out = data.reshape((-1,1,28,28)) # throws ValueError: cannot reshape array of size 9992 into shape (1,28,28) 因此,如果您不想要 ValueError,则需要将输入重塑为一个大小不同的数组,使其适合。
reshape(3,-1) ValueError: cannot reshape array of size 8 into shape (3,newaxis) 综上所述,在重塑数组时,新形状必须包含与旧形状相同数量的元素,这意味着两个形状的维度的乘积必须相等。当使用-1时,对应于-1的维数将是原始数组维数除以给定重塑的维数的乘积,以保持相同数量的元素。 2) Argpartition:查找...
ValueError: cannot reshape array of size 6 into shape (2,4) >>> a.reshape((2,3)) array([[0, 1, 2], [3, 4, 5]]) >>> a = np.arange(8) >>> a array([0, 1, 2, 3, 4, 5, 6, 7]) >>> a.reshape((2, 2, 2)) array([[[0, 1], [2, 3]], [[4, 5], [...
try:# 尝试将数组重塑为 5x3 的形状invalid_reshaped_arr=arr.reshape((5,3))exceptValueErrorase:print(f"重塑失败:{e}")# 输出: 重塑失败: cannot reshape array of size 12 into shape (5,3) 1. 2. 3. 4. 5. 流程图 下面的流程图概述了 reshape 的工作流程: 是否开始创建数组使用 reshape检查新...
reshape((1,2)) ValueError: cannot reshape array of size 4 into shape (1,2) d = a.reshape((1,-1))#reshape(1,-1),-1代表列,不确定列的数目;1代表1行;最终生成一行数组 d Out[12]: array([[1, 2, 3, 4]]) d = a.reshape((-1,1))#reshape(-1,1),-1代表行,不确定行的数目;...
reshape(3,3) ValueError: cannot reshape array of size 12 into shape (3,3) In [111]:bOut[111]:array([[1., 1., 1.], [1., 1., 1.], [1., 1., 1.], [1., 1., 1.]]) In [116]:a.resize(4,3) In [115]:aOut[115]:array([[1., 1., 1., 1.], [1., 1.,...
X_test = X_test.reshape(X_test.shape[0],28,28,1).astype('float32')# X_train = X_train.reshape(1, 28, 28, 1).astype('float32') ValueError: cannot reshape array of size 47040000 into shape (1,28,28,1)#X_test = X_test.reshape(1, 28, 28, 1).astype('float32') ValueError...
ValueError: cannot reshape array of size12 into shape (3,3) 上面的例子都是先创建一个Python序列,然后通过array函数将其转换为数组,这样做显然效率不高。因此NumPy提供了很多专门用来创建数组的函数。 初始化数组: 1importnumpy as np2a=np.arange(0,1,0.1)3print("a=",a)4b=np.linspace(0,1,10)5pri...
a(array_like):要调整大小的输入数组。 new_shape(int or tuple of ints):整数或整数元组,用于指定输出数组的形状。 注1:如果新的形状大于原始数组的形状,那么新的数组会包含原始数组的重复副本。 注2:如果新的形状小于原始数组的形状,那么原始数组内容会被截断。
ValueError: cannot reshape array of size 200 into shape (3,7,8) This raises an error since an array of shape (3, 7, 8) contains 168 elements. The original array with 200 values can’t fit into this new array.You can reshape an array if the dimensions of the new array are compatibl...