def theano_hash(self):
_, d = self
return hash_from_ndarray(d)
def test_hash_from_ndarray():
hashs = []
rng = numpy.random.rand(5, 5)
for data in [
-2,
-1,
0,
1,
2,
numpy.zeros((1, 5)),
numpy.zeros((1, 6)),
# Data buffer empty but different shapes
numpy.zeros((1, 0)),
numpy.zeros((2, 0)),
# Same data buffer and shapes but different strides
numpy.arange(25).reshape(5, 5),
numpy.arange(25).reshape(5, 5).T,
# Same data buffer, shapes and strides but different dtypes
numpy.zeros((5, 5), dtype="uint32"),
numpy.zeros((5, 5), dtype="int32"),
# Test slice
rng,
rng[1:],
rng[:4],
rng[1:3],
rng[::2],
rng[::-1]
]:
data = numpy.asarray(data)
hashs.append(hash_from_ndarray(data))
assert len(set(hashs)) == len(hashs)
# test that different type of views and their copy give the same hash
assert hash_from_ndarray(rng[1:]) == hash_from_ndarray(rng[1:].copy())
assert hash_from_ndarray(rng[1:3]) == hash_from_ndarray(rng[1:3].copy())
assert hash_from_ndarray(rng[:4]) == hash_from_ndarray(rng[:4].copy())
assert hash_from_ndarray(rng[::2]) == hash_from_ndarray(rng[::2].copy())
assert hash_from_ndarray(rng[::-1]) == hash_from_ndarray(rng[::-1].copy())
def test_hash_from_ndarray():
hashs = []
rng = numpy.random.rand(5, 5)
for data in [-2, -1, 0, 1, 2, numpy.zeros((1, 5)), numpy.zeros((1, 6)),
# Data buffer empty but different shapes
numpy.zeros((1, 0)), numpy.zeros((2, 0)),
# Same data buffer and shapes but different strides
numpy.arange(25).reshape(5, 5),
numpy.arange(25).reshape(5, 5).T,
# Same data buffer, shapes and strides but different dtypes
numpy.zeros((5, 5), dtype="uint32"),
numpy.zeros((5, 5), dtype="int32"),
# Test slice
rng, rng[1:], rng[:4], rng[1:3], rng[::2], rng[::-1]
]:
data = numpy.asarray(data)
hashs.append(hash_from_ndarray(data))
assert len(set(hashs)) == len(hashs)
# test that different type of views and their copy give the same hash
assert hash_from_ndarray(rng[1:]) == hash_from_ndarray(rng[1:].copy())
assert hash_from_ndarray(rng[1:3]) == hash_from_ndarray(rng[1:3].copy())
assert hash_from_ndarray(rng[:4]) == hash_from_ndarray(rng[:4].copy())
assert hash_from_ndarray(rng[::2]) == hash_from_ndarray(rng[::2].copy())
assert hash_from_ndarray(rng[::-1]) == hash_from_ndarray(rng[::-1].copy())
def theano_hash(self):
_, d = self
return hash_from_ndarray(d)
