Y_train = np.array([shuffle[i][2]foriinxrange(len(shuffle))])# .reshape((len(shuffle), 5, 1, 1))Y_uniftrain = np_utils.to_categorical(y_unif,5)# shuffle uniformly distribuited training setshuffle = zip(x3_unif, x6_unif, Y_uniftrain) np.random.shuffle(shuffle)# transform shuff...
y_data = y_data_mat['train_label'] y_train = np_utils.to_categorical(y_data, nClass)# train data shuffleindex = np.arange(y_train.shape[0]) np.random.shuffle(index) x_train = x_train[index,:] y_train = y_train[index]return[x_train, y_train]# fix random seed 开发者ID:iy...
numpy随机数函数 numpy 的random子库 rand(d0, d1, …,dn) : 各元素是[0, 1)的浮点数,服从均匀分布 randn(d0, d1, …,dn):标准正态分布 randint(low, high,( shape)): 依shape创建随机整数或整数数组,范围是[ low, high) seed(s) : 随机数种子 shuffle(a) : 根据数组a的第一轴进行随机排列,...
[ind, np.random.randint(1, 10000), random.randint(10000, 20000), 0] tsfm =Transform()(item) return np.array(item + tsfm) def __len__(self): return 20 from torch.utils.data import DataLoader ds = RandomDataset() ds = DataLoader(ds, 10, shuffle=False, num_workers=4) for batch...
mnisten is a library to convert image files toidx formatbinaries. assign label id automatically by directory-name (lexicographical order) auto resizing random-shuffling generate train/test file #example image files: .\ |--foo | |--a.bmp | |--b.bmp | +--1.txt +--bar |--c.bmp |-...
: np.random.permutation是NumPy库中的一个函数,用于对数组进行随机重排。种子(seed)在随机数生成中起到确定随机数序列的作用。当种子固定时,每次生成的随机数序列都是相同的...
效果的功能需求 从一个数组当中，随机抽取数个元素，构成新数组，要求这些元素不能重复。（即随机获取不...
numpy 的random子库 rand(d0, d1, …,dn) : 各元素是[0, 1)的浮点数,服从均匀分布 randn(d0, d1, …,dn):标准正态分布 randint(low, high,( shape)): 依shape创建随机整数或整数数组,范围是[ low, high) seed(s) : 随机数种子 shuffle(a) : 根据数组a的第一轴进行随机排列,改变数组a ...
random.seed(worker_seed) random.seed(worker_seed) def build_yolo_dataset(cfg, img_path, batch, data, mode='train', rect=False, stride=32): """构建YOLO数据集。""" return YOLODataset( img_path=img_path, imgsz=cfg.imgsz, # 图像大小 batch_size=batch, # 批次大小 augment=mode == '...
self.rng =make_np_rng(rng, which_method='random_intergers') 开发者ID:EugenePY,项目名称:tensor-work,代码行数:29,代码来源:im2latex.py 示例5: __init__ ▲点赞 1▼ def__init__(self, X, y):if(self.dataset_nameindataset_info.aod_datasetsandself.which_set =="full"): ...