tfp.substrates.numpy.math.MinimizeTraceableQuantities

Note: This API is new and only available via pip install tfp-nightly.

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

View aliases

Main aliases

tfp.experimental.substrates.numpy.math.MinimizeTraceableQuantities

tfp.substrates.numpy.math.MinimizeTraceableQuantities(
    step, loss, gradients, parameters, has_converged, convergence_criterion_state,
    optimizer_state, seed
)

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 trainable_variables passed to minimize, or init passed to minimize_stateless.
• 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.
• optimizer_state: structure of Tensors containing optional state from a user-provided pure optimizer.

Attributes
step	A namedtuple alias for field number 0
loss	A namedtuple alias for field number 1
gradients	A namedtuple alias for field number 2
parameters	A namedtuple alias for field number 3
has_converged	A namedtuple alias for field number 4
convergence_criterion_state	A namedtuple alias for field number 5
optimizer_state	A namedtuple alias for field number 6
seed	A namedtuple alias for field number 7