import pyOcean_cpu as ocean a = ocean.zeros([0, 5], ocean.float) b = ocean.ones([5], ocean.float) c = a * b print(c)
import pyOcean_cpu as ocean a = ocean.zeros([5, 0], ocean.float) b = ocean.ones([0, 5], ocean.float) c = a * b print(c)
def exceptionMsg():
print("Expected error: %s" % str(sys.exc_info()[1]))
def failTest(command):
try:
eval(command)
except:
print("\n>>> %s" % command)
exceptionMsg()
a = ocean.asTensor([[1, 2], [2, 3, 4]], 0)
print(a)
a = ocean.asTensor([range(3, 7), [7, 8]], 0)
print(a)
a = ocean.asTensor([[[1], [2, 3], [4, 5, 6]], ocean.ones([3, 3])], 0)
print(a)
failTest("ocean.asTensor([1,[1,2]])")
failTest("ocean.asTensor([[1,2],1])")
failTest("ocean.asTensor([xrange(4),[[1,2],[3,4]]],0)")
failTest("ocean.asTensor([[[1,2],[3,4]],xrange(4)],0)")
failTest("ocean.asTensor([ocean.ones([3]),ocean.ones([3,4])],0)")
failTest("ocean.asTensor([ocean.ones([2]),ocean.ones([3])])")
failTest("ocean.asTensor([ocean.ones([2,2,2]),ocean.ones([2,3,2])])")
failTest("ocean.asTensor([ocean.ones([2,2,2]),ocean.ones([2,2,3])])")
import pyOcean_cpu as ocean a = ocean.ones([3,4]) print(a) a = ocean.ones([3,4],ocean.int8) print(a) a = ocean.ones([3,4],ocean.cpu) print(a) a = ocean.ones([3,4],ocean.float,ocean.cpu) print(a)
import pyOcean_cpu as ocean # This should run on a single thread a = ocean.ones([10, 10], ocean.double) print(ocean.sum(a, 0)) # Each thread should reduce the result for its outputs a = ocean.ones([100, 50], ocean.double) print(ocean.sum(a, 0)) # All threads should jointly reduce each output a = ocean.ones([3, 10000], ocean.double) print(ocean.sum(a, 1))