docs: [Automated] Regenerating documenation for 254eab2

Signed-off-by: TRTorch Github Bot <[email protected]>
pytorch · Jul 28, 2021 · 24de61b · 24de61b
1 parent 254eab2
commit 24de61b
Show file tree

Hide file tree

Showing 7 changed files with 157 additions and 149 deletions.
diff --git a/docs/_notebooks/Resnet50-example.html b/docs/_notebooks/Resnet50-example.html
@@ -693,7 +693,7 @@
         </div>
        </div>
        <p>
-        <img alt="ff74b56771a64c978bf8eab7b77f6d64" src="http://developer.download.nvidia.com/compute/machine-learning/frameworks/nvidia_logo.png"/>
+        <img alt="3f3df38af6534d96b3e00b4a5ac32254" 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

diff --git a/docs/_notebooks/lenet-getting-started.html b/docs/_notebooks/lenet-getting-started.html
@@ -787,7 +787,7 @@
         </div>
        </div>
        <p>
-        <img alt="415b837ad51b4452b05ef87991e84465" src="http://developer.download.nvidia.com/compute/machine-learning/frameworks/nvidia_logo.png"/>
+        <img alt="9fafb7c6b26042f09019abca625e72a9" 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

diff --git a/docs/_notebooks/ssd-object-detection-demo.html b/docs/_notebooks/ssd-object-detection-demo.html
@@ -807,7 +807,7 @@
         </div>
        </div>
        <p>
-        <img alt="474905315e234b31a168b62fdd2739fa" src="http://developer.download.nvidia.com/compute/machine-learning/frameworks/nvidia_logo.png"/>
+        <img alt="656583182bac46c79c1fd7d509553e59" 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)

diff --git a/docs/_sources/tutorials/trtorchc.rst.txt b/docs/_sources/tutorials/trtorchc.rst.txt
@@ -19,79 +19,83 @@ to standard TorchScript. Load with ``torch.jit.load()`` and run like you would r
     trtorchc [input_file_path] [output_file_path]
         [input_specs...] {OPTIONS}
 
-    TRTorch is a compiler for TorchScript, it will compile and optimize
-    TorchScript programs to run on NVIDIA GPUs using TensorRT
+        TRTorch is a compiler for TorchScript, it will compile and optimize
+        TorchScript programs to run on NVIDIA GPUs using TensorRT
 
-  OPTIONS:
+      OPTIONS:
 
-      -h, --help                        Display this help menu
-      Verbiosity of the compiler
-        -v, --verbose                     Dumps debugging information about the
-                                          compilation process onto the console
-        -w, --warnings                    Disables warnings generated during
-                                          compilation onto the console (warnings
-                                          are on by default)
-        --i, --info                       Dumps info messages generated during
-                                          compilation onto the console
-      --build-debuggable-engine         Creates a debuggable engine
-      --use-strict-types                Restrict operating type to only use set
-                                        operation precision
-      --allow-gpu-fallback              (Only used when targeting DLA
-                                        (device-type)) Lets engine run layers on
-                                        GPU if they are not supported on DLA
-      --disable-tf32                    Prevent Float32 layers from using the
-                                        TF32 data format
-      -p[precision...],
-      --enabled-precison=[precision...] (Repeatable) Enabling an operating
-                                        precision for kernels to use when
-                                        building the engine (Int8 requires a
-                                        calibration-cache argument) [ float |
-                                        float32 | f32 | half | float16 | f16 |
-                                        int8 | i8 ] (default: float)
-      -d[type], --device-type=[type]    The type of device the engine should be
-                                        built for [ gpu | dla ] (default: gpu)
-      --gpu-id=[gpu_id]                 GPU id if running on multi-GPU platform
-                                        (defaults to 0)
-      --dla-core=[dla_core]             DLACore id if running on available DLA
-                                        (defaults to 0)
-      --engine-capability=[capability]  The type of device the engine should be
-                                        built for [ default | safe_gpu |
-                                        safe_dla ]
-      --calibration-cache-file=[file_path]
-                                        Path to calibration cache file to use
-                                        for post training quantization
-      --num-min-timing-iter=[num_iters] Number of minimization timing iterations
-                                        used to select kernels
-      --num-avg-timing-iters=[num_iters]
-                                        Number of averaging timing iterations
-                                        used to select kernels
-      --workspace-size=[workspace_size] Maximum size of workspace given to
-                                        TensorRT
-      --max-batch-size=[max_batch_size] Maximum batch size (must be >= 1 to be
-                                        set, 0 means not set)
-      -t[threshold],
-      --threshold=[threshold]           Maximum acceptable numerical deviation
-                                        from standard torchscript output
-                                        (default 2e-5)
-      --save-engine                     Instead of compiling a full a
-                                        TorchScript program, save the created
-                                        engine to the path specified as the
-                                        output path
-      input_file_path                   Path to input TorchScript file
-      output_file_path                  Path for compiled TorchScript (or
-                                        TensorRT engine) file
-      input_specs...                    Specs for inputs to engine, can either
-                                        be a single size or a range defined by
-                                        Min, Optimal, Max sizes, e.g.
-                                        "(N,..,C,H,W)"
-                                        "[(MIN_N,..,MIN_C,MIN_H,MIN_W);(OPT_N,..,OPT_C,OPT_H,OPT_W);(MAX_N,..,MAX_C,MAX_H,MAX_W)]".
-                                        Data Type and format can be specified by
-                                        adding an "@" followed by dtype and "%"
-                                        followed by format to the end of the
-                                        shape spec. e.g. "(3, 3, 32,
-                                        32)@f16%NHWC"
-      "--" can be used to terminate flag options and force all following
-      arguments to be treated as positional options
+          -h, --help                        Display this help menu
+          Verbiosity of the compiler
+            -v, --verbose                     Dumps debugging information about the
+                                              compilation process onto the console
+            -w, --warnings                    Disables warnings generated during
+                                              compilation onto the console (warnings
+                                              are on by default)
+            --i, --info                       Dumps info messages generated during
+                                              compilation onto the console
+          --build-debuggable-engine         Creates a debuggable engine
+          --use-strict-types                Restrict operating type to only use set
+                                            operation precision
+          --allow-gpu-fallback              (Only used when targeting DLA
+                                            (device-type)) Lets engine run layers on
+                                            GPU if they are not supported on DLA
+          --disable-tf32                    Prevent Float32 layers from using the
+                                            TF32 data format
+          -p[precision...],
+          --enabled-precison=[precision...] (Repeatable) Enabling an operating
+                                            precision for kernels to use when
+                                            building the engine (Int8 requires a
+                                            calibration-cache argument) [ float |
+                                            float32 | f32 | half | float16 | f16 |
+                                            int8 | i8 ] (default: float)
+          -d[type], --device-type=[type]    The type of device the engine should be
+                                            built for [ gpu | dla ] (default: gpu)
+          --gpu-id=[gpu_id]                 GPU id if running on multi-GPU platform
+                                            (defaults to 0)
+          --dla-core=[dla_core]             DLACore id if running on available DLA
+                                            (defaults to 0)
+          --engine-capability=[capability]  The type of device the engine should be
+                                            built for [ default | safe_gpu |
+                                            safe_dla ]
+          --calibration-cache-file=[file_path]
+                                            Path to calibration cache file to use
+                                            for post training quantization
+          --embed-engine                    Whether to treat input file as a
+                                            serialized TensorRT engine and embed it
+                                            into a TorchScript module (device spec
+                                            must be provided)
+          --num-min-timing-iter=[num_iters] Number of minimization timing iterations
+                                            used to select kernels
+          --num-avg-timing-iters=[num_iters]
+                                            Number of averaging timing iterations
+                                            used to select kernels
+          --workspace-size=[workspace_size] Maximum size of workspace given to
+                                            TensorRT
+          --max-batch-size=[max_batch_size] Maximum batch size (must be >= 1 to be
+                                            set, 0 means not set)
+          -t[threshold],
+          --threshold=[threshold]           Maximum acceptable numerical deviation
+                                            from standard torchscript output
+                                            (default 2e-5)
+          --save-engine                     Instead of compiling a full a
+                                            TorchScript program, save the created
+                                            engine to the path specified as the
+                                            output path
+          input_file_path                   Path to input TorchScript file
+          output_file_path                  Path for compiled TorchScript (or
+                                            TensorRT engine) file
+          input_specs...                    Specs for inputs to engine, can either
+                                            be a single size or a range defined by
+                                            Min, Optimal, Max sizes, e.g.
+                                            "(N,..,C,H,W)"
+                                            "[(MIN_N,..,MIN_C,MIN_H,MIN_W);(OPT_N,..,OPT_C,OPT_H,OPT_W);(MAX_N,..,MAX_C,MAX_H,MAX_W)]".
+                                            Data Type and format can be specified by
+                                            adding an "@" followed by dtype and "%"
+                                            followed by format to the end of the
+                                            shape spec. e.g. "(3, 3, 32,
+                                            32)@f16%NHWC"
+          "--" can be used to terminate flag options and force all following
+          arguments to be treated as positional options
 
 
 e.g.

diff --git a/docs/py_api/trtorch.html b/docs/py_api/trtorch.html
@@ -1121,7 +1121,7 @@ <h2 id="functions">
          <span class="sig-paren">
           )
          </span>
-         → &lt;torch._C.ScriptClass object at 0x7ff7f901d2f0&gt;
+         → &lt;torch._C.ScriptClass object at 0x7fe8b17b4630&gt;
          <a class="headerlink" href="#trtorch.TensorRTCompileSpec" title="Permalink to this definition">
           ¶
          </a>

diff --git a/docs/searchindex.js b/docs/searchindex.js