def main(argv=None):
check_args(FLAGS)
if FLAGS.multigpu == 'n':
if FLAGS.mode == 'train':
from train import train_model
train_model(FLAGS)
elif FLAGS.mode == 'save_pb':
from save_model import load_weights_save_pb
load_weights_save_pb(FLAGS)
elif FLAGS.mode == 'eval':
from eval import eval_model
eval_model(FLAGS)
elif FLAGS.multigpu == 'y':
if FLAGS.mode == 'train':
from multigpu_train import train_model
train_model(FLAGS)
elif FLAGS.mode == 'save_pb':
from save_multigpu_model import load_weights_save_pb
load_weights_save_pb(FLAGS)
elif FLAGS.mode == 'eval':
from eval import eval_model
eval_model(FLAGS)
else:
raise Exception('Please use true option of multigpu')
def main(argv=None):
check_args(FLAGS)
# Create some local cache directories used for transfer data between local path and OBS path
if not FLAGS.data_url.startswith('s3://'):
FLAGS.data_local = FLAGS.data_url
else:
FLAGS.data_local = os.path.join(FLAGS.local_data_root, 'train_data/')
if not os.path.exists(FLAGS.data_local):
mox.file.copy_parallel(FLAGS.data_url, FLAGS.data_local)
# 如果自己的模型需要加载预训练参数文件，可以先手动将参数文件从外网下载到自己的机器本地，再上传到OBS
# 然后用下面的代码，将OBS上的预训练参数文件拷贝到 ModelArts 平台训练代码所在的目录
# 拷贝代码格式为 mox.file.copy(src_path, dst_path)，其中dst_path不能是目录，必须是一个具体的文件名
# mox.file.copy('s3://your_obs_path/imagenet_class_index.json',
# os.path.dirname(os.path.abspath(__file__)) + '/models/imagenet_class_index.json')
# mox.file.copy('s3://your_obs_path/resnet50_weights_tf_dim_ordering_tf_kernels_notop.h5',
# os.path.dirname(os.path.abspath(__file__)) + '/models/resnet50_weights_tf_dim_ordering_tf_kernels_notop.h5')
else:
print('FLAGS.data_local: %s is already exist, skip copy' %
FLAGS.data_local)
if not FLAGS.train_url.startswith('s3://'):
FLAGS.train_local = FLAGS.train_url
else:
FLAGS.train_local = os.path.join(FLAGS.local_data_root,
'model_snapshots/')
if not os.path.exists(FLAGS.train_local):
os.mkdir(FLAGS.train_local)
if not FLAGS.test_data_url.startswith('s3://'):
FLAGS.test_data_local = FLAGS.test_data_url
else:
FLAGS.test_data_local = os.path.join(FLAGS.local_data_root,
'test_data/')
if not os.path.exists(FLAGS.test_data_local):
mox.file.copy_parallel(FLAGS.test_data_url, FLAGS.test_data_local)
else:
print('FLAGS.test_data_local: %s is already exist, skip copy' %
FLAGS.test_data_local)
FLAGS.tmp = os.path.join(FLAGS.local_data_root, 'tmp/')
if not os.path.exists(FLAGS.tmp):
os.mkdir(FLAGS.tmp)
if FLAGS.mode == 'train':
from train import train_model
train_model(FLAGS)
elif FLAGS.mode == 'save_pb':
from save_model import load_weights_save_pb
load_weights_save_pb(FLAGS)
elif FLAGS.mode == 'eval':
from eval import eval_model
eval_model(FLAGS)
def main(argv=None):
check_args(FLAGS)
# Create some local cache directories used for transfer data between local path and OBS path
if not FLAGS.data_url.startswith('s3://'):
FLAGS.data_local = FLAGS.data_url
else:
FLAGS.data_local = os.path.join(FLAGS.local_data_root, 'train_data/')
if not os.path.exists(FLAGS.data_local):
pass
# file.copy_parallel(FLAGS.data_url, FLAGS.data_local)
else:
print('FLAGS.data_local: %s is already exist, skip copy' %
FLAGS.data_local)
if not FLAGS.train_url.startswith('s3://'):
FLAGS.train_local = FLAGS.train_url
else:
FLAGS.train_local = os.path.join(FLAGS.local_data_root,
'model_snapshots/')
if not os.path.exists(FLAGS.train_local):
os.mkdir(FLAGS.train_local)
if not FLAGS.test_data_url.startswith('s3://'):
FLAGS.test_data_local = FLAGS.test_data_url
else:
FLAGS.test_data_local = os.path.join(FLAGS.local_data_root,
'test_data/')
if not os.path.exists(FLAGS.test_data_local):
pass
#file.copy_parallel(FLAGS.test_data_url, FLAGS.test_data_local)
else:
print('FLAGS.test_data_local: %s is already exist, skip copy' %
FLAGS.test_data_local)
FLAGS.tmp = os.path.join(FLAGS.local_data_root, 'tmp/')
if not os.path.exists(FLAGS.tmp):
os.mkdir(FLAGS.tmp)
if FLAGS.mode == 'train':
from train_eval import train_model
train_model(FLAGS)
elif FLAGS.mode == 'save_pb':
from save_model import load_weights_save_pb
load_weights_save_pb(FLAGS)
elif FLAGS.mode == 'eval':
from eval import eval_model
eval_model(FLAGS)
def main(argv=None):
check_args(FLAGS)
# Create some local cache directories used for transfer data between local path and OBS path
FLAGS.data_local = FLAGS.data_url
FLAGS.train_local = FLAGS.train_url
FLAGS.test_data_local = FLAGS.test_data_url
# FLAGS.tmp = os.path.join(FLAGS.local_data_root, 'tmp/')
# print(FLAGS.tmp)
# if not os.path.exists(FLAGS.tmp):
# os.mkdir(FLAGS.tmp)
if FLAGS.mode == 'train':
from train import train_model
train_model(FLAGS)
elif FLAGS.mode == 'save_pb':
from save_model import load_weights_save_pb
load_weights_save_pb(FLAGS)
elif FLAGS.mode == 'eval':
from eval import eval_model
eval_model(FLAGS)