ChaiBapchya commented on a change in pull request #12749: [MXNET-1029] Feature
request: randint operator
URL: https://github.com/apache/incubator-mxnet/pull/12749#discussion_r235504502
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File path: python/mxnet/ndarray/random.py
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@@ -518,3 +518,52 @@ def shuffle(data, **kwargs):
<NDArray 2x3 @cpu(0)>
"""
return _internal._shuffle(data, **kwargs)
+
+
+def randint(low, high, shape=_Null, dtype=_Null, ctx=None, out=None, **kwargs):
+ """Draw random samples from a discrete uniform distribution.
+
+ Samples are uniformly distributed over the half-open interval *[low, high)*
+ (includes *low*, but excludes *high*).
+
+ Parameters
+ ----------
+ low : int, required
+ Lower boundary of the output interval. All values generated will be
+ greater than or equal to low.
+ high : int, required
+ Upper boundary of the output interval. All values generated will be
+ less than high.
+ shape : int or tuple of ints, optional
+ The number of samples to draw. If shape is, e.g., `(m, n)` and `low`
and
+ `high` are scalars, output shape will be `(m, n)`.
+ dtype : {'int32', 'int64'}, optional
+ Data type of output samples. Default is 'int32'
+ ctx : Context, optional
+ Device context of output. Default is current context. Overridden by
+ `low.context` when `low` is an NDArray.
+ out : NDArray, optional
+ Store output to an existing NDArray.
+
+
+ Examples
+ --------
+ >>> mx.nd.random.randint(5, 100)
+ [ 90]
+ <NDArray 1 @cpu(0)
+ >>> mx.nd.random.randint(-10, 2, ctx=mx.gpu(0))
+ [ -8]
+ <NDArray 1 @gpu(0)>
+ >>> mx.nd.random.randint(-10, 10, shape=(2,))
+ [ -5 4]
+ <NDArray 2 @cpu(0)>
+ >>> low = mx.nd.array([1,2,3])
+ >>> high = mx.nd.array([2,3,4])
+ >>> mx.nd.random.randint(low, high, shape=2)
Review comment:
I was going to support arrays too. But had some issues. Hence removed it.
Will update the example accordingly.
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