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))