e13771aec07c844a93e9700216d07b8073ce35fb,src/train.py,,main,#Any#,193

Before Change

def main(argv=None):  
    
    with tf.Graph().as_default():

        saver_hook = tf.train.CheckpointSaverHook(
            checkpoint_dir=FLAGS.output,
            save_secs=150)

        hooks = [saver_hook]

        // Initialize the classifier
        classifier = tf.estimator.Estimator(model_fn=model_fn, 
                                            model_dir=FLAGS.output)

        // Train the model
        classifier.train(input_fn=lambda: mjsynth.bucketed_input_pipeline(
            FLAGS.train_path, 
            str.split(FLAGS.filename_pattern,","),
            batch_size=FLAGS.batch_size,
            num_threads=FLAGS.num_input_threads,
            input_device=FLAGS.input_device,
            width_threshold=FLAGS.width_threshold,
            length_threshold=FLAGS.length_threshold ),
                         hooks=hooks)


    with tf.device(FLAGS.train_device):
        features,sequence_length = model.convnet_layers( image, width, mode)
        logits = model.rnn_layers( features, sequence_length,
                                   dynmj.num_classes() )

After Change

                                            _get_session_config()))

    // Train the model
    classifier.train(input_fn=lambda: _get_input_stream(), hooks=hooks)

if __name__ == "__main__":
    tf.app.run()

Instances