Fix a few sphinx-build errors and warnings

doc/dpctl.rst

@@ -2,7 +2,7 @@
 .. include:: ./ext_links.txt
 
 Interplay with the Data Parallel Control Library
-===============================================
+================================================
 
 `Data Parallel Control Library`_ provides API to manage specific
 `SYCL*`_ resources for SYCL-based Python packages.

doc/index.rst

@@ -5,6 +5,7 @@ Data Parallel Extension for NumPy*
 ==================================
 
 .. module:: dpnp
+    :noindex:
 
 .. toctree::
    :maxdepth: 2

doc/quick_start_guide.rst

@@ -22,7 +22,7 @@ Follow device driver installation instructions to complete the step.
 
 
 Python Interpreter
-=================
+==================
 
 You will need Python 3.8, 3.9, or 3.10 installed on your system. If you
 do not have one yet the easiest way to do that is to install
@@ -38,7 +38,7 @@ Installation
 ============
 
 Install Package from Anaconda
----------------------
+-----------------------------
 
 It is recommended to use conda packages from the ``anaconda.org/intel``
 channel. You will need one of the commands below:

doc/reference/creation.rst

@@ -63,7 +63,7 @@ Numerical ranges
 
 
 Building matrices
----------------
+-----------------
 
 .. autosummary::
    :toctree: generated/

doc/reference/dtypes_table.rst

@@ -1,8 +1,7 @@
-Available array data types
-==========================
-
 .. _Data types:
 
+Available array data types
+==========================
 
 Table below shows a list of all supported data types (dtypes) and constants of the Data Parallel Extension for NumPy*.
 

doc/reference/linalg.rst

@@ -46,7 +46,7 @@ Matrix eigenvalues
    dpnp.linalg.eigvalsh
 
 Norms and other numbers
-----------
+-----------------------
 
 .. autosummary::
    :toctree: generated/

doc/reference/ndarray.rst

@@ -115,7 +115,7 @@ For the following methods there are also corresponding functions in
 :func:`diagonal <dpnp.diagonal>`, :func:`imag <dpnp.imag>`,
 :func:`max <dpnp.max>`, :func:`mean <dpnp.mean>`, :func:`min <dpnp.min>`,
 :func:`nonzero <dpnp.nonzero>`, :func:`partition <dpnp.partition>`,
-:func:`prod <dpnp.prod>`, :func:`ptp <dpnp.ptp>`, :func:`put <dpnp.put>`,
+:func:`prod <dpnp.prod>`, :func:`put <dpnp.put>`,
 :func:`ravel <dpnp.ravel>`, :func:`real <dpnp.real>`, :func:`repeat <dpnp.repeat>`,
 :func:`reshape <dpnp.reshape>`, :func:`round <dpnp.around>`,
 :func:`searchsorted <dpnp.searchsorted>`, :func:`sort <dpnp.sort>`,
@@ -204,7 +204,6 @@ Calculation
    dpnp.ndarray.argmax
    dpnp.ndarray.min
    dpnp.ndarray.argmin
-   dpnp.ndarray.ptp
    dpnp.ndarray.clip
    dpnp.ndarray.conj
    dpnp.ndarray.conjugate

doc/reference/statistics.rst

@@ -18,7 +18,7 @@ Order statistics
 
 
 Averages and variances
--------------------
+----------------------
 
 .. autosummary::
    :toctree: generated/

dpnp/dpnp_array.py

@@ -550,11 +550,13 @@ def astype(self, dtype, order="K", casting="unsafe", subok=True, copy=True):
             Otherwise, a copy is returned.
         casting : {'no', 'equiv', 'safe', 'same_kind', 'unsafe'}, optional
             Controls what kind of data casting may occur. Defaults to 'unsafe' for backwards compatibility.
-            'no' means the data types should not be cast at all.
-            'equiv' means only byte-order changes are allowed.
-            'safe' means only casts which can preserve values are allowed.
-            'same_kind' means only safe casts or casts within a kind, like float64 to float32, are allowed.
-            'unsafe' means any data conversions may be done.
+
+            - 'no' means the data types should not be cast at all.
+            - 'equiv' means only byte-order changes are allowed.
+            - 'safe' means only casts which can preserve values are allowed.
+            - 'same_kind' means only safe casts or casts within a kind, like float64 to float32, are allowed.
+            - 'unsafe' means any data conversions may be done.
+
         copy : bool, optional
             By default, astype always returns a newly allocated array. If this is set to false, and the dtype,
             order, and subok requirements are satisfied, the input array is returned instead of a copy.

dpnp/dpnp_iface.py

@@ -198,12 +198,14 @@ def astype(x1, dtype, order="K", casting="unsafe", copy=True):
     casting : {'no', 'equiv', 'safe', 'same_kind', 'unsafe'}, optional
         Controls what kind of data casting may occur. Defaults to ``unsafe``
         for backwards compatibility.
+
             - 'no' means the data types should not be cast at all.
             - 'equiv' means only byte-order changes are allowed.
             - 'safe' means only casts which can preserve values are allowed.
             - 'same_kind' means only safe casts or casts within a kind, like
-            float64 to float32, are allowed.
+              float64 to float32, are allowed.
             - 'unsafe' means any data conversions may be done.
+
     copy : bool, optional
         By default, astype always returns a newly allocated array. If this
         is set to ``False``, and the dtype, order, and subok requirements

dpnp/dpnp_iface_types.py

@@ -163,6 +163,7 @@ def finfo(dtype):
     -------
     out : finfo_object
         An object have the following attributes
+
         * bits: int
             number of bits occupied by dtype.
         * dtype: dtype
@@ -212,6 +213,7 @@ def iinfo(dtype):
     -------
     out : iinfo_object
         An object with the following attributes
+
         * bits: int
             number of bits occupied by the data type
         * dtype: dtype

dpnp/linalg/dpnp_iface_linalg.py

@@ -577,12 +577,12 @@ def inv(a):
     array([ True])
 
     Inverses of several matrices can be computed at once:
+
     >>> a = np.array([[[1., 2.], [3., 4.]], [[1, 3], [3, 5]]])
     >>> np.linalg.inv(a)
     array([[[-2.  ,  1.  ],
             [ 1.5 , -0.5 ]],
-
-          [[-1.25,  0.75],
+           [[-1.25,  0.75],
             [ 0.75, -0.25]]])
 
     """