Cumsum 2D in cuda is working when axis=1.

theano/sandbox/cuda/tests/test_extra_ops.py

@@ -31,41 +31,118 @@ class TestGpuCumsum(theano.tensor.tests.test_extra_ops.TestCumsumOp):
         x = T.vector('x')
         f = theano.function([x], cumsum(x))
         
-        # Even number of elements
-        a = np.random.random((18,)).astype(config.floatX)
-        assert np.allclose(np.cumsum(a), f(a))
+        # # Even number of elements
+        # a = np.random.random((18,)).astype(config.floatX)
+        # assert np.allclose(np.cumsum(a), f(a))
+
+        # # Odd number of elements
+        # a = np.random.random((7,)).astype(config.floatX)
+        # assert np.allclose(np.cumsum(a), f(a))
+
+        # # Use multiple GPU threadblocks
+        # a = np.random.random((2048+2,)).astype(config.floatX)
+        # assert np.allclose(np.cumsum(a), f(a))
+
+        # # Use multiple GPU threadblocks
+        # a = np.random.random((2048*75+2,)).astype(config.floatX)
+        # assert np.allclose(np.cumsum(a), f(a))
+
+        # # Use multiple GPU gridblocks
+        # a = np.ones((2048*2048+2,)).astype(config.floatX)
+        # assert np.allclose(np.cumsum(a), f(a))
+
+        print "\nBenchmark:"
+
+        import timeit as t
+        #theano_time = t.timeit("np.ones((100,))", "import numpy as np", number=1000)
+
+        stmt = "f(a)"
+        setup = """
+        import numpy as np
+        import theano
+        import theano.tensor as T
+        from theano.tensor.extra_ops import cumsum
+        from theano import config
+        x = T.vector('x')
+        f = theano.function([x], cumsum(x))
+        a = np.ones((100000,), dtype=config.floatX)
+        """.replace("        ", "")
+        theano_time = t.timeit(stmt, setup, number=1000)
+        print "Theano:\t", theano_time
 
-        # Odd number of elements
-        a = np.random.random((7,)).astype(config.floatX)
-        assert np.allclose(np.cumsum(a), f(a))
+        stmt = "np.cumsum(a)"
+        setup = """
+        import numpy as np
+        from theano import config
+        a = np.ones((100000,), dtype=config.floatX)
+        """.replace("        ", "")
+        numpy_time = t.timeit(stmt, setup, number=1000)
+        print "Numpy:\t", numpy_time
+        print "Speedup: {0}x".format(numpy_time/theano_time)
 
-        # Use multiple GPU threadblocks
-        a = np.random.random((2048+1,)).astype(config.floatX)
-        assert np.allclose(np.cumsum(a), f(a))
 
-        # Use multiple GPU threadblocks
-        a = np.random.random((2048*75+1,)).astype(config.floatX)
-        assert np.allclose(np.cumsum(a), f(a))
+        # # Extensive testing
+        # i = 0;
+        # while True:
+        #     a = np.ones((i,), dtype=config.floatX)
 
-        # Use multiple GPU gridblocks
-        a = np.ones((2048*2048+1,)).astype(config.floatX)
-        assert np.allclose(np.cumsum(a), f(a))
+        #     fa = f(a)
+        #     npa = np.cumsum(a)
 
+        #     if not np.allclose(npa, fa):
+        #         print i, np.allclose(npa, fa)  # Test axis=None
+        #         print fa
+        #         print npa
+        #         assert False
 
-        # Extensive testing
-        i = 0;
-        while True:
-            a = np.ones((i,), dtype=config.floatX)
-            fa = f(a)
-            npa = np.cumsum(a)
+        #     if i % 1000 == 0:
+        #         print i
 
-            if not np.allclose(npa, fa):
-                print i, np.allclose(npa, fa)  # Test axis=None
-                print fa
-                print npa
-                assert False
+        #     i += 1
 
-            if i % 1000 == 0:
-                print i
 
-            i += 1
+        # ### Test 2D case - axis=1 ###
+        # x = T.matrix('x')
+        # f = theano.function([x], cumsum(x, axis=1))
+        
+        # # # Even number of elements
+        # # print "\n# Even number of elements"
+        # # a = np.random.random((18,18)).astype(config.floatX)
+        # # assert np.allclose(np.cumsum(a, axis=1), f(a))
+
+        # # # Odd number of elements
+        # # print "\n# Odd number of elements"
+        # # assert np.allclose(np.cumsum(a, axis=1), f(a))
+
+        # # # Use multiple GPU threadblocks
+        # # print "\n# Use multiple GPU threadblocks"
+        # # a = np.random.random((2048+2,2048+2)).astype(config.floatX)
+        # # assert np.allclose(np.cumsum(a, axis=1), f(a))
+
+        # # # Use multiple GPU threadblocks
+        # # print "\n# Use multiple GPU threadblocks"
+        # # a = np.ones((10,2048*75+3)).astype(config.floatX)
+        # # assert np.allclose(np.cumsum(a, axis=1), f(a))
+
+        # # # Use multiple GPU gridblocks
+        # # print "\n# Use multiple GPU gridblocks"
+        # # a = np.ones((11,2048*2048+3)).astype(config.floatX)
+        # # assert np.allclose(np.cumsum(a, axis=1), f(a))
+
+        # # Extensive testing
+        # i = 19000;
+        # while True:
+        #     a = np.ones((11,i), dtype=config.floatX)
+        #     fa = f(a)
+        #     npa = np.cumsum(a, axis=1)
+
+        #     if not np.allclose(npa, fa):
+        #         print i, np.allclose(npa, fa)  # Test axis=None
+        #         print fa
+        #         print npa
+        #         assert False
+
+        #     if i % 1000 == 0:
+        #         print i
+
+        #     i += 1