Updates

• Patched the train.py script to accept tensors as input
• Crafted a script that generates LFW pairs for validation
• Implemented a validation mechanism using embeddings

bob/learn/tensorflow/script/load_and_debug.py

+#!/usr/bin/env python
+# vim: set fileencoding=utf-8 :
+# @author: Tiago de Freitas Pereira <tiago.pereira@idiap.ch>
+
+
+"""
+Load and debug tensorflow models
+
+Usage:
+  load_and_debug.py <configuration> <output-dir>
+  load_and_debug.py -h | --help
+Options:
+  -h --help     Show this screen.
+"""
+
+from docopt import docopt
+import bob.io.base
+import os
+import numpy
+import imp
+import bob.learn.tensorflow
+import tensorflow as tf
+
+import logging
+logger = logging.getLogger("bob.learn")
+
+
+def main():
+    args = docopt(__doc__, version='Mnist training with TensorFlow')
+    output_dir = args['<output-dir>']
+
+    config = imp.load_source('config', args['<configuration>'])
+
+    # Cleaning all variables in case you are loading the checkpoint
+    tf.reset_default_graph() if os.path.exists(output_dir) else None
+
+    logger.info("Directory already exists, trying to get the last checkpoint")
+
+    trainer = config.Trainer(config.train_data_shuffler,
+                             iterations=0,
+                             analizer=None,
+                             temp_dir=output_dir)
+    trainer.create_network_from_file(output_dir)
+    import ipdb; ipdb.set_trace();
+    
+    debug=True