def _create_variables(self):
if self.input_type.ndim != 0:
raise TypeError('Embeddings take scalar inputs.')
dtype = tf.as_dtype(self.input_type.dtype)
if not dtype.is_integer: raise TypeError('Embeddings take integer inputs.')
if dtype not in (tf.int32, tf.int64): # only dtypes supported by tf.gather
if np.iinfo(dtype.as_numpy_dtype).max > 2147483647:
# pedantic future-proofing to handle hypothetical tf.uint64
raise TypeError('cannot gather or upcast dtype %s' % dtype)
self._cast = True
else:
self._cast = False
self._weights = tf.get_variable(
'weights', self._weights_shape, initializer=self._initializer,
trainable=self._trainable)
python类iinfo()的实例源码
def test_signed_integer_division_overflow(self):
# Ticket #1317.
def test_type(t):
min = np.array([np.iinfo(t).min])
min //= -1
with np.errstate(divide="ignore"):
for t in (np.int8, np.int16, np.int32, np.int64, np.int, np.long):
test_type(t)
def test_shape_invalid(self):
# Check that the shape is valid.
max_int = np.iinfo(np.intc).max
max_intp = np.iinfo(np.intp).max
# Too large values (the datatype is part of this)
assert_raises(ValueError, np.dtype, [('a', 'f4', max_int // 4 + 1)])
assert_raises(ValueError, np.dtype, [('a', 'f4', max_int + 1)])
assert_raises(ValueError, np.dtype, [('a', 'f4', (max_int, 2))])
# Takes a different code path (fails earlier:
assert_raises(ValueError, np.dtype, [('a', 'f4', max_intp + 1)])
# Negative values
assert_raises(ValueError, np.dtype, [('a', 'f4', -1)])
assert_raises(ValueError, np.dtype, [('a', 'f4', (-1, -1))])
def test_min_int(self):
# Could make problems because of abs(min_int) == min_int
min_int = np.iinfo(np.int_).min
a = np.array([min_int], dtype=np.int_)
assert_(np.allclose(a, a))
def test_ldexp_overflow(self):
# silence warning emitted on overflow
with np.errstate(over="ignore"):
imax = np.iinfo(np.dtype('l')).max
imin = np.iinfo(np.dtype('l')).min
assert_equal(ncu.ldexp(2., imax), np.inf)
assert_equal(ncu.ldexp(2., imin), 0)
def test_iter_too_large():
# The total size of the iterator must not exceed the maximum intp due
# to broadcasting. Dividing by 1024 will keep it small enough to
# give a legal array.
size = np.iinfo(np.intp).max // 1024
arr = np.lib.stride_tricks.as_strided(np.zeros(1), (size,), (0,))
assert_raises(ValueError, nditer, (arr, arr[:, None]))
# test the same for multiindex. That may get more interesting when
# removing 0 dimensional axis is allowed (since an iterator can grow then)
assert_raises(ValueError, nditer,
(arr, arr[:, None]), flags=['multi_index'])
def test_export_record(self):
dt = [('a', 'b'),
('b', 'h'),
('c', 'i'),
('d', 'l'),
('dx', 'q'),
('e', 'B'),
('f', 'H'),
('g', 'I'),
('h', 'L'),
('hx', 'Q'),
('i', np.single),
('j', np.double),
('k', np.longdouble),
('ix', np.csingle),
('jx', np.cdouble),
('kx', np.clongdouble),
('l', 'S4'),
('m', 'U4'),
('n', 'V3'),
('o', '?'),
('p', np.half),
]
x = np.array(
[(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
asbytes('aaaa'), 'bbbb', asbytes(' '), True, 1.0)],
dtype=dt)
y = memoryview(x)
assert_equal(y.shape, (1,))
assert_equal(y.ndim, 1)
assert_equal(y.suboffsets, EMPTY)
sz = sum([np.dtype(b).itemsize for a, b in dt])
if np.dtype('l').itemsize == 4:
assert_equal(y.format, 'T{b:a:=h:b:i:c:l:d:q:dx:B:e:@H:f:=I:g:L:h:Q:hx:f:i:d:j:^g:k:=Zf:ix:Zd:jx:^Zg:kx:4s:l:=4w:m:3x:n:?:o:@e:p:}')
else:
assert_equal(y.format, 'T{b:a:=h:b:i:c:q:d:q:dx:B:e:@H:f:=I:g:Q:h:Q:hx:f:i:d:j:^g:k:=Zf:ix:Zd:jx:^Zg:kx:4s:l:=4w:m:3x:n:?:o:@e:p:}')
# Cannot test if NPY_RELAXED_STRIDES_CHECKING changes the strides
if not (np.ones(1).strides[0] == np.iinfo(np.intp).max):
assert_equal(y.strides, (sz,))
assert_equal(y.itemsize, sz)
def test_basic(self):
dts = list(zip(['i1', 'i2', 'i4', 'i8',
'u1', 'u2', 'u4', 'u8'],
[np.int8, np.int16, np.int32, np.int64,
np.uint8, np.uint16, np.uint32, np.uint64]))
for dt1, dt2 in dts:
assert_equal(iinfo(dt1).min, iinfo(dt2).min)
assert_equal(iinfo(dt1).max, iinfo(dt2).max)
self.assertRaises(ValueError, iinfo, 'f4')
def test_unsigned_max(self):
types = np.sctypes['uint']
for T in types:
assert_equal(iinfo(T).max, T(-1))
def test_iinfo_repr(self):
expected = "iinfo(min=-32768, max=32767, dtype=int16)"
assert_equal(repr(np.iinfo(np.int16)), expected)
def test_instances():
iinfo(10)
finfo(3.0)
def test_int_raise_behaviour(self):
def overflow_error_func(dtype):
np.typeDict[dtype](np.iinfo(dtype).max + 1)
for code in 'lLqQ':
assert_raises(OverflowError, overflow_error_func, code)
def test_diophantine_overflow():
# Smoke test integer overflow detection
max_intp = np.iinfo(np.intp).max
max_int64 = np.iinfo(np.int64).max
if max_int64 <= max_intp:
# Check that the algorithm works internally in 128-bit;
# solving this problem requires large intermediate numbers
A = (max_int64//2, max_int64//2 - 10)
U = (max_int64//2, max_int64//2 - 10)
b = 2*(max_int64//2) - 10
assert_equal(solve_diophantine(A, U, b), (1, 1))
def test_min_int(self):
a = np.array([np.iinfo(np.int_).min], dtype=np.int_)
# Should not raise:
assert_allclose(a, a)
def test_randint_range(self):
# Test for ticket #1690
lmax = np.iinfo('l').max
lmin = np.iinfo('l').min
try:
random.randint(lmin, lmax)
except:
raise AssertionError
def test_rng_zero_and_extremes(self):
for dt in self.itype:
lbnd = 0 if dt is np.bool_ else np.iinfo(dt).min
ubnd = 2 if dt is np.bool_ else np.iinfo(dt).max + 1
tgt = ubnd - 1
assert_equal(self.rfunc(tgt, tgt + 1, size=1000, dtype=dt), tgt)
tgt = lbnd
assert_equal(self.rfunc(tgt, tgt + 1, size=1000, dtype=dt), tgt)
tgt = (lbnd + ubnd)//2
assert_equal(self.rfunc(tgt, tgt + 1, size=1000, dtype=dt), tgt)
def test_random_integers_max_int(self):
# Tests whether random_integers can generate the
# maximum allowed Python int that can be converted
# into a C long. Previous implementations of this
# method have thrown an OverflowError when attempting
# to generate this integer.
actual = np.random.random_integers(np.iinfo('l').max,
np.iinfo('l').max)
desired = np.iinfo('l').max
np.testing.assert_equal(actual, desired)
def test_random_integers_deprecated(self):
with warnings.catch_warnings():
warnings.simplefilter("error", DeprecationWarning)
# DeprecationWarning raised with high == None
assert_raises(DeprecationWarning,
np.random.random_integers,
np.iinfo('l').max)
# DeprecationWarning raised with high != None
assert_raises(DeprecationWarning,
np.random.random_integers,
np.iinfo('l').max, np.iinfo('l').max)
def test_poisson_exceptions(self):
lambig = np.iinfo('l').max
lamneg = -1
assert_raises(ValueError, np.random.poisson, lamneg)
assert_raises(ValueError, np.random.poisson, [lamneg]*10)
assert_raises(ValueError, np.random.poisson, lambig)
assert_raises(ValueError, np.random.poisson, [lambig]*10)
def dtype_min_max(dtype):
'''Get the min and max value for a numeric dtype'''
if np.issubdtype(dtype, np.integer):
info = np.iinfo(dtype)
else:
info = np.finfo(dtype)
return info.min, info.max
