adjustments

bob/learn/tensorflow/script/db_to_tfrecords.py

@@ -150,14 +150,14 @@ def main(argv=None):
                 logger.info('Processing file %d out of %d', i + 1, n_files)
 
                 path = f.make_path(data_dir, data_extension)
-                data = reader(path)                
+                data = reader(path)
                 if data is None:
                   if allow_missing_files:
                       logger.debug("... Processing original data file '{0}' was not successful".format(path))
                       continue
                   else:
                       raise RuntimeError("Preprocessing of file '{0}' was not successful".format(path))
-                
+
                 label = file_to_label(f)
 
                 if one_file_one_sample:

bob/learn/tensorflow/script/eval_generic.py

@@ -63,7 +63,7 @@ def main(argv=None):
     model_fn = config.model_fn
     eval_input_fn = config.eval_input_fn
 
-    eval_interval_secs = getattr(config, 'eval_interval_secs', 300)
+    eval_interval_secs = getattr(config, 'eval_interval_secs', 60)
     run_once = getattr(config, 'run_once', False)
     run_config = getattr(config, 'run_config', None)
     model_params = getattr(config, 'model_params', None)
@@ -75,7 +75,7 @@ def main(argv=None):
     nn = tf.estimator.Estimator(model_fn=model_fn, model_dir=model_dir,
                                 params=model_params, config=run_config)
     if name:
-        real_name = name + '_eval'
+        real_name = 'eval_' + name
     else:
         real_name = 'eval'
     evaluated_file = os.path.join(nn.model_dir, real_name, 'evaluated')

bob/learn/tensorflow/script/train_generic.py

@@ -66,9 +66,7 @@ def main(argv=None):
 
     if run_config is None:
         # by default create reproducible nets:
-        from bob.learn.tensorflow.utils.reproducible import session_conf
-        run_config = tf.estimator.RunConfig()
-        run_config.replace(session_config=session_conf)
+        from bob.learn.tensorflow.utils.reproducible import run_config
 
     # Instantiate Estimator
     nn = tf.estimator.Estimator(model_fn=model_fn, model_dir=model_dir,

bob/learn/tensorflow/utils/reproducible.py

@@ -32,9 +32,11 @@ session_conf = tf.ConfigProto(intra_op_parallelism_threads=1,
 # in the TensorFlow backend have a well-defined initial state.
 # For further details, see:
 # https://www.tensorflow.org/api_docs/python/tf/set_random_seed
-tf.set_random_seed(1234)
+tf_random_seed = 1234
+tf.set_random_seed(tf_random_seed)
 # sess = tf.Session(graph=tf.get_default_graph(), config=session_conf)
 # keras.backend.set_session(sess)
 
 run_config = tf.estimator.RunConfig()
 run_config = run_config.replace(session_config=session_conf)
+run_config = run_config.replace(tf_random_seed=tf_random_seed)