Add symbol api for randn and fix shape issue for randn ndarray and symbol api

python/mxnet/ndarray/random.py

@@ -220,8 +220,6 @@ def randn(*shape, **kwargs):
     dtype = kwargs.pop('dtype', _Null)
     ctx = kwargs.pop('ctx', None)
     out = kwargs.pop('out', None)
-    assert isinstance(loc, (int, float))
-    assert isinstance(scale, (int, float))
     return _random_helper(_internal._random_normal, _internal._sample_normal,
                           [loc, scale], shape, dtype, ctx, out, kwargs)
 

python/mxnet/symbol/random.py

@@ -113,6 +113,31 @@ def normal(loc=0, scale=1, shape=_Null, dtype=_Null, **kwargs):
                           [loc, scale], shape, dtype, kwargs)
 
 
+def randn(*shape, **kwargs):
+    """Draw random samples from a normal (Gaussian) distribution.
+
+    Samples are distributed according to a normal distribution parametrized
+    by *loc* (mean) and *scale* (standard deviation).
+
+
+    Parameters
+    ----------
+    loc : float or NDArray
+        Mean (centre) of the distribution.
+    scale : float or NDArray
+        Standard deviation (spread or width) of the distribution.
+    shape : int or tuple of ints
+        The number of samples to draw. If shape is, e.g., `(m, n)` and `loc` and
+        `scale` are scalars, output shape will be `(m, n)`. If `loc` and `scale`
+        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 `[loc, scale)` pair.
+    dtype : {'float16', 'float32', 'float64'}
+        Data type of output samples. Default is 'float32'
+    """
+    return _random_helper(_internal._random_normal, _internal._sample_normal,
+                            [loc, scale], shape, dtype, ctx, out, kwargs)
+
+
 def poisson(lam=1, shape=_Null, dtype=_Null, **kwargs):
     """Draw random samples from a Poisson distribution.