许多Python对象被格式化为更易读的形式,或称作pretty-printed,它与普通的print不同。如果在标准Python解释器中打印上述data变量,则可读性要降低: 代码语言:javascript 代码运行次数:0 运行 复制 >>> from numpy.random import randn >>> data = {i : randn() for i in range(7)}
4. PrettyErrors这是一个让你觉得："怎么以前没有人想到它？"的Python库。PrettyErrors[4]只做了一件...
int64) # Define a 3D array my_3d_array = np.array([[[1, 2, 3, 4], [5, 6, 7, 8]], [[1, 2, 3, 4], [9, 10, 11, 12]]], dtype=np.int64) # Print the 1D array print("Printing my_array:") print(my_array) # Print the 2D array print("Printing my_2d_array:") ...
model = Sequential() model.add(Conv2D(16, kernel_size=(3, 3), activation='relu', input_shape=INPUT_SHAPE)) model.add(Conv2D(32, (3,3), padding='same', kernel_regularizer=regularizers.l2(WEIGHT_DECAY), activation='relu')) model.add(BatchNormalization()) model.add(MaxPooling2D(pool_...
在下面的示例中,您创建了一个 2×4 矩阵(2D 数组)来存储一些数字。然后,使用与前面相同的操作,按元素乘以 10 并加 1。占位符的第一个维度是None,这意味着允许任意数量的行。 你也可以考虑用 2D 数组代替 1D 数组。代码如下: 这是一个 2×4 矩阵。所以,如果用 2 代替None,可以看到同样的输出。
model.add(ConvLSTM2D(filters=40, kernel_size=(3,3), padding='same', return_sequences=True)) model.add(BatchNormalization()) model.add(Conv3D(filters=1, kernel_size=(3,3,3), activation='sigmoid', padding='same', data_format="channels_last")) ...
func=u(t))) pprint(dsolve(eq=eq,func=u(t)))#以"pretty"形式打印方程的解# print(dsolve(eq=...
In [104]: print("i am {0},age{1}".format("tom",18)) i am tom,age18 3.1415926{:.2f}3.14保留小数点后两位 3.1415926 {:+.2f} +3.14 带符号保留小数点后两位 -1 {:+.2f} -1.00 带符号保留小数点后两位 2.71828 {:.0f} 3 不带小数 5 {:0>2d} 05 数字补零 (填充左边, 宽度为2)...
Other Pretty Cool FeaturesSo far, you’ve seen the biggest and most impactful new features in Python 3.10. In this section, you’ll get a glimpse of a few of the other changes that the new version brings along. If you’re curious about all the changes made for this new version, check...
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