Update at 2023-09-22 04:32:36.330495

mlc-ai · Sep 22, 2023 · 9cb6b22 · 9cb6b22
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diff --git a/_downloads/7f7965d8006d56cdc5a7bb4ecf47205c/transformation.ipynb b/_downloads/7f7965d8006d56cdc5a7bb4ecf47205c/transformation.ipynb
@@ -1,5 +1,16 @@
 {
   "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "%%shell\n# Installs the nightly dev build of Apache TVM Unity from PyPI. If you wish to build\n# from source, see https://mlc.ai/docs/get_started/install.html#option-2-build-from-source\npip install mlc-ai-nightly --pre -f https://mlc.ai/wheels"
+      ]
+    },
     {
       "cell_type": "markdown",
       "metadata": {},

diff --git a/_downloads/904ea2b1aa828d1e33fe24c7159ed30b/creation.ipynb b/_downloads/904ea2b1aa828d1e33fe24c7159ed30b/creation.ipynb
@@ -1,5 +1,16 @@
 {
   "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "%%shell\n# Installs the nightly dev build of Apache TVM Unity from PyPI. If you wish to build\n# from source, see https://mlc.ai/docs/get_started/install.html#option-2-build-from-source\npip install mlc-ai-nightly --pre -f https://mlc.ai/wheels"
+      ]
+    },
     {
       "cell_type": "markdown",
       "metadata": {},

diff --git a/_downloads/9e9a92d1c5d05ade1e4c52404b577cfb/quick_start.ipynb b/_downloads/9e9a92d1c5d05ade1e4c52404b577cfb/quick_start.ipynb
@@ -1,5 +1,16 @@
 {
   "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "%%shell\n# Installs the nightly dev build of Apache TVM Unity from PyPI. If you wish to build\n# from source, see https://mlc.ai/docs/get_started/install.html#option-2-build-from-source\npip install mlc-ai-nightly --pre -f https://mlc.ai/wheels"
+      ]
+    },
     {
       "cell_type": "markdown",
       "metadata": {},

diff --git a/_downloads/c1f5255fdaaacecf0751cf76b407307e/docs.ipynb b/_downloads/c1f5255fdaaacecf0751cf76b407307e/docs.ipynb
@@ -1,5 +1,16 @@
 {
   "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "%%shell\n# Installs the nightly dev build of Apache TVM Unity from PyPI. If you wish to build\n# from source, see https://mlc.ai/docs/get_started/install.html#option-2-build-from-source\npip install mlc-ai-nightly --pre -f https://mlc.ai/wheels"
+      ]
+    },
     {
       "cell_type": "markdown",
       "metadata": {},

diff --git a/_sources/deep_dive/tensor_ir/tutorials/creation.rst.txt b/_sources/deep_dive/tensor_ir/tutorials/creation.rst.txt
@@ -1,17 +1,21 @@
 
-.. DO NOT EDIT.
-.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
-.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
+.. DO NOT EDIT. THIS FILE WAS AUTOMATICALLY GENERATED BY
+.. TVM'S MONKEY-PATCHED VERSION OF SPHINX-GALLERY. TO MAKE
+.. CHANGES, EDIT THE SOURCE PYTHON FILE:
 .. "deep_dive/tensor_ir/tutorials/creation.py"
-.. LINE NUMBERS ARE GIVEN BELOW.
 
 .. only:: html
 
     .. note::
         :class: sphx-glr-download-link-note
 
-        :ref:`Go to the end <sphx_glr_download_deep_dive_tensor_ir_tutorials_creation.py>`
-        to download the full example code
+        This tutorial can be used interactively with Google Colab! You can also click
+        :ref:`here <sphx_glr_download_deep_dive_tensor_ir_tutorials_creation.py>` to run the Jupyter notebook locally.
+
+        .. image:: https://raw.githubusercontent.com/tlc-pack/web-data/main/images/utilities/colab_button.svg
+            :align: center
+            :target: https://colab.research.google.com/github/mlc-ai/docs/blob/gh-pages/_downloads/904ea2b1aa828d1e33fe24c7159ed30b/creation.ipynb
+            :width: 300px
 
 .. rst-class:: sphx-glr-example-title
 
@@ -322,17 +326,17 @@ Now let's check the runtime dynamic shape inference:
 
  .. code-block:: none
 
-    [[1.3133134  0.6495218  1.4877071  1.2777237 ]
-     [0.8454754  1.0507405  1.5921998  1.2356234 ]
-     [0.94455934 1.255984   1.8895416  1.6804018 ]
-     [1.4048187  0.6619123  1.5425694  1.3525867 ]]
-    [[32.902317 36.31843  38.618576 ... 34.38242  38.077904 36.153496]
-     [30.876074 33.932625 34.957764 ... 34.601574 36.040493 32.987133]
-     [33.488075 35.399403 35.03113  ... 35.47079  36.630905 32.94932 ]
+    [[0.7251116  0.4837423  0.6439595  1.118291  ]
+     [0.9673711  0.7045894  0.71225226 1.1814611 ]
+     [0.6184114  0.39422864 0.6047367  0.84777325]
+     [0.58558464 0.4425925  0.3415207  0.9709453 ]]
+    [[33.19277  36.02573  31.856102 ... 33.393574 35.236103 29.35222 ]
+     [33.238903 32.630024 31.446648 ... 31.905727 31.982487 28.492352]
+     [37.185368 40.832024 33.343285 ... 37.34166  38.25375  30.69067 ]
      ...
-     [30.713055 34.61114  33.705093 ... 32.72695  33.860275 32.264618]
-     [30.804245 34.990288 34.76624  ... 34.223118 34.67062  30.246845]
-     [31.65222  33.824512 34.02362  ... 33.089314 33.401432 32.100853]]
+     [31.280836 34.785255 28.029655 ... 29.905796 30.281767 26.316156]
+     [32.204903 34.12505  29.516499 ... 29.903265 31.0129   29.142958]
+     [34.63931  38.60819  30.792696 ... 31.561054 33.898422 29.278904]]
 
 
 
@@ -510,7 +514,7 @@ is that we need to specify the shape of the input tensors as symbolic variables.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 0.123 seconds)
+   **Total running time of the script:** (0 minutes 0.125 seconds)
 
 
 .. _sphx_glr_download_deep_dive_tensor_ir_tutorials_creation.py:

diff --git a/_sources/deep_dive/tensor_ir/tutorials/sg_execution_times.rst.txt b/_sources/deep_dive/tensor_ir/tutorials/sg_execution_times.rst.txt
@@ -6,10 +6,10 @@
 
 Computation times
 =================
-**00:00.503** total execution time for **deep_dive_tensor_ir_tutorials** files:
+**00:00.533** total execution time for **deep_dive_tensor_ir_tutorials** files:
 
 +-----------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_deep_dive_tensor_ir_tutorials_transformation.py` (``transformation.py``) | 00:00.380 | 0.0 MB |
+| :ref:`sphx_glr_deep_dive_tensor_ir_tutorials_transformation.py` (``transformation.py``) | 00:00.408 | 0.0 MB |
 +-----------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_deep_dive_tensor_ir_tutorials_creation.py` (``creation.py``)             | 00:00.123 | 0.0 MB |
+| :ref:`sphx_glr_deep_dive_tensor_ir_tutorials_creation.py` (``creation.py``)             | 00:00.125 | 0.0 MB |
 +-----------------------------------------------------------------------------------------+-----------+--------+
diff --git a/_sources/deep_dive/tensor_ir/tutorials/transformation.rst.txt b/_sources/deep_dive/tensor_ir/tutorials/transformation.rst.txt
@@ -1,17 +1,21 @@
 
-.. DO NOT EDIT.
-.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
-.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
+.. DO NOT EDIT. THIS FILE WAS AUTOMATICALLY GENERATED BY
+.. TVM'S MONKEY-PATCHED VERSION OF SPHINX-GALLERY. TO MAKE
+.. CHANGES, EDIT THE SOURCE PYTHON FILE:
 .. "deep_dive/tensor_ir/tutorials/transformation.py"
-.. LINE NUMBERS ARE GIVEN BELOW.
 
 .. only:: html
 
     .. note::
         :class: sphx-glr-download-link-note
 
-        :ref:`Go to the end <sphx_glr_download_deep_dive_tensor_ir_tutorials_transformation.py>`
-        to download the full example code
+        This tutorial can be used interactively with Google Colab! You can also click
+        :ref:`here <sphx_glr_download_deep_dive_tensor_ir_tutorials_transformation.py>` to run the Jupyter notebook locally.
+
+        .. image:: https://raw.githubusercontent.com/tlc-pack/web-data/main/images/utilities/colab_button.svg
+            :align: center
+            :target: https://colab.research.google.com/github/mlc-ai/docs/blob/gh-pages/_downloads/7f7965d8006d56cdc5a7bb4ecf47205c/transformation.ipynb
+            :width: 300px
 
 .. rst-class:: sphx-glr-example-title
 
@@ -119,7 +123,7 @@ original implementation.
 
     Execution time summary:
      mean (ms)   median (ms)    max (ms)     min (ms)     std (ms)  
-       2.1389       2.1389       2.1389       2.1389       0.0000                  
+       2.1348       2.1348       2.1348       2.1348       0.0000                  
 
 
 
@@ -291,7 +295,7 @@ action involves reordering these two loops.
 
     Execution time summary:
      mean (ms)   median (ms)    max (ms)     min (ms)     std (ms)  
-       0.6671       0.6671       0.6671       0.6671       0.0000                  
+       0.6609       0.6609       0.6609       0.6609       0.0000                  
 
 
 
@@ -419,7 +423,7 @@ from the reduction update via the **decompose_reduction** primitive.
 
     Execution time summary:
      mean (ms)   median (ms)    max (ms)     min (ms)     std (ms)  
-       0.2647       0.2647       0.2647       0.2647       0.0000                  
+       0.2605       0.2605       0.2605       0.2605       0.0000                  
 
 
 
@@ -533,7 +537,7 @@ Alternatively, we can output the IRModule in conjunction with the historical tra
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 0.380 seconds)
+   **Total running time of the script:** (0 minutes 0.408 seconds)
 
 
 .. _sphx_glr_download_deep_dive_tensor_ir_tutorials_transformation.py:

diff --git a/_sources/index.rst.txt b/_sources/index.rst.txt
@@ -4,26 +4,30 @@
 TVM Unity is developed under Apache TVM's Github Repo in a separate `unity` branch. The documentation will be host here until it is merged into the main branch.
 
 .. toctree::
-   :maxdepth: 2
+   :maxdepth: 1
    :caption: Get Started
 
    get_started/install
    tutorials/get_started/quick_start
 
+
+.. The Deep Dive content is comprehensive
+.. we maintain a ``maxdepth`` of 2 to display more information on the main page.
+
 .. toctree::
    :maxdepth: 2
    :caption: Deep Dive
 
    deep_dive/tensor_ir/index
 
 .. toctree::
-   :maxdepth: 2
+   :maxdepth: 1
    :caption: Contribution
 
    tutorials/contribute/index
 
 .. toctree::
-   :maxdepth: 2
+   :maxdepth: 1
    :caption: References
 
    reference/publications

diff --git a/_sources/tutorials/contribute/docs.rst.txt b/_sources/tutorials/contribute/docs.rst.txt
@@ -1,17 +1,21 @@
 
-.. DO NOT EDIT.
-.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
-.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
+.. DO NOT EDIT. THIS FILE WAS AUTOMATICALLY GENERATED BY
+.. TVM'S MONKEY-PATCHED VERSION OF SPHINX-GALLERY. TO MAKE
+.. CHANGES, EDIT THE SOURCE PYTHON FILE:
 .. "tutorials/contribute/docs.py"
-.. LINE NUMBERS ARE GIVEN BELOW.
 
 .. only:: html
 
     .. note::
         :class: sphx-glr-download-link-note
 
-        :ref:`Go to the end <sphx_glr_download_tutorials_contribute_docs.py>`
-        to download the full example code
+        This tutorial can be used interactively with Google Colab! You can also click
+        :ref:`here <sphx_glr_download_tutorials_contribute_docs.py>` to run the Jupyter notebook locally.
+
+        .. image:: https://raw.githubusercontent.com/tlc-pack/web-data/main/images/utilities/colab_button.svg
+            :align: center
+            :target: https://colab.research.google.com/github/mlc-ai/docs/blob/gh-pages/_downloads/c1f5255fdaaacecf0751cf76b407307e/docs.ipynb
+            :width: 300px
 
 .. rst-class:: sphx-glr-example-title
 

diff --git a/_sources/tutorials/get_started/quick_start.rst.txt b/_sources/tutorials/get_started/quick_start.rst.txt
@@ -1,17 +1,21 @@
 
-.. DO NOT EDIT.
-.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
-.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
+.. DO NOT EDIT. THIS FILE WAS AUTOMATICALLY GENERATED BY
+.. TVM'S MONKEY-PATCHED VERSION OF SPHINX-GALLERY. TO MAKE
+.. CHANGES, EDIT THE SOURCE PYTHON FILE:
 .. "tutorials/get_started/quick_start.py"
-.. LINE NUMBERS ARE GIVEN BELOW.
 
 .. only:: html
 
     .. note::
         :class: sphx-glr-download-link-note
 
-        :ref:`Go to the end <sphx_glr_download_tutorials_get_started_quick_start.py>`
-        to download the full example code
+        This tutorial can be used interactively with Google Colab! You can also click
+        :ref:`here <sphx_glr_download_tutorials_get_started_quick_start.py>` to run the Jupyter notebook locally.
+
+        .. image:: https://raw.githubusercontent.com/tlc-pack/web-data/main/images/utilities/colab_button.svg
+            :align: center
+            :target: https://colab.research.google.com/github/mlc-ai/docs/blob/gh-pages/_downloads/9e9a92d1c5d05ade1e4c52404b577cfb/quick_start.ipynb
+            :width: 300px
 
 .. rst-class:: sphx-glr-example-title
 
@@ -577,7 +581,7 @@ timing result.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 2.429 seconds)
+   **Total running time of the script:** (0 minutes 2.459 seconds)
 
 
 .. _sphx_glr_download_tutorials_get_started_quick_start.py:

diff --git a/_sources/tutorials/get_started/sg_execution_times.rst.txt b/_sources/tutorials/get_started/sg_execution_times.rst.txt
@@ -6,8 +6,8 @@
 
 Computation times
 =================
-**00:02.429** total execution time for **tutorials_get_started** files:
+**00:02.459** total execution time for **tutorials_get_started** files:
 
 +---------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_tutorials_get_started_quick_start.py` (``quick_start.py``) | 00:02.429 | 0.0 MB |
+| :ref:`sphx_glr_tutorials_get_started_quick_start.py` (``quick_start.py``) | 00:02.459 | 0.0 MB |
 +---------------------------------------------------------------------------+-----------+--------+
diff --git a/deep_dive/tensor_ir/tutorials/creation.html b/deep_dive/tensor_ir/tutorials/creation.html
@@ -310,8 +310,9 @@
 
   <div class="sphx-glr-download-link-note admonition note">
 <p class="admonition-title">Note</p>
-<p><a class="reference internal" href="#sphx-glr-download-deep-dive-tensor-ir-tutorials-creation-py"><span class="std std-ref">Go to the end</span></a>
-to download the full example code</p>
+<p>This tutorial can be used interactively with Google Colab! You can also click
+<a class="reference internal" href="#sphx-glr-download-deep-dive-tensor-ir-tutorials-creation-py"><span class="std std-ref">here</span></a> to run the Jupyter notebook locally.</p>
+<a class="reference external image-reference" href="https://colab.research.google.com/github/mlc-ai/docs/blob/gh-pages/_downloads/904ea2b1aa828d1e33fe24c7159ed30b/creation.ipynb"><img alt="https://raw.githubusercontent.com/tlc-pack/web-data/main/images/utilities/colab_button.svg" class="align-center" src="https://raw.githubusercontent.com/tlc-pack/web-data/main/images/utilities/colab_button.svg" width="300px" /></a>
 </div>
 <section class="sphx-glr-example-title" id="tensorir-creation">
 <span id="tir-creation"></span><span id="sphx-glr-deep-dive-tensor-ir-tutorials-creation-py"></span><h1>TensorIR Creation<a class="headerlink" href="#tensorir-creation" title="Permalink to this heading">¶</a></h1>
@@ -502,17 +503,17 @@ <h3>TensorIR Function with Dynamic Shapes<a class="headerlink" href="#tensorir-f
 <span class="nb">print</span><span class="p">(</span><span class="n">evaluate_dynamic_shape</span><span class="p">(</span><span class="n">dyn_shape_lib</span><span class="p">,</span> <span class="n">m</span><span class="o">=</span><span class="mi">64</span><span class="p">,</span> <span class="n">n</span><span class="o">=</span><span class="mi">64</span><span class="p">,</span> <span class="n">k</span><span class="o">=</span><span class="mi">128</span><span class="p">))</span>
 </pre></div>
 </div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>[[1.3133134  0.6495218  1.4877071  1.2777237 ]
- [0.8454754  1.0507405  1.5921998  1.2356234 ]
- [0.94455934 1.255984   1.8895416  1.6804018 ]
- [1.4048187  0.6619123  1.5425694  1.3525867 ]]
-[[32.902317 36.31843  38.618576 ... 34.38242  38.077904 36.153496]
- [30.876074 33.932625 34.957764 ... 34.601574 36.040493 32.987133]
- [33.488075 35.399403 35.03113  ... 35.47079  36.630905 32.94932 ]
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>[[0.7251116  0.4837423  0.6439595  1.118291  ]
+ [0.9673711  0.7045894  0.71225226 1.1814611 ]
+ [0.6184114  0.39422864 0.6047367  0.84777325]
+ [0.58558464 0.4425925  0.3415207  0.9709453 ]]
+[[33.19277  36.02573  31.856102 ... 33.393574 35.236103 29.35222 ]
+ [33.238903 32.630024 31.446648 ... 31.905727 31.982487 28.492352]
+ [37.185368 40.832024 33.343285 ... 37.34166  38.25375  30.69067 ]
  ...
- [30.713055 34.61114  33.705093 ... 32.72695  33.860275 32.264618]
- [30.804245 34.990288 34.76624  ... 34.223118 34.67062  30.246845]
- [31.65222  33.824512 34.02362  ... 33.089314 33.401432 32.100853]]
+ [31.280836 34.785255 28.029655 ... 29.905796 30.281767 26.316156]
+ [32.204903 34.12505  29.516499 ... 29.903265 31.0129   29.142958]
+ [34.63931  38.60819  30.792696 ... 31.561054 33.898422 29.278904]]
 </pre></div>
 </div>
 </section>
@@ -635,7 +636,7 @@ <h3>Create Dynamic-Shape Functions<a class="headerlink" href="#create-dynamic-sh
                 C[v_i, v_j] = T.max(Y[v_i, v_j], T.float32(0))
 </pre></div>
 </div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 0.123 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 0.125 seconds)</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-deep-dive-tensor-ir-tutorials-creation-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
 <p><a class="reference download internal" download="" href="../../../_downloads/5fde583f102218c7d123f522a7aef688/creation.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">creation.py</span></code></a></p>

diff --git a/deep_dive/tensor_ir/tutorials/sg_execution_times.html b/deep_dive/tensor_ir/tutorials/sg_execution_times.html
@@ -285,15 +285,15 @@
 
   <section id="computation-times">
 <span id="sphx-glr-deep-dive-tensor-ir-tutorials-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this heading">¶</a></h1>
-<p><strong>00:00.503</strong> total execution time for <strong>deep_dive_tensor_ir_tutorials</strong> files:</p>
+<p><strong>00:00.533</strong> total execution time for <strong>deep_dive_tensor_ir_tutorials</strong> files:</p>
 <table class="docutils align-default">
 <tbody>
 <tr class="row-odd"><td><p><a class="reference internal" href="transformation.html#sphx-glr-deep-dive-tensor-ir-tutorials-transformation-py"><span class="std std-ref">Transformation</span></a> (<code class="docutils literal notranslate"><span class="pre">transformation.py</span></code>)</p></td>
-<td><p>00:00.380</p></td>
+<td><p>00:00.408</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="creation.html#sphx-glr-deep-dive-tensor-ir-tutorials-creation-py"><span class="std std-ref">TensorIR Creation</span></a> (<code class="docutils literal notranslate"><span class="pre">creation.py</span></code>)</p></td>
-<td><p>00:00.123</p></td>
+<td><p>00:00.125</p></td>
 <td><p>0.0 MB</p></td>
 </tr>
 </tbody>