[SOLVED] how to explain this inhomogeneous numpy.ndarray?

centguy · 10-30-2023, 10:26 PM

Why do I see a inhomogeneous numpy ndarray?

This is the output of a test script.

Quote:

type(train_data)
<class 'numpy.ndarray'>
train_data.shape
(25000,)
train_data[0]
[1, 14, 22, 16, 43, 2, 2, 2, 2, 65, 2, 2, 66, 2, 4, 2, 36, 2, 5, 25, 2, 43, 2, 2, 50, 2, 2, 9, 35, 2, 2, 5, 2, 4, 2, 2, 2, 2, 2, 2, 39, 4, 2, 2, 2, 17, 2, 38, 13, 2, 4, 2, 50, 16, 6, 2, 2, 19, 14, 22, 4, 2, 2, 2, 4, 22, 71, 87, 12, 16, 43, 2, 38, 76, 15, 13, 2, 4, 22, 17, 2, 17, 12, 16, 2, 18, 2, 5, 62, 2, 12, 8, 2, 8, 2, 5, 4, 2, 2, 16, 2, 66, 2, 33, 4, 2, 12, 16, 38, 2, 5, 25, 2, 51, 36, 2, 48, 25, 2, 33, 6, 22, 12, 2, 28, 77, 52, 5, 14, 2, 16, 82, 2, 8, 4, 2, 2, 2, 15, 2, 4, 2, 7, 2, 5, 2, 36, 71, 43, 2, 2, 26, 2, 2, 46, 7, 4, 2, 2, 13, 2, 88, 4, 2, 15, 2, 98, 32, 2, 56, 26, 2, 6, 2, 2, 18, 4, 2, 22, 21, 2, 2, 26, 2, 5, 2, 30, 2, 18, 51, 36, 28, 2, 92, 25, 2, 4, 2, 65, 16, 38, 2, 88, 12, 16, 2, 5, 16, 2, 2, 2, 32, 15, 16, 2, 19, 2, 32]
len(train_data[0])
218
train_data[1]
[1, 2, 2, 2, 2, 78, 2, 5, 6, 2, 2, 2, 2, 26, 4, 2, 8, 2, 2, 14, 2, 20, 13, 2, 2, 2, 2, 5, 2, 2, 2, 21, 14, 69, 2, 8, 30, 23, 7, 4, 2, 2, 93, 4, 2, 9, 2, 2, 5, 2, 4, 2, 9, 35, 2, 4, 2, 9, 2, 2, 4, 2, 9, 4, 2, 2, 19, 4, 2, 5, 89, 29, 2, 46, 37, 4, 2, 9, 45, 43, 38, 2, 2, 2, 4, 2, 26, 2, 5, 2, 11, 2, 2, 4, 2, 9, 2, 2, 7, 2, 2, 2, 2, 2, 2, 2, 2, 15, 2, 2, 68, 2, 2, 15, 2, 2, 2, 98, 5, 4, 2, 9, 43, 2, 2, 15, 2, 2, 5, 2, 2, 11, 2, 2, 2, 50, 9, 2, 2, 2, 5, 2, 2, 2, 2, 5, 4, 2, 2, 2, 2, 18, 2, 32, 2, 2, 14, 9, 6, 2, 78, 22, 2, 64, 2, 9, 8, 2, 2, 23, 4, 2, 15, 16, 4, 2, 5, 28, 6, 52, 2, 2, 33, 89, 78, 2, 16, 2, 95]
len(train_data[1])
189

NevemTeve · 10-31-2023, 12:36 AM

Meta: 'code' tag might be better than 'quote'
On: If you have a problem with your script, you might want to show us it.

pan64 · 10-31-2023, 12:39 AM

Good question! And how do you think we can give you any answer? Because you generated that ndarray. Most probably your python script has an error in line 42.

centguy · 11-01-2023, 12:06 AM

Code:

from tensorflow.keras.datasets import imdb
(trd, trl),(ted,tel)=imdb.load_data(num_words=100)
print("type(trd)")
print(type(trd))
print("trd.shape")
print(trd.shape)
print("trl.shape")
print(trl.shape)
print("ted.shape")
print(ted.shape)
print("tel.shape")
print(tel.shape)
print("trd[0]")
print(trd[0])
print("len(trd[0])")
print(len(trd[0]))
print("trd[1]")
print(trd[1])
print("len(trd[1])")
print(len(trd[1]))

pan64 · 11-01-2023, 03:20 AM

still the same. How do you think we know what was loaded and why is it inhomogeneous?

centguy · 11-01-2023, 04:01 AM

I found something useful here.

A=np.array([[1,2],[],[1,2,3,4]], dtype=object)

I got it from

Quote:

https://stackoverflow.com/questions/...array-of-lists

Thank you for your attention! Cheers!