tfp.math.MinimizeTraceableQuantities

Namedtuple of quantities that may be traced from tfp.math.minimize.

@staticmethod
tfp.math.MinimizeTraceableQuantities(
    _cls, step, loss, gradients, parameters, has_converged,
    convergence_criterion_state
)

These are (in order):

step: int Tensor index (starting from zero) of the current optimization step.
loss: float Tensor value returned from the user-provided loss_fn.
gradients: list of Tensor gradients of loss with respect to the parameters.
parameters: list of Tensor values of parameters being optimized. This corresponds to the trainable_variables passed in to minimize.
has_converged: boolean Tensor of the same shape as loss_fn, with True values corresponding to loss entries that have converged according to the user-provided convergence criterion. If no convergence criterion was specified, this is None.
convergence_criterion_state: structure of Tensors containing any auxiliary state (e.g., moving averages of loss or other quantities) maintained by the user-provided convergence criterion.