optimizer.sweeper.sweep

optimizer.sweeper.sweep(
    tt
    basis
    y
    nsweeps=2
    maxdim=30
    cutoff=0.01
    optax_solver=None
    opt_maxiter=1000
    opt_tol=None
    opt_lambda=0.0
    onedot=False
    use_CG=False
    use_scipy=False
    use_jax_scipy=False
    method='L-BFGS-B'
    ord='fro'
    auto_onedot=True
)

Tensor-train sweep optimization

Parameters

Name	Type	Description	Default
tt	TensorTrain	the tensor-train model.	required
basis	list[Array]	the basis functions.	required
y	Array	the target values.	required
nsweeps	int	The number of sweeps.	2
maxdim	(int, list[int])	the maximum rank of TT-sweep.	30
cutoff	(float, list[float])	the ratio of truncated singular values for TT-sweep. When one-dot core is optimized, this parameter is not used.	0.01
optax_solver	optax.GradientTransformation	the optimizer for TT-sweep. Defaults to None. If None, the optimizer is not used.	None
opt_maxiter	int	the maximum number of iterations for TT-sweep.	1000
opt_tol	(float, list[float])	the convergence criterion of gradient for TT-sweep. Defaults to None, i.e., opt_tol = cutoff.	None
opt_lambda	float	the L2 regularization parameter for TT-sweep. Only use_CG=True is supported.	0.0
onedot	bool	whether to optimize one-dot or two-dot core. Defaults to False, i.e. two-dot core optimization.	False
use_CG	bool	whether to use conjugate gradient method for TT-sweep. Defaults to False. CG is suitable for one-dot core optimization.	False
use_scipy	bool	whether to use scipy.optimize.minimize for TT-sweep. Defaults to False and use L-BFGS-B method. GPU is not supported.	False
use_jax_scipy	bool	whether to use jax.scipy.optimize.minimize for TT-sweep. Defaults to False. This optimizer is only supports BFGS method, which exhausts GPU memory.	False
method	str	the optimization method for scipy.optimize.minimize. Defaults to ‘L-BFGS-B’. Note that jax.scipy.optimize.minimize only supports ‘BFGS’.	'L-BFGS-B'
ord	str	the norm for scaling the initial core. Defaults to ‘fro’, Frobenuis norm. ‘max, maximum absolute value, 'fro', Frobenius norm, are supported. |’fro’| | auto_onedot | [bool](bool) | whether to switch to one-dot core optimization automatically once the maximum rank is reached. Defaults to True. This will cause overfitting in the beginning of the optimization. |True`