result, atol=1e-6, rtol=0)
def memset_test(self):
# create a numpy array as the test-bed
asize = 9
h_result = np.zeros((1, asize))
d_a = self.be.zeros((1, asize))
for i in range(self.be.num_dev):
np.testing.assert_allclose(d_a.tlist[i].asnumpyarray(),
h_result, atol=1e-6, rtol=0)
def frag2rep_test(self):
nr = self.be.num_dev
if nr == 1: # This shouldn't be supported
return
np.random.seed(0)
# create a numpy array as the test-bed
(rows, cols) = (24, 128)
indim = rows * cols
odim = indim * nr
# h_frags has the data in the order we expect on the device
h_frags_t = np.random.randn(odim).reshape(
(nr * cols, rows)).astype(self.be.default_dtype)
h_frags = h_frags_t.transpose().astype(
self.be.default_dtype, order='C')
d_frags = self.be.empty((rows, cols))
d_frags_t = self.be.empty((cols, rows))
d_reps = self.be.empty((rows, cols * nr))
d_reps_t = self.be.empty((cols * nr, rows))
self.be.scatter(h_frags_t, d_frags_t)
self.be.transpose(d_frags_t, d_frags)
np.testing.assert_allclose(d_frags.asnumpyarray(),
h_frags, atol=1e-5, rtol=0)
self.be.fragment_to_replica(d_frags_t, d_reps_t)
self.be.transpose(d_reps_t, d_reps)
for i in range(nr):
np.testing.assert_allclose(d_frags.asnumpyarray(),
d_reps.tlist[i].asnumpyarray(),
atol=1e-5, rtol=0)
print("Frag2Rep OK")
d_frags_t.fill(0)
self.be.replica_to_fragment(d_reps_t, d_frags_t)
self.be.transpose(d_frags_t, d_frags)
for i in range(nr):
np.testing.assert_allclose(d_frags.asnumpyarray(),
d_reps.tlist[i].asnumpyarray(),
atol=1e-5, rtol=0)
print("Rep2Frag OK")
