docs: [Automated] Regenerating documenation for e5e9620

Signed-off-by: TRTorch Github Bot <[email protected]>

Author: TRTorch Github Bot

docs/_notebooks/Resnet50-example.html

@@ -690,7 +690,7 @@
         </div>
        </div>
        <p>
-        <img alt="c85e3eee5f964c87bdbd3da68be9c4e6" src="http://developer.download.nvidia.com/compute/machine-learning/frameworks/nvidia_logo.png"/>
+        <img alt="220e18e0c7ee47e29626163591408bba" src="http://developer.download.nvidia.com/compute/machine-learning/frameworks/nvidia_logo.png"/>
        </p>
        <h1 id="notebooks-resnet50-example--page-root">
         TRTorch Getting Started - ResNet 50

docs/_notebooks/lenet-getting-started.html

@@ -784,7 +784,7 @@
         </div>
        </div>
        <p>
-        <img alt="48e6dc90714648bba0dd002adedc7a38" src="http://developer.download.nvidia.com/compute/machine-learning/frameworks/nvidia_logo.png"/>
+        <img alt="9df4c63d2f1d42129c0898d6cc79d912" src="http://developer.download.nvidia.com/compute/machine-learning/frameworks/nvidia_logo.png"/>
        </p>
        <h1 id="notebooks-lenet-getting-started--page-root">
         TRTorch Getting Started - LeNet

docs/_notebooks/ssd-object-detection-demo.html

@@ -804,7 +804,7 @@
         </div>
        </div>
        <p>
-        <img alt="8fef448da1fa4681b0f1f1027eb1c9a7" src="http://developer.download.nvidia.com/compute/machine-learning/frameworks/nvidia_logo.png"/>
+        <img alt="13aaf97442cb41d498fac3a7296402fd" src="http://developer.download.nvidia.com/compute/machine-learning/frameworks/nvidia_logo.png"/>
        </p>
        <h1 id="notebooks-ssd-object-detection-demo--page-root">
         Object Detection with TRTorch (SSD)

docs/py_api/trtorch.html

@@ -596,11 +596,11 @@ <h2 id="functions">
     <span class="s2">"workspace_size"</span><span class="p">:</span> <span class="mi">0</span><span class="p">,</span> <span class="c1"># Maximum size of workspace given to TensorRT</span>
     <span class="s2">"max_batch_size"</span><span class="p">:</span> <span class="mi">0</span><span class="p">,</span> <span class="c1"># Maximum batch size (must be &gt;= 1 to be set, 0 means not set)</span>
     <span class="s2">"torch_fallback"</span><span class="p">:</span> <span class="p">{</span>
-        <span class="s2">"enabled"</span><span class="p">:</span> <span class="kc">True</span><span class="p">,</span>
+        <span class="s2">"enabled"</span><span class="p">:</span> <span class="kc">True</span><span class="p">,</span> <span class="c1"># Turn on or turn off falling back to PyTorch if operations are not supported in TensorRT</span>
         <span class="s2">"force_fallback_ops"</span><span class="p">:</span> <span class="p">[</span>
-            <span class="s2">"aten::max_pool2d"</span>
+            <span class="s2">"aten::max_pool2d"</span> <span class="c1"># List of specific ops to require running in PyTorch</span>
         <span class="p">],</span>
-        <span class="s2">"min_block_size"</span><span class="p">:</span> <span class="mi">1</span>
+        <span class="s2">"min_block_size"</span><span class="p">:</span> <span class="mi">3</span> <span class="c1"># Minimum number of ops an engine must incapsulate to be run in TensorRT</span>
     <span class="p">}</span>
 <span class="p">}</span>
 </pre>
@@ -1018,7 +1018,7 @@ <h2 id="functions">
          <span class="sig-paren">
           )
          </span>
-         → &lt;torch._C.ScriptClass object at 0x7fabde990ef0&gt;
+         → &lt;torch._C.ScriptClass object at 0x7fdd093be6f0&gt;
          <a class="headerlink" href="#trtorch.TensorRTCompileSpec" title="Permalink to this definition">
           ¶
          </a>
@@ -1052,6 +1052,11 @@ <h2 id="functions">
             </code>
             , describing the input sizes or ranges for inputs
 to the graph. All other keys are optional. Entries for each method to be compiled.
+           </p>
+           <p>
+            Note: Partial compilation of TorchScript modules is not supported through the PyTorch TensorRT backend
+If you need this feature, use trtorch.compile to compile your module. Usage of the resulting module is
+as if you were using the TensorRT integration.
            </p>
            <div class="highlight-py notranslate">
             <div class="highlight">