Add proper handling of unput array of usm_ndarray type in dpnp.ix_ (#2047)

* Proper handling of input array as dpctl.tensor.usm_ndarray

* Update a page for Indexing routines

* Move dpnp.ix_ tests to keep lexycographical order

* Add tests to cover faulty use case

* Added entry to changelog 6314346

Author: github-actions[bot]

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+  <title>dpnp.dpnp_iface &mdash; Data Parallel Extension for NumPy 0.17.0dev0+11.g631434623d6 documentation</title>
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@@ -12,7 +12,7 @@
     </script>
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-  <title>dpnp.dpnp_iface_indexing &mdash; Data Parallel Extension for NumPy 0.17.0dev0+10.gbe5c3f07c44 documentation</title>
+  <title>dpnp.dpnp_iface_indexing &mdash; Data Parallel Extension for NumPy 0.17.0dev0+11.g631434623d6 documentation</title>
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@@ -1050,7 +1050,7 @@ <h1>Source code for dpnp.dpnp_iface_indexing</h1><div class="highlight"><pre>
 <span class="sd">    and the dimension with the non-unit shape value cycles through all</span>
 <span class="sd">    N dimensions.</span>
 
-<span class="sd">    Using  :obj:`dpnp.ix_` one can quickly construct index arrays that will</span>
+<span class="sd">    Using :obj:`dpnp.ix_` one can quickly construct index arrays that will</span>
 <span class="sd">    index the cross product. ``a[dpnp.ix_([1,3],[2,5])]`` returns the array</span>
 <span class="sd">    ``[[a[1,2] a[1,5]], [a[3,2] a[3,5]]]``.</span>
 
@@ -1110,14 +1110,15 @@ <h1>Source code for dpnp.dpnp_iface_indexing</h1><div class="highlight"><pre>
 <span class="sd">    &quot;&quot;&quot;</span>
 
     <span class="n">dpnp</span><span class="o">.</span><span class="n">check_supported_arrays_type</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">)</span>
+
     <span class="n">out</span> <span class="o">=</span> <span class="p">[]</span>
     <span class="n">nd</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">args</span><span class="p">)</span>
     <span class="k">for</span> <span class="n">k</span><span class="p">,</span> <span class="n">new</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">args</span><span class="p">):</span>
         <span class="k">if</span> <span class="n">new</span><span class="o">.</span><span class="n">ndim</span> <span class="o">!=</span> <span class="mi">1</span><span class="p">:</span>
             <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">&quot;Cross index must be 1 dimensional&quot;</span><span class="p">)</span>
         <span class="k">if</span> <span class="n">dpnp</span><span class="o">.</span><span class="n">issubdtype</span><span class="p">(</span><span class="n">new</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span> <span class="n">dpnp</span><span class="o">.</span><span class="n">bool</span><span class="p">):</span>
             <span class="p">(</span><span class="n">new</span><span class="p">,)</span> <span class="o">=</span> <span class="n">dpnp</span><span class="o">.</span><span class="n">nonzero</span><span class="p">(</span><span class="n">new</span><span class="p">)</span>
-        <span class="n">new</span> <span class="o">=</span> <span class="n">new</span><span class="o">.</span><span class="n">reshape</span><span class="p">((</span><span class="mi">1</span><span class="p">,)</span> <span class="o">*</span> <span class="n">k</span> <span class="o">+</span> <span class="p">(</span><span class="n">new</span><span class="o">.</span><span class="n">size</span><span class="p">,)</span> <span class="o">+</span> <span class="p">(</span><span class="mi">1</span><span class="p">,)</span> <span class="o">*</span> <span class="p">(</span><span class="n">nd</span> <span class="o">-</span> <span class="n">k</span> <span class="o">-</span> <span class="mi">1</span><span class="p">))</span>
+        <span class="n">new</span> <span class="o">=</span> <span class="n">dpnp</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="n">new</span><span class="p">,</span> <span class="p">(</span><span class="mi">1</span><span class="p">,)</span> <span class="o">*</span> <span class="n">k</span> <span class="o">+</span> <span class="p">(</span><span class="n">new</span><span class="o">.</span><span class="n">size</span><span class="p">,)</span> <span class="o">+</span> <span class="p">(</span><span class="mi">1</span><span class="p">,)</span> <span class="o">*</span> <span class="p">(</span><span class="n">nd</span> <span class="o">-</span> <span class="n">k</span> <span class="o">-</span> <span class="mi">1</span><span class="p">))</span>
         <span class="n">out</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">new</span><span class="p">)</span>
     <span class="k">return</span> <span class="nb">tuple</span><span class="p">(</span><span class="n">out</span><span class="p">)</span></div>
 

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@@ -43,7 +43,7 @@
             Data Parallel Extension for NumPy
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