WebMar 13, 2024 · 这个错误是因为你试图改变一个数组的大小，但是新数组的总大小必须与原数组的总大小相同。例如，如果你有一个形状为(3,4)的数组，它有12个元素，你不能将其大小更改为(2,6)，因为新数组的总大小为12，与原数组的总大小相同。 WebDec 18, 2024 · Your input is size 9992. Your output is size [? x 1 x 28 x 28] since the -1 indicates that the reshape command should determine how many indices along this dimension are necessary to fit your array. 28x28x1 is 784, so any input you want to reshape to this size must be neatly divisible by 784 so it fits in the output shape. 9992 is not …

valueerror: cannot select an axis to squeeze out which has size not ...

Web3 Answers. It seems that there is a typo, since 1104*1104*50=60940800 and you are trying to reshape to dimensions 50,1104,104. So it seems that you need to change 104 to … WebTo convert a 1D Numpy array to a 3D Numpy array, we need to pass the shape of 3D array as a tuple along with the array to the reshape () function as arguments. We have … early transcendentals 10th edition solutions

numpy.reshape() in Python - GeeksforGeeks

WebFeb 17, 2024 · Note that the v and M objects are both of the type ndarray that the numpy module provides. The difference between the v and M arrays is only their shapes. We can get information about the shape of an array by using the ndarray.shape property.. Since it is statically typing, we can explicitly define the type of the array data when we create it, … WebJan 18, 2024 · Why I got cannot reshape array of size 2352 into shape (784,784) my image has 28*28 size. And how can I predict that? deep-learning; tensorflow; python-3.x; Share. Improve this question. Follow edited Jan 18, 2024 at 13:47. desertnaut. 1,859 2 2 gold badges 13 13 silver badges 21 21 bronze badges. WebMar 22, 2024 · According to your code, the initial shape of X is $(30, 100, 100, 3)$ which translates to having $30$ images each of $(100 \times 100)$ dimension and $3$ channels. To flatten X from $(30,100,100,3)$ to $(30, 100\times100\times3)$ you could replace: csulb health insurance for students