TrainSpec determines the input data for the training, as well as the
duration. Optional hooks run at various stages of training.
A function that provides input data for training as minibatches.
See Premade Estimators
for more information. The function should construct and return one of
A 'tf.data.Dataset' object: Outputs of Dataset object must be a
tuple (features, labels) with same constraints as below.
A tuple (features, labels): Where features is a Tensor or a
dictionary of string feature name to Tensor and labels is a
Tensor or a dictionary of string label name to Tensor.
Int. Positive number of total steps for which to train model.
If None, train forever. The training input_fn is not expected to
generate OutOfRangeError or StopIteration exceptions. See the
train_and_evaluate stop condition section for details.
Iterable of tf.train.SessionRunHook objects to run on all workers
(including chief) during training.
If any of the input arguments is invalid.
If any of the arguments is not of the expected type.