def test_gpucpu_fprop_equality():
'''Test forward propagation CPU/GPU equality.'''
neth = NeuralNet([X.shape[1], 128, 32, y.shape[1]])
netd = op.to_gpu(copy.deepcopy(neth))
outh = neth.forward_pass(X)
outd = netd.forward_pass(Xd)
assert_allclose(outd.get(), outh, rtol=1e-5, err_msg="frop error")
def test_gpucpu_fprop_equality():
'''Test forward propagation CPU/GPU equality.'''
neth = NeuralNet([X.shape[1], 128, 32, y.shape[1]])
netd = op.to_gpu(copy.deepcopy(neth))
outh = neth.forward_pass(X)
outd = netd.forward_pass(Xd)
assert_allclose(outd.get(), outh, rtol=1e-5, err_msg="frop error")
def test_gpucpu_bprop_equality():
'''Test backpropagation CPU/GPU equality.'''
neth = NeuralNet([X.shape[1], 128, 32, y.shape[1]])
netd = op.to_gpu(copy.deepcopy(neth))
outh = neth.forward_pass(X)
lh = neth.backward_pass(outh, y)
outd = netd.forward_pass(Xd)
ld = netd.backward_pass(outd, yd)
assert_almost_equal(lh, ld)
assert_allclose(outd.get(), outh, rtol=1e-5, err_msg="frop error")
for i in reversed(range(len(neth.layersizes) - 1)):
dwh = neth.layers[i].dW
dbh = neth.layers[i].db
dwd = netd.layers[i].dW.get()
dbd = netd.layers[i].db.get()
assert_allclose(dwh, dwd, atol=1e-5, err_msg="dW diff in layer %d" % i)
assert_allclose(dbh, dbd, atol=1e-5, err_msg="db diff in layer %d" % i)
def test_gpucpu_bprop_equality():
'''Test backpropagation CPU/GPU equality.'''
neth = NeuralNet([X.shape[1], 128, 32, y.shape[1]])
netd = op.to_gpu(copy.deepcopy(neth))
outh = neth.forward_pass(X)
lh = neth.backward_pass(outh, y)
outd = netd.forward_pass(Xd)
ld = netd.backward_pass(outd, yd)
assert_almost_equal(lh, ld)
assert_allclose(outd.get(), outh, rtol=1e-5, err_msg="frop error")
for i in reversed(range(len(neth.layersizes)-1)):
dwh = neth.layers[i].dW
dbh = neth.layers[i].db
dwd = netd.layers[i].dW.get()
dbd = netd.layers[i].db.get()
assert_allclose(dwh, dwd, atol=1e-5, err_msg="dW diff in layer %d" % i)
assert_allclose(dbh, dbd, atol=1e-5, err_msg="db diff in layer %d" % i)
