ChaiBapchya commented on issue #14183: Multinominal distribution returns same results during different runs URL: https://github.com/apache/incubator-mxnet/issues/14183#issuecomment-464572662 I tried it 6 times and looks like it ain't that bad But certainly need to delve deeper I guess ``` >>> from mxnet import nd /Users/chaitanyabapat/anaconda3/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`. from ._conv import register_converters as _register_converters >>> >>> data = nd.array([0.5, 0.5]) >>> >>> for k in range(3): ... a = nd.random.multinomial(data, shape=(5, 1)) ... print(a) ... [[1] [1] [1] [1] [1]] <NDArray 5x1 @cpu(0)> [[1] [1] [1] [0] [1]] <NDArray 5x1 @cpu(0)> [[1] [0] [0] [0] [1]] <NDArray 5x1 @cpu(0)> >>> for k in range(3): ... a = nd.random.multinomial(data, shape=(5, 1)) ... print(a) ... [[0] [1] [0] [0] [0]] <NDArray 5x1 @cpu(0)> [[1] [1] [1] [0] [1]] <NDArray 5x1 @cpu(0)> [[0] [1] [1] [0] [0]] <NDArray 5x1 @cpu(0)> ```
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