def test_NanGuardMode():
# Tests if NanGuardMode is working by feeding in numpy.inf and numpy.nans
# intentionally. A working implementation should be able to capture all
# the abnormalties.
x = T.matrix()
w = theano.shared(numpy.random.randn(5, 7).astype(theano.config.floatX))
y = T.dot(x, w)
fun = theano.function(
[x], y,
mode=NanGuardMode(nan_is_error=True, inf_is_error=True)
)
a = numpy.random.randn(3, 5).astype(theano.config.floatX)
infa = numpy.tile(
(numpy.asarray(100.) ** 1000000).astype(theano.config.floatX), (3, 5))
nana = numpy.tile(
numpy.asarray(numpy.nan).astype(theano.config.floatX), (3, 5))
biga = numpy.tile(
numpy.asarray(1e20).astype(theano.config.floatX), (3, 5))
fun(a) # normal values
# Temporarily silence logger
_logger = logging.getLogger("theano.compile.nanguardmode")
try:
_logger.propagate = False
assert_raises(AssertionError, fun, infa) # INFs
assert_raises(AssertionError, fun, nana) # NANs
assert_raises(AssertionError, fun, biga) # big values
finally:
_logger.propagate = True
# slices
a = numpy.random.randn(3, 4, 5).astype(theano.config.floatX)
infa = numpy.tile(
(numpy.asarray(100.) ** 1000000).astype(theano.config.floatX),
(3, 4, 5))
nana = numpy.tile(
numpy.asarray(numpy.nan).astype(theano.config.floatX), (3, 4, 5))
biga = numpy.tile(
numpy.asarray(1e20).astype(theano.config.floatX), (3, 4, 5))
x = T.tensor3()
y = x[:, T.arange(2), T.arange(2)]
fun = theano.function(
[x], y,
mode=NanGuardMode(nan_is_error=True, inf_is_error=True)
)
fun(a) # normal values
try:
_logger.propagate = False
assert_raises(AssertionError, fun, infa) # INFs
assert_raises(AssertionError, fun, nana) # NANs
assert_raises(AssertionError, fun, biga) # big values
finally:
_logger.propagate = True
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