def get_trainer_by_name(name, param_dict, rest_args):
if name == 'normal':
param_dict['num_epoch'] = args.num_epoch
return Trainer(**param_dict)
num_minibatch = util.string_to_int_list(args.num_minibatch)
if len(num_minibatch) == 1:
param_dict['num_minibatch'] = num_minibatch[0]
else:
param_dict['num_minibatch'] = num_minibatch
if name == 'minibatch':
return MiniBatchTrainer(**param_dict)
if name == 'catewise':
param_dict['num_caterange_list'] = util.string_to_int_list(args.num_caterange_list)
return ImageNetCatewisedTrainer(**param_dict)
if name == 'categroup':
param_dict['num_group_list'] = util.string_to_int_list(args.num_group_list)
return ImageNetCateGroupTrainer(**param_dict)
raise Exception, 'No trainer found for name: %s' % name
if not getattr(args, a) and a not in extra_argument:
assert False, 'You have to specify a value of %s' % a
param_dict = {}
param_dict['image_color'] = 3
param_dict['test_id'] = args.test_id
param_dict['data_dir'] = args.data_dir
param_dict['data_provider'] = args.data_provider
if args.data_provider.startswith('imagenet'):
param_dict['image_size'] = 224
elif args.data_provider.startswith('cifar'):
param_dict['image_size'] = 32
else:
assert False, 'Unknown data_provider %s' % args.data_provider
param_dict['train_range'] = util.string_to_int_list(args.train_range)
param_dict['test_range'] = util.string_to_int_list(args.test_range)
param_dict['save_freq'] = args.save_freq
param_dict['test_freq'] = args.test_freq
param_dict['adjust_freq'] = args.adjust_freq
factor = util.string_to_float_list(args.factor)
if len(factor) == 1:
param_dict['factor'] = factor[0]
else:
param_dict['factor'] = factor
learning_rate = util.string_to_float_list(args.learning_rate)
if len(learning_rate) == 1:
param_dict['learning_rate'] = learning_rate[0]
else:
param_dict['learning_rate'] = learning_rate
assert False, 'You have to specify a value of %s' % a
param_dict = {}
param_dict['image_color'] = 3
param_dict['test_id'] = args.test_id
param_dict['data_dir'] = args.data_dir
param_dict['data_provider'] = args.data_provider
if args.data_provider.startswith('imagenet'):
param_dict['image_size'] = 224
elif args.data_provider.startswith('cifar'):
param_dict['image_size'] = 32
else:
assert False, 'Unknown data_provider %s' % args.data_provider
param_dict['train_range'] = util.string_to_int_list(args.train_range)
param_dict['test_range'] = util.string_to_int_list(args.test_range)
param_dict['save_freq'] = args.save_freq
param_dict['test_freq'] = args.test_freq
param_dict['adjust_freq'] = args.adjust_freq
factor = util.string_to_float_list(args.factor)
if len(factor) == 1:
param_dict['factor'] = factor[0]
else:
param_dict['factor'] = factor
learning_rate = util.string_to_float_list(args.learning_rate)
if len(learning_rate) == 1:
param_dict['learning_rate'] = learning_rate[0]
else:
assert False, 'You have to specify a value of %s' % a
param_dict = {}
param_dict['image_color'] = 3
param_dict['test_id'] = args.test_id
param_dict['data_dir'] = args.data_dir
param_dict['data_provider'] = args.data_provider
if args.data_provider.startswith('imagenet'):
param_dict['image_size'] = 224
elif args.data_provider.startswith('cifar'):
param_dict['image_size'] = 32
else:
assert False, 'Unknown data_provider %s' % args.data_provider
param_dict['train_range'] = util.string_to_int_list(args.train_range)
param_dict['test_range'] = util.string_to_int_list(args.test_range)
util.log('%s %s', args.test_range, param_dict['test_range'])
param_dict['save_freq'] = args.save_freq
param_dict['test_freq'] = args.test_freq
param_dict['adjust_freq'] = args.adjust_freq
factor = util.string_to_float_list(args.factor)
if len(factor) == 1:
param_dict['factor'] = factor[0]
else:
param_dict['factor'] = factor
learning_rate = util.string_to_float_list(args.learning_rate)
if len(learning_rate) == 1:
param_dict['learning_rate'] = learning_rate[0]
