[GitHub] anirudhacharya commented on a change in pull request #12749: [MXNET-1029] Feature request: randint operator

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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_r223203436
 
 

 ##########
 File path: python/mxnet/ndarray/random.py
 ##########
 @@ -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:
   this behavior of the `randint` operator seems weird. 
   
   Why are we not mimicking the behavior of [`numpy.random.randint`](https://docs.scipy.org/doc/numpy-1.15.1/reference/generated/numpy.random.randint.html) function. Even pytorch's [`torch.randperm`](https://pytorch.org/docs/0.3.1/torch.html?highlight=torch%20random#torch.randperm) is defined similarly.

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