tf.compat.v1.train.add_queue

Basic loop to train a model.

tf.compat.v1.train.basic_train_loop(
    supervisor, train_step_fn, args=None, kwargs=None, master=''
)

Calls train_step_fn in a loop to train a model. The function is called as:

train_step_fn(session, *args, **kwargs)

It is passed a tf.compat.v1.Session in addition to args and kwargs. The function typically runs one training step in the session.

Args
`supervisor`	`tf.compat.v1.train.Supervisor` to run the training services.
`train_step_fn`	Callable to execute one training step. Called repeatedly as `train_step_fn(session, args *kwargs)`.
`args`	Optional positional arguments passed to `train_step_fn`.
`kwargs`	Optional keyword arguments passed to `train_step_fn`.
`master`	Master to use to create the training session. Defaults to `""` which causes the session to be created in the local process.

TensorFlow

tf.compat / v1 / v1.train.add_queue_runner

Args

TensorFlow

tf

tf.audio

tf.autograph

tf.bitwise

tf.compat

tf.config

tf.data

tf.debugging

tf.distribute

tf.dtypes

tf.errors

tf.estimator

tf.experimental

tf.feature_column

tf.graph_util

tf.image

tf.initializers

tf.io

tf.keras

tf.linalg

tf.lite

tf.lookup

tf.losses

tf.math

tf.metrics

tf.nest

tf.nn

tf.optimizers

tf.quantization

tf.queue

tf.ragged

tf.random

tf.raw_ops

tf.saved_model

tf.sets

tf.signal

tf.sparse

tf.strings

tf.summary

tf.sysconfig

tf.test

tf.tpu

tf.train

tf.version

tf.xla

tf.compat / v1 / v1.train.add_queue_runner

Args