def test_gpu():
from neon.backends.nervanagpu import NervanaGPU
ng = NervanaGPU()
# test_nms((ng, nc), (0.1, 5))
import datetime
time_old = datetime.datetime.now()
score = 4
box_count = 5
thre = 0.1
for i in range(10000):
dets = np.asarray(
[[1, 2, 3, 4, 0.6], [1, 3, 3, 4, 0.7], [1, 1, 4, 4, 0.9], [2, 1, 4, 4, 0.85], [1, 1, 3, 4, 0.85]],
dtype=np.float32)
# print(dets)
dets[:, score] = np.sort(np.random.random((box_count,)))[::-1]
dets_ng = ng.array(dets)
scores = dets_ng[:, 4].get()
order = scores.argsort()[::-1]
sorted_dets_dev = dets_ng[order, :]
keep_ng = ng.nms(sorted_dets_dev, thre)
# print("gpu nms", keep_ng)
print('requests gpu', (datetime.datetime.now() - time_old).microseconds)
def test_slicing(fargs_tests):
dims, dtype = fargs_tests
gpu = NervanaGPU(default_dtype=dtype)
cpu = NervanaCPU(default_dtype=dtype)
array_np = np.random.uniform(-1, 1, dims).astype(dtype)
array_ng = gpu.array(array_np, dtype=dtype)
array_nc = cpu.array(array_np, dtype=dtype)
assert_tensors_allclose(array_ng[0], array_nc[0], rtol=0, atol=1e-3)
assert_tensors_allclose(array_ng[-1], array_nc[-1], rtol=0, atol=1e-3)
assert_tensors_allclose(array_ng[0, :], array_nc[0, :], rtol=0, atol=1e-3)
assert_tensors_allclose(array_ng[0:], array_nc[0:], rtol=0, atol=1e-3)
assert_tensors_allclose(array_ng[:-1], array_nc[:-1], rtol=0, atol=1e-3)
assert_tensors_allclose(array_ng[:, 0], array_nc[:, 0], rtol=0, atol=1e-3)
assert_tensors_allclose(array_ng[:, 0:1], array_nc[:, 0:1], rtol=0, atol=1e-3)
assert_tensors_allclose(array_ng[-1, 0:], array_nc[-1:, 0:], rtol=0, atol=1e-3)
array_ng[0] = 0
array_nc[0] = 0
assert_tensors_allclose(array_ng, array_nc, rtol=0, atol=1e-3)
del(gpu)
