reminisce commented on a change in pull request #15744: [Numpy] Numpy behavior
random.uniform()
URL: https://github.com/apache/incubator-mxnet/pull/15744#discussion_r310925587
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File path: python/mxnet/ndarray/numpy/random.py
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@@ -139,6 +139,58 @@ def normal(loc=0.0, scale=1.0, size=None, **kwargs):
[loc, scale], size, dtype, ctx, out, kwargs)
+def uniform(low=0.0, high=1.0, size=None, ctx=None, dtype=None, out=None):
+ """Draw samples from a uniform distribution.
+
+ Samples are uniformly distributed over the half-open interval
+ ``[low, high)`` (includes low, but excludes high). In other words,
+ any value within the given interval is equally likely to be drawn
+ by `uniform`.
+
+ Parameters
+ ----------
+ low : float, ndarray, optional
+ Lower boundary of the output interval. All values generated will be
+ greater than or equal to low. The default value is 0.
+ high : float, ndarray, optional
+ Upper boundary of the output interval. All values generated will be
+ less than high. The default value is 1.0.
+ size : int or tuple of ints, optional
+ Output shape. If the given shape is, e.g., ``(m, n, k)``, then
+ ``m * n * k`` samples are drawn. If size is ``None`` (default),
+ a scalar tensor containing a single value is returned if
+ ``low`` and ``high`` are both scalars.
+ dtype : {'float16', 'float32', 'float64'}, optional
+ Data type of output samples. Default is 'float32'
+ ctx : Context, optional
+ Device context of output. Default is current context.
+
+ Returns
+ -------
+ out : ndarray
+ Drawn samples from the parameterized uniform distribution.
+ """
+ input_type = (isinstance(low, NDArray), isinstance(high, NDArray))
Review comment:
We should not allow `NDArray` as input type. Only `mxnet.numpy.ndarray` is
allowed.
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