def main(unused_argv):
try:
for d in ['checkpoint', 'target']:
# Pull the required training checkpoints and models from GCS.
dst = os.path.join(FLAGS.dst_dir, d)
src = os.path.join(FLAGS.src_dir, d)
utils.ensure_dir_exists(dst)
utils.wait(utils.checked_run('gsutil', '-m', 'cp', '-r', src, dst))
# Freeze the target model.
freeze_graph(os.path.join(FLAGS.dst_dir, 'target', 'target', 'target'))
# Freeze the training checkpoint models.
pattern = os.path.join(FLAGS.dst_dir, 'checkpoint', 'checkpoint',
'work_dir', 'work_dir', '*.index')
patterns = glob.glob(pattern)
if not patterns:
raise FileNotFoundError("No files found in {}.".format(pattern))
for path in patterns:
# Avoid refreezing previously created checkpoint file.
if "raw.ckpt" not in path:
freeze_graph(os.path.splitext(path)[0])
finally:
asyncio.get_event_loop().close()
def main(unused_argv):
try:
for d in ['checkpoint', 'target']:
# Pull the required training checkpoints and models from GCS.
src = os.path.join(FLAGS.src_dir, d, N)
dst = os.path.join(FLAGS.dst_dir, d)
utils.ensure_dir_exists(dst)
utils.wait(utils.checked_run(None, 'gsutil', '-m', 'cp', '-r', src, dst))
# Freeze the target model.
freeze_graph(os.path.join(FLAGS.dst_dir, 'target', N, 'target'), 2048)
# Freeze the training checkpoint models.
pattern = os.path.join(FLAGS.dst_dir, 'checkpoint', N, 'work_dir', '*.index')
for path in glob.glob(pattern):
freeze_graph(os.path.splitext(path)[0], 2048)
finally:
asyncio.get_event_loop().close()