Implement __usm_ndarray__ protocol (#2261)

The PR is intended to adopt to dpctl changes implemented in
[dpctl#1959](IntelPython/dpctl#1959).

It implements support of `__usm_ndarray__` protocol for `dpnp.ndarray`
and returns a property with `dpctl.tensor.usm_ndarray` instance
corresponding to the content of the array object.

This property is intended to speed-up conversion from `dpnp.ndarray` to
`dpt.usm_ndarray` in `x=dpt.asarray(dpnp_array_obj)`.
The input object that implements `__usm_ndarray__` is recognized as
owner of USM allocation that is managed by a smart pointer, and
asynchronous deallocation of `x` need not involve GIL. 9ad1bb5

.buildinfo

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 # This file records the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: 7efca1f7cf0fd12d36cc8c2589bae464
+config: 786d33f83216659ff3c12418a10ba431
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_modules/dpnp/dpnp_array.html

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-  <title>dpnp.dpnp_array &mdash; Data Parallel Extension for NumPy 0.17.0dev4+5.g6cc23484bc9 documentation</title>
+  <title>dpnp.dpnp_array &mdash; Data Parallel Extension for NumPy 0.17.0dev4+6.g9ad1bb5a530 documentation</title>
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+      <script src="../../_static/documentation_options.js?v=ac9a9b01"></script>
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@@ -695,6 +695,25 @@ <h1>Source code for dpnp.dpnp_array</h1><div class="highlight"><pre>
 <span class="w">        </span><span class="sd">&quot;&quot;&quot;Return ``self/value``.&quot;&quot;&quot;</span>
         <span class="k">return</span> <span class="n">dpnp</span><span class="o">.</span><span class="n">true_divide</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">)</span>
 
+    <span class="nd">@property</span>
+    <span class="k">def</span><span class="w"> </span><span class="nf">__usm_ndarray__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">        Property to support `__usm_ndarray__` protocol.</span>
+
+<span class="sd">        It assumes to return :class:`dpctl.tensor.usm_ndarray` instance</span>
+<span class="sd">        corresponding to the content of the object.</span>
+
+<span class="sd">        This property is intended to speed-up conversion from</span>
+<span class="sd">        :class:`dpnp.ndarray` to :class:`dpctl.tensor.usm_ndarray` passed</span>
+<span class="sd">        into  `dpctl.tensor.asarray` function. The input object that implements</span>
+<span class="sd">        `__usm_ndarray__` protocol is recognized as owner of USM allocation</span>
+<span class="sd">        that is managed by a smart pointer, and asynchronous deallocation</span>
+<span class="sd">        will not involve GIL.</span>
+
+<span class="sd">        &quot;&quot;&quot;</span>
+
+        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_array_obj</span>
+
     <span class="k">def</span><span class="w"> </span><span class="fm">__xor__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span>
 <span class="w">        </span><span class="sd">&quot;&quot;&quot;Return ``self^value``.&quot;&quot;&quot;</span>
         <span class="k">return</span> <span class="n">dpnp</span><span class="o">.</span><span class="n">bitwise_xor</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">)</span>

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+  <title>dpnp.dpnp_iface &mdash; Data Parallel Extension for NumPy 0.17.0dev4+6.g9ad1bb5a530 documentation</title>
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+  <title>dpnp.dpnp_iface_arraycreation &mdash; Data Parallel Extension for NumPy 0.17.0dev4+6.g9ad1bb5a530 documentation</title>
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+  <title>dpnp.dpnp_iface_bitwise &mdash; Data Parallel Extension for NumPy 0.17.0dev4+6.g9ad1bb5a530 documentation</title>
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+  <title>dpnp.dpnp_iface_counting &mdash; Data Parallel Extension for NumPy 0.17.0dev4+6.g9ad1bb5a530 documentation</title>
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+  <title>dpnp.dpnp_iface_functional &mdash; Data Parallel Extension for NumPy 0.17.0dev4+6.g9ad1bb5a530 documentation</title>
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