reminisce commented on a change in pull request #15377: [numpy][doc-fix]
zeros_like, linspace, reciprocal, square, and arcsin
URL: https://github.com/apache/incubator-mxnet/pull/15377#discussion_r298003048
##########
File path: python/mxnet/_numpy_op_doc.py
##########
@@ -71,19 +71,63 @@ def _np_ones_like(a):
pass
-def _np_zeros_like(a):
- """Return an array of zeros with the same shape and type as a given array.
+def _np_zeros_like(a, dtype=None, **kwargs):
+ """
+ zeros_like(a, dtype=None, order='C', subok=True)
+
+ Return an array of zeros with the same shape and type as a given array.
Parameters
----------
a : ndarray
- The shape and data-type of `a` define these same attributes of
+ The shape of `a` define these same attributes of
the returned array.
-
+ dtype : data-type, optional
+ Overrides the data type of the result.
+ .. versionadded:: 1.6.0
+ order : {'C'}, optional, default: C
+ Store multi-dimensional data in row-major
+ (C-style) in memory. Note that the column-major is not supported yet.
+
Returns
-------
out : ndarray
Array of zeros with the same shape and type as `a`.
+
+
+ See Also
+ --------
+ empty_like : Return an empty array with shape and type of input.
+ ones_like : Return an array of ones with shape and type of input.
+ full_like : Return a new array with shape of input filled with value.
+ zeros : Return a new array setting values to zero.
+
+ Examples
+ --------
+ >>> x = np.arange(6)
+ >>> x = x.reshape((2, 3))
+ >>> x
+ array([[0, 1, 2],
+ [3, 4, 5]])
+ >>> np.zeros_like(x)
+ array([[0, 0, 0],
+ [0, 0, 0]])
+ >>> y = np.arange(3, dtype=float)
Review comment:
No need to use `dtype=float`. Please update the output with the latest code.
```python
>>> y = np.arange(3)
>>> y
array([0., 1., 2.])
```
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