提交 d5faa5be authored 作者: Frederic Bastien's avatar Frederic Bastien

white space fix.

上级 85824792
......@@ -28,7 +28,7 @@ def test_neibs():
neibs = f()
#print neibs
g = function([], neibs2images(neibs, neib_shape, images.shape), mode=mode_without_gpu)
#print g()
assert numpy.allclose(images.value,g())
......@@ -149,7 +149,7 @@ def test_neibs_manual():
[88, 89, 92, 93],
[90, 91, 94, 95]])
g = function([], neibs2images(neibs, neib_shape, images.shape), mode=mode_without_gpu)
#print g()
assert numpy.allclose(images.value,g())
......@@ -198,7 +198,7 @@ def test_neibs_step_manual():
[135, 136, 137, 140, 141, 142, 145, 146, 147],
[137, 138, 139, 142, 143, 144, 147, 148, 149]])
#g = function([], neibs2images(neibs, neib_shape, images.shape), mode=mode_without_gpu)
#print g()
#assert numpy.allclose(images.value,g())
......@@ -243,7 +243,7 @@ def test_neibs_wrap_centered_step_manual():
[ 13, 14, 10, 18, 19, 15, 23, 24, 20]]
#TODO test discontinous image
for shp_idx,(shape,neib_shape,neib_step,expected) in enumerate([
[(7,8,5,5),(3,3),(2,2),expected1],
[(7,8,5,5),(3,3),(3,3),expected2],
......@@ -274,13 +274,13 @@ def test_neibs_wrap_centered_step_manual():
assert GpuImages2Neibs in [type(node.op) for node in f.maker.env.toposort()]
#g = function([], neibs2images(neibs, neib_shape, images.shape), mode=mode_without_gpu)
#assert numpy.allclose(images.value,g())
def test_neibs_gpu():
if cuda.cuda_available == False:
raise SkipTest('Optional package cuda disabled')
raise SkipTest('Optional package cuda disabled')
for shape, pshape in [((100,40,18,18),(2,2)),
((100,40,6,18),(3,2)),
((10,40,66,66),(33,33)),
......@@ -315,7 +315,7 @@ def speed_neibs():
from theano.sandbox.cuda.basic_ops import gpu_from_host
f = function([], images2neibs(images,neib_shape))#, mode=mode_without_gpu)
for i in range(1000):
f()
......@@ -327,10 +327,10 @@ def speed_neibs_wrap_centered():
from theano.sandbox.cuda.basic_ops import gpu_from_host
f = function([], images2neibs(images,neib_shape,mode="wrap_centered"))#, mode=mode_without_gpu)
for i in range(1000):
f()
def test_neibs_grad():
shape = (2,3,4,4)
images = T.shared(numpy.arange(numpy.prod(shape), dtype='float32').reshape(shape))
......@@ -427,4 +427,3 @@ if __name__ == '__main__':
#test_neibs()
#test_neibs_grad_verify_grad()
test_neibs2images_crash_on_grad()
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