Implement asynchronous fill method using dpctl kernels (#2055)

* Enhance `dpnp_array.fill` method

Leverages dpctl's strided fill and memset for setting contiguous memory to 0

* Fix missing disclaimer in dpnp_arraycreation.py

* Import `dpnp_array` directly

* Skip `test_fill_with_numpy_scalar_ndarray`

New fill implementation does not permit NumPy array values, consistent with fill_diagonal

* Add dependencies to zeros and full kernels in `dpnp_fill`

* Remove redundant validation of first `dpnp_fill` argument

* Improve `dpnp_fill` array/scalar path logic

* Disallow inputs to `dpnp_fill` on separate queues

* Adjust skip message for `test_fill_with_numpy_scalar_ndarray`

* Tweak error messages in `dpnp_fill`

* Add tests for new `fill` method

* Update docstring for `fill` method

* Fix pre-commit in cupy fill tests

* Change `asarray` to `astype` in `dpnp_fill`

NumPy arrays are no longer permitted and queue coercion does not occur in the `fill` method, so `astype` is sufficient

* Expand TEST_SCOPE to include `test_fill.py`

* Remove redundant check from `dpnp_fill`

* Use `_cast_fill_val` private function from `dpctl.tensor._ctors`

* Add tests per PR review by @antonwolfy

* Improve validation of `val` for `fill` method

* Add to permit NumPy bools as `dpnp_fill` scalar fill values

* Use `dpnp.bool` in `dpnp_fill` and make `isinstance` check more efficient

* Replace branching for `fill` scalar type with `_cast_fill_value`

* Add additional tests for `fill`

`test_fill_non_scalar` now checks for strings and `test_fill_bool` added to verify bools are properly cast to 1

---------

Co-authored-by: Anton <[email protected]> 29239b6

Author: github-actions[bot]

.buildinfo

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-  <title>dpnp.dpnp_array &mdash; Data Parallel Extension for NumPy 0.17.0dev0+60.ge236ad9f0ee documentation</title>
+  <title>dpnp.dpnp_array &mdash; Data Parallel Extension for NumPy 0.17.0dev0+61.g29239b67173 documentation</title>
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@@ -1098,13 +1098,16 @@ <h1>Source code for dpnp.dpnp_array</h1><div class="highlight"><pre>
 <span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Fill the array with a scalar value.</span>
 
+<span class="sd">        For full documentation refer to :obj:`numpy.ndarray.fill`.</span>
+
 <span class="sd">        Parameters</span>
 <span class="sd">        ----------</span>
-<span class="sd">        value : scalar</span>
+<span class="sd">        value : {dpnp.ndarray, usm_ndarray, scalar}</span>
 <span class="sd">            All elements of `a` will be assigned this value.</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; a = np.array([1, 2])</span>
 <span class="sd">        &gt;&gt;&gt; a.fill(0)</span>
 <span class="sd">        &gt;&gt;&gt; a</span>
@@ -1116,8 +1119,10 @@ <h1>Source code for dpnp.dpnp_array</h1><div class="highlight"><pre>
 
 <span class="sd">        &quot;&quot;&quot;</span>
 
-        <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">size</span><span class="p">):</span>
-            <span class="bp">self</span><span class="o">.</span><span class="n">flat</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">value</span></div>
+        <span class="c1"># lazy import avoids circular imports</span>
+        <span class="kn">from</span> <span class="nn">.dpnp_algo.dpnp_fill</span> <span class="kn">import</span> <span class="n">dpnp_fill</span>
+
+        <span class="n">dpnp_fill</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">value</span><span class="p">)</span></div>
 
 
     <span class="nd">@property</span>

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