def run_snapshot(submit_config, metric_args, run_id, snapshot):
ctx = dnnlib.RunContext(submit_config)
tflib.init_tf()
print('Evaluating %s metric on run_id %s, snapshot %s...' % (metric_args.name, run_id, snapshot))
run_dir = misc.locate_run_dir(run_id)
network_pkl = misc.locate_network_pkl(run_dir, snapshot)
metric = dnnlib.util.call_func_by_name(**metric_args)
print()
metric.run(network_pkl, run_dir=run_dir, num_gpus=submit_config.num_gpus)
print()
ctx.close()
def run_all_snapshots(submit_config, metric_args, run_id):
ctx = dnnlib.RunContext(submit_config)
tflib.init_tf()
print('Evaluating %s metric on all snapshots of run_id %s...' % (metric_args.name, run_id))
run_dir = misc.locate_run_dir(run_id)
network_pkls = misc.list_network_pkls(run_dir)
metric = dnnlib.util.call_func_by_name(**metric_args)
print()
for idx, network_pkl in enumerate(network_pkls):
ctx.update('', idx, len(network_pkls))
metric.run(network_pkl, run_dir=run_dir, num_gpus=submit_config.num_gpus)
print()
ctx.close()
