allowing for non-command line use

[CorbanSwain]

This fixes an issure for me where I wanted to call retrain from within another script. This PR is now enables this functionality:

# call_retrain.py

# We're assuming the project directory has been renamed to tffp2

# Some other python script in the same parent directory as the tffp2 directory
# parent_dir
#    + - call_retrain.py
#    + tffp2
#    + tf_files
#    + flower_images
#    + logs

from tffp2.scripts import retrain
import os

def retrain_on_flowers(log_dir):
    model_arch = 'mobilenet_0.5_224'
    summaries_dir = os.path.join(log_dir, model_arch)
    retrain_args = dict(
        bottleneck_dir='tf_files/bottlenecks',
        model_dir='tf_files/models/%s' % model_arch,
        summaries_dir=summaries_dir,
        output_graph='tf_files/retrained_graph.pb',
        output_labels='tf_files/retrained_labels.txt',
        architecture=model_arch,
        image_dir='flower_images',
    )
    retrain(**retrain_args)

def start_tensorboard(pth):
    import tensorboard as tb
    import tensorboard.main
    import tensorboard.program
    from threading import Thread

    tb.program.FLAGS.logdir = pth
    thread = Thread(target=tb.main.main, args=tuple())
    thread.start()
    return thread

if __name__ == "__main__":
    tf_logdir = 'logs'
    start_tensorboard(tf_logdir)
    retrain_on_flowers(tf_logdir)

• Adds a wrapper function init_parser() to generate the argument parser in the scripts/retrain.py script.
• Adds a function run_with_args(**kwargs) which takes in keyword arguments in the scripts/retrain.py script.
  1. formats keyword arguments to be passed as command-line-like arguments
  2. passes the command-line like arguments to the parser to generate the flags
  3. runs the main(_) function.

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[CorbanSwain]

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