Update broadcast_arrays to return a tuple instead of a list (#2944)

This PR updates `dpnp.broadcast_arrays()` and
`dpnp.tensor.broadcast_arrays()` to return a tuple instead of a list
aligning their behavior with the Python Array API 2025.12 and NumPy 01c5a42

Author: github-actions[bot]

_modules/dpnp/dpnp_iface_manipulation.html

@@ -2122,8 +2122,8 @@ <h1>Source code for dpnp.dpnp_iface_manipulation</h1><div class="highlight"><pre
 
 <span class="sd">    Returns</span>
 <span class="sd">    -------</span>
-<span class="sd">    out : list of dpnp.ndarray</span>
-<span class="sd">        A list of arrays which are views on the original arrays from `args`.</span>
+<span class="sd">    out : tuple of dpnp.ndarray</span>
+<span class="sd">        A tuple of arrays which are views on the original arrays from `args`.</span>
 
 <span class="sd">    Limitations</span>
 <span class="sd">    -----------</span>
@@ -2140,20 +2140,20 @@ <h1>Source code for dpnp.dpnp_iface_manipulation</h1><div class="highlight"><pre
 <span class="sd">    &gt;&gt;&gt; x = np.array([[1, 2, 3]])</span>
 <span class="sd">    &gt;&gt;&gt; y = np.array([[4], [5]])</span>
 <span class="sd">    &gt;&gt;&gt; np.broadcast_arrays(x, y)</span>
-<span class="sd">    [array([[1, 2, 3],</span>
+<span class="sd">    (array([[1, 2, 3],</span>
 <span class="sd">            [1, 2, 3]]), array([[4, 4, 4],</span>
-<span class="sd">            [5, 5, 5]])]</span>
+<span class="sd">            [5, 5, 5]]))</span>
 
 <span class="sd">    &quot;&quot;&quot;</span>
 
     <span class="k">if</span> <span class="n">subok</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">False</span><span class="p">:</span>
         <span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;subok=</span><span class="si">{</span><span class="n">subok</span><span class="si">}</span><span class="s2"> is currently not supported&quot;</span><span class="p">)</span>
 
     <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">args</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
-        <span class="k">return</span> <span class="p">[]</span>
+        <span class="k">return</span> <span class="p">()</span>
 
     <span class="n">usm_arrays</span> <span class="o">=</span> <span class="n">dpt</span><span class="o">.</span><span class="n">broadcast_arrays</span><span class="p">(</span><span class="o">*</span><span class="p">[</span><span class="n">dpnp</span><span class="o">.</span><span class="n">get_usm_ndarray</span><span class="p">(</span><span class="n">a</span><span class="p">)</span> <span class="k">for</span> <span class="n">a</span> <span class="ow">in</span> <span class="n">args</span><span class="p">])</span>
-    <span class="k">return</span> <span class="p">[</span><span class="n">dpnp_array</span><span class="o">.</span><span class="n">_create_from_usm_ndarray</span><span class="p">(</span><span class="n">a</span><span class="p">)</span> <span class="k">for</span> <span class="n">a</span> <span class="ow">in</span> <span class="n">usm_arrays</span><span class="p">]</span></div>
+    <span class="k">return</span> <span class="nb">tuple</span><span class="p">(</span><span class="n">dpnp_array</span><span class="o">.</span><span class="n">_create_from_usm_ndarray</span><span class="p">(</span><span class="n">a</span><span class="p">)</span> <span class="k">for</span> <span class="n">a</span> <span class="ow">in</span> <span class="n">usm_arrays</span><span class="p">)</span></div>
 
 
 

reference/comparison.html

@@ -1047,7 +1047,7 @@
 <h1>Comparison Table NumPy/ DPNP/ CuPy<a class="headerlink" href="#comparison-table-numpy-dpnp-cupy" title="Link to this heading">¶</a></h1>
 <p>Here is a list of NumPy and CuPy APIs and its corresponding DPNP implementations.</p>
 <p><code class="docutils literal notranslate"><span class="pre">-</span></code> in DPNP column means that DPNP implementation is not provided yet.</p>
-<p><strong>NumPy(v2.5.1) / DPNP(v0.21.0dev3+18.g24e3ac1e2e2) / CuPy(v14.1.1) APIs</strong></p>
+<p><strong>NumPy(v2.5.1) / DPNP(v0.21.0dev3+19.g01c5a420319) / CuPy(v14.1.1) APIs</strong></p>
 <section id="summary">
 <h2>Summary<a class="headerlink" href="#summary" title="Link to this heading">¶</a></h2>
 <div class="table-wrapper docutils container">

reference/generated/dpnp.broadcast_arrays.html

@@ -1055,10 +1055,10 @@ <h1>dpnp.broadcast_arrays<a class="headerlink" href="#dpnp-broadcast-arrays" tit
 <dd class="field-odd"><p><strong>args</strong> (<em>{dpnp.ndarray</em><em>, </em><em>usm_ndarray}</em>) -- A list of arrays to broadcast.</p>
 </dd>
 <dt class="field-even">Returns<span class="colon">:</span></dt>
-<dd class="field-even"><p><strong>out</strong> -- A list of arrays which are views on the original arrays from <cite>args</cite>.</p>
+<dd class="field-even"><p><strong>out</strong> -- A tuple of arrays which are views on the original arrays from <cite>args</cite>.</p>
 </dd>
 <dt class="field-odd">Return type<span class="colon">:</span></dt>
-<dd class="field-odd"><p><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.14)">list</a> of <a class="reference internal" href="dpnp.ndarray.html#dpnp.ndarray" title="dpnp.ndarray">dpnp.ndarray</a></p>
+<dd class="field-odd"><p><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#tuple" title="(in Python v3.14)">tuple</a> of <a class="reference internal" href="dpnp.ndarray.html#dpnp.ndarray" title="dpnp.ndarray">dpnp.ndarray</a></p>
 </dd>
 </dl>
 <p class="rubric">Limitations</p>
@@ -1076,9 +1076,9 @@ <h1>dpnp.broadcast_arrays<a class="headerlink" href="#dpnp-broadcast-arrays" tit
 <span class="gp">&gt;&gt;&gt; </span><span class="n">x</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">]])</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="n">y</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([[</span><span class="mi">4</span><span class="p">],</span> <span class="p">[</span><span class="mi">5</span><span class="p">]])</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">broadcast_arrays</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">)</span>
-<span class="go">[array([[1, 2, 3],</span>
+<span class="go">(array([[1, 2, 3],</span>
 <span class="go">        [1, 2, 3]]), array([[4, 4, 4],</span>
-<span class="go">        [5, 5, 5]])]</span>
+<span class="go">        [5, 5, 5]]))</span>
 </pre></div>
 </div>
 </dd></dl>