Add a script to call tf.estimator.train_and_evaluate

bob/learn/tensorflow/script/train_and_evaluate.py

+#!/usr/bin/env python
+
+"""Trains and evaluates a network using Tensorflow estimators.
+This script calls the estimator.train_and_evaluate function. Please see:
+https://www.tensorflow.org/api_docs/python/tf/estimator/train_and_evaluate
+https://www.tensorflow.org/api_docs/python/tf/estimator/TrainSpec
+https://www.tensorflow.org/api_docs/python/tf/estimator/EvalSpec
+for more details.
+
+Usage:
+    %(prog)s [-v...] [options] <config_files>...
+    %(prog)s --help
+    %(prog)s --version
+
+Arguments:
+    <config_files>                     The configuration files. The
+                                       configuration files are loaded in order
+                                       and they need to have several objects
+                                       inside totally. See below for
+                                       explanation.
+
+Options:
+    -h --help                          Show this help message and exit
+    --version                          Show version and exit
+    -v, --verbose                      Increases the output verbosity level
+
+The configuration files should have the following objects totally:
+
+  ## Required objects:
+
+  estimator
+  train_spec
+  eval_spec
+"""
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+# import pkg_resources so that bob imports work properly:
+import pkg_resources
+import tensorflow as tf
+from bob.extension.config import load as read_config_file
+from bob.learn.tensorflow.utils.commandline import \
+    get_from_config_or_commandline
+from bob.core.log import setup, set_verbosity_level
+logger = setup(__name__)
+
+
+def main(argv=None):
+  from docopt import docopt
+  import os
+  import sys
+  docs = __doc__ % {'prog': os.path.basename(sys.argv[0])}
+  version = pkg_resources.require('bob.learn.tensorflow')[0].version
+  defaults = docopt(docs, argv=[""])
+  args = docopt(docs, argv=argv, version=version)
+  config_files = args['<config_files>']
+  config = read_config_file(config_files)
+
+  # optional arguments
+  verbosity = get_from_config_or_commandline(
+      config, 'verbose', args, defaults)
+
+  # Sets-up logging
+  set_verbosity_level(logger, verbosity)
+
+  # required arguments
+  estimator = config.estimator
+  train_spec = config.train_spec
+  eval_spec = config.eval_spec
+
+  # Train and evaluate
+  tf.estimator.train_and_evaluate(estimator, train_spec, eval_spec)
+
+
+if __name__ == '__main__':
+  main()