train_spec: Configuration for the train component of 'train_and_evaluate'

In tfestimators: Interface to 'TensorFlow' Estimators

Description

TrainSpec determines the input data for the training, as well as the duration. Optional hooks run at various stages of training.

Usage

train_spec(input_fn, max_steps = NULL, hooks = NULL)

Arguments

input_fn	Training input function returning a tuple of: features - Tensor or dictionary of string feature name to Tensor. labels - Tensor or dictionary of Tensor with labels.
max_steps	Positive number of total steps for which to train model. If NULL, train forever. The training input_fn is not expected to generate OutOfRangeError or StopIteration exceptions.
hooks	List of session run hooks to run on all workers (including chief) during training.

See Also

Other training methods: eval_spec(), train_and_evaluate.tf_estimator()

tfestimators documentation built on Aug. 10, 2021, 1:06 a.m.