('int32', 'int32') >>> a.size, b.size (5, 8) >>> type(a), type(b) (<class 'numpy.ndarray'>, <class 'numpy.ndarray'>) >>> a array([ 2, 4, 6, 8, 10]) >>> b array([[1, 2, 3, 4], [5, 6, 7, 8]]) >>> print(a) [ 2 4 6 8 10] >>> print(b)...
import numpy as np # Create a new array from which we will select elements a = np.array([[1,2,3], [4,5,6], [7,8,9], [10, 11, 12]]) print(a) # Create an array of indices b = np.array([0, 2, 0, 1]) # Select one element from each row of a using the indices ...
# 定义数组大小 array_size = 5 # 定义空列表 my_array = [] # 定义计数器 count = 0 # 使用while循环创建固定大小的数组 while count < array_size: # 获取用户输入的元素 element = input("请输入数组元素:") # 将元素添加到列表中 my_array.append(element) # 计数器加1 count += 1 # 打...
classCrop(object):def__init__(self,min_size_ratio,max_size_ratio=(1,1)):self.min_size_ratio=np.array(list(min_size_ratio))self.max_size_ratio=np.array(list(max_size_ratio))def__call__(self,X,Y):size=np.array(X.shape[:2])mini=self.min_size_ratio*size maxi=self.max_size_ra...
String Form:<built-in function array> Docstring: array(object, dtype=None, copy=True, order=None, subok=False, ndmin=0, ... 搜寻: >>> >>> np.lookfor('create array') Search results for 'create array' --- numpy.array Create an array. numpy.memmap Create a memory-map to an array ...
array([[4, 0, 0], [0, 5, 0], [0, 0, 6]]) Create an array using repeating list (or seenp.tile) np.array([1, 2, 3] * 3) Output: array([1, 2, 3, 1, 2, 3, 1, 2, 3]) Repeat elements of an array usingrepeat. ...
# Opening the parameters JSON filewithopen("params.json","r")asf:config=json.load(f)# Printing the contentprint(config)### OUTPUT ###{'dim':4096,'n_layers':32,'n_heads':32,'n_kv_heads':8,'vocab_size':128256,'multiple_of':1024,'ffn_dim_multiplier':1.3,'norm_eps':1e-05,'...
window.maxsize(400,400) 设置窗口被允许调整的最大范围,即宽和高各400 window.attributes("-alpha",0.5) 用来设置窗口的一些属性,比如透明度(-alpha)、是否置顶(-topmost)即将主屏置于其他图标之上、是否全屏(-fullscreen)全屏显示等 window.state("normal") 用来设置窗口的显示状态,参数值 normal(正常显示),icon...
c = torch.tensor(3.14159) # Create a scalar (zero-dimensional tensor) d = torch.tensor([]) # Create an empty tensor (of size (0,)) print(a) print(b) print(c) print(d) """ tensor([[ 0.1000, 1.2000], [ 2.2000, 3.1000], ...
create table bigtab (mycol varchar2(20));begin for i in 1..20000 loop insert into bigtab (mycol) values (dbms_random.string('A',20)); end loop;end;/show errorscommit; 在终端窗口中,使用 SQL*Plus 运行该脚本: sqlplus pythonhol/welcome@127.0.0.1/orcl@query_arraysize exit . 查看$HOME...