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import os
import os.path as osp
from collections import OrderedDict
import yaml
def ordered_yaml():
"""Support OrderedDict for yaml.
Returns:
yaml Loader and Dumper.
"""
try:
from yaml import CDumper as Dumper
from yaml import CLoader as Loader
except ImportError:
from yaml import Dumper, Loader
_mapping_tag = yaml.resolver.BaseResolver.DEFAULT_MAPPING_TAG
def dict_representer(dumper, data):
return dumper.represent_dict(data.items())
def dict_constructor(loader, node):
return OrderedDict(loader.construct_pairs(node))
Dumper.add_representer(OrderedDict, dict_representer)
Loader.add_constructor(_mapping_tag, dict_constructor)
return Loader, Dumper
def parse(opt_path, is_train=True):
"""Parse option file.
Args:
opt_path (str): Option file path.
is_train (str): Indicate whether in training or not. Default: True.
Returns:
(dict): Options.
"""
with open(opt_path, mode='r') as f:
Loader, _ = ordered_yaml()
opt = yaml.load(f, Loader=Loader)
gpu_list = ','.join(str(x) for x in opt['gpu_ids'])
if opt.get('set_CUDA_VISIBLE_DEVICES', None):
os.environ['CUDA_VISIBLE_DEVICES'] = gpu_list
print('export CUDA_VISIBLE_DEVICES=' + gpu_list, flush=True)
else:
print('gpu_list: ', gpu_list, flush=True)
opt['is_train'] = is_train
# paths
opt['path'] = {}
opt['path']['root'] = osp.abspath(
osp.join(__file__, osp.pardir, osp.pardir))
if is_train:
experiments_root = osp.join(opt['path']['root'], 'experiments',
opt['name'])
opt['path']['experiments_root'] = experiments_root
opt['path']['models'] = osp.join(experiments_root, 'models')
opt['path']['log'] = experiments_root
opt['path']['visualization'] = osp.join(experiments_root,
'visualization')
# change some options for debug mode
if 'debug' in opt['name']:
opt['debug'] = True
opt['val_freq'] = 1
opt['print_freq'] = 1
opt['save_checkpoint_freq'] = 1
else: # test
results_root = osp.join(opt['path']['root'], 'results', opt['name'])
opt['path']['results_root'] = results_root
opt['path']['log'] = results_root
opt['path']['visualization'] = osp.join(results_root, 'visualization')
return opt
def dict2str(opt, indent_level=1):
"""dict to string for printing options.
Args:
opt (dict): Option dict.
indent_level (int): Indent level. Default: 1.
Return:
(str): Option string for printing.
"""
msg = ''
for k, v in opt.items():
if isinstance(v, dict):
msg += ' ' * (indent_level * 2) + k + ':[\n'
msg += dict2str(v, indent_level + 1)
msg += ' ' * (indent_level * 2) + ']\n'
else:
msg += ' ' * (indent_level * 2) + k + ': ' + str(v) + '\n'
return msg
class NoneDict(dict):
"""None dict. It will return none if key is not in the dict."""
def __missing__(self, key):
return None
def dict_to_nonedict(opt):
"""Convert to NoneDict, which returns None for missing keys.
Args:
opt (dict): Option dict.
Returns:
(dict): NoneDict for options.
"""
if isinstance(opt, dict):
new_opt = dict()
for key, sub_opt in opt.items():
new_opt[key] = dict_to_nonedict(sub_opt)
return NoneDict(**new_opt)
elif isinstance(opt, list):
return [dict_to_nonedict(sub_opt) for sub_opt in opt]
else:
return opt
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