anirudhacharya commented on a change in pull request #12749: [MXNET-1029]
Feature request: randint operator
URL: https://github.com/apache/incubator-mxnet/pull/12749#discussion_r226802837
##########
File path: python/mxnet/ndarray/random.py
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@@ -518,3 +518,47 @@ def shuffle(data, **kwargs):
<NDArray 2x3 @cpu(0)>
"""
return _internal._shuffle(data, **kwargs)
+
+
+def randint(low=0, high=1, 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 : float or NDArray
+ Lower boundary of the output interval. All values generated will be
+ greater than or equal to low. The default value is 0.
+ high : float or NDArray
+ Upper boundary of the output interval. All values generated will be
+ less than high. The default value is 1.
+ shape : int or tuple of ints
+ 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)`. If `low` and `high`
+ are NDArrays with shape, e.g., `(x, y)`, then output will have shape
+ `(x, y, m, n)`, where `m*n` samples are drawn for each `[low, high)`
pair.
Review comment:
As discussed in this [dev
thread](https://lists.apache.org/thread.html/1e80983b9e78b88dc5e5d83edadc0f86b9e368702b954ce05d212e3c@%3Cdev.mxnet.apache.org%3E)
there are two sets of sampling functions within MXNet `sample_x` and
`random_x`. make sure your implementation is consistent with this and update
the documentation accordingly.
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