Leverage on dpctl.tensor implementation in dpnp.put_along_axis d321c7c

Author: github-actions[bot]

pull/2134/.buildinfo

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 # Sphinx build info version 1
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pull/2134/_modules/dpnp/dpnp_array.html

@@ -14,14 +14,14 @@
     </script>
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-  <title>dpnp.dpnp_array &mdash; Data Parallel Extension for NumPy 0.17.0dev0+71.g97121023d42 documentation</title>
+  <title>dpnp.dpnp_array &mdash; Data Parallel Extension for NumPy 0.17.0dev0+83.gd321c7c0fa documentation</title>
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@@ -1162,7 +1162,7 @@ <h1>Source code for dpnp.dpnp_array</h1><div class="highlight"><pre>
 
 <span class="sd">        Returns</span>
 <span class="sd">        -------</span>
-<span class="sd">        out: dpnp.ndarray</span>
+<span class="sd">        out : dpnp.ndarray</span>
 <span class="sd">            A copy of the input array, flattened to one dimension.</span>
 
 <span class="sd">        See Also</span>
@@ -1228,43 +1228,56 @@ <h1>Source code for dpnp.dpnp_array</h1><div class="highlight"><pre>
 
 <div class="viewcode-block" id="dpnp_array.item">
 <a class="viewcode-back" href="../../reference/generated/dpnp.dpnp_array.dpnp_array.html#dpnp.dpnp_array.dpnp_array.item">[docs]</a>
-    <span class="k">def</span> <span class="nf">item</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="nb">id</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
+    <span class="k">def</span> <span class="nf">item</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">):</span>
 <span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Copy an element of an array to a standard Python scalar and return it.</span>
 
 <span class="sd">        For full documentation refer to :obj:`numpy.ndarray.item`.</span>
 
+<span class="sd">        Parameters</span>
+<span class="sd">        ----------</span>
+<span class="sd">        *args : {none, int, tuple of ints}</span>
+<span class="sd">            - none: in this case, the method only works for arrays with</span>
+<span class="sd">              one element (``a.size == 1``), which element is copied into a</span>
+<span class="sd">              standard Python scalar object and returned.</span>
+<span class="sd">            - int: this argument is interpreted as a flat index into the array,</span>
+<span class="sd">              specifying which element to copy and return.</span>
+<span class="sd">            - tuple of ints: functions as does a single int argument, except</span>
+<span class="sd">              that the argument is interpreted as an nd-index into the array.</span>
+
+<span class="sd">        Returns</span>
+<span class="sd">        -------</span>
+<span class="sd">        out : Standard Python scalar object</span>
+<span class="sd">            A copy of the specified element of the array as a suitable Python scalar.</span>
+
 <span class="sd">        Examples</span>
 <span class="sd">        --------</span>
+<span class="sd">        &gt;&gt;&gt; import dpnp as np</span>
 <span class="sd">        &gt;&gt;&gt; np.random.seed(123)</span>
 <span class="sd">        &gt;&gt;&gt; x = np.random.randint(9, size=(3, 3))</span>
 <span class="sd">        &gt;&gt;&gt; x</span>
-<span class="sd">        array([[2, 2, 6],</span>
-<span class="sd">               [1, 3, 6],</span>
-<span class="sd">               [1, 0, 1]])</span>
+<span class="sd">        array([[0, 0, 7],</span>
+<span class="sd">               [6, 6, 6],</span>
+<span class="sd">               [0, 7, 1]])</span>
 <span class="sd">        &gt;&gt;&gt; x.item(3)</span>
-<span class="sd">        1</span>
+<span class="sd">        6</span>
 <span class="sd">        &gt;&gt;&gt; x.item(7)</span>
-<span class="sd">        0</span>
+<span class="sd">        7</span>
 <span class="sd">        &gt;&gt;&gt; x.item((0, 1))</span>
-<span class="sd">        2</span>
+<span class="sd">        0</span>
 <span class="sd">        &gt;&gt;&gt; x.item((2, 2))</span>
 <span class="sd">        1</span>
 
-<span class="sd">        &quot;&quot;&quot;</span>
+<span class="sd">        &gt;&gt;&gt; x = np.array(5)</span>
+<span class="sd">        &gt;&gt;&gt; x.item()</span>
+<span class="sd">        5</span>
 
-        <span class="k">if</span> <span class="nb">id</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
-            <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">size</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;DPNP ndarray::item(): can only convert an array of size 1 to a Python scalar&quot;</span>
-                <span class="p">)</span>
-            <span class="k">else</span><span class="p">:</span>
-                <span class="nb">id</span> <span class="o">=</span> <span class="mi">0</span>
-
-        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">flat</span><span class="p">[</span><span class="nb">id</span><span class="p">]</span></div>
+<span class="sd">        &quot;&quot;&quot;</span>
 
+        <span class="c1"># TODO: implement a more efficient way to avoid copying to host</span>
+        <span class="c1"># for large arrays using `asnumpy()`</span>
+        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">asnumpy</span><span class="p">()</span><span class="o">.</span><span class="n">item</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">)</span></div>
 
-    <span class="c1"># &#39;itemset&#39;,</span>
 
     <span class="nd">@property</span>
     <span class="k">def</span> <span class="nf">itemsize</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
@@ -1379,8 +1392,6 @@ <h1>Source code for dpnp.dpnp_array</h1><div class="highlight"><pre>
 
         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_array_obj</span><span class="o">.</span><span class="n">ndim</span>
 
-    <span class="c1"># &#39;newbyteorder&#39;,</span>
-
 <div class="viewcode-block" id="dpnp_array.nonzero">
 <a class="viewcode-back" href="../../reference/generated/dpnp.dpnp_array.dpnp_array.html#dpnp.dpnp_array.dpnp_array.nonzero">[docs]</a>
     <span class="k">def</span> <span class="nf">nonzero</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>

pull/2134/_modules/dpnp/dpnp_flatiter.html

@@ -14,14 +14,14 @@
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   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-  <title>dpnp.dpnp_flatiter &mdash; Data Parallel Extension for NumPy 0.17.0dev0+71.g97121023d42 documentation</title>
+  <title>dpnp.dpnp_flatiter &mdash; Data Parallel Extension for NumPy 0.17.0dev0+83.gd321c7c0fa documentation</title>
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pull/2134/_modules/dpnp/dpnp_iface.html

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