def test_strided_elementwise_inplace():
from brainstorm.handlers import PyCudaHandler
_h = PyCudaHandler()
rdm = np.random.RandomState(1345)
def get_rdm_array(shape, dims):
if dims == 2: return rdm.randn(shape[0],shape[1])
elif dims == 3: return rdm.randn(shape[0],shape[1], shape[2])
else: return rdm.randn(shape[0],shape[1], shape[2], shape[3])
for dims in range(2,5):
for i in range(10):
shape = rdm.randint(1,17,dims)
a1 = np.float32(get_rdm_array(shape, dims))
a2 = np.float32(get_rdm_array(shape, dims))
a3 = np.float32(get_rdm_array(shape, dims))
a = np.vstack([a1,a2,a3])
original_shape = a.shape
a = a.reshape([int(original_shape[0]/3)] + list(original_shape[1:])+[3])
b = np.zeros_like(a, dtype=np.float32)
A = _h.create_from_numpy(a)
_h.strided_elementwise_inplace(A, 1,'logistic')
_h.strided_elementwise_inplace(A, 0,'tanh')
outputs = _h.get_numpy_copy(A).reshape(original_shape)
c1 = np.tanh(a1)
c2 = 1./(1.+np.exp(a2))
c3 = a3
c = np.vstack([c1,c2,c3])
passed = np.allclose(outputs, c)
assert passed
