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))