def exit_handler(run):
"""Function that is called before the script exits.
Arguments:
run: The run that needs exit handling.
"""
force_drop_run = True
# remove run if no image was saved
output_files = os.listdir(run.output_path)
if len(output_files) > 0:
force_drop_run = False
if force_drop_run and os.path.exists(run.base_path):
shutil.rmtree(run.base_path)
# skip if run does not exist
if not os.path.exists(run.base_path):
return
# ask user to keep the run
should_keep_run = query_yes_no("Should the run '{}' be kept?".format(
os.path.basename(run.base_path)),
default="yes")
if not should_keep_run:
shutil.rmtree(run.base_path)
def exit_handler(run):
"""Function that is called before the script exits.
Arguments:
run: The run that needs exit handling.
"""
force_drop_run = True
# remove run if no checkpoint was saved
for file in os.listdir(run.checkpoints_path):
if file.startswith("model") or file == "checkpoint":
force_drop_run = False
break
if force_drop_run and os.path.exists(run.base_path):
shutil.rmtree(run.base_path)
# skip if run does not exist
if not os.path.exists(run.base_path):
return
# ask user to keep the run
should_keep_run = query_yes_no("Should the run '{}' be kept?".format(
os.path.basename(run.base_path)),
default="yes")
if not should_keep_run:
shutil.rmtree(run.base_path)
"Tensorflow minimum log level.", default=3)
arguments = argument_list.parse()
# print some information
logging_info("Image filename: {}".format(
arguments.image_filename))
logging_info("Model: {}".format(arguments.model))
logging_info("Model name: {}".format(
arguments.model_name))
logging_info("Dataset: {}".format(arguments.dataset))
logging_info("Tensorflow verbosity: {}".format(
arguments.tf_verbosity))
logging_info("Tensorflow minimum log level: {}".format(
arguments.tf_min_log_level))
should_continue = query_yes_no("Continue?", default="yes")
if not should_continue:
exit()
# set verbosity of tensorflow
tfu_set_logging(arguments.tf_verbosity,
min_log_level=arguments.tf_min_log_level)
# load the graph
graph_filename = arguments.model_name
if not graph_filename.endswith(".pb"):
graph_filename = "{}.pb".format(graph_filename)
graph_path = get_full_path("models", graph_filename)
graph = tfu_load_graph(graph_path)
# load the dataset
