feat: reformatted log2 function (ivy-llc#26318)

ivy/data_classes/array/elementwise.py

@@ -1438,6 +1438,27 @@ def log2(self: ivy.Array, *, out: Optional[ivy.Array] = None) -> ivy.Array:
             an array containing the evaluated base ``2`` logarithm for each element
             in ``self``. The returned array must have a real-valued floating-point
             data type determined by :ref:`type-promotion`.
+
+        Examples
+        --------
+        Using :code:`ivy.Array` instance method:
+
+        >>> x = ivy.array([5.0, 1, -0.0, -6.0])
+        >>> y = ivy.log2(x)
+        >>> print(y)
+        ivy.array([2.32, 0., -inf, nan])
+
+        >>> x = ivy.array([float('nan'), -5.0, -0.0, 1.0, 5.0, float('+inf')])
+        >>> y = x.log2()
+        >>> print(y)
+        ivy.array([nan, nan, -inf, 0., 2.32, inf])
+
+        >>> x = ivy.array([[float('nan'), 1, 5.0, float('+inf')],\
+                            [+0, -2.0, -5, float('-inf')]])
+        >>> y = x.log2()
+        >>> print(y)
+        ivy.array([[nan, 0., 2.32, inf],
+                   [-inf, nan, nan, nan]])
         """
         return ivy.log2(self._data, out=out)
 

ivy/data_classes/container/elementwise.py

@@ -5167,6 +5167,21 @@ def _static_log2(
             a container containing the evaluated base ``2`` logarithm for
             each element in ``x``. The returned array must have a real-valued
             floating-point data type determined by :ref:`type-promotion`.
+
+        Examples
+        --------
+        Using :code:`ivy.Container` input:
+
+        >>> x = ivy.Container(a=ivy.array([0.0, float('nan')]),\
+                              b=ivy.array([-0., -4.9, float('+inf')]),\
+                              c=ivy.array([8.9, 2.1, 1.]))
+        >>> y = ivy.Container.static_log2(x)
+        >>> print(y)
+        {
+            a: ivy.array([-inf, nan]),
+            b: ivy.array([-inf, nan, inf]),
+            c: ivy.array([3.15, 1.07, 0.])
+        }
         """
         return ContainerBase.cont_multi_map_in_function(
             "log2",
@@ -5217,6 +5232,21 @@ def log2(
             a container containing the evaluated base ``2`` logarithm for each
             element in ``self``. The returned array must have a real-valued
             floating-point data type determined by :ref:`type-promotion`.
+
+        Examples
+        --------
+        Using :code:`ivy.Container` instance method:
+
+        >>> x = ivy.Container(a=ivy.array([0.0, float('nan')]),
+        ...                   b=ivy.array([-0., -5.9, float('+inf')]),
+        ...                   c=ivy.array([8.9, 2.1, 1.]))
+        >>> y = ivy.log2(x)
+        >>> print(y)
+        {
+            a: ivy.array([-inf, nan]),
+            b: ivy.array([-inf, nan, inf]),
+            c: ivy.array([3.15, 1.07, 0.])
+        }
         """
         return self._static_log2(
             self,

ivy/functional/ivy/elementwise.py

@@ -4246,6 +4246,37 @@ def log2(
     Both the description and the type hints above assumes an array input for simplicity,
     but this function is *nestable*, and therefore also accepts :class:`ivy.Container`
     instances in place of any of the arguments.
+
+    Examples
+    --------
+    With :class:`ivy.Array` input:
+    >>> x = ivy.array([5.0, 1, -0.0, -6.0])
+    >>> y = ivy.log2(x)
+    >>> print(y)
+    ivy.array([2.32, 0., -inf, nan])
+    >>> x = ivy.array([[float('nan'), 1, 6.0, float('+inf')],
+    ...               [+0, -2.0, -7, float('-inf')]])
+    >>> y = ivy.empty_like(x)
+    >>> ivy.log2(x, out=y)
+    >>> print(y)
+    ivy.array([[nan, 0., 2.58, inf],[inf, nan, nan, nan]])
+    >>> x = ivy.array([[float('nan'), 1, 7.0, float('+inf')],
+    ...               [+0, -3.0, -8, float('-inf')]])
+    >>> ivy.log2(x, out=x)
+    >>> print(x)
+    ivy.array([[nan, 0., 2.81, inf],[inf, nan, nan, nan]])
+
+    With :class:`ivy.Container` input:
+    >>> x = ivy.Container(a=ivy.array([0.0, float('nan')]),
+    ...                   b=ivy.array([-0., -4.9, float('+inf')]),
+    ...                   c=ivy.array([8.9, 2.1, 1.]))
+    >>> y = ivy.log2(x)
+    >>> print(y)
+    {
+        a: ivy.array([-inf, nan]),
+        b: ivy.array([-inf, nan, inf]),
+        c: ivy.array([3.15, 1.07, 0.])
+    }
     """
     return ivy.current_backend(x).log2(x, out=out)