def kron(a, b): # pylint: disable=missing-function-docstring
# pylint: disable=protected-access,g-complex-comprehension
a, b = np_array_ops._promote_dtype(a, b)
t_a = np_utils.cond(
a.ndim < b.ndim,
lambda: np_array_ops.reshape( # pylint: disable=g-long-lambda
a, np_array_ops._pad_left_to(b.ndim, a.shape)),
lambda: a)
t_b = np_utils.cond(
b.ndim < a.ndim,
lambda: np_array_ops.reshape( # pylint: disable=g-long-lambda
b, np_array_ops._pad_left_to(a.ndim, b.shape)),
lambda: b)
def _make_shape(shape, prepend):
ones = array_ops.ones_like(shape)
if prepend:
shapes = [ones, shape]
else:
shapes = [shape, ones]
return array_ops.reshape(array_ops.stack(shapes, axis=1), [-1])
a_shape = array_ops.shape(t_a)
b_shape = array_ops.shape(t_b)
a_reshaped = np_array_ops.reshape(t_a, _make_shape(a_shape, False))
b_reshaped = np_array_ops.reshape(t_b, _make_shape(b_shape, True))
out_shape = a_shape * b_shape
return np_array_ops.reshape(a_reshaped * b_reshaped, out_shape)
def vdot(a, b): # pylint: disable=missing-docstring
a, b = np_array_ops._promote_dtype(a, b)
a = np_array_ops.reshape(a, [-1])
b = np_array_ops.reshape(b, [-1])
if a.dtype == np_dtypes.complex128 or a.dtype == np_dtypes.complex64:
a = conj(a)
return dot(a, b)
def kron(a, b): # pylint: disable=missing-function-docstring
# pylint: disable=protected-access,g-complex-comprehension
a, b = np_array_ops._promote_dtype(a, b)
ndim = max(a.ndim, b.ndim)
if a.ndim < ndim:
a = np_array_ops.reshape(a, np_array_ops._pad_left_to(ndim, a.shape))
if b.ndim < ndim:
b = np_array_ops.reshape(b, np_array_ops._pad_left_to(ndim, b.shape))
a_reshaped = np_array_ops.reshape(a, [i for d in a.shape for i in (d, 1)])
b_reshaped = np_array_ops.reshape(b, [i for d in b.shape for i in (1, d)])
out_shape = tuple(np.multiply(a.shape, b.shape))
return np_array_ops.reshape(a_reshaped * b_reshaped, out_shape)
def run_test(arr, newshape, *args, **kwargs):
for fn1 in self.array_transforms:
for fn2 in self.array_transforms:
arr_arg = fn1(arr)
newshape_arg = fn2(newshape)
self.match(
np_array_ops.reshape(arr_arg, newshape_arg, *args, **kwargs),
np.reshape(arr_arg, newshape, *args, **kwargs))
