问题
I am trying to generate a numpy array with elements as two other numpy arrays, as below.
W1b1 = np.zeros((256, 161))
W2b2 = np.zeros((256, 257))
Wx = np.array([W1b1, W2b2], dtype=np.object)
this gives an error:
ValueError: could not broadcast input array from shape (256,161) into shape (256).
However, if I take entirely different dimensions for of W1b1 and W2b2 then I do not get an error, as below.
A1 = np.zeros((256, 161))
A2 = np.zeros((257, 257))
A3 = np.array([A1, A2], dtype=np.object)
I do not get what is wrong in the first code and why is numpy array trying to broadcast one of the input arrays.
I have tried on below versions (Python 2.7.6, Numpy 1.13.1) and (Python 3.6.4, Numpy 1.14.1).
回答1:
Don't count on np.array(..., object) making the right object array. At the moment we don't have control over how many dimensions it makes. Conceivably it could make a (2,) array, or (2, 256) (with 1d contents). Sometimes it works, sometimes raises an error. There's something of a pattern, but I haven't seen an analysis of the code that shows exactly what is happening.
For now it is safer to allocate the array, and fill it:
In [57]: arr = np.empty(2, object)
In [58]: arr[:] = [W1b1, W2b2]
np.array([np.zeros((3,2)),np.ones((3,4))], object) also raises this error. So the error arises when the first dimensions match, but the later ones don't. Now that I think about, I've seen this error before.
Earlier SO questions on the topic
numpy array 1.9.2 getting ValueError: could not broadcast input array from shape (4,2) into shape (4)
Creation of array of arrays fails, when first size of first dimension matches
Creating array of arrays in numpy with different dimensions
来源：https://stackoverflow.com/questions/51005699/broadcasting-error-when-forming-numpy-array-with-elements-as-two-other-numpy-arr