Complete missing docstrings in keras-core/ops/core.py

keras_core/ops/core.py

@@ -273,30 +273,83 @@ def stop_gradient(variable):
 
 @keras_core_export("keras_core.ops.shape")
 def shape(x):
-    """Gets the shape of the tensor input."""
+    """Gets the shape of the tensor input.
+
+    Args:
+        x: A tensor. This function will try to access the `shape` attribute of
+            the input tensor.
+
+    Returns:
+        A tuple of integers or None values, indicating the shape of the input
+            tensor.
+
+    Example:
+    >>> x = keras_core.zeros((8, 12))
+    >>> keras_core.ops.shape(x)
+    (8, 12)
+
+    """
+
     if any_symbolic_tensors((x,)):
         return x.shape
     return backend.core.shape(x)
 
 
 @keras_core_export("keras_core.ops.cast")
 def cast(x, dtype):
-    """Cast a tensor to the desired dtype."""
+    """Cast a tensor to the desired dtype.
+
+    Args:
+        x: A tensor or variable.
+        dtype: The target type.
+
+    Returns:
+        A tensor of the specified `dtype`.
+
+    Example:
+    >>> x = keras_core.ops.arange(4)
+    >>> keras_core.ops.cast(x, "float32")
+
+    """
     dtype = backend.standardize_dtype(dtype)
+
     if any_symbolic_tensors((x,)):
         return backend.KerasTensor(shape=x.shape, dtype=dtype)
     return backend.core.cast(x, dtype)
 
 
 @keras_core_export("keras_core.ops.convert_to_tensor")
 def convert_to_tensor(x, dtype=None):
-    """Convert a NumPy array to a tensor."""
+    """Convert a NumPy array to a tensor.
+
+    Args:
+        x: A NumPy array.
+        dtype: The target type.
+
+    Returns:
+        A tensor of the specified `dtype`.
+
+    Example:
+    >>> x = np.array([1, 2, 3])
+    >>> keras_core.ops.convert_to_tensor(x)
+
+    """
+
     return backend.convert_to_tensor(x, dtype=dtype)
 
 
 @keras_core_export("keras_core.ops.convert_to_numpy")
 def convert_to_numpy(x):
-    """Convert a tensor to a NumPy array."""
+    """Convert a tensor to a NumPy array.
+
+    Args:
+        x: A tensor.
+
+    Returns:
+        A NumPy array.
+
+    """
+
     if any_symbolic_tensors((x,)):
         # This will raise a `ValueError` defined in the `KerasTensor` class. We
         # trigger it rather than duplicate it here.