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diff --git a/ivy/docs/data_classes/data_classes/array/ivy.data_classes.array.experimental.html b/ivy/docs/data_classes/data_classes/array/ivy.data_classes.array.experimental.html
index 76e3f58df8..22151c732b 100644
--- a/ivy/docs/data_classes/data_classes/array/ivy.data_classes.array.experimental.html
+++ b/ivy/docs/data_classes/data_classes/array/ivy.data_classes.array.experimental.html
@@ -2171,7 +2171,7 @@
 
 <dl class="py function">
 <dt class="sig sig-object py" id="ivy.data_classes.array.experimental.creation.polyval">
-<span class="sig-prename descclassname"><span class="pre">ivy.data_classes.array.experimental.creation.</span></span><span class="sig-name descname"><span class="pre">polyval</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="pre">coeffs=&lt;class</span> <span class="pre">'ivy.Array'&gt;,</span> <span class="pre">x=typing.Union[ivy.Array,</span> <span class="pre">ivy.NativeArray,</span> <span class="pre">int,</span> <span class="pre">float],</span> <span class="pre">/,</span> <span class="pre">*,</span> <span class="pre">dtype=None,</span> <span class="pre">device=None</span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/unifyai/ivy/blob/main/ivy/data_classes/array/experimental/creation.py#L308-L347"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#ivy.data_classes.array.experimental.creation.polyval" title="Link to this definition">#</a></dt>
+<span class="sig-prename descclassname"><span class="pre">ivy.data_classes.array.experimental.creation.</span></span><span class="sig-name descname"><span class="pre">polyval</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="pre">coeffs=&lt;class</span> <span class="pre">'ivy.Array'&gt;,</span> <span class="pre">x=typing.Union[ivy.Array,</span> <span class="pre">ivy.NativeArray,</span> <span class="pre">int,</span> <span class="pre">float],</span> <span class="pre">/,</span> <span class="pre">*,</span> <span class="pre">dtype=None,</span> <span class="pre">device=None</span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/unifyai/ivy/blob/main/ivy/data_classes/array/experimental/creation.py#L308-L345"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#ivy.data_classes.array.experimental.creation.polyval" title="Link to this definition">#</a></dt>
 <dd><p>ivy.Array instance method of polyval. This method simply wraps the
 function, and so the docstring for ivy.polyval also applies to this method
 with minimal changes.</p>
diff --git a/ivy/docs/functional/ivy/ivy.functional.ivy.meta.html b/ivy/docs/functional/ivy/ivy.functional.ivy.meta.html
index 19d4653cb8..33dba9bde9 100644
--- a/ivy/docs/functional/ivy/ivy.functional.ivy.meta.html
+++ b/ivy/docs/functional/ivy/ivy.functional.ivy.meta.html
@@ -1390,7 +1390,7 @@ <h1>Meta<a class="headerlink" href="#meta" title="Link to this heading">#</a></h
 <li><p><strong>variables</strong> (<a class="reference internal" href="../../data_classes/data_classes/ivy.data_classes.container.html#ivy.data_classes.container.container.Container" title="ivy.data_classes.container.container.Container"><code class="xref py py-class docutils literal notranslate"><span class="pre">Container</span></code></a>) – Variables to be optimized during the meta step</p></li>
 <li><p><strong>inner_grad_steps</strong> (<code class="xref py py-class docutils literal notranslate"><span class="pre">int</span></code>) – Number of gradient steps to perform during the inner loop.</p></li>
 <li><p><strong>inner_learning_rate</strong> (<code class="xref py py-class docutils literal notranslate"><span class="pre">float</span></code>) – The learning rate of the inner loop.</p></li>
-<li><p><strong>inner_optimization_step</strong> (<code class="xref py py-data docutils literal notranslate"><span class="pre">Callable</span></code>, default: <code class="docutils literal notranslate"><span class="pre">&lt;function</span> <span class="pre">gradient_descent_update</span> <span class="pre">at</span> <span class="pre">0x7f1019c83250&gt;</span></code>) – The function used for the inner loop optimization.
+<li><p><strong>inner_optimization_step</strong> (<code class="xref py py-data docutils literal notranslate"><span class="pre">Callable</span></code>, default: <code class="docutils literal notranslate"><span class="pre">&lt;function</span> <span class="pre">gradient_descent_update</span> <span class="pre">at</span> <span class="pre">0x7f705dcc3250&gt;</span></code>) – The function used for the inner loop optimization.
 Default is ivy.gradient_descent_update.</p></li>
 <li><p><strong>inner_batch_fn</strong> (<code class="xref py py-data docutils literal notranslate"><span class="pre">Optional</span></code>[<code class="xref py py-data docutils literal notranslate"><span class="pre">Callable</span></code>], default: <code class="docutils literal notranslate"><span class="pre">None</span></code>) – Function to apply to the task sub-batch, before passing to the inner_cost_fn.
 Default is <code class="docutils literal notranslate"><span class="pre">None</span></code>.</p></li>
@@ -1444,7 +1444,7 @@ <h1>Meta<a class="headerlink" href="#meta" title="Link to this heading">#</a></h
 <li><p><strong>variables</strong> (<a class="reference internal" href="../../data_classes/data_classes/ivy.data_classes.container.html#ivy.data_classes.container.container.Container" title="ivy.data_classes.container.container.Container"><code class="xref py py-class docutils literal notranslate"><span class="pre">Container</span></code></a>) – Variables to be optimized during the meta step</p></li>
 <li><p><strong>inner_grad_steps</strong> (<code class="xref py py-class docutils literal notranslate"><span class="pre">int</span></code>) – Number of gradient steps to perform during the inner loop.</p></li>
 <li><p><strong>inner_learning_rate</strong> (<code class="xref py py-class docutils literal notranslate"><span class="pre">float</span></code>) – The learning rate of the inner loop.</p></li>
-<li><p><strong>inner_optimization_step</strong> (<code class="xref py py-data docutils literal notranslate"><span class="pre">Callable</span></code>, default: <code class="docutils literal notranslate"><span class="pre">&lt;function</span> <span class="pre">gradient_descent_update</span> <span class="pre">at</span> <span class="pre">0x7f1019c83250&gt;</span></code>) – The function used for the inner loop optimization.
+<li><p><strong>inner_optimization_step</strong> (<code class="xref py py-data docutils literal notranslate"><span class="pre">Callable</span></code>, default: <code class="docutils literal notranslate"><span class="pre">&lt;function</span> <span class="pre">gradient_descent_update</span> <span class="pre">at</span> <span class="pre">0x7f705dcc3250&gt;</span></code>) – The function used for the inner loop optimization.
 Default is ivy.gradient_descent_update.</p></li>
 <li><p><strong>inner_batch_fn</strong> (<code class="xref py py-data docutils literal notranslate"><span class="pre">Optional</span></code>[<code class="xref py py-data docutils literal notranslate"><span class="pre">Callable</span></code>], default: <code class="docutils literal notranslate"><span class="pre">None</span></code>) – Function to apply to the task sub-batch, before passing to the inner_cost_fn.
 Default is <code class="docutils literal notranslate"><span class="pre">None</span></code>.</p></li>
@@ -1521,7 +1521,7 @@ <h1>Meta<a class="headerlink" href="#meta" title="Link to this heading">#</a></h
 <li><p><strong>variables</strong> (<a class="reference internal" href="../../data_classes/data_classes/ivy.data_classes.container.html#ivy.data_classes.container.container.Container" title="ivy.data_classes.container.container.Container"><code class="xref py py-class docutils literal notranslate"><span class="pre">Container</span></code></a>) – Variables to be optimized.</p></li>
 <li><p><strong>inner_grad_steps</strong> (<code class="xref py py-class docutils literal notranslate"><span class="pre">int</span></code>) – Number of gradient steps to perform during the inner loop.</p></li>
 <li><p><strong>inner_learning_rate</strong> (<code class="xref py py-class docutils literal notranslate"><span class="pre">float</span></code>) – The learning rate of the inner loop.</p></li>
-<li><p><strong>inner_optimization_step</strong> (<code class="xref py py-data docutils literal notranslate"><span class="pre">Callable</span></code>, default: <code class="docutils literal notranslate"><span class="pre">&lt;function</span> <span class="pre">gradient_descent_update</span> <span class="pre">at</span> <span class="pre">0x7f1019c83250&gt;</span></code>) – The function used for the inner loop optimization. It takes the learnable
+<li><p><strong>inner_optimization_step</strong> (<code class="xref py py-data docutils literal notranslate"><span class="pre">Callable</span></code>, default: <code class="docutils literal notranslate"><span class="pre">&lt;function</span> <span class="pre">gradient_descent_update</span> <span class="pre">at</span> <span class="pre">0x7f705dcc3250&gt;</span></code>) – The function used for the inner loop optimization. It takes the learnable
 weights,the derivative of the cost with respect to the weights, and the learning
 rate as arguments, and returns the updated variables.
 Default is <cite>gradient_descent_update</cite>.</p></li>
diff --git a/ivy/docs/functional/ivy/meta/ivy.functional.ivy.meta.fomaml_step.html b/ivy/docs/functional/ivy/meta/ivy.functional.ivy.meta.fomaml_step.html
index f79e060b25..f3b6805eb9 100644
--- a/ivy/docs/functional/ivy/meta/ivy.functional.ivy.meta.fomaml_step.html
+++ b/ivy/docs/functional/ivy/meta/ivy.functional.ivy.meta.fomaml_step.html
@@ -1393,7 +1393,7 @@ <h1>fomaml_step<a class="headerlink" href="#fomaml-step" title="Link to this hea
 <li><p><strong>variables</strong> (<a class="reference internal" href="../../../data_classes/data_classes/ivy.data_classes.container.html#ivy.data_classes.container.container.Container" title="ivy.data_classes.container.container.Container"><code class="xref py py-class docutils literal notranslate"><span class="pre">Container</span></code></a>) – Variables to be optimized during the meta step</p></li>
 <li><p><strong>inner_grad_steps</strong> (<code class="xref py py-class docutils literal notranslate"><span class="pre">int</span></code>) – Number of gradient steps to perform during the inner loop.</p></li>
 <li><p><strong>inner_learning_rate</strong> (<code class="xref py py-class docutils literal notranslate"><span class="pre">float</span></code>) – The learning rate of the inner loop.</p></li>
-<li><p><strong>inner_optimization_step</strong> (<code class="xref py py-data docutils literal notranslate"><span class="pre">Callable</span></code>, default: <code class="docutils literal notranslate"><span class="pre">&lt;function</span> <span class="pre">gradient_descent_update</span> <span class="pre">at</span> <span class="pre">0x7f1019c83250&gt;</span></code>) – The function used for the inner loop optimization.
+<li><p><strong>inner_optimization_step</strong> (<code class="xref py py-data docutils literal notranslate"><span class="pre">Callable</span></code>, default: <code class="docutils literal notranslate"><span class="pre">&lt;function</span> <span class="pre">gradient_descent_update</span> <span class="pre">at</span> <span class="pre">0x7f705dcc3250&gt;</span></code>) – The function used for the inner loop optimization.
 Default is ivy.gradient_descent_update.</p></li>
 <li><p><strong>inner_batch_fn</strong> (<code class="xref py py-data docutils literal notranslate"><span class="pre">Optional</span></code>[<code class="xref py py-data docutils literal notranslate"><span class="pre">Callable</span></code>], default: <code class="docutils literal notranslate"><span class="pre">None</span></code>) – Function to apply to the task sub-batch, before passing to the inner_cost_fn.
 Default is <code class="docutils literal notranslate"><span class="pre">None</span></code>.</p></li>
diff --git a/ivy/docs/functional/ivy/meta/ivy.functional.ivy.meta.maml_step.html b/ivy/docs/functional/ivy/meta/ivy.functional.ivy.meta.maml_step.html
index bf18026274..b65cfb7341 100644
--- a/ivy/docs/functional/ivy/meta/ivy.functional.ivy.meta.maml_step.html
+++ b/ivy/docs/functional/ivy/meta/ivy.functional.ivy.meta.maml_step.html
@@ -1393,7 +1393,7 @@ <h1>maml_step<a class="headerlink" href="#maml-step" title="Link to this heading
 <li><p><strong>variables</strong> (<a class="reference internal" href="../../../data_classes/data_classes/ivy.data_classes.container.html#ivy.data_classes.container.container.Container" title="ivy.data_classes.container.container.Container"><code class="xref py py-class docutils literal notranslate"><span class="pre">Container</span></code></a>) – Variables to be optimized during the meta step</p></li>
 <li><p><strong>inner_grad_steps</strong> (<code class="xref py py-class docutils literal notranslate"><span class="pre">int</span></code>) – Number of gradient steps to perform during the inner loop.</p></li>
 <li><p><strong>inner_learning_rate</strong> (<code class="xref py py-class docutils literal notranslate"><span class="pre">float</span></code>) – The learning rate of the inner loop.</p></li>
-<li><p><strong>inner_optimization_step</strong> (<code class="xref py py-data docutils literal notranslate"><span class="pre">Callable</span></code>, default: <code class="docutils literal notranslate"><span class="pre">&lt;function</span> <span class="pre">gradient_descent_update</span> <span class="pre">at</span> <span class="pre">0x7f1019c83250&gt;</span></code>) – The function used for the inner loop optimization.
+<li><p><strong>inner_optimization_step</strong> (<code class="xref py py-data docutils literal notranslate"><span class="pre">Callable</span></code>, default: <code class="docutils literal notranslate"><span class="pre">&lt;function</span> <span class="pre">gradient_descent_update</span> <span class="pre">at</span> <span class="pre">0x7f705dcc3250&gt;</span></code>) – The function used for the inner loop optimization.
 Default is ivy.gradient_descent_update.</p></li>
 <li><p><strong>inner_batch_fn</strong> (<code class="xref py py-data docutils literal notranslate"><span class="pre">Optional</span></code>[<code class="xref py py-data docutils literal notranslate"><span class="pre">Callable</span></code>], default: <code class="docutils literal notranslate"><span class="pre">None</span></code>) – Function to apply to the task sub-batch, before passing to the inner_cost_fn.
 Default is <code class="docutils literal notranslate"><span class="pre">None</span></code>.</p></li>
diff --git a/ivy/docs/functional/ivy/meta/ivy.functional.ivy.meta.reptile_step.html b/ivy/docs/functional/ivy/meta/ivy.functional.ivy.meta.reptile_step.html
index 913ffa7708..447e1dafeb 100644
--- a/ivy/docs/functional/ivy/meta/ivy.functional.ivy.meta.reptile_step.html
+++ b/ivy/docs/functional/ivy/meta/ivy.functional.ivy.meta.reptile_step.html
@@ -1390,7 +1390,7 @@ <h1>reptile_step<a class="headerlink" href="#reptile-step" title="Link to this h
 <li><p><strong>variables</strong> (<a class="reference internal" href="../../../data_classes/data_classes/ivy.data_classes.container.html#ivy.data_classes.container.container.Container" title="ivy.data_classes.container.container.Container"><code class="xref py py-class docutils literal notranslate"><span class="pre">Container</span></code></a>) – Variables to be optimized.</p></li>
 <li><p><strong>inner_grad_steps</strong> (<code class="xref py py-class docutils literal notranslate"><span class="pre">int</span></code>) – Number of gradient steps to perform during the inner loop.</p></li>
 <li><p><strong>inner_learning_rate</strong> (<code class="xref py py-class docutils literal notranslate"><span class="pre">float</span></code>) – The learning rate of the inner loop.</p></li>
-<li><p><strong>inner_optimization_step</strong> (<code class="xref py py-data docutils literal notranslate"><span class="pre">Callable</span></code>, default: <code class="docutils literal notranslate"><span class="pre">&lt;function</span> <span class="pre">gradient_descent_update</span> <span class="pre">at</span> <span class="pre">0x7f1019c83250&gt;</span></code>) – The function used for the inner loop optimization. It takes the learnable
+<li><p><strong>inner_optimization_step</strong> (<code class="xref py py-data docutils literal notranslate"><span class="pre">Callable</span></code>, default: <code class="docutils literal notranslate"><span class="pre">&lt;function</span> <span class="pre">gradient_descent_update</span> <span class="pre">at</span> <span class="pre">0x7f705dcc3250&gt;</span></code>) – The function used for the inner loop optimization. It takes the learnable
 weights,the derivative of the cost with respect to the weights, and the learning
 rate as arguments, and returns the updated variables.
 Default is <cite>gradient_descent_update</cite>.</p></li>
diff --git a/ivy/docs/helpers/ivy_tests.test_ivy.helpers.globals.html b/ivy/docs/helpers/ivy_tests.test_ivy.helpers.globals.html
index 9e8ea7d7df..f8d57a9476 100644
--- a/ivy/docs/helpers/ivy_tests.test_ivy.helpers.globals.html
+++ b/ivy/docs/helpers/ivy_tests.test_ivy.helpers.globals.html
@@ -1379,7 +1379,7 @@
 <p>Should not be used inside any of the test functions.</p>
 <dl class="py data">
 <dt class="sig sig-object py" id="ivy_tests.test_ivy.helpers.globals.CURRENT_FRONTEND_CONFIG">
-<span class="sig-prename descclassname"><span class="pre">ivy_tests.test_ivy.helpers.globals.</span></span><span class="sig-name descname"><span class="pre">CURRENT_FRONTEND_CONFIG</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">&lt;object</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7f100d211d90&gt;</span></em><a class="headerlink" href="#ivy_tests.test_ivy.helpers.globals.CURRENT_FRONTEND_CONFIG" title="Link to this definition">#</a></dt>
+<span class="sig-prename descclassname"><span class="pre">ivy_tests.test_ivy.helpers.globals.</span></span><span class="sig-name descname"><span class="pre">CURRENT_FRONTEND_CONFIG</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">&lt;object</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7f705121dda0&gt;</span></em><a class="headerlink" href="#ivy_tests.test_ivy.helpers.globals.CURRENT_FRONTEND_CONFIG" title="Link to this definition">#</a></dt>
 <dd></dd></dl>
 
 <dl class="py exception">
diff --git a/ivy/docs/stateful/ivy.stateful.layers.html b/ivy/docs/stateful/ivy.stateful.layers.html
index 19268b2553..9a4d17514a 100644
--- a/ivy/docs/stateful/ivy.stateful.layers.html
+++ b/ivy/docs/stateful/ivy.stateful.layers.html
@@ -1506,8 +1506,8 @@
 <li><p><strong>strides</strong> – The stride of the sliding window for each dimension of input.</p></li>
 <li><p><strong>padding</strong> – SAME” or “VALID” indicating the algorithm, or
 list indicating the per-dimension paddings.</p></li>
-<li><p><strong>weight_initializer</strong> (default: <code class="docutils literal notranslate"><span class="pre">&lt;ivy.stateful.initializers.GlorotUniform</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7f10198b66e0&gt;</span></code>) – Initializer for the weights. Default is GlorotUniform.</p></li>
-<li><p><strong>bias_initializer</strong> (default: <code class="docutils literal notranslate"><span class="pre">&lt;ivy.stateful.initializers.Zeros</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7f10198b6740&gt;</span></code>) – Initializer for the bias. Default is Zeros.</p></li>
+<li><p><strong>weight_initializer</strong> (default: <code class="docutils literal notranslate"><span class="pre">&lt;ivy.stateful.initializers.GlorotUniform</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7f705d8f66b0&gt;</span></code>) – Initializer for the weights. Default is GlorotUniform.</p></li>
+<li><p><strong>bias_initializer</strong> (default: <code class="docutils literal notranslate"><span class="pre">&lt;ivy.stateful.initializers.Zeros</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7f705d8f6710&gt;</span></code>) – Initializer for the bias. Default is Zeros.</p></li>
 <li><p><strong>with_bias</strong> (default: <code class="docutils literal notranslate"><span class="pre">True</span></code>) – Whether or not to include a bias term, default is <code class="docutils literal notranslate"><span class="pre">True</span></code>.</p></li>
 <li><p><strong>data_format</strong> (default: <code class="docutils literal notranslate"><span class="pre">'NWC'</span></code>) – NWC” or “NCW”. Defaults to “NWC”.</p></li>
 <li><p><strong>dilations</strong> (default: <code class="docutils literal notranslate"><span class="pre">1</span></code>) – The dilation factor for each dimension of input. (Default value = 1)</p></li>
@@ -1544,8 +1544,8 @@
 <li><p><strong>strides</strong> – The stride of the sliding window for each dimension of input.</p></li>
 <li><p><strong>padding</strong> – SAME” or “VALID” indicating the algorithm, or
 list indicating the per-dimension paddings.</p></li>
-<li><p><strong>weight_initializer</strong> (default: <code class="docutils literal notranslate"><span class="pre">&lt;ivy.stateful.initializers.GlorotUniform</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7f10198b67a0&gt;</span></code>) – Initializer for the weights. Default is GlorotUniform.</p></li>
-<li><p><strong>bias_initializer</strong> (default: <code class="docutils literal notranslate"><span class="pre">&lt;ivy.stateful.initializers.Zeros</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7f10198b6800&gt;</span></code>) – Initializer for the bias. Default is Zeros.</p></li>
+<li><p><strong>weight_initializer</strong> (default: <code class="docutils literal notranslate"><span class="pre">&lt;ivy.stateful.initializers.GlorotUniform</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7f705d8f6770&gt;</span></code>) – Initializer for the weights. Default is GlorotUniform.</p></li>
+<li><p><strong>bias_initializer</strong> (default: <code class="docutils literal notranslate"><span class="pre">&lt;ivy.stateful.initializers.Zeros</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7f705d8f67d0&gt;</span></code>) – Initializer for the bias. Default is Zeros.</p></li>
 <li><p><strong>with_bias</strong> (default: <code class="docutils literal notranslate"><span class="pre">True</span></code>) – Whether or not to include a bias term, default is <code class="docutils literal notranslate"><span class="pre">True</span></code>.</p></li>
 <li><p><strong>output_shape</strong> (default: <code class="docutils literal notranslate"><span class="pre">None</span></code>) – Shape of the output (Default value = None)</p></li>
 <li><p><strong>data_format</strong> (default: <code class="docutils literal notranslate"><span class="pre">'NWC'</span></code>) – NWC” or “NCW”. Defaults to “NWC”.</p></li>
@@ -1583,8 +1583,8 @@
 <li><p><strong>strides</strong> – The stride of the sliding window for each dimension of input.</p></li>
 <li><p><strong>padding</strong> – SAME” or “VALID” indicating the algorithm, or
 list indicating the per-dimension paddings.</p></li>
-<li><p><strong>weight_initializer</strong> (default: <code class="docutils literal notranslate"><span class="pre">&lt;ivy.stateful.initializers.GlorotUniform</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7f10198b6860&gt;</span></code>) – Initializer for the weights. Default is GlorotUniform.</p></li>
-<li><p><strong>bias_initializer</strong> (default: <code class="docutils literal notranslate"><span class="pre">&lt;ivy.stateful.initializers.Zeros</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7f10198b68c0&gt;</span></code>) – Initializer for the bias. Default is Zeros.</p></li>
+<li><p><strong>weight_initializer</strong> (default: <code class="docutils literal notranslate"><span class="pre">&lt;ivy.stateful.initializers.GlorotUniform</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7f705d8f6830&gt;</span></code>) – Initializer for the weights. Default is GlorotUniform.</p></li>
+<li><p><strong>bias_initializer</strong> (default: <code class="docutils literal notranslate"><span class="pre">&lt;ivy.stateful.initializers.Zeros</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7f705d8f6890&gt;</span></code>) – Initializer for the bias. Default is Zeros.</p></li>
 <li><p><strong>with_bias</strong> (default: <code class="docutils literal notranslate"><span class="pre">True</span></code>) – Whether or not to include a bias term, default is <code class="docutils literal notranslate"><span class="pre">True</span></code>.</p></li>
 <li><p><strong>data_format</strong> (default: <code class="docutils literal notranslate"><span class="pre">'NHWC'</span></code>) – NHWC” or “NCHW”. Defaults to “NHWC”.</p></li>
 <li><p><strong>dilations</strong> (default: <code class="docutils literal notranslate"><span class="pre">1</span></code>) – The dilation factor for each dimension of input. (Default value = 1)</p></li>
@@ -1621,8 +1621,8 @@
 <li><p><strong>strides</strong> – The stride of the sliding window for each dimension of input.</p></li>
 <li><p><strong>padding</strong> – SAME” or “VALID” indicating the algorithm, or
 list indicating the per-dimension paddings.</p></li>
-<li><p><strong>weight_initializer</strong> (default: <code class="docutils literal notranslate"><span class="pre">&lt;ivy.stateful.initializers.GlorotUniform</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7f10198b6920&gt;</span></code>) – Initializer for the weights. Default is GlorotUniform.</p></li>
-<li><p><strong>bias_initializer</strong> (default: <code class="docutils literal notranslate"><span class="pre">&lt;ivy.stateful.initializers.Zeros</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7f10198b6980&gt;</span></code>) – Initializer for the bias. Default is Zeros.</p></li>
+<li><p><strong>weight_initializer</strong> (default: <code class="docutils literal notranslate"><span class="pre">&lt;ivy.stateful.initializers.GlorotUniform</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7f705d8f68f0&gt;</span></code>) – Initializer for the weights. Default is GlorotUniform.</p></li>
+<li><p><strong>bias_initializer</strong> (default: <code class="docutils literal notranslate"><span class="pre">&lt;ivy.stateful.initializers.Zeros</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7f705d8f6950&gt;</span></code>) – Initializer for the bias. Default is Zeros.</p></li>
 <li><p><strong>with_bias</strong> (default: <code class="docutils literal notranslate"><span class="pre">True</span></code>) – Whether or not to include a bias term, default is <code class="docutils literal notranslate"><span class="pre">True</span></code>.</p></li>
 <li><p><strong>output_shape</strong> (default: <code class="docutils literal notranslate"><span class="pre">None</span></code>) – Shape of the output (Default value = None)</p></li>
 <li><p><strong>data_format</strong> (default: <code class="docutils literal notranslate"><span class="pre">'NHWC'</span></code>) – NHWC” or “NCHW”. Defaults to “NHWC”.</p></li>
@@ -1660,8 +1660,8 @@
 <li><p><strong>strides</strong> – The stride of the sliding window for each dimension of input.</p></li>
 <li><p><strong>padding</strong> – SAME” or “VALID” indicating the algorithm, or
 list indicating the per-dimension paddings.</p></li>
-<li><p><strong>weight_initializer</strong> (default: <code class="docutils literal notranslate"><span class="pre">&lt;ivy.stateful.initializers.GlorotUniform</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7f10198b6aa0&gt;</span></code>) – Initializer for the weights. Default is GlorotUniform.</p></li>
-<li><p><strong>bias_initializer</strong> (default: <code class="docutils literal notranslate"><span class="pre">&lt;ivy.stateful.initializers.Zeros</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7f10198b6b00&gt;</span></code>) – Initializer for the bias. Default is Zeros.</p></li>
+<li><p><strong>weight_initializer</strong> (default: <code class="docutils literal notranslate"><span class="pre">&lt;ivy.stateful.initializers.GlorotUniform</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7f705d8f6a70&gt;</span></code>) – Initializer for the weights. Default is GlorotUniform.</p></li>
+<li><p><strong>bias_initializer</strong> (default: <code class="docutils literal notranslate"><span class="pre">&lt;ivy.stateful.initializers.Zeros</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7f705d8f6ad0&gt;</span></code>) – Initializer for the bias. Default is Zeros.</p></li>
 <li><p><strong>with_bias</strong> (default: <code class="docutils literal notranslate"><span class="pre">True</span></code>) – Whether or not to include a bias term, default is <code class="docutils literal notranslate"><span class="pre">True</span></code>.</p></li>
 <li><p><strong>data_format</strong> (default: <code class="docutils literal notranslate"><span class="pre">'NDHWC'</span></code>) – NDHWC” or “NCDHW”. Defaults to “NDHWC”.</p></li>
 <li><p><strong>dilations</strong> (default: <code class="docutils literal notranslate"><span class="pre">1</span></code>) – The dilation factor for each dimension of input. (Default value = 1)</p></li>
@@ -1698,8 +1698,8 @@
 <li><p><strong>strides</strong> – The stride of the sliding window for each dimension of input.</p></li>
 <li><p><strong>padding</strong> – SAME” or “VALID” indicating the algorithm, or
 list indicating the per-dimension paddings.</p></li>
-<li><p><strong>weight_initializer</strong> (default: <code class="docutils literal notranslate"><span class="pre">&lt;ivy.stateful.initializers.GlorotUniform</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7f10198b6b60&gt;</span></code>) – Initializer for the weights. Default is GlorotUniform.</p></li>
-<li><p><strong>bias_initializer</strong> (default: <code class="docutils literal notranslate"><span class="pre">&lt;ivy.stateful.initializers.Zeros</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7f10198b6bc0&gt;</span></code>) – Initializer for the bias. Default is Zeros.</p></li>
+<li><p><strong>weight_initializer</strong> (default: <code class="docutils literal notranslate"><span class="pre">&lt;ivy.stateful.initializers.GlorotUniform</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7f705d8f6b30&gt;</span></code>) – Initializer for the weights. Default is GlorotUniform.</p></li>
+<li><p><strong>bias_initializer</strong> (default: <code class="docutils literal notranslate"><span class="pre">&lt;ivy.stateful.initializers.Zeros</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7f705d8f6b90&gt;</span></code>) – Initializer for the bias. Default is Zeros.</p></li>
 <li><p><strong>with_bias</strong> (default: <code class="docutils literal notranslate"><span class="pre">True</span></code>) – Whether or not to include a bias term, default is <code class="docutils literal notranslate"><span class="pre">True</span></code>.</p></li>
 <li><p><strong>output_shape</strong> (default: <code class="docutils literal notranslate"><span class="pre">None</span></code>) – Shape of the output (Default value = None)</p></li>
 <li><p><strong>data_format</strong> (default: <code class="docutils literal notranslate"><span class="pre">'NDHWC'</span></code>) – NDHWC” or “NCDHW”. Defaults to “NDHWC”.</p></li>
@@ -1762,8 +1762,8 @@
 <li><p><strong>strides</strong> – The stride of the sliding window for each dimension of input.</p></li>
 <li><p><strong>padding</strong> – SAME” or “VALID” indicating the algorithm, or
 list indicating the per-dimension paddings.</p></li>
-<li><p><strong>weight_initializer</strong> (default: <code class="docutils literal notranslate"><span class="pre">&lt;ivy.stateful.initializers.GlorotUniform</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7f10198b69e0&gt;</span></code>) – Initializer for the weights. Default is GlorotUniform.</p></li>
-<li><p><strong>bias_initializer</strong> (default: <code class="docutils literal notranslate"><span class="pre">&lt;ivy.stateful.initializers.Zeros</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7f10198b6a40&gt;</span></code>) – Initializer for the bias. Default is Zeros.</p></li>
+<li><p><strong>weight_initializer</strong> (default: <code class="docutils literal notranslate"><span class="pre">&lt;ivy.stateful.initializers.GlorotUniform</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7f705d8f69b0&gt;</span></code>) – Initializer for the weights. Default is GlorotUniform.</p></li>
+<li><p><strong>bias_initializer</strong> (default: <code class="docutils literal notranslate"><span class="pre">&lt;ivy.stateful.initializers.Zeros</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7f705d8f6a10&gt;</span></code>) – Initializer for the bias. Default is Zeros.</p></li>
 <li><p><strong>with_bias</strong> (default: <code class="docutils literal notranslate"><span class="pre">True</span></code>) – Whether or not to include a bias term, default is <code class="docutils literal notranslate"><span class="pre">True</span></code>.</p></li>
 <li><p><strong>data_format</strong> (default: <code class="docutils literal notranslate"><span class="pre">'NHWC'</span></code>) – NHWC” or “NCHW”. Defaults to “NHWC”.</p></li>
 <li><p><strong>dilations</strong> (default: <code class="docutils literal notranslate"><span class="pre">1</span></code>) – The dilation factor for each dimension of input. (Default value = 1)</p></li>
@@ -1919,7 +1919,7 @@
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>input_channels</strong> – Number of input channels for the layer</p></li>
 <li><p><strong>output_channels</strong> – Number of output channels for the layer</p></li>
-<li><p><strong>weight_initializer</strong> (default: <code class="docutils literal notranslate"><span class="pre">&lt;ivy.stateful.initializers.GlorotUniform</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7f10198b6c20&gt;</span></code>) – Initializer for the weights. Default is GlorotUniform.</p></li>
+<li><p><strong>weight_initializer</strong> (default: <code class="docutils literal notranslate"><span class="pre">&lt;ivy.stateful.initializers.GlorotUniform</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7f705d8f6bf0&gt;</span></code>) – Initializer for the weights. Default is GlorotUniform.</p></li>
 <li><p><strong>num_layers</strong> (default: <code class="docutils literal notranslate"><span class="pre">1</span></code>) – Number of lstm cells in the lstm layer, default is <code class="docutils literal notranslate"><span class="pre">1</span></code>.</p></li>
 <li><p><strong>return_sequence</strong> (default: <code class="docutils literal notranslate"><span class="pre">True</span></code>) – Whether or not to return the entire output sequence, or
 just the latest timestep.
@@ -1978,8 +1978,8 @@
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>input_channels</strong> – Number of input channels for the layer.</p></li>
 <li><p><strong>output_channels</strong> – Number of output channels for the layer.</p></li>
-<li><p><strong>weight_initializer</strong> (default: <code class="docutils literal notranslate"><span class="pre">&lt;ivy.stateful.initializers.GlorotUniform</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7f10198b6620&gt;</span></code>) – Initializer for the weights. Default is GlorotUniform.</p></li>
-<li><p><strong>bias_initializer</strong> (default: <code class="docutils literal notranslate"><span class="pre">&lt;ivy.stateful.initializers.Zeros</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7f10198b6680&gt;</span></code>) – Initializer for the bias. Default is Zeros.</p></li>
+<li><p><strong>weight_initializer</strong> (default: <code class="docutils literal notranslate"><span class="pre">&lt;ivy.stateful.initializers.GlorotUniform</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7f705d8f65f0&gt;</span></code>) – Initializer for the weights. Default is GlorotUniform.</p></li>
+<li><p><strong>bias_initializer</strong> (default: <code class="docutils literal notranslate"><span class="pre">&lt;ivy.stateful.initializers.Zeros</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7f705d8f6650&gt;</span></code>) – Initializer for the bias. Default is Zeros.</p></li>
 <li><p><strong>with_bias</strong> (default: <code class="docutils literal notranslate"><span class="pre">True</span></code>) – Whether or not to include a bias term, default is <code class="docutils literal notranslate"><span class="pre">True</span></code>.</p></li>
 <li><p><strong>device</strong> (default: <code class="docutils literal notranslate"><span class="pre">None</span></code>) – device on which to create the layer’s variables ‘cuda:0’, ‘cuda:1’, ‘cpu’
 etc. Default is cpu.</p></li>
diff --git a/ivy/searchindex.js b/ivy/searchindex.js
index 2de7738366..f1376b7053 100644
--- a/ivy/searchindex.js
+++ b/ivy/searchindex.js
@@ -1 +1 @@
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24, 26, 27, 29, 30, 42, 43, 44, 48, 52, 53, 56, 57, 59, 62, 63, 65, 69, 71, 74, 75, 76, 77, 79, 80, 82, 83, 85, 86, 87, 88, 92, 121, 124, 134, 136, 137, 138, 148, 150, 208, 229, 235, 242, 243, 260, 266, 267, 268, 287, 296, 306, 309, 310, 328, 334, 337, 340, 341, 344, 345, 346, 348, 349, 356, 360, 362, 365, 366, 368, 369, 370, 371, 374, 375, 380, 389, 391, 395, 396, 399, 400, 403, 411, 416, 418, 427, 434, 448, 452, 453, 454, 458, 464, 465, 466, 471, 473, 478, 481, 490, 491, 492, 497, 502, 512, 513, 516, 517, 518, 519, 520, 521, 523, 561, 565, 566, 568, 585, 587, 588, 601, 603, 604, 607, 609, 610, 611, 612, 617, 618, 619, 620, 622, 623, 624, 625, 627, 630, 632, 633, 635, 638, 639, 640, 641, 642, 643, 646, 662, 665, 666, 670, 672, 681, 682, 690, 691, 692, 695, 697, 701, 725, 732, 735, 737, 738, 739, 740, 745, 747, 764, 766, 783, 786, 789, 794, 797, 800, 805, 806, 807, 809, 810, 811, 812, 813, 815, 816, 817, 820, 821, 822, 823, 824, 825, 826, 827, 828, 830, 832, 833, 834, 837, 838, 840, 841, 842, 843, 846, 847, 850, 856, 857, 859, 862], "cost": [3, 54, 77, 603, 604, 607, 609, 610, 611, 623, 628, 703, 704, 705, 794, 815, 833, 854], "arg": [3, 5, 6, 7, 11, 13, 21, 22, 24, 26, 27, 31, 32, 33, 44, 47, 69, 91, 101, 117, 198, 208, 589, 616, 617, 619, 622, 759, 761, 776, 777, 780, 781, 782, 786, 789, 793, 798, 800, 810, 815, 816, 819, 825, 826, 827, 833, 835, 839, 849, 850, 851], "asarrai": [3, 4, 5, 6, 7, 41, 48, 52, 53, 64, 71, 75, 76, 87, 122, 378, 503, 504, 534, 545, 549, 550, 580, 581, 617, 622, 624, 633, 634, 638, 738, 742, 819, 824, 827, 828], "cuda": [3, 4, 5, 6, 7, 8, 9, 17, 26, 41, 42, 45, 48, 52, 61, 71, 75, 84, 132, 133, 136, 188, 189, 190, 204, 206, 375, 497, 498, 500, 501, 617, 619, 625, 631, 676, 726, 727, 728, 729, 779, 780, 781, 782, 783, 784, 785, 800, 835, 841, 843, 861], "7": [3, 5, 6, 7, 8, 9, 11, 13, 18, 19, 21, 22, 23, 24, 38, 40, 41, 42, 44, 45, 46, 48, 49, 51, 52, 53, 54, 56, 57, 58, 59, 61, 62, 63, 64, 65, 72, 73, 74, 75, 76, 77, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 97, 98, 107, 108, 109, 110, 121, 122, 123, 132, 135, 136, 154, 160, 163, 193, 215, 218, 221, 225, 226, 228, 229, 230, 231, 233, 235, 236, 237, 238, 239, 241, 242, 245, 246, 247, 252, 253, 254, 255, 256, 257, 258, 259, 260, 263, 265, 266, 267, 268, 270, 271, 272, 274, 275, 278, 279, 280, 282, 285, 286, 288, 289, 291, 292, 293, 295, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 309, 312, 313, 324, 328, 332, 334, 335, 342, 343, 344, 346, 348, 349, 356, 360, 362, 365, 366, 368, 369, 370, 371, 376, 380, 386, 387, 388, 389, 394, 395, 399, 400, 404, 409, 410, 411, 412, 414, 417, 420, 431, 443, 444, 445, 446, 448, 449, 452, 453, 454, 458, 460, 464, 469, 470, 473, 474, 479, 480, 482, 483, 485, 488, 489, 499, 501, 502, 509, 512, 513, 515, 516, 521, 527, 529, 530, 534, 535, 538, 549, 550, 551, 558, 565, 566, 580, 583, 603, 604, 606, 607, 608, 609, 610, 611, 614, 617, 618, 619, 620, 622, 623, 624, 625, 626, 627, 629, 630, 631, 632, 633, 634, 635, 638, 639, 641, 643, 645, 646, 647, 648, 653, 655, 656, 657, 658, 660, 661, 662, 665, 667, 670, 672, 673, 675, 676, 677, 679, 680, 681, 684, 685, 686, 687, 690, 691, 696, 698, 699, 701, 706, 707, 714, 718, 725, 726, 727, 728, 729, 731, 736, 737, 739, 741, 742, 744, 745, 746, 747, 749, 751, 753, 754, 764, 806, 807, 811, 813, 814, 817, 823, 826, 830], "output": [3, 4, 5, 7, 17, 23, 24, 26, 27, 39, 40, 41, 43, 46, 48, 49, 50, 51, 52, 53, 54, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 68, 70, 71, 72, 73, 74, 75, 76, 77, 79, 80, 81, 82, 83, 84, 85, 87, 88, 89, 97, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 121, 122, 123, 124, 125, 126, 127, 128, 130, 131, 132, 133, 134, 136, 137, 138, 139, 140, 141, 143, 144, 147, 149, 174, 208, 209, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 311, 312, 316, 323, 324, 325, 326, 327, 328, 329, 330, 331, 332, 333, 334, 335, 336, 337, 338, 339, 340, 341, 343, 344, 345, 346, 347, 348, 349, 350, 351, 352, 353, 354, 355, 357, 358, 359, 360, 362, 365, 367, 368, 369, 370, 371, 374, 375, 376, 378, 380, 381, 382, 383, 384, 386, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 399, 400, 401, 403, 404, 405, 406, 409, 411, 412, 413, 415, 416, 418, 419, 420, 422, 424, 427, 428, 431, 432, 433, 434, 436, 437, 440, 442, 443, 444, 445, 446, 447, 448, 449, 450, 457, 458, 459, 462, 464, 465, 466, 467, 468, 471, 472, 473, 475, 476, 477, 478, 479, 480, 481, 482, 483, 484, 486, 487, 490, 491, 492, 493, 494, 495, 496, 497, 498, 499, 500, 501, 502, 504, 509, 511, 512, 513, 514, 515, 516, 517, 518, 519, 520, 521, 522, 528, 529, 530, 534, 535, 536, 538, 542, 551, 558, 565, 566, 567, 590, 602, 603, 604, 605, 606, 607, 608, 609, 610, 611, 612, 613, 614, 617, 618, 619, 620, 622, 623, 624, 625, 626, 627, 629, 630, 631, 632, 634, 635, 636, 637, 638, 639, 640, 641, 642, 643, 644, 645, 646, 647, 648, 649, 650, 653, 654, 655, 656, 657, 658, 660, 661, 662, 663, 664, 665, 666, 668, 669, 670, 671, 672, 673, 674, 676, 677, 679, 680, 681, 682, 683, 684, 685, 686, 687, 688, 689, 690, 691, 692, 693, 694, 695, 697, 698, 699, 700, 702, 719, 725, 726, 727, 728, 729, 731, 732, 733, 734, 735, 736, 741, 742, 743, 744, 745, 746, 747, 748, 749, 750, 751, 752, 753, 754, 755, 756, 759, 764, 779, 780, 793, 794, 800, 802, 806, 807, 808, 809, 810, 812, 813, 815, 816, 817, 818, 821, 822, 823, 824, 825, 826, 827, 828, 830, 831, 832, 835, 837, 839, 840, 841, 843, 849, 850, 857], "softmax": [3, 7, 11, 24, 26, 27, 42, 46, 56, 67, 68, 79, 370, 444, 614, 624, 650, 653, 776, 800], "pass": [3, 5, 6, 7, 8, 9, 11, 13, 17, 24, 26, 27, 33, 39, 40, 42, 44, 45, 51, 52, 67, 69, 74, 75, 90, 98, 117, 118, 120, 152, 174, 189, 208, 223, 269, 368, 370, 371, 374, 375, 380, 413, 444, 464, 490, 492, 497, 517, 518, 551, 616, 618, 619, 620, 622, 628, 703, 704, 759, 761, 765, 772, 777, 781, 782, 784, 785, 789, 793, 798, 800, 803, 805, 807, 809, 810, 811, 813, 815, 816, 817, 818, 819, 820, 821, 822, 823, 824, 825, 826, 827, 828, 830, 833, 841, 849, 850, 851, 854], "argsort": [3, 7, 64, 87, 634, 743, 827], "descend": [3, 7, 64, 87, 625, 634, 675, 676, 741, 744], "top": [3, 7, 10, 15, 24, 26, 27, 40, 41, 52, 59, 75, 313, 362, 370, 371, 442, 484, 534, 622, 688, 800, 806, 807, 815, 820, 827, 829, 830, 833, 838, 839, 856, 860], "logit": [3, 4, 5, 7, 40, 41, 42, 43, 52, 58, 75, 81, 360, 375, 497, 500, 626, 684, 686, 776, 800, 849], "gather": [3, 7, 40, 52, 53, 75, 76, 324, 325, 326, 362, 542, 544, 622, 863], "print": [3, 4, 6, 7, 9, 11, 13, 17, 18, 20, 24, 26, 27, 28, 38, 39, 40, 41, 42, 43, 45, 46, 48, 49, 50, 51, 52, 53, 54, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 71, 72, 73, 74, 75, 76, 77, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 97, 98, 105, 107, 108, 109, 110, 111, 112, 113, 114, 117, 118, 120, 121, 124, 127, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 142, 143, 144, 147, 148, 149, 150, 152, 158, 159, 160, 161, 162, 165, 167, 168, 170, 175, 187, 188, 192, 194, 195, 196, 197, 199, 200, 201, 202, 203, 206, 207, 209, 210, 211, 214, 215, 216, 217, 218, 220, 221, 222, 223, 224, 225, 226, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 240, 241, 242, 246, 247, 249, 250, 251, 252, 254, 255, 256, 257, 258, 259, 260, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 288, 289, 290, 291, 292, 293, 294, 295, 297, 299, 300, 301, 303, 304, 305, 307, 314, 315, 322, 324, 328, 329, 330, 332, 346, 347, 352, 356, 360, 362, 365, 368, 369, 370, 371, 374, 380, 386, 387, 388, 389, 391, 392, 394, 396, 399, 401, 404, 405, 406, 409, 411, 412, 417, 420, 422, 424, 425, 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753, 754, 755, 756, 789, 793, 794, 798, 800, 806, 807, 813, 815, 817, 828, 830, 832, 835, 837, 838, 839, 849, 851], "indic": [3, 7, 48, 52, 53, 56, 57, 59, 60, 62, 63, 64, 69, 71, 72, 75, 76, 79, 80, 82, 83, 85, 86, 87, 92, 95, 122, 123, 136, 140, 142, 163, 167, 168, 279, 322, 323, 324, 342, 362, 365, 368, 369, 370, 371, 376, 378, 386, 387, 388, 390, 394, 395, 396, 400, 401, 404, 405, 406, 407, 411, 412, 422, 441, 444, 452, 453, 454, 457, 460, 462, 464, 465, 466, 469, 473, 479, 480, 482, 483, 484, 487, 488, 502, 503, 504, 526, 541, 542, 544, 565, 566, 570, 602, 605, 606, 617, 620, 622, 623, 624, 625, 627, 629, 630, 631, 632, 633, 634, 638, 640, 641, 642, 643, 646, 650, 668, 682, 690, 691, 692, 694, 695, 696, 697, 699, 701, 706, 709, 711, 713, 714, 715, 717, 721, 722, 723, 724, 725, 726, 732, 733, 734, 735, 737, 739, 741, 743, 744, 761, 762, 764, 766, 780, 786, 793, 794, 796, 806, 814, 822, 825, 827, 840, 849], "to_list": [3, 7, 53, 76, 622], "arrai": [3, 4, 7, 8, 9, 17, 18, 19, 21, 22, 23, 24, 26, 27, 28, 29, 31, 32, 33, 38, 39, 40, 41, 42, 44, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 92, 93, 95, 98, 101, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 117, 118, 120, 121, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 147, 148, 149, 150, 153, 154, 155, 156, 157, 158, 160, 163, 164, 166, 167, 168, 170, 172, 173, 174, 175, 181, 191, 192, 196, 201, 203, 205, 208, 209, 213, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 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76, 77, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 92, 93, 95, 96, 97, 101, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 121, 122, 123, 124, 125, 126, 127, 128, 130, 131, 132, 133, 134, 136, 137, 138, 139, 140, 141, 142, 143, 144, 147, 148, 149, 203, 209, 215, 216, 217, 218, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 240, 241, 242, 246, 247, 248, 249, 250, 251, 252, 254, 255, 256, 257, 258, 259, 260, 262, 263, 264, 265, 266, 267, 268, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 288, 289, 290, 291, 292, 293, 295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 310, 311, 312, 313, 315, 317, 318, 319, 320, 321, 322, 323, 329, 330, 331, 332, 333, 335, 337, 339, 341, 343, 345, 346, 347, 348, 352, 353, 355, 360, 362, 365, 368, 369, 370, 371, 374, 375, 376, 378, 380, 382, 383, 384, 386, 387, 388, 390, 391, 392, 393, 394, 395, 396, 400, 401, 403, 404, 405, 406, 409, 411, 412, 413, 416, 417, 418, 419, 421, 422, 423, 426, 427, 428, 429, 431, 432, 433, 434, 435, 436, 440, 441, 442, 443, 444, 445, 446, 447, 448, 449, 450, 454, 455, 457, 459, 462, 467, 472, 473, 474, 475, 476, 477, 478, 480, 481, 482, 483, 484, 486, 490, 491, 492, 493, 494, 495, 496, 497, 498, 499, 500, 501, 502, 504, 509, 510, 511, 512, 513, 514, 529, 530, 534, 535, 536, 538, 541, 542, 545, 551, 558, 565, 566, 576, 584, 586, 598, 602, 603, 604, 607, 609, 610, 611, 612, 614, 617, 618, 619, 620, 622, 623, 624, 625, 626, 627, 630, 631, 632, 634, 635, 636, 637, 638, 639, 640, 641, 642, 643, 644, 645, 646, 647, 648, 649, 650, 653, 654, 655, 656, 657, 658, 659, 660, 661, 662, 663, 664, 665, 666, 667, 668, 669, 670, 671, 672, 673, 674, 675, 676, 677, 679, 681, 682, 683, 684, 685, 686, 687, 688, 689, 690, 691, 692, 693, 694, 695, 696, 697, 698, 699, 700, 702, 725, 726, 727, 728, 729, 731, 732, 733, 734, 735, 736, 741, 742, 744, 745, 746, 747, 749, 751, 752, 754, 755, 756, 761, 764, 766, 779, 780, 783, 793, 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761, 764, 766, 767, 779, 780, 781, 782, 783, 785, 800, 803, 809, 811, 815, 816, 817, 819, 820, 823, 824, 826, 827, 828, 830, 831, 835, 837, 850], "int32": [3, 38, 40, 49, 52, 53, 61, 62, 65, 72, 75, 76, 84, 85, 127, 132, 138, 144, 147, 150, 152, 154, 156, 158, 161, 163, 164, 168, 171, 175, 179, 183, 185, 203, 230, 376, 380, 502, 512, 513, 514, 542, 551, 587, 617, 618, 619, 620, 622, 631, 632, 635, 727, 728, 729, 733, 745, 746, 751, 753, 764, 765, 815, 827, 830, 835], "6477362": 3, "29496726": 3, "04526032": 3, "float32": [3, 5, 7, 9, 11, 13, 18, 19, 38, 40, 41, 42, 48, 49, 52, 53, 56, 71, 72, 75, 76, 79, 88, 133, 136, 138, 144, 145, 146, 150, 154, 155, 158, 159, 160, 161, 164, 167, 168, 170, 175, 178, 184, 248, 275, 327, 339, 362, 365, 368, 369, 370, 380, 389, 399, 412, 436, 442, 447, 514, 551, 587, 617, 618, 620, 622, 624, 625, 628, 640, 642, 643, 646, 673, 675, 676, 682, 704, 705, 761, 764, 765, 800, 815, 817, 828, 830, 831, 850, 851], "As": [3, 5, 6, 8, 9, 11, 13, 19, 23, 24, 26, 27, 29, 32, 38, 39, 63, 67, 90, 633, 737, 738, 739, 740, 800, 803, 805, 806, 807, 810, 812, 813, 814, 815, 816, 819, 820, 821, 822, 823, 826, 827, 828, 829, 830, 833, 837, 838, 839, 841, 845, 849, 850, 851, 856, 861], "expect": [3, 5, 6, 8, 19, 23, 26, 27, 29, 42, 43, 45, 52, 57, 58, 75, 81, 174, 242, 286, 368, 370, 390, 412, 447, 525, 618, 620, 622, 626, 670, 684, 779, 780, 800, 806, 807, 809, 815, 816, 819, 821, 824, 826, 828, 830, 833, 841, 842, 847, 849, 850, 851], "ident": [3, 9, 24, 41, 43, 57, 69, 127, 196, 544, 570, 617, 619, 622, 625, 629, 662, 667, 719, 780, 813, 823, 824, 827, 828, 831, 833, 837, 838, 841, 843, 845, 847], "had": [3, 813, 814, 826, 831, 835, 856, 857], "anoth": [3, 17, 19, 20, 23, 24, 26, 27, 29, 30, 42, 43, 128, 148, 150, 617, 618, 800, 805, 806, 807, 811, 813, 815, 816, 819, 821, 823, 826, 827, 830, 835, 837, 840, 843, 846, 848, 849, 850, 856, 862], "postprocess": 3, "routin": [3, 814, 826, 827, 833, 841, 856], "feed": [3, 208, 619, 849, 856, 857], "other": 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785, 800, 801, 803, 804, 805, 806, 808, 809, 810, 811, 812, 813, 814, 815, 816, 817, 818, 819, 821, 823, 825, 827, 828, 829, 830, 831, 833, 834, 835, 836, 837, 838, 839, 840, 842, 845, 846, 847, 849, 850, 856, 863], "quickest": 3, "particular": [3, 26, 27, 263, 620, 765, 806, 807, 809, 811, 814, 815, 817, 824, 826, 827, 830, 831, 852, 856, 862], "hardwar": [3, 40, 97, 101, 800, 806, 833, 846, 852, 854, 855, 856, 857, 858, 859, 860, 861, 862], "again": [3, 5, 20, 21, 29, 30, 31, 32, 625, 673, 807, 810, 811, 812, 813, 817, 819, 821, 826, 827, 830, 831, 833, 838, 840, 841, 846, 847, 861, 862], "speed": [3, 6, 8, 9, 26, 27, 40, 45, 53, 76, 558, 622, 830, 845, 859], "up": [3, 5, 6, 8, 9, 26, 52, 53, 75, 76, 368, 371, 390, 403, 458, 466, 546, 558, 622, 624, 647, 800, 801, 803, 805, 807, 809, 810, 811, 813, 814, 815, 816, 817, 818, 819, 821, 822, 823, 824, 825, 826, 827, 828, 830, 831, 833, 835, 836, 837, 838, 839, 840, 841, 845, 846, 847, 849, 857, 862, 863], "12": [3, 5, 6, 7, 9, 17, 19, 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807, 809, 811, 814, 816, 822, 827, 830, 833, 840, 841, 859], "trace": [3, 4, 5, 6, 7, 8, 15, 16, 20, 23, 26, 29, 31, 32, 44, 53, 57, 69, 76, 80, 553, 554, 557, 568, 577, 591, 599, 622, 625, 761, 772, 782, 784, 800, 809, 813, 815, 827, 832, 833, 835, 840, 841, 848, 849, 850, 857, 862], "befor": [3, 4, 5, 18, 19, 20, 21, 22, 28, 29, 30, 31, 32, 33, 40, 52, 56, 57, 59, 63, 65, 69, 75, 79, 80, 205, 208, 213, 368, 371, 380, 395, 400, 410, 414, 458, 465, 466, 467, 474, 512, 513, 619, 624, 625, 627, 628, 629, 633, 635, 637, 638, 639, 640, 642, 644, 646, 649, 650, 653, 665, 682, 688, 703, 704, 718, 737, 738, 739, 740, 745, 746, 751, 753, 780, 789, 793, 805, 806, 807, 809, 810, 812, 815, 816, 818, 819, 820, 821, 822, 824, 825, 826, 827, 828, 830, 835, 838, 841, 849, 850, 856], "13": [3, 5, 6, 7, 17, 21, 22, 23, 24, 38, 40, 42, 46, 51, 52, 56, 57, 61, 65, 74, 75, 76, 77, 79, 82, 84, 88, 97, 113, 163, 193, 218, 233, 242, 253, 273, 282, 342, 349, 356, 365, 368, 371, 388, 389, 399, 404, 410, 414, 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856, 857, 862], "appropri": [6, 17, 21, 22, 24, 26, 27, 53, 62, 67, 85, 90, 218, 235, 242, 268, 328, 344, 365, 620, 632, 732, 800, 805, 806, 807, 819, 824, 830], "get_scal": 6, "cfg": [6, 821], "kei": [6, 19, 20, 26, 27, 42, 44, 47, 52, 56, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 79, 80, 81, 82, 84, 85, 86, 87, 88, 89, 98, 105, 106, 107, 108, 109, 110, 111, 112, 113, 129, 131, 136, 138, 144, 148, 150, 163, 167, 168, 175, 209, 215, 216, 217, 218, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 240, 241, 242, 246, 247, 249, 250, 251, 252, 254, 255, 256, 257, 258, 259, 260, 262, 263, 264, 265, 266, 267, 268, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 288, 289, 290, 291, 292, 293, 297, 298, 299, 300, 301, 303, 304, 305, 307, 328, 329, 330, 332, 334, 336, 343, 344, 350, 352, 354, 355, 356, 378, 391, 392, 393, 411, 442, 443, 444, 445, 446, 447, 448, 449, 458, 459, 480, 482, 484, 490, 492, 493, 494, 496, 498, 504, 511, 512, 513, 514, 523, 524, 526, 527, 529, 530, 531, 534, 535, 536, 537, 538, 541, 542, 545, 547, 549, 550, 551, 553, 554, 557, 565, 566, 580, 581, 583, 585, 587, 588, 601, 607, 612, 622, 624, 628, 629, 638, 639, 640, 641, 647, 648, 650, 653, 654, 655, 660, 661, 662, 663, 665, 666, 668, 670, 672, 673, 679, 684, 685, 686, 687, 691, 694, 695, 696, 697, 698, 701, 702, 703, 704, 709, 715, 719, 726, 727, 728, 729, 731, 734, 737, 738, 739, 740, 741, 745, 746, 749, 751, 752, 754, 755, 756, 764, 765, 771, 777, 780, 784, 800, 812, 813, 814, 823, 826, 827, 828, 830, 838, 850, 856, 859, 863], "input_shap": [6, 13, 24, 26, 27, 800], "block": [6, 26, 27, 30, 31, 32, 33, 369, 428, 800, 807, 813, 815, 819, 823, 830, 834, 836, 840, 841, 843, 850, 861, 863], "url": [6, 8, 23, 26, 27, 40, 43, 800, 850], "cocodataset": [6, 8, 23, 26, 27, 43, 800, 850], "org": [6, 7, 8, 23, 26, 27, 40, 42, 43, 45, 51, 52, 74, 75, 77, 142, 150, 238, 248, 249, 264, 322, 329, 330, 362, 365, 368, 371, 380, 411, 482, 511, 603, 604, 617, 618, 620, 623, 625, 627, 635, 673, 674, 702, 752, 800, 818, 850], "val2017": [6, 8, 26, 43], "000000039769": [6, 8, 26, 43], "stream": [6, 8, 23, 26, 27, 40, 43, 50, 73, 209, 619, 800, 850, 860], "_config": 6, "train_pipelin": 6, "tensor_imag": 6, "And": [6, 8, 9, 11, 13, 18, 21, 26, 27, 28, 41, 72, 358, 359, 367, 800, 809, 812, 821, 823, 830, 849], "final": [6, 8, 11, 13, 15, 23, 26, 27, 32, 38, 39, 48, 52, 53, 75, 76, 92, 120, 132, 133, 316, 362, 368, 412, 538, 616, 617, 622, 624, 649, 650, 794, 805, 807, 809, 810, 812, 814, 815, 817, 818, 823, 825, 826, 827, 829, 833, 834, 838, 849, 850, 852, 862], "transpiled_graph": [6, 8, 26], "what": [6, 8, 15, 20, 26, 27, 30, 31, 34, 39, 40, 368, 401, 412, 766, 794, 800, 805, 807, 808, 813, 814, 817, 818, 821, 822, 824, 825, 826, 827, 828, 830, 834, 835, 837, 838, 839, 840, 841, 846, 847, 852, 857, 858, 861], "improv": [6, 8, 9, 26, 29, 807, 815, 822, 823, 833, 835, 843, 847, 849, 854, 856, 858, 859], "For": [6, 7, 8, 9, 17, 19, 26, 27, 29, 32, 34, 48, 52, 57, 63, 75, 80, 121, 134, 215, 216, 217, 218, 220, 221, 222, 223, 224, 231, 232, 233, 235, 236, 238, 240, 241, 242, 249, 250, 251, 256, 257, 258, 259, 260, 263, 268, 270, 271, 273, 277, 278, 279, 280, 281, 282, 285, 286, 288, 324, 325, 326, 329, 330, 332, 352, 362, 365, 369, 371, 432, 434, 454, 474, 477, 617, 620, 625, 627, 633, 635, 673, 675, 679, 687, 698, 737, 738, 739, 740, 748, 750, 751, 753, 765, 777, 805, 806, 807, 808, 810, 811, 813, 814, 815, 816, 817, 818, 819, 820, 822, 823, 824, 826, 827, 828, 829, 830, 831, 833, 835, 837, 838, 839, 840, 841, 842, 845, 846, 847, 849, 853, 854, 857, 862, 863], "compil": [6, 7, 8, 9, 21, 22, 24, 26, 27, 30, 43, 45, 286, 620, 772, 800, 806, 827, 831, 835, 841, 843, 850, 852, 855, 856, 857, 860, 863], "origin": [6, 8, 9, 24, 26, 27, 28, 29, 30, 32, 39, 40, 41, 45, 52, 57, 59, 65, 69, 75, 80, 82, 88, 92, 95, 97, 98, 223, 248, 275, 313, 362, 368, 369, 371, 380, 411, 435, 467, 473, 475, 478, 512, 513, 517, 518, 519, 520, 521, 620, 625, 627, 635, 666, 694, 695, 746, 761, 766, 789, 790, 800, 802, 805, 806, 807, 811, 812, 814, 815, 820, 824, 826, 827, 828, 835, 847, 849, 850, 856, 857], "_f": [6, 8, 26], "comp_model": [6, 8, 26], "equival": [6, 8, 26, 57, 80, 92, 93, 121, 229, 242, 263, 264, 277, 278, 371, 458, 482, 487, 617, 620, 625, 668, 671, 674, 682, 789, 826, 827, 833, 838, 840, 842, 850], "just": [6, 8, 9, 11, 13, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 26, 27, 38, 40, 42, 52, 57, 65, 80, 92, 95, 142, 322, 362, 369, 434, 617, 625, 635, 668, 747, 772, 780, 800, 803, 806, 807, 809, 811, 814, 815, 816, 817, 818, 820, 823, 824, 826, 827, 828, 830, 835, 837, 838, 841, 846, 847, 850, 856, 857, 862], "np_imag": [6, 23, 26, 27], "jax_imag": 6, "hk": [6, 8, 26, 40, 44, 800, 840, 850], "rng_kei": [6, 8, 26, 800, 850], "random": [6, 8, 11, 13, 18, 19, 20, 21, 22, 24, 26, 27, 28, 29, 31, 32, 33, 40, 42, 43, 52, 56, 69, 75, 79, 317, 318, 319, 320, 321, 362, 369, 370, 426, 435, 441, 447, 497, 498, 499, 500, 501, 624, 647, 726, 727, 728, 729, 730, 731, 764, 766, 779, 793, 794, 800, 805, 816, 828, 830, 831, 840, 850, 851, 856], "prngkei": [6, 8, 19, 20, 26, 27, 40, 800, 840, 850], "42": [6, 8, 9, 19, 20, 24, 26, 27, 38, 40, 41, 46, 61, 68, 77, 84, 113, 229, 368, 389, 399, 603, 607, 614, 620, 623, 625, 630, 631, 635, 666, 670, 725, 726, 727, 728, 729, 730, 745, 747, 800, 835, 840, 850], "jax_mlp_forward": 6, "param": [6, 8, 9, 26, 40, 41, 42, 44, 69, 75, 76, 98, 524, 541, 542, 622, 786, 800, 840, 850], "init": [6, 8, 26, 40, 42, 52, 75, 369, 426, 435, 441, 800, 809, 840, 850], "rng": [6, 8, 26, 40, 800, 840, 850], "appli": [6, 8, 21, 22, 23, 24, 26, 27, 40, 46, 47, 48, 49, 50, 51, 52, 53, 54, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 92, 93, 97, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 123, 124, 126, 128, 129, 131, 133, 134, 135, 136, 138, 140, 141, 144, 148, 149, 150, 163, 167, 168, 175, 192, 209, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 311, 312, 313, 316, 323, 325, 326, 327, 328, 329, 330, 331, 332, 333, 334, 335, 336, 337, 338, 339, 340, 341, 343, 344, 345, 346, 347, 348, 349, 350, 351, 352, 353, 354, 355, 356, 360, 365, 366, 368, 369, 370, 371, 374, 380, 382, 383, 384, 386, 387, 388, 389, 391, 392, 393, 395, 399, 400, 401, 403, 404, 405, 406, 410, 411, 414, 415, 416, 417, 418, 419, 421, 422, 423, 424, 425, 426, 428, 430, 431, 432, 433, 434, 435, 437, 438, 439, 440, 441, 442, 443, 444, 445, 446, 447, 448, 449, 450, 451, 452, 453, 454, 455, 458, 459, 460, 461, 463, 464, 465, 466, 467, 468, 469, 470, 471, 472, 473, 474, 475, 476, 477, 478, 479, 480, 481, 482, 483, 484, 485, 486, 487, 488, 489, 490, 491, 492, 493, 494, 495, 496, 498, 499, 500, 501, 502, 503, 504, 509, 510, 511, 512, 513, 514, 515, 516, 517, 518, 519, 520, 521, 522, 523, 526, 527, 529, 530, 533, 534, 535, 536, 537, 538, 541, 542, 545, 547, 549, 550, 551, 553, 554, 555, 557, 558, 560, 565, 566, 580, 581, 582, 583, 585, 587, 588, 601, 603, 604, 607, 609, 610, 611, 612, 614, 618, 620, 622, 623, 624, 625, 626, 627, 628, 629, 630, 633, 635, 637, 638, 639, 640, 641, 642, 643, 644, 646, 647, 648, 649, 650, 653, 654, 655, 657, 658, 659, 660, 661, 662, 663, 665, 666, 668, 670, 671, 672, 673, 675, 679, 682, 684, 685, 686, 687, 688, 689, 690, 691, 692, 693, 694, 695, 696, 697, 698, 699, 700, 701, 702, 703, 704, 712, 715, 718, 719, 725, 726, 727, 728, 729, 731, 732, 733, 734, 735, 736, 737, 738, 739, 740, 741, 742, 743, 744, 745, 746, 747, 748, 749, 750, 751, 752, 754, 755, 756, 766, 767, 776, 780, 783, 800, 805, 806, 807, 810, 813, 815, 816, 817, 818, 819, 821, 822, 823, 824, 826, 827, 830, 831, 833, 837, 838, 839, 840, 841, 849, 850, 857], "both": [6, 7, 8, 9, 11, 13, 21, 23, 26, 27, 31, 32, 39, 41, 48, 51, 52, 53, 56, 57, 71, 74, 75, 76, 79, 80, 121, 122, 123, 125, 126, 127, 128, 130, 131, 132, 133, 134, 136, 137, 138, 139, 140, 141, 143, 144, 150, 166, 170, 173, 215, 216, 217, 218, 220, 221, 222, 223, 224, 225, 226, 227, 229, 230, 231, 232, 233, 235, 236, 238, 240, 241, 242, 246, 247, 248, 249, 250, 251, 255, 257, 258, 259, 260, 262, 263, 264, 265, 268, 270, 271, 272, 273, 275, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 288, 307, 323, 329, 330, 332, 333, 335, 339, 344, 362, 365, 368, 369, 371, 375, 380, 386, 387, 388, 389, 391, 392, 393, 399, 404, 405, 406, 411, 413, 422, 468, 474, 482, 485, 497, 511, 514, 541, 545, 547, 549, 558, 588, 612, 613, 617, 618, 620, 622, 623, 624, 625, 627, 630, 632, 633, 634, 635, 636, 638, 639, 640, 641, 642, 646, 647, 648, 649, 650, 653, 654, 655, 656, 657, 658, 660, 661, 662, 663, 665, 666, 667, 668, 669, 670, 671, 672, 673, 674, 675, 676, 677, 679, 681, 682, 683, 687, 688, 689, 690, 691, 692, 693, 694, 695, 696, 697, 698, 699, 700, 701, 702, 725, 732, 733, 735, 736, 737, 738, 739, 740, 741, 744, 748, 749, 750, 751, 752, 753, 754, 755, 756, 759, 780, 800, 803, 805, 807, 811, 813, 814, 815, 816, 817, 818, 819, 820, 822, 823, 826, 827, 830, 833, 835, 837, 838, 839, 840, 841, 849, 850, 856, 859, 861, 862, 863], "optim": [6, 8, 9, 17, 21, 22, 24, 26, 27, 40, 42, 43, 45, 52, 54, 75, 77, 306, 362, 370, 446, 447, 525, 611, 622, 623, 628, 703, 704, 705, 779, 794, 800, 815, 826, 833, 836, 838, 840, 847, 850, 854, 855, 856, 857, 858, 859, 860, 863], "each": [6, 8, 9, 19, 20, 21, 26, 27, 29, 30, 31, 33, 40, 46, 48, 49, 51, 52, 53, 54, 56, 57, 59, 62, 63, 65, 69, 72, 74, 75, 76, 77, 79, 80, 82, 85, 86, 88, 92, 93, 95, 97, 98, 106, 107, 109, 110, 111, 113, 117, 134, 148, 160, 163, 208, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 238, 240, 241, 242, 246, 247, 248, 249, 250, 251, 252, 254, 255, 256, 257, 258, 259, 260, 262, 263, 264, 265, 268, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 288, 290, 292, 297, 299, 300, 301, 303, 304, 305, 310, 321, 324, 325, 326, 332, 339, 343, 347, 352, 355, 360, 362, 365, 368, 369, 371, 374, 375, 378, 380, 386, 387, 388, 391, 392, 393, 396, 404, 405, 406, 407, 410, 412, 413, 414, 421, 422, 427, 434, 435, 439, 441, 452, 453, 454, 458, 459, 460, 465, 466, 468, 469, 471, 473, 474, 477, 479, 487, 488, 495, 497, 504, 509, 510, 511, 512, 513, 514, 523, 526, 534, 541, 542, 558, 582, 602, 604, 605, 607, 609, 610, 611, 614, 616, 617, 618, 619, 620, 622, 623, 624, 625, 627, 629, 631, 632, 633, 635, 637, 638, 639, 640, 641, 642, 643, 644, 645, 646, 647, 650, 654, 655, 656, 659, 660, 661, 665, 667, 668, 669, 671, 673, 674, 675, 680, 689, 693, 695, 696, 698, 700, 702, 712, 719, 726, 735, 737, 738, 740, 746, 747, 754, 764, 766, 780, 783, 784, 785, 794, 803, 805, 806, 807, 808, 809, 810, 811, 812, 813, 814, 815, 816, 817, 818, 819, 820, 821, 822, 823, 824, 826, 827, 828, 830, 831, 832, 833, 835, 837, 838, 840, 841, 845, 846, 847, 849, 850, 852, 853, 857, 859, 862], "timeit": [6, 8, 9, 19, 26, 27, 43, 45], "06": [6, 9, 21, 42, 49, 61, 74, 77, 96, 105, 160, 217, 233, 368, 389, 399, 609, 614, 618, 623, 729, 759, 761, 830, 838], "m": [6, 7, 8, 9, 26, 39, 41, 43, 45, 48, 52, 57, 61, 74, 75, 80, 84, 97, 134, 140, 141, 142, 262, 322, 323, 362, 368, 369, 370, 371, 375, 390, 421, 426, 427, 429, 443, 454, 465, 466, 480, 497, 498, 499, 500, 501, 617, 625, 629, 631, 654, 656, 658, 659, 660, 661, 662, 663, 664, 665, 666, 667, 668, 669, 670, 671, 672, 673, 674, 675, 676, 679, 714, 727, 728, 729, 800, 806, 807, 808, 814, 835], "per": [6, 8, 9, 19, 40, 42, 52, 56, 75, 79, 313, 362, 368, 369, 371, 386, 387, 388, 404, 405, 406, 407, 434, 481, 624, 638, 640, 641, 642, 643, 646, 650, 780, 807, 814, 824, 827, 838], "loop": [6, 8, 9, 19, 34, 67, 75, 90, 117, 120, 368, 413, 616, 628, 703, 704, 705, 800, 811, 841, 849], "100": [6, 7, 8, 9, 38, 40, 42, 48, 51, 52, 71, 74, 75, 76, 79, 96, 133, 142, 229, 269, 282, 322, 344, 353, 362, 365, 368, 369, 371, 391, 392, 435, 441, 479, 542, 550, 566, 617, 620, 622, 625, 629, 663, 712, 800, 814, 815, 830, 838, 839, 840, 841, 846, 847, 849], "block_until_readi": 6, "08": [6, 52, 65, 75, 84, 221, 328, 344, 365, 368, 370, 389, 399, 447, 620, 728, 729, 754, 759, 764, 821], "\u00b5": [6, 8, 9, 19], "made": [6, 8, 26, 52, 59, 75, 369, 371, 428, 452, 453, 454, 698, 805, 807, 809, 810, 813, 814, 819, 821, 823, 825, 826, 827, 831, 833, 835, 837, 846, 856], "significantli": [6, 8, 26, 52, 57, 75, 80, 369, 439, 625, 675, 814, 845, 854], "line": [6, 8, 9, 15, 16, 19, 20, 23, 26, 27, 29, 30, 41, 42, 285, 620, 800, 806, 809, 810, 814, 816, 817, 819, 827, 830, 833, 836, 837, 838, 839, 847, 850, 859], "even": [6, 23, 26, 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809, 815, 827, 830, 833], "own": [11, 13, 17, 26, 27, 32, 800, 806, 809, 814, 815, 818, 819, 826, 827, 831, 835, 841, 843, 846, 847, 852, 855, 856, 861, 862], "directli": [11, 13, 17, 20, 24, 26, 27, 30, 368, 369, 403, 427, 629, 718, 800, 805, 806, 807, 809, 810, 813, 814, 815, 816, 818, 821, 823, 824, 826, 827, 828, 831, 832, 835, 837, 839, 840, 841, 842, 847, 849, 850, 851, 860, 861, 862], "case": [11, 13, 19, 21, 26, 27, 29, 30, 31, 32, 40, 47, 48, 52, 53, 59, 65, 69, 71, 75, 76, 82, 92, 93, 98, 123, 134, 161, 162, 189, 194, 195, 202, 210, 214, 215, 216, 217, 218, 220, 221, 222, 223, 224, 231, 232, 233, 235, 236, 238, 240, 241, 242, 243, 249, 250, 251, 256, 257, 258, 259, 260, 263, 268, 271, 273, 277, 278, 279, 280, 281, 282, 285, 286, 288, 329, 330, 340, 342, 352, 365, 368, 370, 371, 374, 375, 381, 391, 392, 393, 413, 442, 452, 453, 454, 460, 462, 464, 465, 466, 469, 473, 479, 480, 488, 490, 492, 499, 522, 539, 540, 544, 551, 565, 566, 567, 617, 618, 619, 620, 622, 625, 627, 629, 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845, 849, 850, 855, 856, 857, 862, 863], "retriev": [11, 13, 17, 524, 546, 571, 622, 807, 827], "mlp_encod": [11, 26, 27, 800, 850], "create_model": [11, 26, 27, 800, 850], "mixer_b16_224": [11, 26, 27, 800, 850], "nois": [11, 13, 26, 27, 800, 849, 850], "randn": [11, 13, 26, 27, 800, 850], "tf_mlp_encod": [11, 26, 27], "output_torch": [11, 13], "output_tf": [11, 13], "constant": [11, 13, 18, 21, 22, 28, 31, 33, 38, 52, 59, 60, 75, 82, 83, 92, 93, 316, 362, 368, 370, 371, 413, 446, 447, 474, 627, 629, 630, 689, 712, 725, 779, 783, 800, 823, 828, 831, 839, 840, 841, 849, 851], "output_dens": [11, 26, 27, 800], "layer": [11, 13, 17, 23, 24, 26, 27, 38, 43, 52, 60, 75, 83, 630, 649, 650, 725, 777, 779, 781, 782, 783, 784, 785, 800, 818, 827, 831, 833, 835, 836, 839, 845, 850, 854, 856, 860, 863], "dens": [11, 24, 26, 27, 310, 362, 780, 800], "unit": [11, 26, 27, 52, 68, 75, 92, 93, 105, 107, 108, 109, 110, 111, 112, 113, 290, 291, 293, 297, 299, 300, 303, 304, 305, 360, 493, 494, 614, 800, 806, 809, 815, 827, 828, 830, 841, 857, 860], "activ": [11, 24, 26, 27, 52, 53, 56, 67, 75, 79, 90, 105, 106, 107, 108, 109, 110, 111, 112, 113, 290, 291, 292, 293, 297, 298, 299, 300, 301, 302, 303, 304, 305, 583, 624, 650, 653, 779, 780, 800, 805, 806, 807, 815, 821, 831, 832, 839, 850, 856, 859], "mention": [11, 13, 26, 27, 32, 805, 806, 807, 810, 817, 822, 823, 826, 827, 830, 833, 846, 851, 856], "basic": [11, 13, 17, 20, 24, 26, 27, 30, 33, 371, 481, 800, 801, 805, 817, 830], "fulli": [11, 13, 15, 16, 19, 24, 26, 27, 40, 52, 75, 380, 518, 780, 800, 810, 815, 822, 825, 833, 835, 836, 837, 838, 839, 840, 841, 847, 851, 854, 855, 856, 862, 863], "trainabl": [11, 13, 17, 23, 24, 26, 27, 44, 777, 781, 782, 785, 800, 818, 836, 838, 839, 850, 851], "fine": [11, 13, 26, 27, 806, 807, 815, 817, 827, 837, 840, 862], "tune": [11, 13, 26, 27, 861, 862], "train": [11, 13, 24, 26, 27, 43, 52, 54, 56, 75, 77, 79, 95, 368, 369, 374, 391, 392, 393, 438, 490, 492, 603, 604, 609, 623, 624, 647, 650, 653, 779, 780, 781, 782, 783, 800, 813, 816, 823, 838, 839, 840, 841, 847, 850, 854, 855, 860, 862, 863], "ground": [11, 13, 370, 443, 759, 761, 772, 803, 820, 827, 830, 845], "ret": [11, 13, 26, 27, 46, 47, 48, 49, 51, 52, 53, 54, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 97, 98, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 117, 118, 120, 121, 122, 123, 124, 125, 126, 127, 128, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 158, 159, 160, 161, 162, 163, 165, 166, 167, 168, 169, 170, 171, 172, 173, 175, 187, 188, 189, 191, 192, 193, 194, 195, 196, 197, 199, 200, 201, 202, 207, 208, 209, 210, 211, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 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860, 863], "alongsid": [15, 16, 17, 18, 28, 624, 650, 846], "turn": [15, 16, 19, 29, 56, 79, 92, 93, 391, 392, 393, 624, 647, 780, 806, 812, 813, 816, 817, 827, 830, 847], "wrapper": [15, 16, 19, 772, 810, 812, 813, 815, 819, 823, 826, 827, 837, 843, 852, 856], "unus": [15, 16, 19, 817, 826], "part": [15, 16, 19, 48, 51, 52, 74, 75, 80, 97, 107, 110, 113, 140, 141, 142, 248, 252, 275, 322, 323, 348, 362, 365, 368, 369, 371, 380, 411, 422, 474, 521, 614, 617, 620, 625, 660, 661, 761, 800, 805, 806, 807, 809, 812, 815, 821, 823, 826, 827, 830, 831, 833, 835, 836, 840, 841, 849, 850, 851, 854, 856, 861, 862, 863], "lazi": [15, 16, 19, 22, 29, 32, 33, 44], "eager": [15, 16, 19, 22, 24, 29, 32, 33, 44, 813, 841, 856], "understand": [15, 16, 17, 21, 38, 44, 803, 804, 805, 806, 807, 808, 809, 812, 817, 818, 822, 828, 829, 834, 847, 852, 862], "decor": [15, 16, 21, 23, 24, 32, 44, 528, 622, 764, 766, 772, 803, 809, 810, 813, 815, 816, 820, 823, 826, 827, 828, 833], "kornia": [15, 16, 23, 26, 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220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 240, 241, 242, 246, 247, 249, 250, 251, 252, 254, 255, 256, 257, 258, 259, 260, 262, 263, 264, 265, 266, 267, 268, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 288, 289, 290, 291, 292, 293, 296, 297, 298, 299, 300, 301, 303, 304, 305, 307, 319, 328, 329, 330, 331, 332, 334, 336, 343, 344, 350, 352, 354, 355, 356, 362, 371, 390, 391, 392, 393, 411, 442, 443, 444, 445, 446, 447, 448, 449, 452, 453, 454, 458, 459, 474, 480, 482, 483, 484, 490, 492, 493, 494, 496, 498, 511, 512, 513, 514, 523, 524, 526, 527, 529, 530, 534, 535, 536, 537, 538, 539, 540, 541, 542, 545, 547, 549, 550, 551, 553, 554, 557, 561, 565, 566, 580, 581, 583, 585, 587, 588, 601, 612, 616, 618, 619, 622, 629, 638, 639, 640, 641, 647, 648, 653, 654, 655, 660, 661, 662, 663, 665, 666, 668, 670, 672, 673, 679, 684, 685, 686, 687, 691, 694, 695, 696, 697, 698, 701, 702, 706, 707, 709, 712, 713, 714, 715, 717, 718, 719, 723, 724, 726, 727, 728, 729, 731, 734, 737, 738, 739, 740, 741, 745, 746, 749, 751, 752, 754, 755, 756, 761, 762, 777, 780, 782, 789, 794, 810, 813, 838, 839, 843, 849, 850, 851], "recurs": [17, 26, 27, 40, 42, 47, 69, 70, 161, 162, 194, 195, 369, 438, 539, 540, 546, 618, 619, 622, 629, 706, 707, 710, 716, 717, 718, 759, 806, 809, 812, 813, 820, 823, 826, 839, 841], "oper": [17, 18, 21, 22, 23, 24, 26, 27, 28, 32, 39, 42, 48, 49, 51, 52, 53, 56, 69, 71, 72, 74, 75, 76, 79, 98, 113, 132, 133, 175, 205, 213, 218, 220, 229, 232, 235, 242, 257, 259, 268, 269, 273, 277, 280, 285, 296, 304, 324, 325, 326, 357, 360, 362, 367, 368, 370, 371, 382, 383, 384, 386, 387, 388, 394, 395, 396, 400, 404, 405, 406, 407, 409, 410, 412, 414, 415, 442, 479, 481, 527, 534, 535, 536, 583, 614, 617, 618, 619, 620, 622, 624, 625, 635, 637, 638, 639, 640, 641, 642, 643, 644, 645, 646, 648, 650, 677, 679, 751, 753, 764, 767, 780, 794, 800, 805, 806, 808, 809, 810, 813, 815, 816, 817, 818, 819, 823, 826, 827, 830, 833, 835, 838, 839, 843, 845, 849, 852, 853, 854, 855, 856, 857, 859, 860, 861, 862, 863], "fashion": [17, 766, 830, 850], "native_arrai": [17, 26, 27, 48, 49, 51, 71, 73, 74, 75, 76, 80, 87, 105, 108, 131, 134, 136, 138, 144, 147, 148, 149, 150, 158, 163, 170, 192, 201, 209, 225, 229, 234, 235, 236, 238, 242, 246, 254, 255, 263, 268, 271, 274, 277, 282, 329, 330, 356, 365, 370, 371, 448, 474, 480, 484, 523, 526, 553, 554, 557, 587, 614, 617, 618, 619, 620, 622, 624, 625, 626, 627, 631, 632, 635, 636, 638, 639, 646, 653, 656, 660, 661, 667, 668, 672, 676, 677, 679, 682, 684, 686, 687, 694, 726, 735, 744, 750, 753, 755, 761, 771, 789, 803, 820, 828, 830], "data_class": [17, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 100, 101, 102, 387, 388, 534, 538, 675, 700], "low": [17, 26, 29, 45, 52, 56, 61, 75, 79, 84, 368, 410, 414, 624, 631, 637, 638, 639, 640, 642, 644, 646, 727, 729, 766, 813, 819, 826, 827, 833, 835, 852, 854, 856, 857, 858, 860, 862], "level": [17, 26, 27, 29, 52, 75, 76, 369, 438, 526, 794, 800, 801, 805, 806, 807, 813, 815, 819, 823, 825, 826, 827, 829, 832, 833, 834, 835, 838, 839, 840, 841, 843, 847, 852, 853, 854, 855, 856, 857, 858, 860, 861, 862, 863], "c": [17, 26, 32, 41, 42, 48, 52, 53, 54, 56, 59, 65, 71, 72, 74, 75, 76, 77, 79, 80, 82, 86, 88, 92, 93, 111, 122, 123, 133, 136, 160, 163, 218, 229, 235, 236, 256, 257, 259, 268, 271, 279, 286, 368, 369, 371, 374, 380, 382, 383, 384, 395, 400, 416, 418, 420, 421, 423, 433, 452, 453, 454, 464, 482, 490, 491, 492, 495, 513, 526, 534, 535, 536, 537, 545, 549, 550, 588, 603, 604, 607, 609, 610, 611, 614, 617, 618, 620, 622, 623, 624, 625, 627, 629, 632, 633, 635, 638, 639, 640, 641, 642, 643, 645, 659, 661, 663, 694, 698, 706, 709, 713, 714, 715, 717, 718, 723, 724, 735, 740, 746, 747, 752, 754, 783, 793, 794, 801, 806, 808, 811, 812, 813, 817, 823, 825, 834, 835, 836, 838, 841, 843, 844, 846, 847, 850, 852, 856, 860, 861, 863], "fundament": [17, 26, 814, 827, 833, 835, 845, 856], "common": [17, 20, 26, 30, 51, 52, 69, 74, 174, 245, 253, 333, 339, 365, 618, 620, 801, 803, 805, 806, 812, 815, 816, 817, 823, 824, 827, 831, 833, 841, 845, 853, 856, 863], "signatur": [17, 26, 371, 380, 474, 511, 815, 816, 817, 818, 822, 826, 830, 831, 833, 846, 853, 862], "matmul": [17, 26, 27, 43, 57, 80, 369, 436, 602, 622, 625, 675, 811, 830, 831, 835], "to_n": [17, 26, 27, 38, 47, 70, 835], "jaxlib": [17, 23, 41, 789, 806, 810, 815, 816, 822, 831, 835, 837], "xla_extens": [17, 23, 789, 810, 815, 816, 822, 831, 835, 837], "arrayimpl": [17, 23, 789], "abov": [17, 22, 26, 27, 32, 33, 48, 51, 52, 57, 61, 68, 74, 75, 80, 84, 93, 113, 121, 122, 123, 125, 126, 127, 128, 130, 131, 132, 133, 134, 137, 138, 139, 140, 141, 142, 143, 144, 150, 166, 170, 215, 216, 217, 218, 220, 221, 222, 223, 224, 225, 226, 227, 229, 230, 231, 232, 233, 235, 236, 238, 240, 241, 242, 246, 247, 248, 249, 250, 251, 252, 255, 257, 258, 259, 260, 262, 263, 264, 265, 268, 270, 271, 272, 273, 275, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 288, 305, 307, 322, 323, 329, 330, 332, 335, 360, 362, 365, 368, 369, 371, 380, 386, 387, 388, 389, 391, 392, 393, 399, 401, 404, 405, 406, 411, 412, 413, 421, 422, 474, 482, 511, 514, 541, 545, 547, 549, 551, 588, 612, 614, 617, 618, 620, 622, 623, 624, 625, 627, 630, 631, 632, 633, 634, 635, 636, 638, 639, 640, 641, 642, 646, 647, 648, 650, 653, 654, 655, 656, 657, 658, 659, 660, 661, 662, 663, 665, 666, 667, 668, 669, 670, 671, 672, 673, 674, 675, 676, 677, 679, 681, 682, 683, 687, 688, 689, 690, 691, 692, 693, 694, 695, 696, 697, 698, 699, 700, 701, 702, 725, 727, 732, 733, 735, 736, 737, 738, 739, 740, 741, 744, 748, 749, 750, 751, 752, 753, 754, 755, 756, 800, 803, 805, 806, 807, 810, 811, 812, 813, 814, 815, 816, 817, 818, 819, 820, 822, 823, 825, 826, 827, 828, 830, 833, 835, 837, 838, 839, 840, 856, 861], "why": [17, 800, 807, 826, 837, 844, 846], "underli": [17, 26, 27, 38, 52, 59, 75, 82, 95, 225, 228, 230, 265, 370, 371, 447, 464, 620, 625, 627, 673, 694, 813, 826, 833, 849, 856], "disabl": [17, 26, 52, 75, 371, 482, 782, 812], "array_mod": [17, 26, 567, 590, 622, 832], "set_array_mod": [17, 26, 590, 622, 832], "composit": [17, 26, 161, 162, 194, 195, 287, 369, 428, 539, 540, 618, 619, 620, 622, 765, 767, 805, 808, 810, 811, 813, 815, 816, 824, 826, 827, 828, 830, 833, 835, 839, 840, 841, 843, 849, 857], "ultim": [17, 26, 849], "sigmoid": [17, 26, 27, 38, 46, 52, 68, 75, 295, 360, 375, 497, 614, 776, 835, 838, 839], "z": [17, 26, 27, 39, 40, 48, 51, 52, 53, 57, 58, 61, 63, 65, 71, 74, 75, 76, 80, 81, 82, 84, 88, 97, 98, 132, 133, 135, 136, 196, 218, 219, 223, 225, 228, 230, 235, 246, 247, 250, 251, 252, 254, 255, 260, 262, 264, 265, 266, 267, 275, 284, 294, 295, 329, 330, 332, 360, 365, 370, 380, 443, 445, 446, 447, 448, 449, 455, 459, 470, 510, 511, 514, 521, 526, 538, 541, 542, 549, 550, 566, 579, 580, 581, 589, 602, 617, 619, 620, 622, 625, 626, 627, 629, 631, 632, 633, 635, 655, 665, 670, 671, 675, 682, 684, 685, 686, 687, 709, 713, 715, 723, 727, 728, 729, 732, 737, 747, 748, 750, 751, 752, 779, 800, 811, 813, 816, 817, 835, 837, 849], "divid": [17, 22, 26, 27, 43, 51, 52, 53, 59, 69, 74, 75, 82, 97, 98, 242, 374, 444, 490, 491, 492, 495, 580, 620, 622, 627, 696, 810, 813, 817, 821, 830], "exp": [17, 26, 27, 51, 52, 74, 75, 111, 113, 240, 260, 273, 295, 360, 368, 370, 395, 400, 447, 614, 620, 625, 673, 825, 827], "high": [17, 26, 27, 45, 52, 56, 61, 75, 79, 84, 368, 410, 414, 574, 622, 624, 631, 637, 638, 639, 640, 642, 644, 646, 727, 729, 766, 805, 819, 825, 827, 838, 843, 847, 852, 853, 854, 855, 856, 860, 862, 863], "network": [17, 24, 26, 27, 38, 40, 45, 624, 648, 776, 779, 780, 800, 813, 823, 835, 839, 846, 850, 852, 854, 855, 856, 860, 862, 863], "entir": [17, 26, 27, 29, 42, 52, 65, 66, 69, 75, 76, 88, 89, 208, 238, 240, 280, 281, 329, 330, 365, 368, 371, 380, 391, 392, 393, 474, 514, 547, 619, 620, 635, 636, 748, 749, 750, 751, 752, 753, 754, 755, 756, 780, 794, 805, 806, 807, 809, 810, 813, 815, 817, 819, 826, 827, 828, 830, 833, 835, 838, 839, 840, 841, 846, 847, 850, 856, 862, 863], "further": [17, 69, 98, 766, 807, 809, 810, 814, 817, 819, 822, 823, 826, 827, 829, 830, 834, 835, 838, 839, 846, 847, 861, 862], "congratul": [17, 23], "There": [17, 24, 27, 32, 92, 361, 363, 364, 372, 373, 377, 766, 800, 805, 806, 807, 809, 810, 812, 813, 815, 816, 817, 819, 821, 823, 825, 827, 828, 832, 835, 838, 841, 845, 849, 857, 858, 862, 863], "come": [17, 40, 805, 806, 807, 810, 814, 827, 832, 833, 839, 843, 856], "independ": [17, 27, 52, 61, 75, 84, 218, 235, 268, 278, 374, 375, 495, 497, 620, 625, 631, 655, 674, 726, 800, 809, 815, 817, 824, 835, 840, 850, 854], "good": [17, 26, 27, 800, 804, 805, 806, 807, 809, 810, 811, 812, 813, 814, 815, 816, 817, 818, 819, 821, 822, 823, 824, 825, 826, 828, 830, 831, 833, 835, 836, 839], "foundat": [17, 846, 859], "power": [17, 26, 27, 51, 52, 53, 57, 74, 75, 76, 80, 97, 98, 229, 238, 239, 273, 327, 339, 362, 365, 368, 415, 571, 581, 593, 620, 622, 625, 629, 667, 680, 712, 779, 832, 837, 838, 839, 856, 858, 862], "defin": [18, 24, 26, 27, 28, 48, 52, 53, 57, 71, 75, 76, 80, 95, 111, 136, 140, 141, 142, 218, 235, 242, 268, 269, 277, 279, 282, 294, 298, 302, 308, 311, 312, 313, 322, 323, 324, 325, 326, 329, 330, 332, 360, 362, 365, 368, 369, 371, 380, 403, 420, 474, 480, 514, 549, 550, 570, 614, 617, 620, 622, 625, 635, 655, 660, 661, 674, 748, 749, 750, 752, 800, 805, 806, 810, 811, 814, 815, 818, 822, 825, 827, 828, 830, 831, 837, 839, 841, 843, 851, 853, 854, 855, 856, 857, 860, 862, 863], "div": [18, 19, 20, 21, 22, 26, 27, 28, 29, 30, 31, 32, 33, 851], "sub": [18, 19, 20, 21, 22, 26, 27, 28, 29, 30, 31, 32, 33, 52, 57, 59, 69, 70, 74, 75, 76, 80, 82, 98, 267, 369, 371, 380, 422, 460, 469, 488, 517, 518, 546, 622, 625, 627, 628, 658, 679, 696, 703, 704, 705, 805, 807, 808, 813, 819, 827, 828, 830, 837, 838, 839, 851, 852], "By": [18, 38, 45, 52, 58, 59, 65, 66, 75, 81, 82, 88, 89, 282, 327, 329, 330, 342, 349, 362, 365, 368, 370, 371, 378, 380, 390, 446, 447, 482, 504, 511, 514, 569, 620, 622, 625, 626, 627, 635, 636, 655, 681, 684, 693, 745, 748, 749, 750, 751, 752, 753, 754, 755, 756, 806, 811, 815, 817, 819, 823, 825, 826, 827, 835, 839, 840, 849], "uniform": [18, 19, 20, 21, 22, 26, 27, 28, 29, 31, 32, 33, 40, 52, 61, 75, 84, 380, 514, 631, 726, 727, 729, 779, 800, 829, 839, 850, 851, 863], "x_": [18, 28, 93, 279, 620, 851], "82997245": 18, "44733784": 18, "32163444": 18, "93330479": 18, "52438271": 18, "20438017": 18, "252316": 18, "0827222": 18, "26017165": 18, "88881904": 18, "compat": [18, 24, 28, 32, 38, 45, 51, 52, 57, 59, 62, 65, 66, 74, 75, 80, 82, 85, 88, 89, 97, 98, 149, 218, 223, 225, 227, 228, 229, 230, 235, 236, 242, 246, 247, 254, 255, 260, 262, 264, 265, 268, 271, 273, 277, 284, 289, 329, 330, 365, 618, 620, 625, 627, 632, 635, 636, 655, 668, 671, 674, 677, 681, 682, 694, 733, 748, 749, 750, 751, 752, 753, 754, 755, 756, 800, 806, 811, 822, 827, 828, 831, 835, 841, 846], "sever": [18, 19, 28, 29, 31, 32, 33, 52, 75, 92, 368, 369, 382, 383, 384, 434, 764, 806, 807, 831, 841, 854, 860], "pro": [18, 19, 20, 28, 29, 30, 31, 32, 33], "pick": [19, 29, 779], "off": [19, 29, 56, 57, 79, 80, 391, 392, 393, 624, 625, 647, 658, 679, 779, 780, 806, 820, 834, 847, 849, 862], "last": [19, 24, 26, 29, 48, 52, 56, 57, 58, 59, 62, 64, 65, 66, 69, 71, 75, 79, 80, 81, 82, 87, 88, 89, 93, 97, 132, 133, 136, 191, 307, 335, 362, 365, 368, 369, 370, 371, 378, 380, 396, 401, 411, 412, 413, 424, 446, 464, 474, 476, 482, 504, 512, 513, 617, 619, 624, 625, 626, 627, 632, 634, 635, 636, 649, 650, 655, 658, 670, 679, 681, 685, 686, 688, 691, 694, 695, 696, 698, 732, 733, 741, 743, 744, 745, 746, 755, 756, 780, 789, 800, 807, 809, 811, 812, 815, 817, 826, 828, 830, 833, 835, 841, 847, 850, 856], 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849, 851, 857, 862], "constitu": [19, 29, 69, 840], "due": [19, 26, 27, 29, 43, 45, 268, 278, 371, 482, 620, 806, 809, 814, 819, 826, 827, 846, 849, 850, 856], "manner": [19, 27, 29, 39, 47, 70, 629, 718, 806, 815, 816, 818, 823, 827, 831, 838, 841, 845, 852, 854, 862, 863], "non": [19, 29, 49, 51, 52, 57, 61, 62, 65, 66, 72, 74, 75, 80, 84, 85, 88, 89, 129, 147, 165, 174, 243, 263, 264, 269, 329, 330, 334, 340, 353, 365, 368, 369, 371, 380, 411, 422, 426, 430, 453, 454, 514, 517, 617, 618, 620, 625, 629, 631, 632, 635, 636, 655, 656, 666, 668, 675, 677, 681, 682, 719, 728, 732, 733, 734, 735, 748, 749, 750, 751, 752, 754, 755, 756, 764, 779, 781, 782, 784, 810, 813, 817, 835, 849, 850, 851, 856], "5556394": 19, "655387": 19, "1415051": 19, "4695197": 19, "3022028": 19, "1473966": 19, "5701794": 19, "91962665": 19, "51028997": 19, "5964439": 19, "assess": [19, 29, 805, 833], "985": 19, "000": [19, 74, 269, 764, 803, 814, 820], "69": [19, 38, 45, 51, 77, 84, 216, 258, 368, 389, 399, 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24], "env": [21, 22, 23, 24], "multienv": [21, 22, 23, 24], "site": [21, 22, 23, 24, 857], "psutil": [21, 22, 23, 24, 40, 42, 45], "termcolor": [21, 22, 23, 24, 40, 42, 45, 69, 98], "colorama": [21, 22, 23, 24, 40, 42], "nvidia": [21, 22, 23, 24, 40, 42, 45, 860, 861], "535": [21, 22, 23, 24, 46, 68, 113, 614, 819], "diskcach": [21, 22, 23, 24, 40], "auth": [21, 22, 23, 24], "urllib3": [21, 22, 23, 24, 40], "pyvi": [21, 22, 23, 24, 26, 27], "dill": [21, 22, 23, 24, 40], "astunpars": [21, 22, 23, 24], "cloudpickl": [21, 22, 23, 24], "gast": [21, 22, 23, 24], "66": [21, 22, 23, 24, 38, 40, 42, 65, 75, 76, 77, 368, 399, 534, 535, 607, 622, 623, 625, 635, 670, 747], "wheel": [21, 22, 23, 24, 40, 42, 45, 845], "six": [21, 22, 23, 24, 40, 45, 806, 833], "cachetool": [21, 22, 23, 24], "pyasn1": [21, 22, 23, 24], "rsa": [21, 22, 23, 24], "jinja2": [21, 22, 23, 24], "jsonpickl": [21, 22, 23, 24], "networkx": [21, 22, 23, 24, 45], "charset": [21, 22, 23, 24, 40], "idna": [21, 22, 23, 24, 40], 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809, 814, 816, 819, 832], "becaus": [21, 29, 31, 41, 52, 368, 390, 759, 806, 807, 809, 810, 811, 812, 813, 815, 816, 818, 819, 820, 822, 823, 824, 825, 826, 827, 828, 830, 833, 835, 839, 840, 841, 856, 859, 862], "argument": [21, 23, 24, 26, 27, 29, 31, 32, 33, 38, 40, 42, 44, 47, 48, 51, 52, 53, 57, 69, 70, 74, 75, 76, 92, 93, 98, 121, 122, 123, 125, 126, 127, 128, 130, 131, 132, 133, 134, 137, 138, 139, 140, 141, 142, 143, 144, 150, 166, 170, 175, 215, 216, 217, 218, 220, 221, 222, 223, 224, 225, 226, 227, 229, 230, 231, 232, 233, 235, 236, 238, 240, 241, 242, 246, 247, 248, 249, 250, 251, 255, 257, 258, 259, 260, 262, 263, 264, 265, 268, 270, 271, 272, 273, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 288, 307, 322, 323, 329, 330, 332, 335, 337, 362, 365, 368, 369, 371, 380, 386, 387, 388, 389, 390, 391, 392, 393, 395, 396, 399, 400, 401, 404, 405, 406, 411, 413, 415, 422, 474, 482, 511, 514, 518, 524, 525, 527, 528, 533, 535, 536, 541, 545, 547, 549, 551, 561, 565, 566, 583, 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88, 105, 106, 107, 108, 109, 110, 111, 112, 113, 137, 138, 153, 167, 176, 182, 215, 216, 217, 218, 219, 220, 221, 224, 232, 233, 235, 236, 238, 240, 248, 249, 250, 251, 252, 256, 257, 258, 259, 268, 270, 271, 273, 275, 278, 279, 280, 281, 282, 285, 286, 290, 294, 295, 297, 332, 337, 360, 365, 368, 369, 380, 390, 401, 411, 412, 416, 421, 422, 423, 432, 434, 519, 520, 580, 581, 614, 617, 618, 620, 622, 625, 632, 635, 659, 660, 661, 666, 673, 675, 677, 679, 682, 735, 750, 751, 753, 765, 776, 794, 805, 812, 815, 817, 824, 827, 830, 831, 833, 838, 839, 840, 841, 843, 850, 852, 854, 856, 858, 862, 863], "neccessari": 24, "set_random_se": [24, 43], "manual_se": 24, "301436": 24, "_c": 24, "0x7f252c392390": 24, "convolut": [24, 52, 56, 75, 79, 368, 388, 406, 624, 637, 638, 639, 640, 641, 642, 643, 644, 645, 646, 766, 780, 850, 854, 856], "flatten": [24, 26, 27, 40, 42, 45, 52, 53, 57, 59, 62, 63, 75, 76, 80, 82, 85, 86, 334, 349, 365, 369, 371, 380, 419, 463, 473, 477, 482, 483, 487, 509, 516, 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804, 805, 806, 807, 812, 819, 827, 830, 831, 832, 833, 850, 859], "interest": [24, 26, 38, 235, 268, 620, 805, 807], "continu": [24, 26, 27, 42, 120, 282, 290, 360, 616, 620, 800, 804, 805, 806, 808, 809, 820, 826, 829, 830, 841, 846, 847, 856], "regress": [25, 856, 863], "checkout": [26, 41, 807, 809, 830], "f705efe7cb5d18df17ce6c1e20f04d0eb4933f48": 26, "theoret": 26, "aspect": [26, 27, 801, 825, 838, 856], "switch": [26, 38, 772, 811, 819, 823, 824, 863], "easiest": [26, 800, 802, 806, 842], "defer": [26, 27, 805, 810, 815, 816, 823, 826, 827, 830, 862], "similarli": [26, 39, 134, 142, 218, 322, 329, 330, 362, 365, 617, 620, 811, 815, 827, 833, 837, 862], "obtain": [26, 27, 45, 52, 75, 313, 362, 368, 407, 624, 650, 766, 827, 849], "essenc": [26, 857, 862], "becom": [26, 52, 75, 92, 339, 365, 371, 454, 627, 687, 789, 807, 813, 815, 817, 819, 826, 841, 845, 847, 849], "regardless": [26, 27, 38, 69, 801, 815, 819, 837, 840, 847], "being": [26, 27, 38, 52, 69, 75, 90, 97, 101, 121, 369, 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721, 722, 723, 724, 726, 727, 728, 729, 731, 737, 747, 755, 756, 759, 761, 762, 764, 765, 766, 767, 772, 779, 794, 798, 800, 804, 805, 806, 808, 813, 815, 816, 819, 822, 823, 827, 828, 830, 835, 838, 841, 842, 843, 844, 845, 846, 847, 849, 850, 851, 856, 857], "regressor": [26, 27, 800], "input_dim": [26, 27, 41, 800], "output_dim": [26, 27, 41, 800], "linear0": [26, 27, 38, 800, 838, 839], "linear1": [26, 27, 38, 800, 838, 839], "instanti": [26, 27, 772, 818], "adam": [26, 27, 38, 42, 54, 77, 525, 603, 604, 609, 622, 623, 784, 800, 838, 839, 840, 856], "n_training_exampl": [26, 27, 800], "2000": [26, 27, 75, 308, 362, 800], "random_norm": [26, 27, 56, 57, 61, 79, 80, 84, 534, 622, 624, 625, 631, 639, 641, 642, 643, 645, 646, 649, 675, 800], "linspac": [26, 27, 48, 71, 121, 617, 800, 822, 833, 835, 863], "loss_fn": [26, 27, 38, 40, 42, 800, 838, 839, 840], "pred": [26, 27, 41, 42, 52, 58, 75, 81, 370, 443, 446, 626, 684, 685, 686, 800, 813, 823, 826], "epoch": [26, 27, 40, 42, 800], "loss": [26, 27, 40, 42, 52, 75, 92, 442, 443, 444, 445, 446, 447, 448, 449, 574, 596, 622, 684, 685, 686, 800, 814, 815, 823, 827, 831, 832, 838, 839, 840, 856, 863], "gradient": [26, 27, 40, 42, 52, 75, 92, 208, 357, 365, 603, 604, 605, 606, 607, 608, 609, 610, 611, 612, 613, 619, 628, 703, 704, 705, 761, 772, 784, 800, 808, 831, 838, 839, 841, 856], "grad": [26, 27, 38, 42, 603, 623, 784, 800, 825, 838, 839, 840], "execute_with_gradi": [26, 27, 38, 42, 623, 800, 838, 839, 840, 841], "lambda": [26, 27, 43, 45, 75, 118, 120, 292, 301, 533, 605, 606, 608, 613, 616, 622, 623, 625, 629, 660, 713, 714, 718, 800, 805, 823, 824, 825, 828, 833, 835, 838], "2d": [26, 27, 42, 52, 75, 92, 307, 362, 368, 369, 371, 380, 383, 384, 391, 392, 432, 439, 453, 463, 511, 780, 800, 827, 833], "5f": [26, 27, 800], "nonetheless": [26, 27], "slight": [26, 27, 815, 830, 839], "introduc": [26, 27, 242, 620, 627, 633, 695, 737, 805, 813, 814, 815, 824, 828, 830, 833, 838, 845], "address": [26, 27, 52, 53, 75, 371, 482, 587, 622, 805, 807, 809, 810, 822, 829, 835, 847, 852, 854, 856, 862], "extract": [26, 27, 34, 41, 52, 75, 93, 371, 457, 483, 827, 829, 831, 852, 856, 857, 862], "gc": [26, 27, 546, 622], "decompos": [26, 27, 52, 75, 92, 95, 317, 318, 319, 320, 321, 341, 348, 362, 365, 369, 430, 435, 438, 441, 827, 840], "said": [26, 27, 766, 831, 847, 849], "otherwis": [26, 27, 44, 47, 48, 49, 51, 52, 53, 56, 57, 62, 63, 65, 66, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 79, 80, 81, 82, 84, 85, 86, 87, 88, 89, 92, 105, 106, 107, 108, 109, 110, 111, 112, 113, 118, 121, 123, 124, 129, 131, 132, 133, 136, 138, 144, 147, 148, 150, 151, 153, 154, 155, 156, 157, 166, 170, 174, 175, 191, 209, 215, 216, 217, 218, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 240, 241, 242, 246, 247, 249, 250, 251, 252, 254, 255, 256, 257, 258, 259, 260, 262, 263, 264, 265, 266, 267, 268, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 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751, 752, 753, 754, 755, 756, 759, 764, 765, 780, 782, 783, 789, 800, 807, 810, 813, 815, 816, 817, 823, 824, 826, 830, 835, 842, 849, 850], "x0": [26, 27, 45, 76, 526, 622, 817], "normalize_trac": [26, 27], "html": [26, 27, 41, 51, 52, 74, 75, 142, 150, 238, 248, 249, 264, 322, 329, 330, 362, 365, 368, 371, 380, 411, 482, 511, 617, 618, 620, 625, 627, 635, 673, 674, 702, 752, 800, 818, 846], "fname": [26, 27, 43, 45, 782, 838], "anticip": [26, 27], "addition": [26, 27, 813, 826, 827, 862], "backend_compil": [26, 27], "normalize_native_comp": [26, 27], "return_backend_compiled_fn": 26, "immedi": [26, 27, 805, 806], "built": [26, 27, 32, 40, 42, 45, 121, 617, 780, 781, 782, 800, 806, 807, 812, 813, 830, 836, 842, 849, 855, 856, 860], "summar": [26, 27, 92, 830], "eager_graph": [26, 27, 800, 849, 850], "lazy_graph": [26, 27, 800, 849, 850], "codebas": [26, 27, 206, 207, 619, 801, 808, 815, 821, 826, 827, 829, 830, 831, 834, 847], "thought": [26, 27, 806, 807, 822, 846, 854], "research": [26, 27, 40, 800, 845, 850, 856, 863], "wa": [26, 27, 32, 41, 52, 65, 66, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 79, 80, 81, 82, 84, 85, 86, 87, 88, 89, 95, 105, 106, 107, 108, 109, 110, 111, 112, 113, 129, 131, 136, 138, 144, 148, 150, 175, 209, 215, 216, 217, 218, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 240, 241, 242, 246, 247, 249, 250, 251, 252, 254, 255, 256, 257, 258, 259, 260, 262, 263, 264, 265, 266, 267, 268, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 288, 289, 290, 291, 292, 293, 297, 298, 299, 300, 301, 303, 304, 305, 306, 307, 328, 329, 330, 331, 332, 334, 336, 343, 344, 350, 351, 352, 354, 355, 356, 362, 365, 369, 391, 392, 393, 411, 440, 442, 443, 444, 445, 446, 447, 448, 449, 452, 453, 454, 458, 459, 480, 482, 483, 484, 490, 492, 493, 494, 496, 498, 511, 512, 513, 514, 523, 526, 527, 529, 530, 534, 535, 536, 537, 538, 541, 542, 545, 547, 549, 550, 551, 553, 554, 557, 565, 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50, 69, 72, 73, 153, 154, 155, 156, 157, 158, 164, 191, 192, 204, 618, 619, 815], "certainli": [26, 27, 800, 846, 862], "upon": [26, 27, 44, 807, 817, 826, 830, 833, 841, 855, 856], "unnecessari": [26, 27, 827], "extend": [26, 27, 52, 75, 371, 380, 474, 514, 811, 812, 815, 818, 819, 822, 827, 831, 841, 853, 856, 862], "infrastructur": [26, 27, 800, 852, 858, 859], "least": [26, 51, 52, 57, 74, 75, 235, 253, 268, 368, 371, 380, 395, 400, 452, 453, 454, 463, 465, 511, 620, 625, 632, 665, 735, 800, 807, 810, 814, 815, 816, 817, 823, 826, 830, 850], "coco": 26, "seamlessli": [27, 830], "benefit": [27, 800, 806, 810, 813, 826, 833, 837, 838, 841, 846, 847, 854, 858, 861], "through": [27, 32, 40, 52, 75, 95, 223, 380, 517, 518, 620, 629, 709, 715, 782, 793, 800, 801, 803, 804, 805, 807, 808, 811, 812, 813, 814, 816, 817, 819, 820, 821, 823, 824, 826, 827, 828, 830, 832, 833, 834, 835, 838, 839, 840, 849, 854, 856, 857, 858], "therefor": [27, 32, 48, 51, 52, 57, 74, 75, 121, 122, 123, 125, 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750, 751, 752, 753, 754, 755, 756, 805, 807, 809, 810, 813, 814, 815, 816, 817, 818, 819, 822, 823, 824, 826, 827, 828, 830, 831, 833, 835, 837, 839, 841, 845, 853, 856, 862], "wide": [27, 800, 807, 830, 854, 856], "prepar": [27, 40, 42, 45, 800, 814], "plenti": 27, "resourc": [27, 801, 805, 806, 814], "visit": [27, 805, 806, 807, 814], "page": [27, 800, 805, 806, 807, 812, 814, 820, 836, 837, 840, 842, 851], "newli": [28, 29, 41, 43, 49, 72, 147, 528, 618, 622, 807, 814, 826, 830], "randon": [28, 29, 31, 32, 33], "mean_": 28, "std_": 28, "detect": [28, 32, 51, 69, 74, 250, 620, 629, 706, 717, 805, 806, 811, 813, 814, 821, 830, 838, 839], "inspect": [28, 32, 524, 622], "__": [28, 29, 30, 31, 32, 33, 69, 817, 838], "exhibit": [29, 862], "via": [29, 32, 242, 369, 371, 435, 438, 441, 482, 620, 629, 716, 717, 807, 809, 813, 815, 816, 826, 831, 833, 835, 837, 838, 856], "script": [29, 800, 806, 807, 809, 814, 817, 835, 841, 856], "comp": 29, "low_level": 29, "chain": [29, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 79, 80, 81, 82, 84, 85, 86, 87, 88, 89, 92, 105, 106, 107, 108, 109, 110, 111, 112, 113, 129, 131, 136, 138, 144, 148, 150, 163, 167, 168, 175, 209, 215, 216, 217, 218, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 240, 241, 242, 246, 247, 249, 250, 251, 252, 254, 255, 256, 257, 258, 259, 260, 262, 263, 264, 265, 266, 267, 268, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 288, 289, 290, 291, 292, 293, 297, 298, 299, 300, 301, 303, 304, 305, 307, 328, 329, 330, 332, 334, 336, 343, 344, 350, 352, 354, 355, 356, 391, 392, 393, 411, 442, 443, 444, 445, 446, 447, 448, 449, 458, 459, 480, 482, 484, 490, 492, 493, 494, 496, 498, 511, 512, 513, 514, 523, 526, 527, 529, 530, 534, 535, 536, 537, 538, 541, 542, 545, 547, 549, 550, 551, 553, 554, 557, 565, 566, 580, 581, 583, 585, 587, 588, 601, 607, 612, 628, 629, 638, 639, 640, 641, 647, 648, 653, 654, 655, 660, 661, 662, 663, 665, 666, 668, 670, 672, 673, 679, 684, 685, 686, 687, 691, 694, 695, 696, 697, 698, 701, 702, 703, 704, 708, 719, 726, 727, 728, 729, 731, 734, 737, 738, 739, 740, 741, 745, 746, 749, 751, 752, 754, 755, 756, 785, 810, 813, 825, 827, 839, 840, 841, 856], "un": [29, 165, 618, 815, 835], "partial_comp": 29, "time_funct": 29, "slowest": [29, 52, 59, 75, 82, 371, 464, 627, 694], "express": [29, 51, 52, 74, 75, 93, 216, 220, 222, 223, 232, 234, 274, 280, 285, 352, 365, 620, 786, 794, 818, 827, 835, 840, 856, 857], "fastest": [29, 52, 59, 75, 82, 369, 371, 433, 464, 627, 694], "maxim": [29, 823, 826, 835, 853, 854, 858, 859, 860], "conclud": [30, 831], "collect": [30, 40, 42, 44, 45, 47, 69, 70, 614, 619, 622, 623, 624, 626, 629, 630, 631, 719, 776, 780, 781, 782, 783, 784, 806, 814, 819, 820, 824, 825, 828, 830, 854, 856, 859], "norm_comp": [31, 32], "global": [31, 32, 42, 53, 69, 76, 98, 153, 154, 155, 156, 157, 206, 207, 208, 571, 572, 575, 580, 581, 593, 594, 597, 618, 619, 622, 772, 783, 789, 806, 810, 811, 814, 815, 816, 819, 823, 827, 835, 856], "approach": [31, 803, 805, 806, 807, 810, 813, 815, 816, 820, 823, 827, 830, 831, 833, 837, 838, 841, 853, 860, 862], "b": [32, 46, 51, 52, 53, 56, 57, 65, 68, 71, 72, 73, 74, 75, 76, 77, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 92, 93, 96, 97, 98, 105, 106, 107, 108, 109, 110, 111, 112, 122, 123, 124, 129, 130, 131, 133, 136, 138, 144, 147, 148, 149, 150, 158, 168, 170, 175, 192, 209, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 311, 312, 324, 327, 328, 329, 330, 332, 333, 334, 335, 336, 337, 338, 339, 340, 341, 342, 343, 344, 345, 346, 348, 349, 350, 351, 352, 354, 355, 356, 360, 362, 365, 368, 369, 370, 371, 375, 378, 380, 386, 387, 388, 389, 391, 392, 395, 399, 400, 401, 404, 405, 406, 410, 411, 414, 417, 420, 422, 424, 428, 433, 436, 441, 442, 443, 445, 446, 447, 448, 452, 453, 454, 455, 458, 459, 460, 461, 464, 465, 466, 468, 469, 470, 471, 473, 474, 480, 482, 483, 484, 485, 488, 489, 494, 496, 498, 499, 501, 502, 504, 511, 512, 513, 514, 516, 518, 521, 523, 526, 527, 529, 530, 533, 534, 535, 536, 537, 538, 541, 542, 545, 547, 549, 550, 551, 553, 554, 557, 558, 565, 566, 580, 581, 583, 587, 588, 601, 603, 604, 605, 607, 609, 610, 611, 612, 614, 617, 618, 620, 622, 623, 624, 625, 626, 627, 629, 630, 631, 632, 633, 634, 635, 636, 638, 639, 640, 641, 642, 643, 645, 646, 647, 648, 649, 653, 654, 655, 656, 658, 660, 661, 662, 663, 665, 666, 667, 668, 669, 670, 672, 673, 674, 675, 676, 677, 679, 680, 681, 682, 684, 685, 686, 687, 689, 690, 691, 692, 693, 694, 695, 696, 697, 698, 699, 700, 701, 702, 706, 709, 712, 713, 714, 715, 717, 718, 723, 724, 725, 727, 728, 729, 731, 732, 733, 734, 735, 736, 737, 738, 739, 740, 741, 744, 745, 746, 747, 748, 749, 750, 751, 752, 753, 754, 755, 756, 764, 793, 794, 800, 801, 803, 807, 808, 809, 811, 813, 814, 817, 820, 823, 825, 828, 834, 835, 836, 838, 839, 840, 844, 847, 849, 852], "option": [32, 41, 44, 46, 47, 48, 49, 50, 51, 52, 53, 54, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 92, 97, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 147, 148, 149, 150, 152, 153, 154, 155, 156, 157, 163, 165, 175, 187, 191, 203, 206, 207, 208, 209, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 311, 312, 313, 317, 318, 319, 320, 321, 322, 323, 327, 328, 329, 330, 331, 332, 333, 334, 335, 336, 337, 338, 339, 340, 341, 342, 343, 344, 345, 346, 347, 348, 349, 350, 351, 352, 353, 354, 355, 356, 360, 362, 365, 368, 369, 370, 371, 374, 375, 376, 378, 380, 381, 386, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 399, 400, 401, 403, 404, 405, 406, 407, 409, 411, 412, 413, 415, 416, 418, 419, 420, 422, 424, 426, 427, 428, 429, 430, 431, 432, 433, 434, 435, 436, 437, 438, 439, 440, 441, 442, 443, 444, 445, 446, 447, 448, 449, 452, 453, 454, 457, 458, 459, 460, 462, 464, 465, 466, 467, 468, 469, 471, 472, 473, 475, 476, 477, 478, 479, 480, 481, 482, 483, 484, 485, 486, 487, 488, 490, 491, 492, 493, 494, 495, 496, 497, 498, 499, 500, 501, 502, 504, 509, 510, 511, 512, 513, 514, 515, 516, 517, 518, 519, 520, 521, 522, 523, 524, 526, 527, 529, 530, 532, 534, 535, 536, 537, 538, 541, 542, 544, 545, 546, 547, 549, 550, 551, 553, 554, 557, 562, 565, 566, 570, 580, 581, 583, 585, 587, 588, 589, 601, 603, 604, 607, 609, 610, 611, 612, 614, 617, 618, 619, 620, 622, 623, 624, 625, 626, 627, 628, 629, 630, 631, 632, 633, 634, 635, 636, 637, 638, 639, 640, 641, 642, 643, 644, 645, 646, 647, 648, 649, 650, 653, 654, 655, 656, 657, 658, 660, 661, 662, 663, 664, 665, 666, 668, 669, 670, 671, 672, 673, 674, 676, 677, 679, 680, 681, 682, 683, 684, 685, 686, 687, 688, 689, 690, 691, 692, 693, 694, 695, 696, 697, 698, 699, 700, 701, 702, 703, 704, 705, 706, 712, 713, 717, 718, 723, 725, 726, 727, 728, 729, 731, 732, 733, 734, 735, 736, 737, 738, 739, 740, 741, 742, 743, 744, 745, 746, 747, 748, 749, 750, 751, 752, 753, 754, 755, 756, 759, 761, 765, 772, 776, 777, 779, 780, 782, 784, 785, 793, 798, 805, 806, 807, 813, 814, 815, 816, 817, 818, 819, 820, 821, 822, 823, 826, 827, 828, 830, 831, 833, 835, 840, 841, 849, 850, 851, 856, 862], "prioriti": [32, 69, 789, 805, 807, 816, 826], "normalize_via_oper": 32, "determin": [32, 51, 52, 57, 59, 63, 66, 69, 74, 75, 76, 80, 87, 89, 92, 95, 97, 98, 127, 150, 152, 159, 165, 166, 167, 168, 170, 171, 172, 187, 197, 199, 200, 211, 216, 217, 218, 220, 221, 222, 223, 224, 225, 227, 228, 229, 230, 232, 233, 235, 238, 240, 242, 248, 249, 250, 251, 252, 256, 257, 258, 259, 260, 265, 268, 273, 277, 280, 281, 282, 283, 284, 285, 286, 289, 298, 302, 347, 352, 360, 365, 368, 369, 370, 371, 380, 403, 411, 422, 442, 443, 482, 511, 523, 526, 547, 548, 552, 553, 554, 555, 556, 557, 583, 601, 617, 618, 619, 620, 622, 625, 627, 628, 633, 636, 654, 655, 656, 658, 662, 663, 665, 667, 668, 670, 671, 673, 674, 679, 681, 682, 688, 703, 704, 705, 737, 738, 739, 740, 741, 755, 756, 766, 772, 779, 783, 813, 815, 816, 818, 823, 827, 830, 832, 833, 845], "think": [32, 805, 807, 814, 817, 833, 857], "uniqu": [32, 42, 52, 53, 63, 75, 76, 86, 368, 369, 371, 415, 436, 473, 474, 487, 558, 622, 628, 629, 633, 703, 704, 705, 708, 712, 737, 738, 739, 740, 766, 800, 805, 809, 813, 823, 827, 828, 829, 833, 841, 845, 859], "rule": [32, 49, 51, 52, 57, 72, 74, 75, 80, 147, 150, 173, 174, 175, 224, 235, 268, 270, 277, 279, 287, 289, 368, 371, 380, 411, 462, 511, 618, 620, 625, 627, 654, 655, 662, 667, 670, 674, 688, 766, 793, 809, 810, 813, 814, 815, 817, 821, 822, 823, 825, 830, 833, 857], "broadcast": [32, 46, 48, 49, 50, 51, 52, 53, 54, 56, 57, 58, 59, 60, 61, 62, 63, 65, 66, 68, 70, 71, 72, 73, 74, 75, 76, 77, 79, 80, 81, 82, 83, 84, 85, 87, 88, 89, 92, 97, 98, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 121, 122, 123, 124, 125, 126, 127, 128, 130, 131, 132, 133, 136, 137, 138, 139, 140, 141, 143, 144, 147, 148, 149, 209, 215, 216, 217, 218, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 240, 241, 242, 246, 247, 249, 250, 251, 252, 254, 255, 256, 257, 258, 259, 260, 262, 263, 264, 265, 266, 267, 268, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 288, 289, 290, 291, 292, 293, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 323, 329, 330, 331, 332, 333, 334, 337, 339, 341, 343, 345, 346, 347, 348, 352, 360, 362, 365, 368, 369, 370, 371, 374, 375, 380, 386, 387, 388, 390, 391, 392, 393, 394, 395, 396, 400, 401, 403, 404, 405, 406, 409, 411, 416, 418, 419, 427, 428, 431, 432, 434, 443, 444, 445, 446, 448, 449, 455, 459, 462, 467, 475, 476, 477, 478, 480, 482, 484, 486, 490, 493, 494, 496, 497, 498, 500, 501, 511, 512, 513, 514, 517, 518, 519, 520, 521, 529, 530, 534, 535, 536, 541, 542, 551, 565, 566, 603, 604, 607, 609, 610, 611, 612, 614, 617, 618, 619, 620, 622, 623, 624, 625, 626, 627, 630, 631, 632, 633, 635, 636, 637, 638, 639, 640, 641, 642, 643, 644, 645, 646, 647, 648, 650, 653, 654, 655, 656, 657, 658, 660, 661, 662, 663, 665, 666, 668, 669, 670, 671, 672, 674, 676, 677, 679, 681, 682, 683, 684, 685, 686, 687, 688, 689, 690, 691, 692, 693, 694, 695, 697, 698, 699, 700, 702, 725, 726, 727, 728, 729, 731, 732, 733, 734, 736, 740, 741, 745, 746, 748, 749, 750, 751, 752, 753, 754, 755, 756, 764, 766, 793, 813, 815, 817, 818, 819, 830, 831, 835], "elementwis": [32, 52, 60, 75, 83, 294, 296, 355, 360, 625, 630, 680, 725, 823, 831, 835], "must": [32, 40, 46, 48, 49, 50, 51, 52, 53, 54, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 92, 93, 95, 97, 98, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 136, 137, 138, 139, 140, 141, 143, 144, 147, 148, 149, 208, 209, 215, 216, 217, 218, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 240, 241, 242, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 262, 263, 264, 265, 266, 267, 268, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 288, 289, 290, 291, 292, 293, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 309, 319, 320, 323, 324, 325, 326, 329, 330, 331, 332, 333, 335, 337, 339, 341, 343, 345, 346, 347, 348, 352, 355, 360, 362, 365, 368, 369, 370, 371, 374, 375, 378, 380, 382, 384, 386, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 399, 400, 401, 403, 404, 405, 406, 409, 411, 412, 414, 416, 418, 419, 421, 427, 428, 431, 432, 433, 434, 439, 443, 444, 445, 446, 448, 449, 452, 453, 454, 459, 460, 462, 464, 465, 466, 467, 469, 473, 475, 476, 477, 478, 480, 482, 483, 484, 486, 488, 493, 494, 496, 497, 498, 500, 501, 504, 511, 512, 513, 514, 521, 529, 530, 534, 535, 536, 541, 542, 544, 551, 565, 566, 602, 603, 604, 607, 609, 610, 611, 612, 614, 617, 618, 619, 620, 622, 623, 624, 625, 626, 627, 630, 631, 632, 633, 634, 635, 636, 637, 638, 639, 640, 641, 642, 643, 644, 645, 646, 647, 648, 650, 653, 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47, "mutabl": [47, 629, 707, 713, 714, 718, 723, 724, 811], "to_ivi": [47, 70, 629, 719, 826], "leaf": [47, 69, 76, 88, 98, 537, 629, 716, 717, 719, 746, 813, 823, 838], "travers": [47, 70, 629, 710, 718, 813, 815, 819, 835], "lowest": [47, 52, 61, 70, 75, 84, 380, 514, 629, 631, 718, 727, 794, 823, 841, 843, 853, 857, 861], "search": [47, 52, 70, 75, 732, 733, 772, 804, 806, 813, 817, 820, 830, 831, 845], "to_new_backend": 47, "_arraywithcr": [48, 97], "boolean": [48, 49, 51, 52, 53, 59, 62, 65, 69, 71, 72, 74, 75, 76, 82, 85, 88, 97, 98, 118, 120, 122, 123, 124, 130, 147, 163, 165, 167, 168, 171, 187, 197, 205, 211, 225, 226, 227, 228, 229, 230, 262, 263, 264, 265, 329, 330, 344, 365, 369, 371, 426, 435, 441, 452, 453, 454, 460, 462, 464, 465, 466, 469, 473, 480, 482, 488, 523, 526, 537, 544, 547, 548, 552, 553, 554, 555, 556, 557, 558, 567, 570, 573, 574, 576, 577, 601, 616, 617, 618, 619, 620, 622, 624, 627, 628, 629, 632, 635, 650, 690, 691, 692, 694, 696, 697, 699, 701, 703, 704, 716, 734, 735, 736, 748, 750, 764, 765, 766, 767, 772, 783, 813, 815, 823, 827, 830, 833], "alwai": [48, 49, 52, 53, 59, 71, 72, 75, 82, 105, 123, 147, 218, 268, 339, 365, 369, 371, 437, 452, 453, 454, 460, 462, 464, 465, 466, 469, 473, 480, 488, 544, 551, 614, 618, 620, 622, 627, 690, 691, 692, 694, 696, 697, 699, 701, 766, 800, 805, 806, 807, 810, 811, 813, 815, 818, 821, 822, 823, 826, 827, 828, 829, 830, 831, 833, 835, 841, 849], "never": [48, 52, 59, 71, 75, 82, 123, 371, 452, 453, 454, 460, 462, 464, 465, 466, 469, 473, 480, 488, 544, 622, 627, 690, 691, 692, 694, 696, 697, 699, 701, 807, 815, 826, 827, 830], "valueerror": [48, 52, 59, 71, 75, 82, 86, 123, 368, 370, 401, 412, 447, 452, 453, 460, 462, 464, 465, 466, 473, 488, 627, 690, 691, 692, 694, 696, 697, 699, 701, 740, 766, 795, 819], "buffer": [48, 71, 75, 82, 123, 129, 452, 453, 460, 462, 464, 465, 466, 473, 488, 617, 690, 691, 692, 694, 696, 697, 699, 701, 781, 782, 826, 841], "nativedtyp": [48, 49, 52, 56, 57, 61, 62, 65, 71, 75, 80, 84, 85, 88, 121, 122, 123, 125, 126, 127, 129, 130, 131, 132, 133, 135, 136, 137, 138, 143, 144, 146, 147, 152, 153, 154, 155, 156, 157, 158, 159, 164, 165, 169, 171, 173, 177, 187, 306, 307, 308, 309, 310, 311, 312, 327, 334, 349, 362, 365, 375, 380, 497, 498, 499, 500, 501, 511, 512, 513, 514, 517, 520, 617, 618, 624, 625, 631, 632, 634, 635, 647, 682, 727, 728, 729, 732, 733, 743, 745, 746, 751, 753, 779, 815, 816, 822, 831, 835], "datatyp": [48, 52, 69, 71, 75, 123, 131, 135, 152, 173, 177, 368, 415, 617, 618, 759, 831, 849], "nativedevic": [48, 50, 52, 61, 71, 73, 75, 84, 121, 122, 123, 125, 126, 127, 130, 131, 132, 133, 135, 136, 137, 138, 142, 143, 144, 189, 190, 191, 192, 193, 196, 201, 202, 203, 204, 206, 207, 208, 209, 210, 214, 306, 307, 322, 362, 375, 497, 498, 500, 501, 617, 619, 631, 726, 727, 728, 729, 779, 784, 785, 815, 816, 819, 822, 831], "39999998": [48, 122, 123, 617, 633, 738], "5999999": [48, 52, 75, 79, 122, 123, 292, 360, 369, 417, 617, 624, 647, 653], "0999999": [48, 65, 122, 123, 292, 301, 304, 346, 360, 365, 617, 749], "10000038": [48, 122, 123, 617], "90786433e": [48, 122, 123, 617], "310": [48, 122, 123, 617], "copy_arrai": [48, 71, 617], "to_ivy_arrai": [48, 71, 124, 617], "empty_lik": [48, 52, 71, 75, 259, 369, 420, 617, 620], "uniniti": [48, 125, 126, 617, 821], "from_dlpack": [48, 71, 617], "full_lik": [48, 71, 617, 831], "fill_valu": [48, 52, 62, 71, 75, 85, 130, 131, 247, 255, 371, 375, 482, 501, 617, 620, 632, 735, 815, 828, 831], "scalar": [48, 51, 52, 53, 57, 68, 71, 74, 75, 76, 80, 92, 107, 131, 136, 218, 239, 284, 290, 332, 333, 335, 339, 342, 344, 346, 351, 365, 368, 369, 370, 371, 415, 422, 442, 452, 453, 454, 463, 468, 588, 601, 617, 620, 622, 625, 682, 815, 825, 827, 841, 856], "fill": [48, 51, 52, 61, 62, 69, 71, 74, 75, 84, 85, 125, 130, 131, 133, 136, 137, 138, 143, 144, 269, 307, 362, 369, 371, 375, 426, 430, 435, 441, 463, 482, 483, 498, 500, 501, 617, 620, 631, 632, 727, 735, 779, 805, 828], "000123": [48, 131, 617], "stop": [48, 52, 54, 71, 75, 77, 121, 132, 133, 208, 369, 435, 441, 567, 604, 607, 609, 610, 611, 612, 617, 619, 622, 623, 628, 629, 703, 704, 705, 717, 784, 822, 825, 833, 835, 841, 856], "num": [48, 71, 132, 133, 617, 764, 807, 822, 835], "endpoint": [48, 71, 132, 133, 617, 779, 822], "logspac": [48, 71, 617, 835], "log": [48, 51, 52, 57, 71, 74, 75, 80, 113, 133, 258, 260, 273, 294, 295, 347, 354, 360, 365, 370, 375, 444, 446, 447, 497, 614, 617, 620, 673, 764, 766, 767, 776, 807, 813, 814, 817, 823, 826, 827, 828, 830, 832, 833, 835, 838], "sequenc": [48, 52, 56, 57, 59, 65, 66, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 79, 80, 81, 82, 84, 85, 86, 87, 88, 89, 98, 105, 106, 107, 108, 109, 110, 111, 112, 113, 127, 129, 131, 133, 136, 138, 144, 148, 150, 163, 167, 168, 175, 209, 215, 216, 217, 218, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 240, 241, 242, 246, 247, 249, 250, 251, 252, 254, 255, 256, 257, 258, 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[48, 71, 134, 617], "dimension": [48, 51, 52, 57, 59, 62, 65, 66, 69, 71, 74, 75, 80, 82, 88, 89, 97, 121, 127, 129, 134, 142, 287, 322, 329, 330, 362, 365, 368, 369, 371, 380, 395, 396, 400, 401, 411, 412, 419, 452, 453, 454, 458, 463, 464, 509, 521, 617, 620, 625, 627, 632, 635, 636, 655, 656, 662, 665, 668, 670, 671, 681, 682, 696, 732, 733, 735, 748, 749, 750, 751, 752, 753, 754, 755, 756, 823, 825, 830, 833, 835, 853, 856, 863], "repres": [48, 51, 52, 56, 57, 74, 75, 79, 80, 95, 120, 134, 136, 159, 217, 218, 221, 224, 233, 235, 242, 268, 281, 285, 286, 310, 324, 325, 326, 342, 359, 362, 365, 367, 368, 369, 370, 371, 374, 375, 378, 410, 414, 428, 440, 442, 447, 474, 485, 490, 491, 492, 497, 503, 510, 546, 616, 617, 618, 620, 622, 624, 625, 647, 648, 662, 670, 673, 674, 766, 779, 783, 794, 806, 810, 815, 833, 837, 853, 854, 857], "coordin": [48, 51, 62, 74, 75, 85, 134, 142, 223, 285, 314, 315, 322, 342, 362, 376, 502, 617, 620, 632, 735], "conserv": [48, 134, 617], "cartesian": 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405, 406, 409, 617, 620, 780, 826], "round": [51, 52, 74, 75, 92, 94, 95, 96, 218, 231, 235, 241, 242, 268, 282, 288, 289, 338, 365, 620, 803, 805, 806, 807, 809, 810, 811, 813, 814, 815, 816, 817, 818, 819, 821, 822, 823, 824, 825, 826, 827, 828, 830, 831, 833, 835, 836, 837, 838, 839, 840, 845, 846, 847], "416": [51, 232, 620], "540": [51, 232], "990": [51, 232], "cosh": [51, 74, 232, 620], "deg2rad": [51, 74, 620], "convers": [51, 52, 75, 234, 274, 567, 577, 622, 781, 782, 805, 834, 836, 840, 841, 843, 847, 855, 862], "180": [51, 74, 234, 274, 620], "270": [51, 74, 234, 274, 620], "360": [51, 74, 234, 274, 620, 814], "dividend": [51, 74, 235, 242, 277, 289, 620], "divisor": [51, 52, 54, 65, 74, 75, 77, 88, 235, 242, 245, 246, 277, 289, 368, 371, 386, 387, 388, 460, 469, 488, 603, 604, 609, 620, 623, 635, 752, 754, 780, 784], "375": [51, 236, 271], "erf": [51, 74, 337, 365, 620], "exponenti": [51, 52, 74, 75, 237, 238, 240, 260, 273, 290, 299, 360, 369, 431, 620], "gauss": [51, 74, 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"isfinite": [[249, "isfinite"]], "logical_xor": [[265, "logical-xor"]], "exp2": [[239, "exp2"]], "fmod": [[244, "fmod"]], "deg2rad": [[234, "deg2rad"]], "logaddexp2": [[261, "logaddexp2"]], "negative": [[270, "negative"]], "less": [[254, "less"]], "logical_or": [[264, "logical-or"]], "logical_not": [[263, "logical-not"]], "nan_to_num": [[269, "nan-to-num"]], "multiply": [[268, "multiply"]], "minimum": [[267, "minimum"]], "lcm": [[253, "lcm"]], "positive": [[272, "positive"]], "erf": [[237, "erf"]], "log10": [[257, "log10"]], "maximum": [[266, "maximum"]], "not_equal": [[271, "not-equal"]], "pow": [[273, "pow"]], "fmin": [[243, "fmin"]], "less_equal": [[255, "less-equal"]], "expm1": [[240, "expm1"]], "logaddexp": [[260, "logaddexp"]], "logical_and": [[262, "logical-and"]], "log": [[256, "log"]], "real": [[275, "real"]], "log1p": [[258, "log1p"]], "greater": [[246, "greater"]], "bitwise_xor": [[230, "bitwise-xor"]], "divide": [[235, "divide"]], "atanh": [[224, "atanh"]], "add": [[218, "add"]], "function_supported_devices": [[194, "function-supported-devices"]], "bitwise_and": [[225, "bitwise-and"]], "set_soft_device_mode": [[205, "set-soft-device-mode"]], "bitwise_right_shift": [[229, "bitwise-right-shift"]], "num_cpu_cores": [[199, "num-cpu-cores"]], "bitwise_invert": [[226, "bitwise-invert"]], "set_split_factor": [[206, "set-split-factor"]], "num_ivy_arrays_on_dev": [[201, "num-ivy-arrays-on-dev"]], "clear_cached_mem_on_dev": [[190, "clear-cached-mem-on-dev"]], "asin": [[220, "asin"]], "tpu_is_available": [[211, "tpu-is-available"]], "valid_dtype": [[187, "valid-dtype"]], "bitwise_left_shift": [[227, "bitwise-left-shift"]], "abs": [[215, "abs"]], "acosh": [[217, "acosh"]], "asinh": [[221, "asinh"]], "unset_default_int_dtype": [[185, "unset-default-int-dtype"]], "bitwise_or": [[228, "bitwise-or"]], "acos": [[216, "acos"]], "dev_util": [[193, "dev-util"]], "to_device": [[209, "to-device"]], "unset_default_float_dtype": [[184, "unset-default-float-dtype"]], "total_mem_on_dev": [[210, "total-mem-on-dev"]], "unset_soft_device_mode": [[213, "unset-soft-device-mode"]], "used_mem_on_dev": [[214, "used-mem-on-dev"]], "as_native_dev": [[189, "as-native-dev"]], "atan2": [[223, "atan2"]], "split_factor": [[207, "split-factor"]], "function_unsupported_devices": [[195, "function-unsupported-devices"]], "get_all_ivy_arrays_on_dev": [[196, "get-all-ivy-arrays-on-dev"]], "percent_used_mem_on_dev": [[202, "percent-used-mem-on-dev"]], "as_ivy_dev": [[188, "as-ivy-dev"]], "num_gpus": [[200, "num-gpus"]], "unset_default_uint_dtype": [[186, "unset-default-uint-dtype"]], "dev": [[192, "dev"]], "unset_default_device": [[212, "unset-default-device"]], "default_device": [[191, "default-device"]], "print_all_ivy_arrays_on_dev": [[203, "print-all-ivy-arrays-on-dev"]], "gpu_is_available": [[197, "gpu-is-available"]], "angle": [[219, "angle"]], "atan": [[222, "atan"]], "handle_soft_device_variable": [[198, "handle-soft-device-variable"]], "split_func_call": [[208, "split-func-call"]], "set_default_device": [[204, "set-default-device"]], "Conversions": [[70, "module-ivy.data_classes.container.conversions"], [47, "module-ivy.data_classes.array.conversions"]], "Image": [[55, "module-ivy.data_classes.array.image"], [78, "module-ivy.data_classes.container.image"]], "Wrapping": [[90, "module-ivy.data_classes.container.wrapping"], [67, "module-ivy.data_classes.array.wrapping"]], "3.0: Perceiver": [[36, "3.0:-Perceiver"]], "# Ivy Bert Demo": [[4, "#-Ivy-Bert-Demo"]], "Install the dependecies": [[4, "Install-the-dependecies"]], "Import the modules": [[4, "Import-the-modules"]], "Data Preparation": [[4, "Data-Preparation"], [3, "Data-Preparation"], [5, "Data-Preparation"], [7, "Data-Preparation"]], "Ivy inference with Sequence Classification": [[4, "Ivy-inference-with-Sequence-Classification"]], "Ivy model inference with tensorflow": [[4, "Ivy-model-inference-with-tensorflow"]], "Ivy model inference with Jax": [[4, "Ivy-model-inference-with-Jax"]], "Ivy model inference with torch": [[4, "Ivy-model-inference-with-torch"]], "3.1: Stable Diffusion": [[37, "3.1:-Stable-Diffusion"]], "End-to-End Training Pipeline in Ivy": [[42, "End-to-End-Training-Pipeline-in-Ivy"]], "Importing libraries": [[42, "Importing-libraries"]], "Let\u2019s build the pipeline with a Tensorflow backend": [[42, "Let's-build-the-pipeline-with-a-Tensorflow-backend"]], "We are using MNIST dataset for this Tutorial": [[42, "We-are-using-MNIST-dataset-for-this-Tutorial"]], "Temporary Dataset and Dynamic loader": [[42, "Temporary-Dataset-and-Dynamic-loader"]], "Defining the Ivy Network": [[42, "Defining-the-Ivy-Network"]], "Training Loop with utility functions": [[42, "Training-Loop-with-utility-functions"]], "Plotting the training metrics": [[42, "Plotting-the-training-metrics"]], "Save the trained Model": [[42, "Save-the-trained-Model"]], "Guides": [[10, "guides"], [15, "guides"]], "1.1: Framework Selection": [[32, "1.1:-Framework-Selection"]], "Unify": [[32, "Unify"], [31, "Unify"], [21, "Unify"], [22, "Unify"], [33, "Unify"]], "Compile": [[32, "Compile"], [31, "Compile"], [33, "Compile"]], "Transpile": [[32, "Transpile"], [31, "Transpile"], [21, "Transpile"], [22, "Transpile"], [33, "Transpile"]], "Transpiling a haiku model to build on top": [[12, "Transpiling-a-haiku-model-to-build-on-top"]], "Demo: Transpiling DeepMind\u2019s PerceiverIO": [[40, "Demo:-Transpiling-DeepMind's-PerceiverIO"]], "Table of Contents": [[40, "Table-of-Contents"]], "Defining the model": [[40, "Defining-the-model"]], "Model construction": [[40, "Model-construction"]], "Some helper functions": [[40, "Some-helper-functions"]], "Transpiling the model": [[40, "Transpiling-the-model"]], "PyTorch pipeline": [[40, "PyTorch-pipeline"]], "Dataset download": [[40, "Dataset-download"]], "DataLoader": [[40, "DataLoader"]], "Training": [[40, "Training"]], "Compilation of a Basic Function": [[39, "Compilation-of-a-Basic-Function"]], "Installs \ud83d\udcbe": [[39, "Installs-\ud83d\udcbe"], [38, "Installs-\ud83d\udcbe"]], "Imports \ud83d\udec3": [[39, "Imports-\ud83d\udec3"], [38, "Imports-\ud83d\udec3"]], "Import Ivy compiler": [[39, "Import-Ivy-compiler"]], "Function compilation \ud83d\udee0": [[39, "Function-compilation-\ud83d\udee0"]], "Set backend": [[39, "Set-backend"]], "Sample input": [[39, "Sample-input"]], "Define function to compile": [[39, "Define-function-to-compile"]], "Compile the function": [[39, "Compile-the-function"]], "Check results": [[39, "Check-results"], [39, "id1"]], "Compiling simple neural network \ud83e\udde0": [[39, "Compiling-simple-neural-network-\ud83e\udde0"]], "Define Model": [[39, "Define-Model"], [38, "Define-Model"]], "Create model": [[39, "Create-model"]], "Define input": [[39, "Define-input"]], "Compile network": [[39, "Compile-network"]], "Developing a convolutional network using Ivy": [[14, "Developing-a-convolutional-network-using-Ivy"]], "Basic Operations with Ivy": [[38, "Basic-Operations-with-Ivy"]], "Ivy as a Unified ML Framework \ud83d\udd00": [[38, "Ivy-as-a-Unified-ML-Framework-\ud83d\udd00"]], "Change frameworks by one line of code \u261d": [[38, "Change-frameworks-by-one-line-of-code-\u261d"]], "No need to worry about data types \ud83c\udfa8": [[38, "No-need-to-worry-about-data-types-\ud83c\udfa8"]], "No need to worry about framework differences \ud83d\udcb1": [[38, "No-need-to-worry-about-framework-differences-\ud83d\udcb1"]], "Unifying them all! \ud83c\udf72": [[38, "Unifying-them-all!-\ud83c\udf72"]], "Ivy as a standalone ML framework \ud83c\udf00": [[38, "Ivy-as-a-standalone-ML-framework-\ud83c\udf00"]], "Set Backend Framework": [[38, "Set-Backend-Framework"]], "Create Model": [[38, "Create-Model"]], "Create Optimizer": [[38, "Create-Optimizer"]], "Input and Target": [[38, "Input-and-Target"]], "Loss Function": [[38, "Loss-Function"]], "Training Loop": [[38, "Training-Loop"]], "1.3: Dynamic vs Static": [[34, "1.3:-Dynamic-vs-Static"]], "Dynamic": [[34, "Dynamic"]], "Static": [[34, "Static"]], "ToDo: explain via examples why dynamic mode is set to True by default when transpiling to and from numpy and torch, but set to False by default when transpiling to and from tensorflow and jax.": [[34, "ToDo:-explain-via-examples-why-dynamic-mode-is-set-to-True-by-default-when-transpiling-to-and-from-numpy-and-torch,-but-set-to-False-by-default-when-transpiling-to-and-from-tensorflow-and-jax."]], "1.0: Lazy vs Eager": [[31, "1.0:-Lazy-vs-Eager"]], "Tutorials And Examples": [[15, "tutorials-and-examples"]], "Learn the basics": [[15, "learn-the-basics"], [16, "learn-the-basics"]], "Examples and Demos": [[15, "examples-and-demos"], [2, "examples-and-demos"]], "Lazy vs Eager": [[21, "Lazy-vs-Eager"]], "Trace": [[21, "Trace"], [22, "Trace"]], "Transpiling a Tensorflow model to build on top": [[13, "Transpiling-a-Tensorflow-model-to-build-on-top"]], "Ivy as a Transpiler Introduction": [[44, "Ivy-as-a-Transpiler-Introduction"]], "To use the transpiler:": [[44, "To-use-the-transpiler:"]], "Transpiler Interface": [[44, "Transpiler-Interface"]], "Telemetry": [[44, "Telemetry"]], "1. Transpile Functions \ud83d\udd22": [[44, "1.-Transpile-Functions-\ud83d\udd22"]], "2. Transpile Libraries \ud83d\udcda": [[44, "2.-Transpile-Libraries-\ud83d\udcda"]], "3. Transpile Models \ud83c\udf10": [[44, "3.-Transpile-Models-\ud83c\udf10"]], "Accelerating XGBoost with JAX": [[9, "Accelerating-XGBoost-with-JAX"]], "Imports": [[9, "Imports"], [5, "Imports"], [7, "Imports"]], "Tests": [[9, "Tests"]], "Loading the Data": [[9, "Loading-the-Data"]], "Comparing xgb_frontend.XGBClassifier and xgb.XGBClassifier": [[9, "Comparing-xgb_frontend.XGBClassifier-and-xgb.XGBClassifier"]], "JAX backend": [[9, "JAX-backend"]], "Tensorflow backend": [[9, "Tensorflow-backend"]], "PyTorch backend": [[9, "PyTorch-backend"]], "More exhaustive example": [[9, "More-exhaustive-example"]], "Evaluating Training Time vs. Number of Boosting Rounds": [[9, "Evaluating-Training-Time-vs.-Number-of-Boosting-Rounds"]], "Training Time vs. Fractions of Data": [[9, "Training-Time-vs.-Fractions-of-Data"]], "Comparison of Metrics": [[9, "Comparison-of-Metrics"]], "Transpile code": [[20, "Transpile-code"]], "Transpiling a PyTorch model to build on top": [[11, "Transpiling-a-PyTorch-model-to-build-on-top"]], "Accelerating PyTorch models with JAX": [[8, "Accelerating-PyTorch-models-with-JAX"]], "Ivy AlexNet demo": [[3, "Ivy-AlexNet-demo"]], "Installation": [[3, "Installation"], [7, "Installation"]], "Ivy AlexNet inference in Torch": [[3, "Ivy-AlexNet-inference-in-Torch"]], "TensorFlow inference": [[3, "TensorFlow-inference"]], "JAX inference": [[3, "JAX-inference"]], "Appendix (Ivy code for AlexNet implementation)": [[3, "Appendix-(Ivy-code-for-AlexNet-implementation)"]], "0.2: Transpile": [[30, "0.2:-Transpile"]], "Transpile any model": [[24, "Transpile-any-model"]], "Round up": [[24, "Round-up"]], "Transpile any library": [[23, "Transpile-any-library"]], "TO REPLACE: Title": [[1, "TO-REPLACE:-Title"]], "How to use decorators": [[22, "How-to-use-decorators"]], "Demos": [[0, "demos"]], "Creating a Notebook for Demo": [[0, "creating-a-notebook-for-demo"]], "Unify code": [[18, "Unify-code"]], "1.2: As a Decorator": [[33, "1.2:-As-a-Decorator"]], "Write a model using Ivy": [[25, "Write-a-model-using-Ivy"]], "Quickstart": [[27, "Quickstart"]], "Get familiar with Ivy": [[27, "Get-familiar-with-Ivy"]], "Functional API": [[27, "Functional-API"]], "Stateful API": [[27, "Stateful-API"]], "Tracing code": [[27, "Tracing-code"]], "Any function": [[27, "Any-function"], [26, "Any-function"]], "Any library": [[27, "Any-library"], [26, "Any-library"]], "Any model": [[27, "Any-model"], [26, "Any-model"]], "HuggingFace Tensorflow DeiT": [[43, "HuggingFace-Tensorflow-DeiT"]], "Graph can be visualized and displayed as html file on browser": [[43, "Graph-can-be-visualized-and-displayed-as-html-file-on-browser"]], "Trace code": [[19, "Trace-code"]], "0.1: Compile": [[29, "0.1:-Compile"]], "2.0: Kornia": [[35, "2.0:-Kornia"]], "Resnet 18": [[45, "Resnet-18"]], "Accelerating MMPreTrain models with JAX": [[6, "Accelerating-MMPreTrain-models-with-JAX"]], "0.0: Unify": [[28, "0.0:-Unify"]], "Deepmind PerceiverIO on GPU": [[41, "Deepmind-PerceiverIO-on-GPU"]], "Install Python3.8 and setup the kernel": [[41, "Install-Python3.8-and-setup-the-kernel"]], "Clone the ivy and ivy-models repo": [[41, "Clone-the-ivy-and-ivy-models-repo"]], "Install ivy and ivy_models from the repos": [[41, "Install-ivy-and-ivy_models-from-the-repos"]], "Run the demo\u2026": [[41, "Run-the-demo..."]], "\u2026with torch backend": [[41, "...with-torch-backend"]], "\u2026.with tensorflow backend": [[41, "....with-tensorflow-backend"]], "\u2026with jax backend": [[41, "...with-jax-backend"]], "\u2026with numpy backend": [[41, "...with-numpy-backend"]], "Image Segmentation with Ivy UNet": [[5, "Image-Segmentation-with-Ivy-UNet"]], "Custom Preprocessing": [[5, "Custom-Preprocessing"]], "Load the image example \ud83d\uddbc\ufe0f": [[5, "Load-the-image-example-\ud83d\uddbc\ufe0f"], [7, "Load-the-image-example-\ud83d\uddbc\ufe0f"]], "Visualise image": [[5, "Visualise-image"], [7, "Visualise-image"]], "Model Inference": [[5, "Model-Inference"]], "Initializing Native Torch UNet": [[5, "Initializing-Native-Torch-UNet"]], "Initializing Ivy UNet with Pretrained Weights \u2b07\ufe0f": [[5, "Initializing-Ivy-UNet-with-Pretrained-Weights-\u2b07\ufe0f"]], "Custom masking function": [[5, "Custom-masking-function"]], "Use the model to segment your images \ud83d\ude80": [[5, "Use-the-model-to-segment-your-images-\ud83d\ude80"]], "TensorFlow backend": [[5, "TensorFlow-backend"]], "JAX": [[5, "JAX"]], "Appendix: the Ivy native implementation of UNet": [[5, "Appendix:-the-Ivy-native-implementation-of-UNet"]], "ODSC Ivy Demo": [[26, "ODSC-Ivy-Demo"]], "Ivy Backend Handler": [[26, "Ivy-Backend-Handler"], [17, "Ivy-Backend-Handler"]], "Data Structures": [[26, "Data-Structures"], [17, "Data-Structures"]], "Ivy Functional API": [[26, "Ivy-Functional-API"], [17, "Ivy-Functional-API"]], "Graph Tracer": [[26, "Graph-Tracer"]], "Using Ivy ResNet": [[7, "Using-Ivy-ResNet"]], "Prepare the set of labels": [[7, "Prepare-the-set-of-labels"]], "Model Inference ResNet34": [[7, "Model-Inference-ResNet34"]], "Initializing Native Torch ResNet34": [[7, "Initializing-Native-Torch-ResNet34"]], "Initializing Ivy ResNet34 with Pretrained Weights \u2b07\ufe0f": [[7, "Initializing-Ivy-ResNet34-with-Pretrained-Weights-\u2b07\ufe0f"]], "Use the model to classify your images \ud83d\ude80": [[7, "Use-the-model-to-classify-your-images-\ud83d\ude80"], [7, "id1"]], "Model Inference ResNet50": [[7, "Model-Inference-ResNet50"]], "Initializing Native Torch ResNet50": [[7, "Initializing-Native-Torch-ResNet50"]], "Initializing Ivy ResNet50 with Pretrained Weights \u2b07\ufe0f": [[7, "Initializing-Ivy-ResNet50-with-Pretrained-Weights-\u2b07\ufe0f"]], "Write Ivy code": [[17, "Write-Ivy-code"]], "Contents": [[17, "Contents"]], "Installing Ivy": [[17, "Installing-Ivy"]], "Importing Ivy": [[17, "Importing-Ivy"]]}, "indexentries": {"_arraywithactivations (class in ivy.data_classes.array.activations)": [[46, 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851, 854], "resnet": [2, 8, 15, 26, 849, 850], "imag": [2, 3, 6, 8, 11, 15, 23, 26, 27, 40, 41, 42, 43, 44, 45, 51, 52, 56, 74, 75, 79, 97, 215, 216, 217, 218, 221, 224, 233, 236, 238, 240, 249, 250, 251, 256, 258, 271, 278, 279, 281, 282, 286, 368, 386, 387, 403, 404, 405, 407, 534, 620, 622, 624, 637, 638, 639, 640, 641, 644, 645, 646, 780, 800, 806, 820, 833, 835, 836, 838, 840, 842, 849, 850, 856], "classif": [2, 3, 7, 9, 15, 40, 800, 856], "acceler": [2, 15, 800, 815, 827, 854, 858, 859, 860, 861], "pytorch": [2, 3, 4, 5, 6, 7, 10, 12, 13, 15, 16, 24, 26, 27, 38, 45, 278, 329, 330, 365, 620, 784, 800, 804, 805, 810, 815, 816, 819, 822, 823, 826, 827, 828, 833, 835, 840, 841, 843, 846, 847, 849, 850, 857, 859, 860, 862, 863], "jax": [2, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 26, 27, 28, 29, 30, 32, 38, 40, 44, 46, 51, 52, 53, 63, 68, 74, 75, 76, 105, 106, 107, 108, 109, 110, 111, 112, 113, 286, 290, 294, 295, 297, 342, 360, 365, 380, 521, 551, 583, 602, 614, 620, 622, 633, 737, 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[2, 6, 8, 9, 15, 19, 29, 31, 32, 41, 43, 45, 48, 52, 53, 56, 59, 71, 75, 76, 79, 82, 121, 123, 126, 130, 131, 135, 138, 144, 153, 154, 155, 156, 157, 306, 307, 368, 375, 403, 499, 545, 579, 617, 618, 622, 624, 627, 647, 694, 789, 790, 808, 811, 815, 816, 830, 835, 840, 850, 854, 855, 858, 860], "mmpretrain": [2, 15], "segment": [2, 15, 52, 75, 324, 325, 326, 362, 812, 817], "unet": [2, 15], "alexnet": [2, 15], "In": [2, 3, 4, 11, 13, 15, 17, 19, 20, 21, 22, 23, 24, 26, 27, 28, 29, 30, 31, 32, 33, 34, 38, 40, 45, 50, 52, 53, 59, 73, 75, 76, 82, 92, 93, 202, 209, 210, 214, 218, 235, 236, 242, 250, 251, 268, 271, 277, 279, 368, 371, 374, 391, 392, 393, 413, 452, 453, 454, 460, 462, 464, 465, 466, 467, 469, 473, 479, 480, 488, 490, 492, 524, 544, 551, 569, 619, 620, 622, 625, 627, 631, 673, 690, 691, 692, 694, 696, 697, 699, 701, 729, 800, 805, 806, 807, 809, 811, 812, 813, 814, 815, 816, 817, 818, 819, 820, 821, 822, 823, 824, 826, 827, 828, 830, 831, 832, 833, 837, 838, 839, 840, 841, 845, 847, 849, 850, 851, 852, 854, 856, 857, 859, 862], "we": [2, 3, 4, 5, 6, 7, 8, 9, 11, 13, 15, 17, 18, 19, 20, 21, 22, 23, 24, 26, 27, 28, 29, 30, 31, 32, 33, 34, 38, 39, 40, 43, 44, 45, 52, 57, 58, 59, 67, 75, 80, 81, 90, 92, 93, 113, 357, 367, 371, 452, 453, 454, 460, 462, 464, 465, 466, 469, 473, 480, 484, 488, 534, 544, 583, 605, 606, 608, 613, 614, 622, 623, 625, 626, 627, 668, 684, 690, 691, 692, 694, 696, 697, 699, 701, 776, 782, 789, 794, 800, 801, 803, 804, 805, 806, 807, 808, 809, 810, 811, 812, 813, 814, 815, 816, 817, 818, 819, 820, 821, 822, 823, 824, 825, 826, 827, 828, 829, 831, 833, 835, 836, 837, 838, 839, 840, 841, 842, 843, 844, 845, 846, 847, 849, 850, 851, 852, 856, 857, 861, 862], "show": [2, 3, 4, 7, 15, 21, 26, 27, 28, 29, 31, 38, 40, 42, 43, 568, 577, 599, 622, 800, 805, 806, 807, 812, 814, 817, 821, 826, 827, 830, 832, 841, 849, 856], "how": [2, 3, 4, 5, 6, 8, 11, 13, 15, 16, 17, 18, 19, 21, 23, 24, 26, 27, 28, 29, 31, 32, 33, 34, 38, 41, 44, 45, 46, 51, 52, 68, 74, 75, 95, 105, 106, 107, 108, 109, 110, 111, 112, 113, 235, 268, 286, 290, 294, 295, 297, 360, 370, 371, 442, 457, 482, 483, 614, 620, 776, 779, 780, 781, 782, 800, 801, 802, 803, 804, 806, 807, 808, 809, 810, 811, 813, 814, 815, 816, 817, 818, 819, 821, 822, 824, 825, 826, 827, 828, 831, 832, 833, 834, 836, 837, 838, 839, 840, 841, 845, 847, 852, 856], "written": [2, 3, 4, 15, 17, 26, 27, 40, 53, 371, 463, 806, 809, 810, 818, 821, 822, 826, 827, 831, 835, 837, 840, 841, 845, 850, 854, 856, 860, 862, 863], "xgboost": [2, 15], "video": [3, 5, 6, 7, 8, 11, 13, 17, 18, 19, 20, 21, 22, 23, 24, 27, 800, 801, 806, 807, 809, 810, 811, 813, 814, 815, 816, 817, 818, 819, 821, 822, 823, 824, 825, 826, 827, 828, 830, 831, 833, 842, 854], "tutori": [3, 5, 6, 7, 8, 11, 13, 17, 18, 19, 20, 21, 22, 23, 24, 27, 800, 807, 827, 842], "nativ": [3, 4, 8, 17, 21, 22, 23, 24, 26, 27, 47, 48, 49, 50, 53, 70, 73, 76, 97, 101, 135, 145, 146, 152, 153, 154, 155, 156, 157, 171, 174, 189, 190, 191, 192, 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805, 806, 808, 809, 810, 811, 812, 814, 815, 816, 817, 819, 820, 822, 823, 824, 826, 827, 830, 831, 833, 834, 835, 837, 840, 841, 842, 843, 845, 846, 847, 848, 849, 850, 851, 852, 853, 854, 855, 857, 860], "sinc": [3, 5, 7, 23, 24, 26, 27, 40, 42, 52, 75, 93, 365, 800, 802, 806, 807, 809, 810, 811, 812, 813, 814, 815, 816, 819, 826, 827, 841, 846, 856, 862], "want": [3, 5, 7, 8, 9, 11, 13, 15, 17, 18, 19, 20, 21, 22, 23, 24, 26, 27, 39, 40, 42, 52, 67, 75, 90, 235, 268, 371, 462, 620, 782, 800, 801, 802, 805, 806, 807, 812, 814, 816, 819, 821, 823, 824, 825, 826, 830, 833, 838, 839, 840, 841, 842, 846, 850], "after": [3, 4, 5, 6, 7, 8, 26, 27, 41, 52, 53, 54, 56, 60, 69, 75, 76, 77, 79, 83, 181, 282, 298, 302, 350, 360, 365, 368, 369, 371, 390, 391, 392, 393, 410, 414, 433, 463, 474, 551, 604, 607, 609, 610, 611, 618, 620, 622, 623, 624, 629, 630, 637, 638, 639, 640, 642, 644, 646, 647, 717, 725, 784, 789, 800, 805, 806, 807, 809, 811, 812, 814, 815, 817, 819, 822, 825, 828, 830, 834, 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110, 111, 112, 113, 121, 128, 132, 139, 142, 149, 168, 175, 218, 223, 225, 227, 228, 229, 230, 235, 236, 240, 242, 246, 247, 254, 255, 258, 260, 262, 264, 265, 268, 271, 273, 277, 284, 286, 289, 290, 294, 295, 297, 322, 329, 330, 360, 362, 365, 369, 370, 371, 418, 444, 482, 614, 617, 618, 620, 625, 632, 633, 635, 636, 655, 668, 671, 674, 681, 682, 733, 737, 738, 739, 740, 748, 749, 750, 751, 752, 753, 754, 755, 756, 776, 800, 801, 803, 805, 806, 807, 809, 810, 812, 813, 814, 815, 816, 817, 820, 821, 822, 823, 827, 828, 830, 833, 835, 837, 838, 841, 845, 852], "5": [3, 4, 5, 6, 7, 8, 9, 11, 19, 21, 22, 23, 24, 26, 27, 38, 40, 41, 42, 45, 46, 48, 49, 50, 51, 52, 53, 54, 56, 57, 59, 60, 61, 62, 63, 64, 65, 68, 71, 72, 73, 74, 75, 76, 77, 79, 80, 82, 83, 84, 85, 86, 87, 88, 92, 97, 98, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 117, 118, 121, 122, 123, 129, 131, 132, 133, 134, 135, 136, 137, 138, 143, 144, 148, 149, 150, 154, 158, 160, 168, 170, 175, 192, 201, 206, 209, 215, 217, 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7, 8, 9, 11, 13, 17, 20, 21, 23, 24, 26, 27, 31, 32, 33, 40, 41, 42, 43, 45, 47, 48, 49, 50, 51, 52, 53, 54, 56, 57, 58, 59, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 92, 93, 95, 97, 98, 105, 106, 107, 108, 109, 110, 111, 112, 113, 118, 120, 123, 124, 126, 128, 129, 130, 131, 132, 133, 134, 135, 136, 138, 140, 141, 142, 144, 147, 148, 149, 150, 151, 158, 160, 161, 162, 163, 166, 167, 168, 169, 170, 171, 172, 175, 187, 191, 192, 194, 195, 199, 202, 203, 204, 205, 209, 211, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 240, 241, 242, 246, 247, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 288, 289, 290, 291, 292, 293, 295, 296, 297, 298, 299, 300, 301, 303, 304, 305, 306, 307, 308, 309, 310, 311, 312, 317, 318, 319, 320, 321, 322, 323, 327, 328, 329, 330, 331, 332, 334, 336, 343, 344, 349, 350, 351, 352, 353, 354, 355, 356, 362, 365, 366, 368, 369, 370, 371, 374, 380, 382, 383, 384, 386, 387, 388, 390, 391, 392, 393, 394, 395, 403, 404, 405, 406, 410, 411, 413, 414, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 428, 429, 430, 431, 432, 433, 434, 435, 436, 437, 438, 439, 440, 441, 442, 443, 444, 445, 446, 447, 448, 449, 452, 453, 454, 458, 459, 460, 461, 462, 464, 465, 466, 469, 470, 472, 473, 474, 475, 476, 477, 478, 479, 480, 481, 482, 483, 484, 487, 488, 489, 490, 491, 492, 493, 494, 495, 496, 498, 503, 504, 510, 511, 512, 513, 514, 516, 517, 518, 519, 520, 521, 523, 526, 527, 529, 530, 533, 534, 535, 536, 537, 538, 539, 540, 541, 542, 544, 545, 547, 549, 550, 551, 553, 554, 555, 557, 558, 565, 566, 567, 570, 573, 574, 576, 577, 579, 580, 581, 583, 585, 587, 588, 590, 595, 596, 598, 599, 601, 604, 605, 607, 609, 610, 611, 612, 614, 616, 617, 618, 619, 620, 622, 623, 624, 625, 626, 627, 628, 629, 631, 632, 633, 634, 635, 636, 637, 638, 639, 640, 641, 642, 643, 646, 647, 648, 649, 650, 653, 654, 655, 656, 657, 658, 659, 660, 661, 662, 663, 664, 665, 666, 667, 668, 669, 670, 672, 673, 674, 675, 676, 677, 678, 679, 680, 681, 682, 683, 684, 685, 686, 687, 688, 689, 690, 691, 692, 693, 694, 695, 696, 697, 698, 699, 700, 701, 702, 703, 704, 705, 706, 707, 712, 713, 714, 716, 717, 718, 719, 723, 724, 726, 727, 728, 729, 731, 732, 733, 734, 735, 736, 737, 738, 739, 740, 741, 742, 743, 744, 745, 746, 747, 748, 749, 750, 751, 752, 753, 754, 755, 756, 759, 761, 764, 765, 766, 767, 769, 780, 781, 782, 783, 784, 786, 789, 791, 793, 794, 798, 800, 803, 806, 811, 813, 814, 815, 816, 817, 819, 820, 822, 823, 824, 826, 827, 828, 830, 832, 833, 835, 838, 839, 840, 849, 850], "set_backend": [3, 4, 5, 7, 9, 17, 18, 19, 20, 21, 22, 26, 27, 29, 30, 31, 32, 33, 39, 41, 42, 43, 51, 53, 67, 74, 76, 162, 171, 189, 190, 204, 206, 211, 219, 527, 551, 618, 619, 622, 628, 704, 705, 789, 800, 809, 811, 815, 816, 823, 824, 825, 835, 837, 840, 849, 850, 851], "ivy_model": [3, 4, 5, 7, 43], "ivy_alexnet": 3, "order": [3, 20, 30, 32, 40, 43, 45, 48, 52, 53, 56, 57, 59, 63, 64, 69, 75, 79, 80, 82, 86, 87, 92, 97, 98, 122, 123, 134, 142, 223, 242, 285, 322, 342, 362, 365, 368, 369, 371, 374, 378, 413, 418, 421, 422, 423, 424, 425, 429, 433, 435, 438, 441, 464, 465, 466, 471, 472, 484, 490, 491, 492, 495, 504, 617, 620, 624, 625, 627, 628, 632, 633, 634, 638, 639, 640, 641, 642, 643, 646, 659, 660, 666, 675, 676, 680, 682, 691, 694, 703, 704, 735, 737, 738, 739, 740, 741, 743, 744, 761, 783, 785, 794, 800, 805, 806, 807, 810, 811, 813, 814, 815, 816, 817, 818, 819, 821, 822, 823, 827, 828, 829, 830, 831, 832, 833, 838, 840, 841, 845, 852, 855, 856, 857, 859, 862], "quick": [3, 15, 27, 807, 808, 828, 839], "call": [3, 6, 11, 13, 17, 19, 20, 21, 22, 23, 26, 27, 29, 30, 31, 32, 33, 40, 44, 52, 67, 72, 75, 90, 92, 98, 117, 167, 168, 208, 369, 380, 433, 518, 569, 575, 589, 605, 606, 608, 616, 619, 622, 623, 625, 629, 673, 706, 712, 716, 717, 761, 772, 780, 781, 782, 784, 789, 794, 800, 805, 806, 807, 810, 811, 813, 814, 815, 816, 817, 818, 819, 820, 822, 823, 824, 826, 827, 828, 830, 831, 833, 835, 837, 838, 839, 840, 841, 846, 849, 850, 851, 856, 857, 860], "trace_graph": [3, 4, 5, 7, 19, 20, 21, 22, 26, 27, 29, 30, 31, 32, 33, 34, 43, 782, 800, 835, 840, 848], "take": [3, 7, 17, 24, 26, 27, 32, 38, 40, 43, 52, 57, 59, 65, 75, 82, 92, 117, 118, 120, 136, 275, 282, 296, 360, 368, 369, 371, 387, 395, 400, 405, 415, 424, 436, 457, 464, 483, 512, 513, 616, 617, 620, 624, 625, 627, 628, 650, 665, 669, 694, 705, 745, 764, 772, 779, 780, 793, 800, 801, 805, 806, 807, 809, 810, 812, 813, 814, 815, 816, 817, 818, 819, 820, 821, 823, 826, 827, 828, 830, 833, 835, 837, 839, 840, 841, 842, 847, 849, 850, 853, 854, 862], "moment": [3, 52, 54, 75, 77, 369, 425, 603, 604, 609, 623, 784, 805, 811, 841, 849, 850], "one": [3, 6, 8, 11, 13, 15, 16, 19, 20, 23, 24, 26, 27, 29, 30, 42, 43, 44, 48, 52, 53, 56, 57, 59, 62, 63, 65, 69, 71, 74, 75, 76, 77, 79, 80, 82, 83, 85, 86, 87, 88, 92, 121, 124, 134, 136, 137, 138, 148, 150, 208, 229, 235, 242, 243, 260, 266, 267, 268, 287, 296, 306, 309, 310, 328, 334, 337, 340, 341, 344, 345, 346, 348, 349, 356, 360, 362, 365, 366, 368, 369, 370, 371, 374, 375, 380, 389, 391, 395, 396, 399, 400, 403, 411, 416, 418, 427, 434, 448, 452, 453, 454, 458, 464, 465, 466, 471, 473, 478, 481, 490, 491, 492, 497, 502, 512, 513, 516, 517, 518, 519, 520, 521, 523, 561, 565, 566, 568, 585, 587, 588, 601, 603, 604, 607, 609, 610, 611, 612, 617, 618, 619, 620, 622, 623, 624, 625, 627, 630, 632, 633, 635, 638, 639, 640, 641, 642, 643, 646, 662, 665, 666, 670, 672, 681, 682, 690, 691, 692, 695, 697, 701, 725, 732, 735, 737, 738, 739, 740, 745, 747, 764, 766, 783, 786, 789, 794, 797, 800, 805, 806, 807, 809, 810, 811, 812, 813, 815, 816, 817, 820, 821, 822, 823, 824, 825, 826, 827, 828, 830, 832, 833, 834, 837, 838, 840, 841, 842, 843, 846, 847, 850, 856, 857, 859, 862], "cost": [3, 54, 77, 603, 604, 607, 609, 610, 611, 623, 628, 703, 704, 705, 794, 815, 833, 854], "arg": [3, 5, 6, 7, 11, 13, 21, 22, 24, 26, 27, 31, 32, 33, 44, 47, 69, 91, 101, 117, 198, 208, 589, 616, 617, 619, 622, 759, 761, 776, 777, 780, 781, 782, 786, 789, 793, 798, 800, 810, 815, 816, 819, 825, 826, 827, 833, 835, 839, 849, 850, 851], "asarrai": [3, 4, 5, 6, 7, 41, 48, 52, 53, 64, 71, 75, 76, 87, 122, 378, 503, 504, 534, 545, 549, 550, 580, 581, 617, 622, 624, 633, 634, 638, 738, 742, 819, 824, 827, 828], "cuda": [3, 4, 5, 6, 7, 8, 9, 17, 26, 41, 42, 45, 48, 52, 61, 71, 75, 84, 132, 133, 136, 188, 189, 190, 204, 206, 375, 497, 498, 500, 501, 617, 619, 625, 631, 676, 726, 727, 728, 729, 779, 780, 781, 782, 783, 784, 785, 800, 835, 841, 843, 861], "7": [3, 5, 6, 7, 8, 9, 11, 13, 18, 19, 21, 22, 23, 24, 38, 40, 41, 42, 44, 45, 46, 48, 49, 51, 52, 53, 54, 56, 57, 58, 59, 61, 62, 63, 64, 65, 72, 73, 74, 75, 76, 77, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 97, 98, 107, 108, 109, 110, 121, 122, 123, 132, 135, 136, 154, 160, 163, 193, 215, 218, 221, 225, 226, 228, 229, 230, 231, 233, 235, 236, 237, 238, 239, 241, 242, 245, 246, 247, 252, 253, 254, 255, 256, 257, 258, 259, 260, 263, 265, 266, 267, 268, 270, 271, 272, 274, 275, 278, 279, 280, 282, 285, 286, 288, 289, 291, 292, 293, 295, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 309, 312, 313, 324, 328, 332, 334, 335, 342, 343, 344, 346, 348, 349, 356, 360, 362, 365, 366, 368, 369, 370, 371, 376, 380, 386, 387, 388, 389, 394, 395, 399, 400, 404, 409, 410, 411, 412, 414, 417, 420, 431, 443, 444, 445, 446, 448, 449, 452, 453, 454, 458, 460, 464, 469, 470, 473, 474, 479, 480, 482, 483, 485, 488, 489, 499, 501, 502, 509, 512, 513, 515, 516, 521, 527, 529, 530, 534, 535, 538, 549, 550, 551, 558, 565, 566, 580, 583, 603, 604, 606, 607, 608, 609, 610, 611, 614, 617, 618, 619, 620, 622, 623, 624, 625, 626, 627, 629, 630, 631, 632, 633, 634, 635, 638, 639, 641, 643, 645, 646, 647, 648, 653, 655, 656, 657, 658, 660, 661, 662, 665, 667, 670, 672, 673, 675, 676, 677, 679, 680, 681, 684, 685, 686, 687, 690, 691, 696, 698, 699, 701, 706, 707, 714, 718, 725, 726, 727, 728, 729, 731, 736, 737, 739, 741, 742, 744, 745, 746, 747, 749, 751, 753, 754, 764, 806, 807, 811, 813, 814, 817, 823, 826, 830], "output": [3, 4, 5, 7, 17, 23, 24, 26, 27, 39, 40, 41, 43, 46, 48, 49, 50, 51, 52, 53, 54, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 68, 70, 71, 72, 73, 74, 75, 76, 77, 79, 80, 81, 82, 83, 84, 85, 87, 88, 89, 97, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 121, 122, 123, 124, 125, 126, 127, 128, 130, 131, 132, 133, 134, 136, 137, 138, 139, 140, 141, 143, 144, 147, 149, 174, 208, 209, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 311, 312, 316, 323, 324, 325, 326, 327, 328, 329, 330, 331, 332, 333, 334, 335, 336, 337, 338, 339, 340, 341, 343, 344, 345, 346, 347, 348, 349, 350, 351, 352, 353, 354, 355, 357, 358, 359, 360, 362, 365, 367, 368, 369, 370, 371, 374, 375, 376, 378, 380, 381, 382, 383, 384, 386, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 399, 400, 401, 403, 404, 405, 406, 409, 411, 412, 413, 415, 416, 418, 419, 420, 422, 424, 427, 428, 431, 432, 433, 434, 436, 437, 440, 442, 443, 444, 445, 446, 447, 448, 449, 450, 457, 458, 459, 462, 464, 465, 466, 467, 468, 471, 472, 473, 475, 476, 477, 478, 479, 480, 481, 482, 483, 484, 486, 487, 490, 491, 492, 493, 494, 495, 496, 497, 498, 499, 500, 501, 502, 504, 509, 511, 512, 513, 514, 515, 516, 517, 518, 519, 520, 521, 522, 528, 529, 530, 534, 535, 536, 538, 542, 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27, 29, 32, 38, 39, 63, 67, 90, 633, 737, 738, 739, 740, 800, 803, 805, 806, 807, 810, 812, 813, 814, 815, 816, 819, 820, 821, 822, 823, 826, 827, 828, 829, 830, 833, 837, 838, 839, 841, 845, 849, 850, 851, 856, 861], "expect": [3, 5, 6, 8, 19, 23, 26, 27, 29, 42, 43, 45, 52, 57, 58, 75, 81, 174, 242, 286, 368, 370, 390, 412, 447, 525, 618, 620, 622, 626, 670, 684, 779, 780, 800, 806, 807, 809, 815, 816, 819, 821, 824, 826, 828, 830, 833, 841, 842, 847, 849, 850, 851], "ident": [3, 9, 24, 41, 43, 57, 69, 127, 196, 544, 570, 617, 619, 622, 625, 629, 662, 667, 719, 780, 813, 823, 824, 827, 828, 831, 833, 837, 838, 841, 843, 845, 847], "had": [3, 813, 814, 826, 831, 835, 856, 857], "anoth": [3, 17, 19, 20, 23, 24, 26, 27, 29, 30, 42, 43, 128, 148, 150, 617, 618, 800, 805, 806, 807, 811, 813, 815, 816, 819, 821, 823, 826, 827, 830, 835, 837, 840, 843, 846, 848, 849, 850, 856, 862], "postprocess": 3, "routin": [3, 814, 826, 827, 833, 841, 856], "feed": [3, 208, 619, 849, 856, 857], "other": 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127, 128, 129, 130, 131, 132, 133, 134, 136, 137, 138, 139, 140, 141, 142, 143, 144, 147, 149, 158, 209, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 311, 312, 323, 327, 328, 329, 330, 331, 332, 333, 334, 335, 336, 337, 338, 339, 340, 341, 343, 344, 345, 346, 347, 348, 349, 350, 351, 352, 353, 354, 355, 360, 362, 365, 368, 369, 370, 371, 374, 375, 376, 378, 380, 381, 386, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 399, 400, 401, 403, 404, 405, 406, 409, 411, 412, 415, 416, 417, 418, 419, 420, 421, 424, 425, 427, 428, 429, 431, 432, 433, 434, 436, 440, 443, 444, 445, 446, 448, 449, 455, 457, 458, 459, 461, 462, 464, 465, 466, 467, 468, 470, 471, 472, 473, 474, 475, 476, 477, 478, 479, 480, 481, 482, 483, 484, 486, 489, 490, 491, 492, 493, 494, 495, 496, 497, 498, 499, 500, 501, 502, 504, 509, 510, 511, 512, 513, 514, 515, 516, 517, 518, 519, 520, 521, 522, 525, 529, 530, 534, 535, 536, 538, 541, 542, 551, 561, 565, 566, 603, 604, 607, 609, 610, 611, 612, 614, 615, 617, 618, 619, 620, 621, 622, 623, 624, 625, 626, 627, 628, 629, 630, 631, 632, 633, 634, 635, 636, 637, 638, 639, 640, 641, 642, 643, 644, 645, 646, 647, 648, 649, 650, 653, 654, 655, 656, 657, 658, 659, 660, 661, 662, 663, 664, 665, 666, 667, 668, 669, 670, 671, 672, 674, 675, 676, 677, 678, 679, 680, 681, 682, 683, 684, 685, 686, 687, 688, 689, 690, 691, 692, 693, 694, 695, 697, 698, 699, 700, 702, 725, 726, 727, 728, 729, 731, 732, 733, 734, 736, 740, 741, 742, 743, 744, 745, 746, 747, 748, 749, 750, 751, 752, 753, 754, 755, 756, 764, 772, 776, 777, 779, 780, 782, 783, 784, 785, 800, 801, 803, 804, 805, 806, 808, 809, 810, 811, 812, 813, 814, 815, 816, 817, 818, 819, 821, 823, 825, 827, 828, 829, 830, 831, 833, 834, 835, 836, 837, 838, 839, 840, 842, 845, 846, 847, 849, 850, 856, 863], "quickest": 3, "particular": [3, 26, 27, 263, 620, 765, 806, 807, 809, 811, 814, 815, 817, 824, 826, 827, 830, 831, 852, 856, 862], "hardwar": [3, 40, 97, 101, 800, 806, 833, 846, 852, 854, 855, 856, 857, 858, 859, 860, 861, 862], "again": [3, 5, 20, 21, 29, 30, 31, 32, 625, 673, 807, 810, 811, 812, 813, 817, 819, 821, 826, 827, 830, 831, 833, 838, 840, 841, 846, 847, 861, 862], "speed": [3, 6, 8, 9, 26, 27, 40, 45, 53, 76, 558, 622, 830, 845, 859], "up": [3, 5, 6, 8, 9, 26, 52, 53, 75, 76, 368, 371, 390, 403, 458, 466, 546, 558, 622, 624, 647, 800, 801, 803, 805, 807, 809, 810, 811, 813, 814, 815, 816, 817, 818, 819, 821, 822, 823, 824, 825, 826, 827, 828, 830, 831, 833, 835, 836, 837, 838, 839, 840, 841, 845, 846, 847, 849, 857, 862, 863], "12": [3, 5, 6, 7, 9, 17, 19, 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807, 809, 811, 814, 816, 822, 827, 830, 833, 840, 841, 859], "trace": [3, 4, 5, 6, 7, 8, 15, 16, 20, 23, 26, 29, 31, 32, 44, 53, 57, 69, 76, 80, 553, 554, 557, 568, 577, 591, 599, 622, 625, 761, 772, 782, 784, 800, 809, 813, 815, 827, 832, 833, 835, 840, 841, 848, 849, 850, 857, 862], "befor": [3, 4, 5, 18, 19, 20, 21, 22, 28, 29, 30, 31, 32, 33, 40, 52, 56, 57, 59, 63, 65, 69, 75, 79, 80, 205, 208, 213, 368, 371, 380, 395, 400, 410, 414, 458, 465, 466, 467, 474, 512, 513, 619, 624, 625, 627, 628, 629, 633, 635, 637, 638, 639, 640, 642, 644, 646, 649, 650, 653, 665, 682, 688, 703, 704, 718, 737, 738, 739, 740, 745, 746, 751, 753, 780, 789, 793, 805, 806, 807, 809, 810, 812, 815, 816, 818, 819, 820, 821, 822, 824, 825, 826, 827, 828, 830, 835, 838, 841, 849, 850, 856], "13": [3, 5, 6, 7, 17, 21, 22, 23, 24, 38, 40, 42, 46, 51, 52, 56, 57, 61, 65, 74, 75, 76, 77, 79, 82, 84, 88, 97, 113, 163, 193, 218, 233, 242, 253, 273, 282, 342, 349, 356, 365, 368, 371, 388, 389, 399, 404, 410, 414, 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835, 841, 853], "prealloc": [3, 5], "75": [3, 5, 38, 51, 52, 74, 75, 76, 79, 84, 114, 132, 221, 223, 235, 237, 248, 309, 341, 342, 362, 365, 410, 521, 536, 549, 580, 614, 617, 620, 622, 625, 629, 631, 638, 663, 670, 714, 729], "memori": [3, 5, 8, 21, 22, 23, 24, 48, 52, 59, 71, 75, 82, 123, 134, 190, 202, 208, 210, 214, 371, 380, 452, 453, 460, 462, 464, 465, 466, 473, 488, 518, 564, 569, 592, 617, 619, 622, 624, 627, 649, 690, 691, 692, 694, 696, 697, 699, 701, 794, 814, 815, 816, 826, 827, 833, 835, 841, 849, 856, 858, 859, 860], "temporari": [3, 5, 578, 600, 622, 794, 815, 832], "fix": [3, 5, 42, 52, 75, 92, 93, 365, 368, 369, 413, 441, 624, 650, 800, 803, 806, 807, 809, 815, 821, 830, 831], "until": [3, 5, 794, 807, 826, 835, 841, 846, 849, 863], "handl": [3, 5, 38, 40, 46, 50, 51, 52, 68, 69, 73, 74, 75, 98, 105, 106, 107, 108, 109, 110, 111, 112, 113, 188, 189, 190, 191, 192, 196, 201, 202, 210, 214, 220, 232, 257, 259, 273, 279, 280, 285, 286, 290, 294, 295, 297, 360, 371, 457, 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747, 761, 806, 814, 817, 825, 859], "warm": 3, "_": [3, 6, 8, 9, 26, 39, 40, 51, 52, 69, 74, 75, 77, 93, 150, 238, 240, 248, 249, 264, 329, 330, 365, 368, 371, 380, 411, 438, 441, 482, 511, 534, 603, 604, 618, 620, 622, 623, 625, 627, 629, 635, 673, 674, 676, 702, 713, 752, 807, 814, 815, 818, 826, 838], "rang": [3, 9, 26, 27, 38, 39, 40, 42, 48, 52, 65, 71, 75, 121, 132, 133, 282, 293, 301, 313, 360, 362, 369, 371, 380, 422, 432, 467, 475, 477, 482, 486, 512, 513, 514, 534, 602, 617, 620, 622, 633, 635, 737, 745, 746, 751, 753, 764, 766, 767, 779, 800, 805, 815, 819, 823, 830, 835, 838, 839, 840, 856, 862], "16": [3, 5, 9, 21, 22, 23, 24, 38, 40, 42, 51, 52, 53, 56, 57, 61, 65, 72, 74, 75, 76, 79, 80, 82, 84, 97, 98, 163, 229, 258, 278, 285, 339, 342, 346, 365, 368, 371, 380, 386, 387, 389, 395, 399, 400, 404, 405, 410, 414, 447, 464, 512, 518, 535, 538, 560, 580, 581, 613, 618, 620, 622, 623, 624, 625, 627, 629, 631, 632, 635, 646, 648, 654, 658, 661, 662, 670, 672, 676, 701, 714, 727, 728, 729, 736, 746, 747, 764, 767, 800, 807, 815, 817, 838], "0022192720000475674": 3, "64773613": 3, "29496723": 3, "exact": [3, 52, 68, 69, 105, 368, 370, 403, 408, 446, 447, 633, 737, 739, 766, 776, 806, 807, 809, 817, 835], "note": [3, 5, 9, 22, 26, 27, 32, 41, 42, 43, 52, 53, 57, 59, 63, 75, 80, 82, 92, 129, 142, 174, 242, 277, 278, 285, 322, 323, 342, 362, 365, 368, 369, 371, 390, 421, 426, 434, 435, 441, 464, 482, 618, 620, 624, 625, 627, 633, 635, 650, 659, 660, 672, 673, 675, 694, 698, 738, 740, 749, 780, 794, 803, 805, 806, 807, 810, 815, 817, 818, 821, 826, 827, 828, 830, 831, 833], "were": [3, 5, 43, 69, 72, 163, 167, 168, 242, 620, 624, 650, 805, 806, 807, 815, 819, 821, 825, 826, 828, 830, 831, 833, 835, 849, 856, 857, 862], "function": [3, 9, 11, 13, 15, 16, 18, 19, 20, 21, 22, 23, 24, 28, 29, 30, 31, 32, 33, 34, 43, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 79, 80, 81, 82, 83, 84, 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856, 858, 859, 863], "specif": [17, 18, 23, 24, 26, 27, 28, 30, 32, 40, 50, 52, 53, 73, 75, 76, 175, 206, 209, 242, 263, 264, 273, 316, 329, 330, 362, 365, 371, 375, 482, 501, 534, 535, 536, 562, 618, 619, 620, 622, 625, 627, 628, 631, 634, 635, 660, 661, 677, 698, 703, 704, 705, 726, 743, 748, 749, 750, 752, 759, 761, 781, 782, 789, 790, 796, 800, 803, 805, 806, 807, 809, 810, 811, 812, 813, 815, 816, 819, 821, 822, 823, 826, 827, 828, 829, 830, 831, 833, 835, 836, 837, 839, 840, 841, 842, 843, 845, 849, 850, 851, 852, 854, 855, 857, 858, 859, 863], "quirk": [17, 26], "perk": [17, 26, 800, 810, 813], "under": [17, 26, 27, 52, 370, 446, 447, 793, 800, 805, 806, 808, 809, 816, 817, 818, 821, 827, 828, 830, 833, 834, 835, 838, 840, 841, 849, 850, 856, 859, 863], "hood": [17, 26, 27, 800, 808, 816, 817, 821, 827, 830, 833, 834, 835, 838, 840, 849, 850, 863], "appropi": 17, "string": [17, 26, 27, 42, 52, 53, 56, 69, 75, 79, 145, 146, 158, 165, 187, 188, 189, 190, 191, 193, 202, 209, 210, 214, 368, 369, 371, 410, 414, 422, 474, 485, 513, 532, 618, 619, 622, 624, 625, 637, 638, 639, 640, 642, 644, 646, 661, 759, 761, 765, 793, 794, 811, 812, 814, 815, 816, 819, 827, 835, 838], "simplest": [17, 806, 817, 830, 833], "interact": [17, 26, 41, 44, 805, 855, 856, 861], "submodul": [17, 26, 40, 42, 97, 98, 614, 615, 617, 618, 619, 620, 621, 622, 623, 624, 625, 626, 627, 628, 629, 630, 631, 632, 633, 634, 635, 636, 776, 777, 779, 780, 782, 783, 784, 785, 805, 806, 807, 809, 812, 814, 816, 820, 823, 824, 830, 834, 835, 839, 843], "ones": [17, 24, 26, 38, 44, 48, 52, 54, 56, 61, 69, 71, 75, 79, 84, 127, 131, 136, 138, 144, 194, 195, 231, 307, 362, 380, 520, 603, 617, 619, 620, 623, 624, 642, 643, 727, 728, 729, 765, 800, 805, 810, 814, 817, 822, 823, 829, 830, 837, 838, 856], "likewis": [17, 22, 26, 33, 800, 807, 813, 815, 818, 822, 823, 827, 833, 838, 849, 850, 862], "nativearrai": [17, 26, 27, 47, 48, 49, 51, 52, 53, 54, 56, 57, 58, 59, 60, 61, 63, 65, 68, 70, 71, 72, 73, 74, 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817, 818, 819, 823, 826, 827, 830, 833, 835, 838, 839, 843, 845, 849, 852, 853, 854, 855, 856, 857, 859, 860, 861, 862, 863], "fashion": [17, 766, 830, 850], "native_arrai": [17, 26, 27, 48, 49, 51, 71, 73, 74, 75, 76, 80, 87, 105, 108, 131, 134, 136, 138, 144, 147, 148, 149, 150, 158, 163, 170, 192, 201, 209, 225, 229, 234, 235, 236, 238, 242, 246, 254, 255, 263, 268, 271, 274, 277, 282, 329, 330, 356, 365, 370, 371, 448, 474, 480, 484, 523, 526, 553, 554, 557, 587, 614, 617, 618, 619, 620, 622, 624, 625, 626, 627, 631, 632, 635, 636, 638, 639, 646, 653, 656, 660, 661, 667, 668, 672, 676, 677, 679, 682, 684, 686, 687, 694, 726, 735, 744, 750, 753, 755, 761, 771, 789, 803, 820, 828, 830], "data_class": [17, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 100, 101, 102, 387, 388, 534, 538, 675, 700], "low": [17, 26, 29, 45, 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830, 833, 835, 837, 838, 839, 840, 856, 861], "why": [17, 800, 807, 826, 837, 844, 846], "underli": [17, 26, 27, 38, 52, 59, 75, 82, 95, 225, 228, 230, 265, 370, 371, 447, 464, 620, 625, 627, 673, 694, 813, 826, 833, 849, 856], "disabl": [17, 26, 52, 75, 371, 482, 782, 812], "array_mod": [17, 26, 567, 590, 622, 832], "set_array_mod": [17, 26, 590, 622, 832], "composit": [17, 26, 161, 162, 194, 195, 287, 369, 428, 539, 540, 618, 619, 620, 622, 765, 767, 805, 808, 810, 811, 813, 815, 816, 824, 826, 827, 828, 830, 833, 835, 839, 840, 841, 843, 849, 857], "ultim": [17, 26, 849], "sigmoid": [17, 26, 27, 38, 46, 52, 68, 75, 295, 360, 375, 497, 614, 776, 835, 838, 839], "z": [17, 26, 27, 39, 40, 48, 51, 52, 53, 57, 58, 61, 63, 65, 71, 74, 75, 76, 80, 81, 82, 84, 88, 97, 98, 132, 133, 135, 136, 196, 218, 219, 223, 225, 228, 230, 235, 246, 247, 250, 251, 252, 254, 255, 260, 262, 264, 265, 266, 267, 275, 284, 294, 295, 329, 330, 332, 360, 365, 370, 380, 443, 445, 446, 447, 448, 449, 455, 459, 470, 510, 511, 514, 521, 526, 538, 541, 542, 549, 550, 566, 579, 580, 581, 589, 602, 617, 619, 620, 622, 625, 626, 627, 629, 631, 632, 633, 635, 655, 665, 670, 671, 675, 682, 684, 685, 686, 687, 709, 713, 715, 723, 727, 728, 729, 732, 737, 747, 748, 750, 751, 752, 779, 800, 811, 813, 816, 817, 835, 837, 849], "divid": [17, 22, 26, 27, 43, 51, 52, 53, 59, 69, 74, 75, 82, 97, 98, 242, 374, 444, 490, 491, 492, 495, 580, 620, 622, 627, 696, 810, 813, 817, 821, 830], "exp": [17, 26, 27, 51, 52, 74, 75, 111, 113, 240, 260, 273, 295, 360, 368, 370, 395, 400, 447, 614, 620, 625, 673, 825, 827], "high": [17, 26, 27, 45, 52, 56, 61, 75, 79, 84, 368, 410, 414, 574, 622, 624, 631, 637, 638, 639, 640, 642, 644, 646, 727, 729, 766, 805, 819, 825, 827, 838, 843, 847, 852, 853, 854, 855, 856, 860, 862, 863], "network": [17, 24, 26, 27, 38, 40, 45, 624, 648, 776, 779, 780, 800, 813, 823, 835, 839, 846, 850, 852, 854, 855, 856, 860, 862, 863], "entir": [17, 26, 27, 29, 42, 52, 65, 66, 69, 75, 76, 88, 89, 208, 238, 240, 280, 281, 329, 330, 365, 368, 371, 380, 391, 392, 393, 474, 514, 547, 619, 620, 635, 636, 748, 749, 750, 751, 752, 753, 754, 755, 756, 780, 794, 805, 806, 807, 809, 810, 813, 815, 817, 819, 826, 827, 828, 830, 833, 835, 838, 839, 840, 841, 846, 847, 850, 856, 862, 863], "further": [17, 69, 98, 766, 807, 809, 810, 814, 817, 819, 822, 823, 826, 827, 829, 830, 834, 835, 838, 839, 846, 847, 861, 862], "congratul": [17, 23], "There": [17, 24, 27, 32, 92, 361, 363, 364, 372, 373, 377, 766, 800, 805, 806, 807, 809, 810, 812, 813, 815, 816, 817, 819, 821, 823, 825, 827, 828, 832, 835, 838, 841, 845, 849, 857, 858, 862, 863], "come": [17, 40, 805, 806, 807, 810, 814, 827, 832, 833, 839, 843, 856], "independ": [17, 27, 52, 61, 75, 84, 218, 235, 268, 278, 374, 375, 495, 497, 620, 625, 631, 655, 674, 726, 800, 809, 815, 817, 824, 835, 840, 850, 854], "good": [17, 26, 27, 800, 804, 805, 806, 807, 809, 810, 811, 812, 813, 814, 815, 816, 817, 818, 819, 821, 822, 823, 824, 825, 826, 828, 830, 831, 833, 835, 836, 839], "foundat": [17, 846, 859], "power": [17, 26, 27, 51, 52, 53, 57, 74, 75, 76, 80, 97, 98, 229, 238, 239, 273, 327, 339, 362, 365, 368, 415, 571, 581, 593, 620, 622, 625, 629, 667, 680, 712, 779, 832, 837, 838, 839, 856, 858, 862], "defin": [18, 24, 26, 27, 28, 48, 52, 53, 57, 71, 75, 76, 80, 95, 111, 136, 140, 141, 142, 218, 235, 242, 268, 269, 277, 279, 282, 294, 298, 302, 308, 311, 312, 313, 322, 323, 324, 325, 326, 329, 330, 332, 360, 362, 365, 368, 369, 371, 380, 403, 420, 474, 480, 514, 549, 550, 570, 614, 617, 620, 622, 625, 635, 655, 660, 661, 674, 748, 749, 750, 752, 800, 805, 806, 810, 811, 814, 815, 818, 822, 825, 827, 828, 830, 831, 837, 839, 841, 843, 851, 853, 854, 855, 856, 857, 860, 862, 863], "div": [18, 19, 20, 21, 22, 26, 27, 28, 29, 30, 31, 32, 33, 851], "sub": [18, 19, 20, 21, 22, 26, 27, 28, 29, 30, 31, 32, 33, 52, 57, 59, 69, 70, 74, 75, 76, 80, 82, 98, 267, 369, 371, 380, 422, 460, 469, 488, 517, 518, 546, 622, 625, 627, 628, 658, 679, 696, 703, 704, 705, 805, 807, 808, 813, 819, 827, 828, 830, 837, 838, 839, 851, 852], "By": [18, 38, 45, 52, 58, 59, 65, 66, 75, 81, 82, 88, 89, 282, 327, 329, 330, 342, 349, 362, 365, 368, 370, 371, 378, 380, 390, 446, 447, 482, 504, 511, 514, 569, 620, 622, 625, 626, 627, 635, 636, 655, 681, 684, 693, 745, 748, 749, 750, 751, 752, 753, 754, 755, 756, 806, 811, 815, 817, 819, 823, 825, 826, 827, 835, 839, 840, 849], "uniform": [18, 19, 20, 21, 22, 26, 27, 28, 29, 31, 32, 33, 40, 52, 61, 75, 84, 380, 514, 631, 726, 727, 729, 779, 800, 829, 839, 850, 851, 863], "x_": [18, 28, 93, 279, 620, 851], "82997245": 18, "44733784": 18, "32163444": 18, "93330479": 18, "52438271": 18, "20438017": 18, "252316": 18, "0827222": 18, "26017165": 18, "88881904": 18, "compat": [18, 24, 28, 32, 38, 45, 51, 52, 57, 59, 62, 65, 66, 74, 75, 80, 82, 85, 88, 89, 97, 98, 149, 218, 223, 225, 227, 228, 229, 230, 235, 236, 242, 246, 247, 254, 255, 260, 262, 264, 265, 268, 271, 273, 277, 284, 289, 329, 330, 365, 618, 620, 625, 627, 632, 635, 636, 655, 668, 671, 674, 677, 681, 682, 694, 733, 748, 749, 750, 751, 752, 753, 754, 755, 756, 800, 806, 811, 822, 827, 828, 831, 835, 841, 846], "sever": [18, 19, 28, 29, 31, 32, 33, 52, 75, 92, 368, 369, 382, 383, 384, 434, 764, 806, 807, 831, 841, 854, 860], "pro": [18, 19, 20, 28, 29, 30, 31, 32, 33], "pick": [19, 29, 779], "off": [19, 29, 56, 57, 79, 80, 391, 392, 393, 624, 625, 647, 658, 679, 779, 780, 806, 820, 834, 847, 849, 862], "last": [19, 24, 26, 29, 48, 52, 56, 57, 58, 59, 62, 64, 65, 66, 69, 71, 75, 79, 80, 81, 82, 87, 88, 89, 93, 97, 132, 133, 136, 191, 307, 335, 362, 365, 368, 369, 370, 371, 378, 380, 396, 401, 411, 412, 413, 424, 446, 464, 474, 476, 482, 504, 512, 513, 617, 619, 624, 625, 626, 627, 632, 634, 635, 636, 649, 650, 655, 658, 670, 679, 681, 685, 686, 688, 691, 694, 695, 696, 698, 732, 733, 741, 743, 744, 745, 746, 755, 756, 780, 789, 800, 807, 809, 811, 812, 815, 817, 826, 828, 830, 833, 835, 841, 847, 850, 856], "purpos": [19, 26, 27, 29, 40, 42, 142, 240, 258, 322, 362, 617, 620, 625, 673, 807, 808, 810, 813, 814, 816, 817, 819, 822, 823, 824, 827, 829, 830, 833, 834, 837, 843, 855, 857, 860, 861, 862], "illustr": [19, 29, 811, 835], "trigger": [19, 29, 782, 805, 821], "unif": [19, 21, 22, 29, 31, 801, 837, 846, 852, 862], "detail": [19, 29, 42, 46, 51, 52, 57, 59, 63, 68, 74, 75, 76, 80, 82, 86, 105, 106, 107, 108, 109, 110, 111, 112, 113, 128, 139, 286, 290, 294, 295, 297, 360, 369, 418, 459, 537, 614, 617, 620, 633, 658, 665, 671, 675, 698, 737, 738, 739, 740, 776, 800, 805, 807, 809, 811, 812, 813, 814, 821, 822, 823, 824, 827, 828, 829, 830, 831, 832, 835, 837, 838, 839, 858, 862], "55563945": 19, "65538704": 19, "14150524": 19, "46951997": 19, "30220294": 19, "14739668": 19, "57017946": 19, "91962677": 19, "51029003": 19, "59644395": 19, "arbitrari": [19, 29, 48, 49, 52, 69, 72, 75, 134, 148, 175, 316, 370, 444, 452, 453, 454, 605, 617, 618, 623, 822, 823, 825, 826, 827, 830, 839, 841, 849, 851, 857, 862], "constitu": [19, 29, 69, 840], "due": [19, 26, 27, 29, 43, 45, 268, 278, 371, 482, 620, 806, 809, 814, 819, 826, 827, 846, 849, 850, 856], "manner": [19, 27, 29, 39, 47, 70, 629, 718, 806, 815, 816, 818, 823, 827, 831, 838, 841, 845, 852, 854, 862, 863], "non": [19, 29, 49, 51, 52, 57, 61, 62, 65, 66, 72, 74, 75, 80, 84, 85, 88, 89, 129, 147, 165, 174, 243, 263, 264, 269, 329, 330, 334, 340, 353, 365, 368, 369, 371, 380, 411, 422, 426, 430, 453, 454, 514, 517, 617, 618, 620, 625, 629, 631, 632, 635, 636, 655, 656, 666, 668, 675, 677, 681, 682, 719, 728, 732, 733, 734, 735, 748, 749, 750, 751, 752, 754, 755, 756, 764, 779, 781, 782, 784, 810, 813, 817, 835, 849, 850, 851, 856], "5556394": 19, "655387": 19, "1415051": 19, "4695197": 19, "3022028": 19, "1473966": 19, "5701794": 19, "91962665": 19, "51028997": 19, "5964439": 19, "assess": [19, 29, 805, 833], "985": 19, "000": [19, 74, 269, 764, 803, 814, 820], "69": [19, 38, 45, 51, 77, 84, 216, 258, 368, 389, 399, 607, 620, 623, 625, 666, 667, 728, 830, 838], "slower": [19, 827], "On": [19, 26, 27, 806, 815, 816, 821, 827, 830, 833, 836, 840], "hand": [19, 51, 369, 436, 764, 800, 809, 815, 816, 821, 823, 830, 841], "singl": [19, 29, 38, 43, 51, 61, 69, 74, 84, 93, 287, 344, 365, 369, 375, 433, 498, 588, 601, 605, 620, 622, 623, 624, 631, 633, 650, 727, 728, 729, 737, 764, 780, 805, 806, 807, 809, 814, 817, 822, 823, 824, 825, 826, 827, 828, 830, 831, 833, 835, 838, 839, 840, 841, 847], "learnt": [20, 30], "two": [20, 30, 32, 38, 48, 52, 57, 63, 75, 76, 80, 97, 98, 118, 121, 127, 134, 140, 141, 142, 173, 181, 229, 243, 244, 278, 322, 323, 328, 340, 341, 343, 344, 346, 348, 355, 362, 365, 368, 369, 370, 371, 380, 396, 419, 420, 421, 433, 442, 444, 448, 453, 474, 480, 484, 511, 521, 526, 616, 617, 618, 620, 622, 625, 627, 633, 654, 656, 658, 659, 660, 661, 662, 663, 664, 665, 666, 667, 668, 669, 670, 671, 672, 673, 674, 675, 676, 679, 681, 699, 737, 738, 739, 740, 764, 766, 772, 780, 805, 806, 809, 810, 815, 816, 817, 818, 823, 827, 828, 830, 833, 834, 838, 840, 847, 853, 861], "workflow": [20, 30, 41, 805, 807, 811, 815, 825, 827, 838, 843, 847, 855, 862, 863], "ivy_norm": 20, "jax_norm": [20, 26, 27], "wider": [20, 30, 574, 596, 622, 815, 832, 862], "avoid": [20, 30, 32, 52, 59, 75, 235, 240, 242, 258, 268, 370, 371, 374, 444, 452, 453, 454, 460, 462, 464, 465, 466, 469, 473, 480, 488, 490, 491, 492, 528, 544, 546, 569, 574, 596, 620, 622, 627, 690, 691, 692, 694, 696, 697, 699, 701, 766, 767, 806, 807, 811, 812, 813, 814, 815, 819, 824, 827, 830, 831, 832, 833, 856], "conveni": [20, 30, 805, 815, 816, 822, 828, 836, 838, 839, 843, 862], "act": [20, 30, 52, 75, 356, 366, 807, 817, 832, 841, 863], "shorthand": [20, 30, 32, 830], "pair": [20, 30, 40, 52, 56, 75, 79, 223, 242, 314, 355, 362, 365, 368, 401, 410, 412, 414, 620, 624, 625, 637, 638, 639, 640, 642, 644, 646, 653, 655, 794], "93968587": 20, "26075466": 20, "22723222": 20, "06276492": 20, "47426987": 20, "72835908": 20, "71737559": 20, "50411096": 20, "65419174": 20, "15576624": 20, "implic": [20, 30, 31, 34, 813], "requir": [21, 22, 23, 24, 31, 40, 41, 42, 45, 51, 52, 69, 74, 75, 269, 282, 286, 369, 371, 421, 422, 474, 620, 625, 627, 659, 660, 661, 698, 764, 772, 777, 794, 802, 805, 806, 810, 812, 814, 815, 816, 817, 818, 819, 821, 822, 824, 827, 828, 829, 830, 831, 833, 835, 837, 841, 850, 856, 862], "satisfi": [21, 22, 23, 24, 40, 42, 45, 52, 368, 369, 390, 422, 815, 817], "opt": [21, 22, 23, 24, 44, 806, 811, 815, 826, 830, 833], "fw": [21, 22, 23, 24, 56, 79, 380, 511, 624, 637, 638, 639, 640, 641, 642, 643, 644, 645, 646, 761, 806, 830], "mxnet": [21, 22, 23, 24, 789, 805, 806, 846, 863], "26": [21, 22, 23, 24, 38, 40, 42, 45, 51, 52, 60, 61, 75, 76, 77, 84, 230, 235, 281, 368, 369, 389, 425, 433, 549, 603, 620, 622, 623, 624, 625, 629, 630, 635, 646, 658, 670, 677, 707, 725, 727, 728, 747], "einop": [21, 22, 23, 24, 40, 42, 45, 53, 76, 534, 535, 536, 622, 815, 846], "miniconda": [21, 22, 23, 24], "env": [21, 22, 23, 24], "multienv": [21, 22, 23, 24], "site": [21, 22, 23, 24, 857], "psutil": [21, 22, 23, 24, 40, 42, 45], "termcolor": [21, 22, 23, 24, 40, 42, 45, 69, 98], "colorama": [21, 22, 23, 24, 40, 42], "nvidia": [21, 22, 23, 24, 40, 42, 45, 860, 861], "535": [21, 22, 23, 24, 46, 68, 113, 614, 819], "diskcach": [21, 22, 23, 24, 40], "auth": [21, 22, 23, 24], "urllib3": [21, 22, 23, 24, 40], "pyvi": [21, 22, 23, 24, 26, 27], "dill": [21, 22, 23, 24, 40], "astunpars": [21, 22, 23, 24], "cloudpickl": [21, 22, 23, 24], "gast": [21, 22, 23, 24], "66": [21, 22, 23, 24, 38, 40, 42, 65, 75, 76, 77, 368, 399, 534, 535, 607, 622, 623, 625, 635, 670, 747], "wheel": [21, 22, 23, 24, 40, 42, 45, 845], "six": [21, 22, 23, 24, 40, 45, 806, 833], "cachetool": [21, 22, 23, 24], "pyasn1": [21, 22, 23, 24], "rsa": [21, 22, 23, 24], "jinja2": [21, 22, 23, 24], "jsonpickl": [21, 22, 23, 24], "networkx": [21, 22, 23, 24, 45], "charset": [21, 22, 23, 24, 40], "idna": [21, 22, 23, 24, 40], "certifi": [21, 22, 23, 24, 40], "2017": [21, 22, 23, 24, 40, 624, 650], "jedi": [21, 22, 23, 24], "inlin": [21, 22, 23, 24, 812], "prompt": [21, 22, 23, 24, 805, 807], "toolkit": [21, 22, 23, 24, 856, 857, 863], "pygment": [21, 22, 23, 24], "traitlet": [21, 22, 23, 24], "exceptiongroup": [21, 22, 23, 24], "paddl": [21, 22, 23, 24, 329, 330, 365, 777, 789, 805, 806, 815, 820], "pexpect": [21, 22, 23, 24], "markupsaf": [21, 22, 23, 24], "parso": [21, 22, 23, 24], "ptyprocess": [21, 22, 23, 24], "wcwidth": [21, 22, 23, 24], "asttoken": [21, 22, 23, 24], "pure": [21, 22, 23, 24, 32, 42, 800, 818, 822, 827, 833, 837, 840, 841, 856, 862, 863], "eagerli": [21, 22, 26, 27, 31, 32, 33, 40, 800, 849, 850, 851], "lazili": [21, 22, 23, 26, 27, 31, 33, 44, 800, 849, 850, 851], "actual": [21, 31, 803, 807, 808, 814, 820, 823, 824, 826, 827, 828, 830, 833, 834, 839, 841, 857, 862], "occur": [21, 26, 27, 31, 44, 49, 51, 63, 72, 74, 86, 150, 269, 285, 618, 620, 632, 633, 732, 733, 737, 738, 739, 740, 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"loss": [26, 27, 40, 42, 52, 75, 92, 442, 443, 444, 445, 446, 447, 448, 449, 574, 596, 622, 684, 685, 686, 800, 814, 815, 823, 827, 831, 832, 838, 839, 840, 856, 863], "gradient": [26, 27, 40, 42, 52, 75, 92, 208, 357, 365, 603, 604, 605, 606, 607, 608, 609, 610, 611, 612, 613, 619, 628, 703, 704, 705, 761, 772, 784, 800, 808, 831, 838, 839, 841, 856], "grad": [26, 27, 38, 42, 603, 623, 784, 800, 825, 838, 839, 840], "execute_with_gradi": [26, 27, 38, 42, 623, 800, 838, 839, 840, 841], "lambda": [26, 27, 43, 45, 75, 118, 120, 292, 301, 533, 605, 606, 608, 613, 616, 622, 623, 625, 629, 660, 713, 714, 718, 800, 805, 823, 824, 825, 828, 833, 835, 838], "2d": [26, 27, 42, 52, 75, 92, 307, 362, 368, 369, 371, 380, 383, 384, 391, 392, 432, 439, 453, 463, 511, 780, 800, 827, 833], "5f": [26, 27, 800], "nonetheless": [26, 27], "slight": [26, 27, 815, 830, 839], "introduc": [26, 27, 242, 620, 627, 633, 695, 737, 805, 813, 814, 815, 824, 828, 830, 833, 838, 845], "address": [26, 27, 52, 53, 75, 371, 482, 587, 622, 805, 807, 809, 810, 822, 829, 835, 847, 852, 854, 856, 862], "extract": [26, 27, 34, 41, 52, 75, 93, 371, 457, 483, 827, 829, 831, 852, 856, 857, 862], "gc": [26, 27, 546, 622], "decompos": [26, 27, 52, 75, 92, 95, 317, 318, 319, 320, 321, 341, 348, 362, 365, 369, 430, 435, 438, 441, 827, 840], "said": [26, 27, 766, 831, 847, 849], "otherwis": [26, 27, 44, 47, 48, 49, 51, 52, 53, 56, 57, 62, 63, 65, 66, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 79, 80, 81, 82, 84, 85, 86, 87, 88, 89, 92, 105, 106, 107, 108, 109, 110, 111, 112, 113, 118, 121, 123, 124, 129, 131, 132, 133, 136, 138, 144, 147, 148, 150, 151, 153, 154, 155, 156, 157, 166, 170, 174, 175, 191, 209, 215, 216, 217, 218, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 240, 241, 242, 246, 247, 249, 250, 251, 252, 254, 255, 256, 257, 258, 259, 260, 262, 263, 264, 265, 266, 267, 268, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 288, 289, 290, 291, 292, 293, 294, 297, 298, 299, 300, 301, 303, 304, 305, 307, 317, 318, 319, 320, 321, 328, 329, 330, 331, 332, 334, 335, 336, 343, 344, 350, 352, 354, 355, 356, 360, 362, 365, 368, 369, 374, 386, 387, 388, 391, 392, 393, 411, 424, 437, 439, 442, 443, 444, 445, 446, 447, 448, 449, 452, 453, 454, 458, 459, 460, 462, 464, 465, 466, 473, 480, 482, 483, 484, 488, 490, 492, 493, 494, 496, 498, 510, 511, 512, 513, 514, 523, 526, 527, 529, 530, 534, 535, 536, 537, 538, 541, 542, 545, 547, 549, 550, 551, 553, 554, 557, 558, 565, 566, 580, 581, 583, 585, 587, 588, 589, 601, 605, 607, 612, 616, 617, 618, 619, 620, 622, 623, 624, 625, 628, 629, 632, 633, 634, 635, 636, 638, 639, 640, 641, 647, 648, 650, 653, 654, 655, 656, 660, 661, 662, 663, 665, 666, 668, 670, 672, 673, 675, 679, 681, 682, 684, 685, 686, 687, 690, 691, 692, 694, 695, 696, 697, 698, 699, 701, 702, 703, 704, 719, 726, 727, 728, 729, 731, 732, 733, 734, 736, 737, 738, 739, 740, 741, 743, 745, 746, 748, 749, 750, 751, 752, 753, 754, 755, 756, 759, 764, 765, 780, 782, 783, 789, 800, 807, 810, 813, 815, 816, 817, 823, 824, 826, 830, 835, 842, 849, 850], "x0": [26, 27, 45, 76, 526, 622, 817], "normalize_trac": [26, 27], "html": [26, 27, 41, 51, 52, 74, 75, 142, 150, 238, 248, 249, 264, 322, 329, 330, 362, 365, 368, 371, 380, 411, 482, 511, 617, 618, 620, 625, 627, 635, 673, 674, 702, 752, 800, 818, 846], "fname": [26, 27, 43, 45, 782, 838], "anticip": [26, 27], "addition": [26, 27, 813, 826, 827, 862], "backend_compil": [26, 27], "normalize_native_comp": [26, 27], "return_backend_compiled_fn": 26, "immedi": [26, 27, 805, 806], "built": [26, 27, 32, 40, 42, 45, 121, 617, 780, 781, 782, 800, 806, 807, 812, 813, 830, 836, 842, 849, 855, 856, 860], "summar": [26, 27, 92, 830], "eager_graph": [26, 27, 800, 849, 850], "lazy_graph": [26, 27, 800, 849, 850], "codebas": [26, 27, 206, 207, 619, 801, 808, 815, 821, 826, 827, 829, 830, 831, 834, 847], "thought": [26, 27, 806, 807, 822, 846, 854], "research": [26, 27, 40, 800, 845, 850, 856, 863], "wa": [26, 27, 32, 41, 52, 65, 66, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 79, 80, 81, 82, 84, 85, 86, 87, 88, 89, 95, 105, 106, 107, 108, 109, 110, 111, 112, 113, 129, 131, 136, 138, 144, 148, 150, 175, 209, 215, 216, 217, 218, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 240, 241, 242, 246, 247, 249, 250, 251, 252, 254, 255, 256, 257, 258, 259, 260, 262, 263, 264, 265, 266, 267, 268, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 288, 289, 290, 291, 292, 293, 297, 298, 299, 300, 301, 303, 304, 305, 306, 307, 328, 329, 330, 331, 332, 334, 336, 343, 344, 350, 351, 352, 354, 355, 356, 362, 365, 369, 391, 392, 393, 411, 440, 442, 443, 444, 445, 446, 447, 448, 449, 452, 453, 454, 458, 459, 480, 482, 483, 484, 490, 492, 493, 494, 496, 498, 511, 512, 513, 514, 523, 526, 527, 529, 530, 534, 535, 536, 537, 538, 541, 542, 545, 547, 549, 550, 551, 553, 554, 557, 565, 566, 580, 581, 583, 585, 587, 588, 589, 601, 607, 612, 620, 622, 629, 635, 636, 638, 639, 640, 641, 647, 648, 653, 654, 655, 660, 661, 662, 663, 665, 666, 668, 670, 672, 673, 679, 684, 685, 686, 687, 691, 694, 695, 696, 697, 698, 701, 702, 719, 726, 727, 728, 729, 731, 734, 737, 738, 739, 740, 741, 745, 746, 748, 749, 750, 751, 752, 753, 754, 755, 756, 789, 800, 802, 807, 809, 811, 812, 814, 817, 823, 825, 827, 835, 837, 846, 849, 850, 855, 856, 858], "No": [26, 27, 40, 52, 58, 75, 81, 370, 444, 445, 446, 448, 449, 626, 684, 807, 814, 815, 856], "matter": [26, 27, 32, 817, 845], "job": [26, 27, 800, 812, 814, 850], "haven": [26, 27, 32, 842, 856], "jax_out": [26, 27], "ideal": [26, 27, 814, 815, 827, 833, 838], "But": [26, 27, 766, 813, 814, 818, 821, 824, 833, 840], "bring": [26, 27, 809, 829, 830, 835, 836, 843, 846], "wise": [26, 46, 51, 52, 57, 68, 74, 75, 80, 97, 98, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 215, 216, 218, 219, 220, 222, 223, 225, 226, 227, 228, 229, 230, 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50, 69, 72, 73, 153, 154, 155, 156, 157, 158, 164, 191, 192, 204, 618, 619, 815], "certainli": [26, 27, 800, 846, 862], "upon": [26, 27, 44, 807, 817, 826, 830, 833, 841, 855, 856], "unnecessari": [26, 27, 827], "extend": [26, 27, 52, 75, 371, 380, 474, 514, 811, 812, 815, 818, 819, 822, 827, 831, 841, 853, 856, 862], "infrastructur": [26, 27, 800, 852, 858, 859], "least": [26, 51, 52, 57, 74, 75, 235, 253, 268, 368, 371, 380, 395, 400, 452, 453, 454, 463, 465, 511, 620, 625, 632, 665, 735, 800, 807, 810, 814, 815, 816, 817, 823, 826, 830, 850], "coco": 26, "seamlessli": [27, 830], "benefit": [27, 800, 806, 810, 813, 826, 833, 837, 838, 841, 846, 847, 854, 858, 861], "through": [27, 32, 40, 52, 75, 95, 223, 380, 517, 518, 620, 629, 709, 715, 782, 793, 800, 801, 803, 804, 805, 807, 808, 811, 812, 813, 814, 816, 817, 819, 820, 821, 823, 824, 826, 827, 828, 830, 832, 833, 834, 835, 838, 839, 840, 849, 854, 856, 857, 858], "therefor": [27, 32, 48, 51, 52, 57, 74, 75, 121, 122, 123, 125, 126, 127, 128, 130, 131, 132, 133, 134, 137, 138, 139, 140, 141, 142, 143, 144, 150, 166, 170, 174, 215, 216, 217, 218, 220, 221, 222, 223, 224, 225, 226, 227, 229, 230, 231, 232, 233, 235, 236, 238, 240, 241, 242, 246, 247, 248, 249, 250, 251, 255, 257, 258, 259, 260, 262, 263, 264, 265, 268, 270, 271, 272, 273, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 288, 307, 322, 323, 329, 330, 332, 335, 362, 365, 368, 369, 371, 380, 386, 387, 388, 389, 391, 392, 393, 399, 404, 405, 406, 411, 413, 422, 467, 474, 475, 477, 482, 486, 511, 514, 518, 527, 535, 536, 541, 545, 547, 549, 551, 565, 583, 588, 612, 617, 618, 620, 622, 623, 624, 625, 627, 630, 632, 633, 634, 635, 636, 638, 639, 640, 641, 642, 646, 647, 648, 650, 653, 654, 655, 656, 657, 658, 660, 661, 662, 663, 665, 666, 667, 668, 669, 670, 671, 672, 673, 674, 675, 676, 677, 681, 682, 683, 687, 688, 689, 690, 691, 692, 693, 694, 695, 696, 697, 698, 699, 700, 701, 702, 725, 732, 733, 735, 736, 737, 738, 739, 740, 741, 744, 748, 749, 750, 751, 752, 753, 754, 755, 756, 805, 807, 809, 810, 813, 814, 815, 816, 817, 818, 819, 822, 823, 824, 826, 827, 828, 830, 831, 833, 835, 837, 839, 841, 845, 853, 856, 862], "wide": [27, 800, 807, 830, 854, 856], "prepar": [27, 40, 42, 45, 800, 814], "plenti": 27, "resourc": [27, 801, 805, 806, 814], "visit": [27, 805, 806, 807, 814], "page": [27, 800, 805, 806, 807, 812, 814, 820, 836, 837, 840, 842, 851], "newli": [28, 29, 41, 43, 49, 72, 147, 528, 618, 622, 807, 814, 826, 830], "randon": [28, 29, 31, 32, 33], "mean_": 28, "std_": 28, "detect": [28, 32, 51, 69, 74, 250, 620, 629, 706, 717, 805, 806, 811, 813, 814, 821, 830, 838, 839], "inspect": [28, 32, 524, 622], "__": [28, 29, 30, 31, 32, 33, 69, 817, 838], "exhibit": [29, 862], "via": [29, 32, 242, 369, 371, 435, 438, 441, 482, 620, 629, 716, 717, 807, 809, 813, 815, 816, 826, 831, 833, 835, 837, 838, 856], "script": [29, 800, 806, 807, 809, 814, 817, 835, 841, 856], "comp": 29, "low_level": 29, "chain": [29, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 79, 80, 81, 82, 84, 85, 86, 87, 88, 89, 92, 105, 106, 107, 108, 109, 110, 111, 112, 113, 129, 131, 136, 138, 144, 148, 150, 163, 167, 168, 175, 209, 215, 216, 217, 218, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 240, 241, 242, 246, 247, 249, 250, 251, 252, 254, 255, 256, 257, 258, 259, 260, 262, 263, 264, 265, 266, 267, 268, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 288, 289, 290, 291, 292, 293, 297, 298, 299, 300, 301, 303, 304, 305, 307, 328, 329, 330, 332, 334, 336, 343, 344, 350, 352, 354, 355, 356, 391, 392, 393, 411, 442, 443, 444, 445, 446, 447, 448, 449, 458, 459, 480, 482, 484, 490, 492, 493, 494, 496, 498, 511, 512, 513, 514, 523, 526, 527, 529, 530, 534, 535, 536, 537, 538, 541, 542, 545, 547, 549, 550, 551, 553, 554, 557, 565, 566, 580, 581, 583, 585, 587, 588, 601, 607, 612, 628, 629, 638, 639, 640, 641, 647, 648, 653, 654, 655, 660, 661, 662, 663, 665, 666, 668, 670, 672, 673, 679, 684, 685, 686, 687, 691, 694, 695, 696, 697, 698, 701, 702, 703, 704, 708, 719, 726, 727, 728, 729, 731, 734, 737, 738, 739, 740, 741, 745, 746, 749, 751, 752, 754, 755, 756, 785, 810, 813, 825, 827, 839, 840, 841, 856], "un": [29, 165, 618, 815, 835], "partial_comp": 29, "time_funct": 29, "slowest": [29, 52, 59, 75, 82, 371, 464, 627, 694], "express": [29, 51, 52, 74, 75, 93, 216, 220, 222, 223, 232, 234, 274, 280, 285, 352, 365, 620, 786, 794, 818, 827, 835, 840, 856, 857], "fastest": [29, 52, 59, 75, 82, 369, 371, 433, 464, 627, 694], "maxim": [29, 823, 826, 835, 853, 854, 858, 859, 860], "conclud": [30, 831], "collect": [30, 40, 42, 44, 45, 47, 69, 70, 614, 619, 622, 623, 624, 626, 629, 630, 631, 719, 776, 780, 781, 782, 783, 784, 806, 814, 819, 820, 824, 825, 828, 830, 854, 856, 859], "norm_comp": [31, 32], "global": [31, 32, 42, 53, 69, 76, 98, 153, 154, 155, 156, 157, 206, 207, 208, 571, 572, 575, 580, 581, 593, 594, 597, 618, 619, 622, 772, 783, 789, 806, 810, 811, 814, 815, 816, 819, 823, 827, 835, 856], "approach": [31, 803, 805, 806, 807, 810, 813, 815, 816, 820, 823, 827, 830, 831, 833, 837, 838, 841, 853, 860, 862], "b": [32, 46, 51, 52, 53, 56, 57, 65, 68, 71, 72, 73, 74, 75, 76, 77, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 92, 93, 96, 97, 98, 105, 106, 107, 108, 109, 110, 111, 112, 122, 123, 124, 129, 130, 131, 133, 136, 138, 144, 147, 148, 149, 150, 158, 168, 170, 175, 192, 209, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 311, 312, 324, 327, 328, 329, 330, 332, 333, 334, 335, 336, 337, 338, 339, 340, 341, 342, 343, 344, 345, 346, 348, 349, 350, 351, 352, 354, 355, 356, 360, 362, 365, 368, 369, 370, 371, 375, 378, 380, 386, 387, 388, 389, 391, 392, 395, 399, 400, 401, 404, 405, 406, 410, 411, 414, 417, 420, 422, 424, 428, 433, 436, 441, 442, 443, 445, 446, 447, 448, 452, 453, 454, 455, 458, 459, 460, 461, 464, 465, 466, 468, 469, 470, 471, 473, 474, 480, 482, 483, 484, 485, 488, 489, 494, 496, 498, 499, 501, 502, 504, 511, 512, 513, 514, 516, 518, 521, 523, 526, 527, 529, 530, 533, 534, 535, 536, 537, 538, 541, 542, 545, 547, 549, 550, 551, 553, 554, 557, 558, 565, 566, 580, 581, 583, 587, 588, 601, 603, 604, 605, 607, 609, 610, 611, 612, 614, 617, 618, 620, 622, 623, 624, 625, 626, 627, 629, 630, 631, 632, 633, 634, 635, 636, 638, 639, 640, 641, 642, 643, 645, 646, 647, 648, 649, 653, 654, 655, 656, 658, 660, 661, 662, 663, 665, 666, 667, 668, 669, 670, 672, 673, 674, 675, 676, 677, 679, 680, 681, 682, 684, 685, 686, 687, 689, 690, 691, 692, 693, 694, 695, 696, 697, 698, 699, 700, 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716, 734, 735, 736, 748, 750, 764, 765, 766, 767, 772, 783, 813, 815, 823, 827, 830, 833], "alwai": [48, 49, 52, 53, 59, 71, 72, 75, 82, 105, 123, 147, 218, 268, 339, 365, 369, 371, 437, 452, 453, 454, 460, 462, 464, 465, 466, 469, 473, 480, 488, 544, 551, 614, 618, 620, 622, 627, 690, 691, 692, 694, 696, 697, 699, 701, 766, 800, 805, 806, 807, 810, 811, 813, 815, 818, 821, 822, 823, 826, 827, 828, 829, 830, 831, 833, 835, 841, 849], "never": [48, 52, 59, 71, 75, 82, 123, 371, 452, 453, 454, 460, 462, 464, 465, 466, 469, 473, 480, 488, 544, 622, 627, 690, 691, 692, 694, 696, 697, 699, 701, 807, 815, 826, 827, 830], "valueerror": [48, 52, 59, 71, 75, 82, 86, 123, 368, 370, 401, 412, 447, 452, 453, 460, 462, 464, 465, 466, 473, 488, 627, 690, 691, 692, 694, 696, 697, 699, 701, 740, 766, 795, 819], "buffer": [48, 71, 75, 82, 123, 129, 452, 453, 460, 462, 464, 465, 466, 473, 488, 617, 690, 691, 692, 694, 696, 697, 699, 701, 781, 782, 826, 841], "nativedtyp": [48, 49, 52, 56, 57, 61, 62, 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647, 653], "0999999": [48, 65, 122, 123, 292, 301, 304, 346, 360, 365, 617, 749], "10000038": [48, 122, 123, 617], "90786433e": [48, 122, 123, 617], "310": [48, 122, 123, 617], "copy_arrai": [48, 71, 617], "to_ivy_arrai": [48, 71, 124, 617], "empty_lik": [48, 52, 71, 75, 259, 369, 420, 617, 620], "uniniti": [48, 125, 126, 617, 821], "from_dlpack": [48, 71, 617], "full_lik": [48, 71, 617, 831], "fill_valu": [48, 52, 62, 71, 75, 85, 130, 131, 247, 255, 371, 375, 482, 501, 617, 620, 632, 735, 815, 828, 831], "scalar": [48, 51, 52, 53, 57, 68, 71, 74, 75, 76, 80, 92, 107, 131, 136, 218, 239, 284, 290, 332, 333, 335, 339, 342, 344, 346, 351, 365, 368, 369, 370, 371, 415, 422, 442, 452, 453, 454, 463, 468, 588, 601, 617, 620, 622, 625, 682, 815, 825, 827, 841, 856], "fill": [48, 51, 52, 61, 62, 69, 71, 74, 75, 84, 85, 125, 130, 131, 133, 136, 137, 138, 143, 144, 269, 307, 362, 369, 371, 375, 426, 430, 435, 441, 463, 482, 483, 498, 500, 501, 617, 620, 631, 632, 727, 735, 779, 805, 828], 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[48, 71, 134, 617], "dimension": [48, 51, 52, 57, 59, 62, 65, 66, 69, 71, 74, 75, 80, 82, 88, 89, 97, 121, 127, 129, 134, 142, 287, 322, 329, 330, 362, 365, 368, 369, 371, 380, 395, 396, 400, 401, 411, 412, 419, 452, 453, 454, 458, 463, 464, 509, 521, 617, 620, 625, 627, 632, 635, 636, 655, 656, 662, 665, 668, 670, 671, 681, 682, 696, 732, 733, 735, 748, 749, 750, 751, 752, 753, 754, 755, 756, 823, 825, 830, 833, 835, 853, 856, 863], "repres": [48, 51, 52, 56, 57, 74, 75, 79, 80, 95, 120, 134, 136, 159, 217, 218, 221, 224, 233, 235, 242, 268, 281, 285, 286, 310, 324, 325, 326, 342, 359, 362, 365, 367, 368, 369, 370, 371, 374, 375, 378, 410, 414, 428, 440, 442, 447, 474, 485, 490, 491, 492, 497, 503, 510, 546, 616, 617, 618, 620, 622, 624, 625, 647, 648, 662, 670, 673, 674, 766, 779, 783, 794, 806, 810, 815, 833, 837, 853, 854, 857], "coordin": [48, 51, 62, 74, 75, 85, 134, 142, 223, 285, 314, 315, 322, 342, 362, 376, 502, 617, 620, 632, 735], "conserv": [48, 134, 617], "cartesian": [48, 134, 617], "matrix": [48, 52, 53, 56, 57, 75, 76, 79, 80, 92, 93, 95, 97, 134, 140, 141, 142, 322, 323, 362, 369, 371, 380, 418, 421, 422, 425, 426, 427, 429, 430, 431, 432, 433, 434, 435, 436, 437, 440, 441, 472, 511, 523, 529, 617, 622, 624, 625, 648, 654, 656, 658, 659, 660, 661, 663, 665, 666, 667, 668, 669, 671, 672, 673, 674, 675, 676, 677, 679, 680, 683, 764, 766, 779, 780, 794, 805, 815, 827, 854, 856], "ij": [48, 65, 134, 617, 635, 747, 794], "respect": [48, 51, 52, 54, 57, 74, 75, 77, 80, 92, 134, 215, 218, 223, 225, 227, 228, 229, 230, 235, 236, 242, 246, 247, 254, 255, 260, 262, 264, 265, 268, 271, 277, 281, 284, 285, 294, 342, 357, 360, 365, 367, 369, 371, 374, 424, 439, 451, 490, 492, 546, 603, 604, 605, 606, 607, 608, 609, 610, 611, 613, 617, 620, 622, 623, 624, 625, 628, 637, 644, 645, 650, 655, 672, 675, 703, 704, 705, 761, 764, 779, 794, 804, 805, 806, 807, 810, 811, 813, 814, 815, 816, 817, 822, 823, 825, 826, 827, 830, 831, 832, 852, 862], "rank": [48, 52, 57, 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322, 323, 362, 369, 436, 617, 625, 654, 660, 661, 668, 672], "alloc": [48, 49, 52, 72, 140, 141, 147, 323, 362, 617, 618, 805, 807, 841], "triu": [48, 71, 617], "upper": [48, 52, 57, 61, 75, 80, 84, 127, 141, 142, 307, 323, 362, 369, 380, 436, 514, 617, 625, 631, 654, 660, 661, 672, 729, 815, 826, 830], "zeros_lik": [48, 52, 71, 147, 264, 371, 482, 603, 604, 607, 609, 610, 611, 617, 618, 620, 623, 625, 627, 672, 687, 827, 833], "data_typ": [49, 52, 72, 75, 177, 618, 812, 815, 830, 831], "_arraywithdatatyp": [49, 97], "irrespect": [49, 57, 72, 80, 147, 618, 625, 675, 813, 826, 837, 863], "promot": [49, 51, 52, 57, 72, 74, 75, 80, 87, 97, 98, 147, 150, 173, 174, 175, 181, 216, 217, 218, 220, 221, 222, 223, 224, 225, 227, 228, 229, 230, 232, 233, 235, 238, 240, 242, 256, 257, 258, 259, 260, 265, 268, 273, 277, 280, 281, 282, 283, 284, 285, 286, 289, 339, 347, 352, 365, 368, 380, 411, 511, 574, 596, 618, 620, 622, 625, 627, 635, 654, 655, 662, 663, 665, 666, 667, 668, 670, 671, 673, 674, 681, 682, 688, 698, 741, 749, 752, 764, 765, 809, 818, 819, 823, 832], "nan": [49, 51, 52, 53, 63, 65, 72, 74, 75, 76, 147, 215, 216, 217, 218, 220, 221, 222, 223, 224, 231, 232, 233, 234, 235, 236, 238, 240, 241, 242, 243, 244, 249, 250, 251, 256, 257, 258, 259, 260, 263, 268, 269, 271, 273, 274, 277, 278, 279, 280, 281, 282, 285, 286, 288, 294, 328, 329, 330, 340, 344, 349, 352, 360, 365, 371, 380, 482, 509, 510, 517, 518, 519, 520, 547, 601, 615, 618, 620, 622, 633, 635, 636, 737, 738, 739, 740, 748, 749, 750, 752, 753, 754, 755, 756, 764, 767, 809, 815, 818, 825, 831, 832], "infin": [49, 51, 53, 57, 72, 74, 80, 147, 215, 216, 217, 218, 221, 222, 223, 224, 231, 232, 233, 235, 236, 238, 240, 241, 242, 249, 250, 256, 257, 258, 259, 260, 263, 268, 269, 271, 273, 277, 278, 280, 281, 282, 285, 286, 288, 329, 330, 352, 365, 547, 615, 618, 620, 622, 625, 635, 636, 673, 682, 748, 750, 755, 756, 809, 818], "desir": [49, 50, 52, 62, 69, 72, 73, 75, 85, 92, 147, 149, 150, 209, 313, 353, 362, 365, 371, 380, 472, 517, 520, 521, 618, 619, 625, 632, 677, 734, 779, 780, 807, 811, 814, 815, 816, 827, 835, 845, 849, 856], "broadcast_arrai": [49, 72, 618], "mix": [49, 51, 72, 74, 75, 76, 81, 84, 97, 98, 148, 161, 162, 175, 194, 195, 225, 228, 229, 230, 235, 236, 242, 246, 254, 255, 265, 268, 271, 277, 370, 380, 448, 518, 537, 539, 540, 541, 542, 551, 585, 588, 618, 619, 620, 622, 624, 625, 626, 627, 630, 635, 638, 640, 643, 645, 646, 648, 653, 654, 677, 684, 686, 687, 725, 747, 749, 752, 765, 767, 805, 808, 815, 816, 817, 826, 833, 835, 843, 856, 860, 862], "broadcast_to": [49, 72, 618, 815], "can_cast": [49, 72, 618, 815, 823, 827], "accord": [49, 52, 53, 59, 65, 72, 82, 88, 150, 160, 218, 229, 235, 242, 268, 279, 313, 362, 368, 371, 412, 474, 541, 544, 565, 566, 618, 620, 622, 625, 627, 635, 681, 689, 702, 752, 754, 759, 766, 786, 793, 805, 806, 809, 815, 821, 823, 827, 830], "finfo": [49, 72, 618, 830], "resolut": [49, 72, 160, 618, 807], "4028235e": [49, 160, 618], "iinfo": [49, 72, 618], "integ": [49, 51, 52, 56, 57, 59, 61, 65, 66, 69, 74, 75, 76, 79, 80, 82, 84, 88, 89, 97, 98, 121, 130, 163, 164, 170, 174, 175, 179, 215, 225, 226, 227, 228, 229, 230, 231, 241, 242, 253, 265, 270, 273, 277, 278, 288, 289, 324, 325, 326, 329, 330, 334, 338, 339, 362, 365, 368, 371, 375, 378, 380, 395, 400, 410, 413, 414, 415, 460, 469, 474, 482, 488, 497, 498, 499, 500, 501, 503, 504, 509, 511, 512, 513, 518, 521, 544, 560, 570, 602, 617, 618, 620, 622, 624, 625, 627, 631, 634, 635, 636, 637, 638, 639, 640, 642, 644, 646, 655, 657, 667, 681, 682, 696, 726, 727, 728, 729, 730, 731, 743, 745, 746, 748, 749, 750, 751, 752, 753, 754, 755, 756, 764, 765, 766, 767, 772, 780, 794, 807, 813, 815, 825, 828, 830, 835, 837], "119": [49, 163], "1220": [49, 163], "int16": [49, 52, 61, 65, 72, 84, 150, 154, 156, 161, 163, 170, 185, 380, 512, 513, 618, 635, 727, 745, 746, 751, 753, 764, 765, 815, 827, 830, 835], "32768": [49, 72, 163, 581, 622], "32767": [49, 72, 163], "is_bool_dtyp": [49, 72, 618], "is_float_dtyp": [49, 72, 618, 831], "is_int_dtyp": [49, 72, 618, 828, 831], "is_uint_dtyp": [49, 72, 618, 828, 831], "result_typ": [49, 72, 618, 815], "arrays_and_dtyp": [49, 72, 175, 618], "_arraywithdevic": [50, 97], "move": [50, 52, 73, 75, 142, 205, 209, 213, 322, 362, 371, 473, 617, 619, 782, 800, 807, 816, 831], "addit": [50, 52, 53, 60, 73, 75, 76, 83, 118, 120, 209, 218, 278, 370, 374, 380, 442, 495, 510, 515, 534, 535, 536, 602, 616, 619, 620, 622, 624, 628, 630, 650, 705, 725, 780, 794, 805, 806, 807, 811, 815, 817, 818, 821, 823, 825, 826, 827, 830, 831, 833, 837, 838, 840, 849, 856, 857, 858, 862], "__dlpack__": [50, 73, 128, 209, 617, 619], "caveat": [50, 73, 209, 370, 446, 619], "portabl": [50, 73, 209, 619, 800, 854], "_arraywithelementwis": [51, 97], "ab": [51, 57, 67, 74, 90, 97, 98, 273, 328, 344, 365, 371, 481, 620, 625, 629, 666, 676, 682, 714, 717, 761, 793, 794, 803, 810, 815, 820, 824, 827, 830], "absolut": [51, 52, 57, 67, 69, 74, 75, 80, 97, 215, 279, 328, 344, 347, 353, 365, 369, 370, 422, 437, 443, 445, 620, 625, 666, 667, 668, 673, 759, 761, 764, 766, 767, 801, 806], "aco": [51, 74, 620], "invers": [51, 52, 57, 74, 75, 80, 216, 217, 220, 221, 222, 223, 224, 368, 378, 390, 399, 401, 411, 503, 620, 625, 663, 667, 671, 786, 815], "cosin": [51, 74, 216, 217, 232, 233, 306, 309, 362, 368, 389, 399, 620, 780], "acosh": [51, 74, 161, 162, 618, 620, 803, 820], "area": [51, 52, 74, 75, 79, 217, 221, 224, 368, 403, 410, 414, 620, 826, 833, 846, 852], "hyperbol": [51, 74, 217, 221, 224, 233, 281, 285, 286, 298, 302, 360, 620], "sector": [51, 74, 217, 221, 224, 620, 846], "second": [51, 52, 54, 57, 59, 63, 74, 75, 76, 77, 80, 82, 86, 93, 97, 98, 118, 142, 173, 181, 218, 223, 225, 227, 228, 229, 230, 236, 242, 243, 244, 245, 246, 247, 253, 254, 255, 260, 261, 262, 264, 265, 268, 271, 273, 284, 313, 322, 328, 340, 342, 343, 344, 350, 354, 355, 362, 365, 369, 370, 371, 378, 380, 420, 421, 422, 424, 428, 448, 480, 487, 498, 500, 504, 511, 514, 526, 575, 597, 603, 604, 609, 616, 617, 618, 620, 622, 623, 625, 627, 628, 629, 633, 655, 658, 659, 660, 662, 665, 670, 672, 673, 675, 677, 679, 681, 698, 699, 704, 707, 737, 738, 739, 784, 806, 809, 812, 815, 817, 821, 826, 827, 830, 832, 837, 847, 861], "multipli": [51, 52, 56, 65, 74, 75, 79, 92, 218, 284, 345, 368, 369, 403, 432, 433, 512, 513, 620, 624, 635, 647, 745, 751, 807, 810, 811, 813, 817], "angl": [51, 74, 223, 233, 281, 286, 343, 365, 620], "deg": [51, 74, 219, 620], "radian": [51, 52, 74, 75, 216, 219, 220, 222, 223, 232, 234, 274, 280, 285, 352, 365, 620, 818], "degre": [51, 52, 65, 74, 75, 88, 219, 234, 274, 316, 362, 371, 480, 620, 635, 752, 754, 855], "1j": [51, 74, 75, 219, 220, 232, 233, 238, 240, 252, 275, 280, 281, 285, 332, 580, 620, 622], "2j": [51, 52, 74, 75, 219, 248, 332, 368, 395, 400, 581, 620, 622], "3j": [51, 52, 74, 75, 219, 252, 275, 332, 365, 620], "35619449": [51, 219, 620], "78539816": [51, 219, 620], "135": [51, 219, 529, 620, 622], 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"shape-conversion"]], "View Handling": [[824, "view-handling"]], "Exception Handling": [[824, "exception-handling"], [819, "exception-handling"]], "Miscellaneous Wrappers": [[824, "miscellaneous-wrappers"]], "Deep Dive": [[808, "deep-dive"]], "Data Types": [[815, "data-types"]], "Data Type Module": [[815, "data-type-module"]], "Data Type Promotion": [[815, "data-type-promotion"]], "Precise Mode": [[815, "precise-mode"]], "Precise Promotion Table": [[815, "precise-promotion-table"]], "Non-Precise Promotion Table": [[815, "non-precise-promotion-table"]], "Supported and Unsupported Data Types": [[815, "supported-and-unsupported-data-types"]], "Supported and Unsupported Data Types Attributes": [[815, "supported-and-unsupported-data-types-attributes"]], "Special Case": [[815, "special-case"]], "Backend Data Type Bugs": [[815, "backend-data-type-bugs"]], "Data Type Casting Modes": [[815, "data-type-casting-modes"]], "Superset Data Type Support": [[815, "superset-data-type-support"]], 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"unset_default_device": [[212, "unset-default-device"]], "print_all_ivy_arrays_on_dev": [[203, "print-all-ivy-arrays-on-dev"]], "set_soft_device_mode": [[205, "set-soft-device-mode"]], "bitwise_invert": [[226, "bitwise-invert"]], "dev": [[192, "dev"]], "to_device": [[209, "to-device"]], "total_mem_on_dev": [[210, "total-mem-on-dev"]], "acos": [[216, "acos"]], "add": [[218, "add"]], "function_supported_devices": [[194, "function-supported-devices"]], "handle_soft_device_variable": [[198, "handle-soft-device-variable"]], "as_native_dev": [[189, "as-native-dev"]], "set_split_factor": [[206, "set-split-factor"]], "acosh": [[217, "acosh"]], "bitwise_or": [[228, "bitwise-or"]], "atan2": [[223, "atan2"]], "default_device": [[191, "default-device"]], "function_unsupported_devices": [[195, "function-unsupported-devices"]], "unset_default_float_dtype": [[184, "unset-default-float-dtype"]], "dev_util": [[193, "dev-util"]], "gpu_is_available": [[197, "gpu-is-available"]], "bitwise_left_shift": [[227, "bitwise-left-shift"]], "split_factor": [[207, "split-factor"]], "Image": [[55, "module-ivy.data_classes.array.image"], [78, "module-ivy.data_classes.container.image"]], "Wrapping": [[90, "module-ivy.data_classes.container.wrapping"], [67, "module-ivy.data_classes.array.wrapping"]], "Conversions": [[47, "module-ivy.data_classes.array.conversions"], [70, "module-ivy.data_classes.container.conversions"]], "Compilation of a Basic Function": [[39, "Compilation-of-a-Basic-Function"]], "Installs \ud83d\udcbe": [[39, "Installs-\ud83d\udcbe"], [38, "Installs-\ud83d\udcbe"]], "Imports \ud83d\udec3": [[39, "Imports-\ud83d\udec3"], [38, "Imports-\ud83d\udec3"]], "Import Ivy compiler": [[39, "Import-Ivy-compiler"]], "Function compilation \ud83d\udee0": [[39, "Function-compilation-\ud83d\udee0"]], "Set backend": [[39, "Set-backend"]], "Sample input": [[39, "Sample-input"]], "Define function to compile": [[39, "Define-function-to-compile"]], "Compile the function": [[39, "Compile-the-function"]], "Check results": [[39, "Check-results"], [39, "id1"]], "Compiling simple neural network \ud83e\udde0": [[39, "Compiling-simple-neural-network-\ud83e\udde0"]], "Define Model": [[39, "Define-Model"], [38, "Define-Model"]], "Create model": [[39, "Create-model"]], "Define input": [[39, "Define-input"]], "Compile network": [[39, "Compile-network"]], "Ivy AlexNet demo": [[3, "Ivy-AlexNet-demo"]], "Installation": [[3, "Installation"], [7, "Installation"]], "Data Preparation": [[3, "Data-Preparation"], [4, "Data-Preparation"], [7, "Data-Preparation"], [5, "Data-Preparation"]], "Ivy AlexNet inference in Torch": [[3, "Ivy-AlexNet-inference-in-Torch"]], "TensorFlow inference": [[3, "TensorFlow-inference"]], "JAX inference": [[3, "JAX-inference"]], "Appendix (Ivy code for AlexNet implementation)": [[3, "Appendix-(Ivy-code-for-AlexNet-implementation)"]], "0.0: Unify": [[28, "0.0:-Unify"]], "0.1: Compile": [[29, "0.1:-Compile"]], "How to use decorators": [[22, "How-to-use-decorators"]], "Unify": [[22, "Unify"], [21, "Unify"], [31, "Unify"], [33, "Unify"], [32, "Unify"]], "Trace": [[22, "Trace"], [21, "Trace"]], "Transpile": [[22, "Transpile"], [21, "Transpile"], [31, "Transpile"], [33, "Transpile"], [32, "Transpile"]], "Resnet 18": [[45, "Resnet-18"]], "Transpiling a Tensorflow model to build on top": [[13, "Transpiling-a-Tensorflow-model-to-build-on-top"]], "Transpile any model": [[24, "Transpile-any-model"]], "Round up": [[24, "Round-up"]], "1.3: Dynamic vs Static": [[34, "1.3:-Dynamic-vs-Static"]], "Dynamic": [[34, "Dynamic"]], "Static": [[34, "Static"]], "ToDo: explain via examples why dynamic mode is set to True by default when transpiling to and from numpy and torch, but set to False by default when transpiling to and from tensorflow and jax.": [[34, "ToDo:-explain-via-examples-why-dynamic-mode-is-set-to-True-by-default-when-transpiling-to-and-from-numpy-and-torch,-but-set-to-False-by-default-when-transpiling-to-and-from-tensorflow-and-jax."]], "Developing a convolutional network using Ivy": [[14, "Developing-a-convolutional-network-using-Ivy"]], "TO REPLACE: Title": [[1, "TO-REPLACE:-Title"]], "Demo: Transpiling DeepMind\u2019s PerceiverIO": [[40, "Demo:-Transpiling-DeepMind's-PerceiverIO"]], "Table of Contents": [[40, "Table-of-Contents"]], "Defining the model": [[40, "Defining-the-model"]], "Model construction": [[40, "Model-construction"]], "Some helper functions": [[40, "Some-helper-functions"]], "Transpiling the model": [[40, "Transpiling-the-model"]], "PyTorch pipeline": [[40, "PyTorch-pipeline"]], "Dataset download": [[40, "Dataset-download"]], "DataLoader": [[40, "DataLoader"]], "Training": [[40, "Training"]], "Deepmind PerceiverIO on GPU": [[41, "Deepmind-PerceiverIO-on-GPU"]], "Install Python3.8 and setup the kernel": [[41, "Install-Python3.8-and-setup-the-kernel"]], "Clone the ivy and ivy-models repo": [[41, "Clone-the-ivy-and-ivy-models-repo"]], "Install ivy and ivy_models from the repos": [[41, "Install-ivy-and-ivy_models-from-the-repos"]], "Run the demo\u2026": [[41, "Run-the-demo..."]], "\u2026with torch backend": [[41, "...with-torch-backend"]], "\u2026.with tensorflow backend": [[41, "....with-tensorflow-backend"]], "\u2026with jax backend": [[41, "...with-jax-backend"]], "\u2026with numpy backend": [[41, "...with-numpy-backend"]], "Write Ivy code": [[17, "Write-Ivy-code"]], "Contents": [[17, "Contents"]], "Installing Ivy": [[17, "Installing-Ivy"]], "Importing Ivy": [[17, "Importing-Ivy"]], "Ivy Backend Handler": [[17, "Ivy-Backend-Handler"], [26, "Ivy-Backend-Handler"]], "Data Structures": [[17, "Data-Structures"], [26, "Data-Structures"]], "Ivy Functional API": [[17, "Ivy-Functional-API"], [26, "Ivy-Functional-API"]], "Transpiling a haiku model to build on top": [[12, "Transpiling-a-haiku-model-to-build-on-top"]], "End-to-End Training Pipeline in Ivy": [[42, "End-to-End-Training-Pipeline-in-Ivy"]], "Importing libraries": [[42, "Importing-libraries"]], "Let\u2019s build the pipeline with a Tensorflow backend": [[42, "Let's-build-the-pipeline-with-a-Tensorflow-backend"]], "We are using MNIST dataset for this Tutorial": [[42, "We-are-using-MNIST-dataset-for-this-Tutorial"]], "Temporary Dataset and Dynamic loader": [[42, "Temporary-Dataset-and-Dynamic-loader"]], "Defining the Ivy Network": [[42, "Defining-the-Ivy-Network"]], "Training Loop with utility functions": [[42, "Training-Loop-with-utility-functions"]], "Plotting the training metrics": [[42, "Plotting-the-training-metrics"]], "Save the trained Model": [[42, "Save-the-trained-Model"]], "Demos": [[0, "demos"]], "Creating a Notebook for Demo": [[0, "creating-a-notebook-for-demo"]], "Lazy vs Eager": [[21, "Lazy-vs-Eager"]], "Write a model using Ivy": [[25, "Write-a-model-using-Ivy"]], "Tutorials And Examples": [[15, "tutorials-and-examples"]], "Learn the basics": [[15, "learn-the-basics"], [16, "learn-the-basics"]], "Guides": [[15, "guides"], [10, "guides"]], "Examples and Demos": [[15, "examples-and-demos"], [2, "examples-and-demos"]], "1.0: Lazy vs Eager": [[31, "1.0:-Lazy-vs-Eager"]], "Compile": [[31, "Compile"], [33, "Compile"], [32, "Compile"]], "Accelerating XGBoost with JAX": [[9, "Accelerating-XGBoost-with-JAX"]], "Imports": [[9, "Imports"], [7, "Imports"], [5, "Imports"]], "Tests": [[9, "Tests"]], "Loading the Data": [[9, "Loading-the-Data"]], "Comparing xgb_frontend.XGBClassifier and xgb.XGBClassifier": [[9, "Comparing-xgb_frontend.XGBClassifier-and-xgb.XGBClassifier"]], "JAX backend": [[9, "JAX-backend"]], "Tensorflow backend": [[9, "Tensorflow-backend"]], "PyTorch backend": [[9, "PyTorch-backend"]], "More exhaustive example": [[9, "More-exhaustive-example"]], "Evaluating Training Time vs. Number of Boosting Rounds": [[9, "Evaluating-Training-Time-vs.-Number-of-Boosting-Rounds"]], "Training Time vs. Fractions of Data": [[9, "Training-Time-vs.-Fractions-of-Data"]], "Comparison of Metrics": [[9, "Comparison-of-Metrics"]], "# Ivy Bert Demo": [[4, "#-Ivy-Bert-Demo"]], "Install the dependecies": [[4, "Install-the-dependecies"]], "Import the modules": [[4, "Import-the-modules"]], "Ivy inference with Sequence Classification": [[4, "Ivy-inference-with-Sequence-Classification"]], "Ivy model inference with tensorflow": [[4, "Ivy-model-inference-with-tensorflow"]], "Ivy model inference with Jax": [[4, "Ivy-model-inference-with-Jax"]], "Ivy model inference with torch": [[4, "Ivy-model-inference-with-torch"]], "Transpile code": [[20, "Transpile-code"]], "ODSC Ivy Demo": [[26, "ODSC-Ivy-Demo"]], "Graph Tracer": [[26, "Graph-Tracer"]], "Any function": [[26, "Any-function"], [27, "Any-function"]], "Any library": [[26, "Any-library"], [27, "Any-library"]], "Any model": [[26, "Any-model"], [27, "Any-model"]], "0.2: Transpile": [[30, "0.2:-Transpile"]], "Basic Operations with Ivy": [[38, "Basic-Operations-with-Ivy"]], "Ivy as a Unified ML Framework \ud83d\udd00": [[38, "Ivy-as-a-Unified-ML-Framework-\ud83d\udd00"]], "Change frameworks by one line of code \u261d": [[38, "Change-frameworks-by-one-line-of-code-\u261d"]], "No need to worry about data types \ud83c\udfa8": [[38, "No-need-to-worry-about-data-types-\ud83c\udfa8"]], "No need to worry about framework differences \ud83d\udcb1": [[38, "No-need-to-worry-about-framework-differences-\ud83d\udcb1"]], "Unifying them all! \ud83c\udf72": [[38, "Unifying-them-all!-\ud83c\udf72"]], "Ivy as a standalone ML framework \ud83c\udf00": [[38, "Ivy-as-a-standalone-ML-framework-\ud83c\udf00"]], "Set Backend Framework": [[38, "Set-Backend-Framework"]], "Create Model": [[38, "Create-Model"]], "Create Optimizer": [[38, "Create-Optimizer"]], "Input and Target": [[38, "Input-and-Target"]], "Loss Function": [[38, "Loss-Function"]], "Training Loop": [[38, "Training-Loop"]], "Accelerating MMPreTrain models with JAX": [[6, "Accelerating-MMPreTrain-models-with-JAX"]], "Ivy as a Transpiler Introduction": [[44, "Ivy-as-a-Transpiler-Introduction"]], "To use the transpiler:": [[44, "To-use-the-transpiler:"]], "Transpiler Interface": [[44, "Transpiler-Interface"]], "Telemetry": [[44, "Telemetry"]], "1. Transpile Functions \ud83d\udd22": [[44, "1.-Transpile-Functions-\ud83d\udd22"]], "2. Transpile Libraries \ud83d\udcda": [[44, "2.-Transpile-Libraries-\ud83d\udcda"]], "3. Transpile Models \ud83c\udf10": [[44, "3.-Transpile-Models-\ud83c\udf10"]], "HuggingFace Tensorflow DeiT": [[43, "HuggingFace-Tensorflow-DeiT"]], "Graph can be visualized and displayed as html file on browser": [[43, "Graph-can-be-visualized-and-displayed-as-html-file-on-browser"]], "Using Ivy ResNet": [[7, "Using-Ivy-ResNet"]], "Prepare the set of labels": [[7, "Prepare-the-set-of-labels"]], "Load the image example \ud83d\uddbc\ufe0f": [[7, "Load-the-image-example-\ud83d\uddbc\ufe0f"], [5, "Load-the-image-example-\ud83d\uddbc\ufe0f"]], "Visualise image": [[7, "Visualise-image"], [5, "Visualise-image"]], "Model Inference ResNet34": [[7, "Model-Inference-ResNet34"]], "Initializing Native Torch ResNet34": [[7, "Initializing-Native-Torch-ResNet34"]], "Initializing Ivy ResNet34 with Pretrained Weights \u2b07\ufe0f": [[7, "Initializing-Ivy-ResNet34-with-Pretrained-Weights-\u2b07\ufe0f"]], "Use the model to classify your images \ud83d\ude80": [[7, "Use-the-model-to-classify-your-images-\ud83d\ude80"], [7, "id1"]], "Model Inference ResNet50": [[7, "Model-Inference-ResNet50"]], "Initializing Native Torch ResNet50": [[7, "Initializing-Native-Torch-ResNet50"]], "Initializing Ivy ResNet50 with Pretrained Weights \u2b07\ufe0f": [[7, "Initializing-Ivy-ResNet50-with-Pretrained-Weights-\u2b07\ufe0f"]], "3.1: Stable Diffusion": [[37, "3.1:-Stable-Diffusion"]], "1.2: As a Decorator": [[33, "1.2:-As-a-Decorator"]], "1.1: Framework Selection": [[32, "1.1:-Framework-Selection"]], "Transpiling a PyTorch model to build on top": [[11, "Transpiling-a-PyTorch-model-to-build-on-top"]], "Quickstart": [[27, "Quickstart"]], "Get familiar with Ivy": [[27, "Get-familiar-with-Ivy"]], "Functional API": [[27, "Functional-API"]], "Stateful API": [[27, "Stateful-API"]], "Tracing code": [[27, "Tracing-code"]], "3.0: Perceiver": [[36, "3.0:-Perceiver"]], "Unify code": [[18, "Unify-code"]], "Image Segmentation with Ivy UNet": [[5, "Image-Segmentation-with-Ivy-UNet"]], "Custom Preprocessing": [[5, "Custom-Preprocessing"]], "Model Inference": [[5, "Model-Inference"]], "Initializing Native Torch UNet": [[5, "Initializing-Native-Torch-UNet"]], "Initializing Ivy UNet with Pretrained Weights \u2b07\ufe0f": [[5, "Initializing-Ivy-UNet-with-Pretrained-Weights-\u2b07\ufe0f"]], "Custom masking function": [[5, "Custom-masking-function"]], "Use the model to segment your images \ud83d\ude80": [[5, "Use-the-model-to-segment-your-images-\ud83d\ude80"]], "TensorFlow backend": [[5, "TensorFlow-backend"]], "JAX": [[5, "JAX"]], "Appendix: the Ivy native implementation of UNet": [[5, "Appendix:-the-Ivy-native-implementation-of-UNet"]], "2.0: Kornia": [[35, "2.0:-Kornia"]], "Accelerating PyTorch models with JAX": [[8, "Accelerating-PyTorch-models-with-JAX"]], "Trace code": [[19, "Trace-code"]], "Transpile any library": [[23, "Transpile-any-library"]]}, "indexentries": {"_arraywithactivations (class in 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