[jira] [Created] (MXNET-1455) np.random.multinomial returns unreasonable result

["Yucheng Huang (Jira)" <ji...@apache.org>]

Yucheng Huang created MXNET-1455:
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             Summary: np.random.multinomial returns unreasonable result
                 Key: MXNET-1455
                 URL: https://issues.apache.org/jira/browse/MXNET-1455
             Project: Apache MXNet
          Issue Type: Bug
            Reporter: Yucheng Huang


Hi,

I am new to MXNet. When I run tutorial d2l section 2.6 Probability.

%matplotlib inline
import random
from mxnet import np, npx
from d2l import mxnet as d2l

npx.set_np()

counts = np.random.multinomial(1000, fair_probs).astype(np.float32)
counts / 1000

I get:

array([0., 0., 0., 0., 0., 1.]), which I think it is unreasonable.

When I try:

import numpy
counts = numpy.random.multinomial(1000, fair_probs).astype(np.float32)
counts / 1000

I get:

array([0.159, 0.159, 0.172, 0.169, 0.172, 0.169], dtype=float32), which meets my expectation.

I see someone reports in Github [https://github.com/apache/incubator-mxnet/issues/15383#issuecomment-637583446]

However, this issue still exists in Windows.

 

 



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