feat!: Lock bazel version

.bazelversion

@@ -0,0 +1 @@
+3.2.0

README.md

@@ -68,6 +68,7 @@ torch.jit.save(trt_ts_module, "trt_torchscript_module.ts")
 
 ### Dependencies
 
+- Bazel 3.2.0
 - Libtorch 1.5.0
 - CUDA 10.2
 - cuDNN 7.6.5
@@ -81,7 +82,24 @@ Releases: https://github.com/NVIDIA/TRTorch/releases
 
 ### Installing Dependencies
 
-You need to start by having CUDA installed on the system, Libtorch will automatically be pulled for you by bazel,
+#### 0. Install Bazel
+
+If you don't have bazel installed, the easiest way is to install bazelisk using the method of you choosing https://github.com/bazelbuild/bazelisk
+
+Otherwise you can use the following instructions to install binaries https://docs.bazel.build/versions/master/install.html
+
+Finally if you need to compile from source (e.g. aarch64 until bazel distributes binaries for the architecture) you can use these instructions
+
+```sh
+export BAZEL_VERSION=<VERSION>
+mkdir bazel
+cd bazel
+curl -fSsL -O https://github.com/bazelbuild/bazel/releases/download/$BAZEL_VERSION/bazel-$BAZEL_VERSION-dist.zip
+unzip bazel-$BAZEL_VERSION-dist.zip
+bash ./compile.sh
+```
+
+You need to start by having CUDA installed on the system, LibTorch will automatically be pulled for you by bazel,
 then you have two options.
 
 #### 1. Building using cuDNN & TensorRT tarball distributions

docs/_sources/tutorials/installation.rst.txt

@@ -48,7 +48,23 @@ Compiling From Source
 Dependencies for Compilation
 ******************************************
 
-TRTorch is built with Bazel, so begin by installing it. https://docs.bazel.build/versions/master/install.html
+TRTorch is built with Bazel, so begin by installing it.
+
+The easiest way is to install bazelisk using the method of you choosing https://github.com/bazelbuild/bazelisk
+
+Otherwise you can use the following instructions to install binaries https://docs.bazel.build/versions/master/install.html
+
+Finally if you need to compile from source (e.g. aarch64 until bazel distributes binaries for the architecture) you can use these instructions
+
+```sh
+export BAZEL_VERSION=3.2.0
+mkdir bazel
+cd bazel
+curl -fSsL -O https://github.com/bazelbuild/bazel/releases/download/$BAZEL_VERSION/bazel-$BAZEL_VERSION-dist.zip
+unzip bazel-$BAZEL_VERSION-dist.zip
+bash ./compile.sh
+cp output/bazel /usr/local/bin/
+```
 
 You will also need to have CUDA installed on the system (or if running in a container, the system must have
 the CUDA driver installed and the container must have CUDA)

docs/sitemap.xml

@@ -1 +1 @@
-<urlset xmlns="http://www.sitemaps.org/schemas/sitemap/0.9"><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/class_view_hierarchy.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/classtrtorch_1_1ExtraInfo_1_1DataType.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/classtrtorch_1_1ExtraInfo_1_1DeviceType.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/classtrtorch_1_1ptq_1_1Int8CacheCalibrator.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/classtrtorch_1_1ptq_1_1Int8Calibrator.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/define_macros_8h_1a18d295a837ac71add5578860b55e5502.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/define_macros_8h_1a20c1fbeb21757871c52299dc52351b5f.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/define_macros_8h_1a25ee153c325dfc7466a33cbd5c1ff055.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/define_macros_8h_1a48d6029a45583a06848891cb0e86f7ba.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/define_macros_8h_1a71b02dddfabe869498ad5a88e11c440f.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/define_macros_8h_1a9d31d0569348d109b1b069b972dd143e.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/define_macros_8h_1abe87b341f562fd1cf40b7672e4d759da.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/define_macros_8h_1ae1c56ab8a40af292a9a4964651524d84.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/dir_cpp.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/dir_cpp_api.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/dir_cpp_api_include.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/dir_cpp_api_include_trtorch.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/enum_logging_8h_1a5f612ff2f783ff4fbe89d168f0d817d4.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/file_cpp_api_include_trtorch_logging.h.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/file_cpp_api_include_trtorch_macros.h.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/file_cpp_api_include_trtorch_ptq.h.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/file_cpp_api_include_trtorch_trtorch.h.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/file_view_hierarchy.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/function_logging_8h_1a118d65b179defff7fff279eb9cd126cb.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/function_logging_8h_1a396a688110397538f8b3fb7dfdaf38bb.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/function_logging_8h_1a9b420280bfacc016d7e36a5704021949.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/function_logging_8h_1aa533955a2b908db9e5df5acdfa24715f.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/function_logging_8h_1abc57d473f3af292551dee8b9c78373ad.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/function_logging_8h_1adf5435f0dbb09c0d931a1b851847236b.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/function_logging_8h_1aef44b69c62af7cf2edc8875a9506641a.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/function_trtorch_8h_1a2cf17d43ba9117b3b4d652744b4f0447.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/function_trtorch_8h_1a4422781719d7befedb364cacd91c6247.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/function_trtorch_8h_1a536bba54b70e44554099d23fa3d7e804.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/function_trtorch_8h_1a5f33b142bc2f3f2aaf462270b3ad7e31.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/function_trtorch_8h_1a726f6e7091b6b7be45b5a4275b2ffb10.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/function_trtorch_8h_1ab01696cfe08b6a5293c55935a9713c25.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/function_trtorch_8h_1ae38897d1ca4438227c970029d0f76fb5.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/namespace_trtorch.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/namespace_trtorch__logging.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/namespace_trtorch__ptq.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/program_listing_file_cpp_api_include_trtorch_logging.h.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/program_listing_file_cpp_api_include_trtorch_macros.h.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/program_listing_file_cpp_api_include_trtorch_ptq.h.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/program_listing_file_cpp_api_include_trtorch_trtorch.h.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/structtrtorch_1_1ExtraInfo.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/structtrtorch_1_1ExtraInfo_1_1InputRange.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/trtorch_cpp.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/unabridged_api.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/unabridged_orphan.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/contributors/execution.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/contributors/phases.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/contributors/system_overview.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/index.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/genindex.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/py-modindex.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/search.html</loc></url></urlset>
+<urlset xmlns="http://www.sitemaps.org/schemas/sitemap/0.9"><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/class_view_hierarchy.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/classtrtorch_1_1ExtraInfo_1_1DataType.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/classtrtorch_1_1ExtraInfo_1_1DeviceType.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/classtrtorch_1_1ptq_1_1Int8CacheCalibrator.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/classtrtorch_1_1ptq_1_1Int8Calibrator.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/define_macros_8h_1a18d295a837ac71add5578860b55e5502.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/define_macros_8h_1a20c1fbeb21757871c52299dc52351b5f.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/define_macros_8h_1a25ee153c325dfc7466a33cbd5c1ff055.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/define_macros_8h_1a48d6029a45583a06848891cb0e86f7ba.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/define_macros_8h_1a71b02dddfabe869498ad5a88e11c440f.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/define_macros_8h_1a9d31d0569348d109b1b069b972dd143e.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/define_macros_8h_1abe87b341f562fd1cf40b7672e4d759da.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/define_macros_8h_1ae1c56ab8a40af292a9a4964651524d84.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/dir_cpp.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/dir_cpp_api.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/dir_cpp_api_include.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/dir_cpp_api_include_trtorch.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/enum_logging_8h_1a5f612ff2f783ff4fbe89d168f0d817d4.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/file_cpp_api_include_trtorch_logging.h.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/file_cpp_api_include_trtorch_macros.h.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/file_cpp_api_include_trtorch_ptq.h.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/file_cpp_api_include_trtorch_trtorch.h.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/file_view_hierarchy.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/function_logging_8h_1a118d65b179defff7fff279eb9cd126cb.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/function_logging_8h_1a396a688110397538f8b3fb7dfdaf38bb.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/function_logging_8h_1a9b420280bfacc016d7e36a5704021949.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/function_logging_8h_1aa533955a2b908db9e5df5acdfa24715f.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/function_logging_8h_1abc57d473f3af292551dee8b9c78373ad.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/function_logging_8h_1adf5435f0dbb09c0d931a1b851847236b.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/function_logging_8h_1aef44b69c62af7cf2edc8875a9506641a.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/function_trtorch_8h_1a2cf17d43ba9117b3b4d652744b4f0447.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/function_trtorch_8h_1a4422781719d7befedb364cacd91c6247.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/function_trtorch_8h_1a536bba54b70e44554099d23fa3d7e804.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/function_trtorch_8h_1a5f33b142bc2f3f2aaf462270b3ad7e31.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/function_trtorch_8h_1a726f6e7091b6b7be45b5a4275b2ffb10.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/function_trtorch_8h_1ab01696cfe08b6a5293c55935a9713c25.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/function_trtorch_8h_1ae38897d1ca4438227c970029d0f76fb5.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/namespace_trtorch.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/namespace_trtorch__logging.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/namespace_trtorch__ptq.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/program_listing_file_cpp_api_include_trtorch_logging.h.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/program_listing_file_cpp_api_include_trtorch_macros.h.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/program_listing_file_cpp_api_include_trtorch_ptq.h.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/program_listing_file_cpp_api_include_trtorch_trtorch.h.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/structtrtorch_1_1ExtraInfo.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/structtrtorch_1_1ExtraInfo_1_1InputRange.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/trtorch_cpp.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/unabridged_api.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/_cpp_api/unabridged_orphan.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/index.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/tutorials/installation.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/genindex.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/py-modindex.html</loc></url><url><loc>https://nvidia.github.io/TRTorch/search.html</loc></url></urlset>

docs/tutorials/installation.html

@@ -455,32 +455,32 @@
            <ul class="md-nav__list">
             <li class="md-nav__item">
              <a class="md-nav__link" href="../contributors/useful_links.html#tensorrt-available-layers-and-expected-dimensions">
-              TensorRT Available Layers and Expected Dimensions:
+              TensorRT Available Layers and Expected Dimensions
              </a>
             </li>
             <li class="md-nav__item">
              <a class="md-nav__link" href="../contributors/useful_links.html#tensorrt-c-documentation">
-              TensorRT C++ Documentation:
+              TensorRT C++ Documentation
              </a>
             </li>
             <li class="md-nav__item">
              <a class="md-nav__link" href="../contributors/useful_links.html#tensorrt-python-documentation-sometimes-easier-to-read">
-              TensorRT Python Documentation (Sometimes easier to read):
+              TensorRT Python Documentation (Sometimes easier to read)
              </a>
             </li>
             <li class="md-nav__item">
              <a class="md-nav__link" href="../contributors/useful_links.html#pytorch-functional-api">
-              PyTorch Functional API:
+              PyTorch Functional API
              </a>
             </li>
             <li class="md-nav__item">
              <a class="md-nav__link" href="../contributors/useful_links.html#pytorch-native-ops">
-              PyTorch native_ops:
+              PyTorch native_ops
              </a>
             </li>
             <li class="md-nav__item">
              <a class="md-nav__link" href="../contributors/useful_links.html#pytorch-ir-documentation">
-              PyTorch IR Documentation:
+              PyTorch IR Documentation
              </a>
             </li>
            </ul>
@@ -751,10 +751,83 @@ <h2 id="dependencies-for-compilation">
        </h2>
        <p>
         TRTorch is built with Bazel, so begin by installing it.
+       </p>
+       <p>
+        The easiest way is to install bazelisk using the method of you choosing
+        <a class="reference external" href="https://github.com/bazelbuild/bazelisk">
+         https://github.com/bazelbuild/bazelisk
+        </a>
+       </p>
+       <p>
+        Otherwise you can use the following instructions to install binaries
         <a class="reference external" href="https://docs.bazel.build/versions/master/install.html">
          https://docs.bazel.build/versions/master/install.html
         </a>
        </p>
+       <p>
+        Finally if you need to compile from source (e.g. aarch64 until bazel distributes binaries for the architecture) you can use these instructions
+       </p>
+       <p>
+        <code class="docutils literal notranslate">
+         <span class="pre">
+          `sh
+         </span>
+         <span class="pre">
+          export
+         </span>
+         <span class="pre">
+          BAZEL_VERSION=3.2.0
+         </span>
+         <span class="pre">
+          mkdir
+         </span>
+         <span class="pre">
+          bazel
+         </span>
+         <span class="pre">
+          cd
+         </span>
+         <span class="pre">
+          bazel
+         </span>
+         <span class="pre">
+          curl
+         </span>
+         <span class="pre">
+          -fSsL
+         </span>
+         <span class="pre">
+          -O
+         </span>
+         <span class="pre">
+          https://github.com/bazelbuild/bazel/releases/download/$BAZEL_VERSION/bazel-$BAZEL_VERSION-dist.zip
+         </span>
+         <span class="pre">
+          unzip
+         </span>
+         <span class="pre">
+          bazel-$BAZEL_VERSION-dist.zip
+         </span>
+         <span class="pre">
+          bash
+         </span>
+         <span class="pre">
+          ./compile.sh
+         </span>
+         <span class="pre">
+          cp
+         </span>
+         <span class="pre">
+          output/bazel
+         </span>
+         <span class="pre">
+          /usr/local/bin/
+         </span>
+         <span class="pre">
+          `
+         </span>
+        </code>
+       </p>
        <p>
         You will also need to have CUDA installed on the system (or if running in a container, the system must have
 the CUDA driver installed and the container must have CUDA)

docsrc/tutorials/installation.rst

@@ -48,7 +48,23 @@ Compiling From Source
 Dependencies for Compilation
 ******************************************
 
-TRTorch is built with Bazel, so begin by installing it. https://docs.bazel.build/versions/master/install.html
+TRTorch is built with Bazel, so begin by installing it.
+
+The easiest way is to install bazelisk using the method of you choosing https://github.com/bazelbuild/bazelisk
+
+Otherwise you can use the following instructions to install binaries https://docs.bazel.build/versions/master/install.html
+
+Finally if you need to compile from source (e.g. aarch64 until bazel distributes binaries for the architecture) you can use these instructions
+
+```sh
+export BAZEL_VERSION=3.2.0
+mkdir bazel
+cd bazel
+curl -fSsL -O https://github.com/bazelbuild/bazel/releases/download/$BAZEL_VERSION/bazel-$BAZEL_VERSION-dist.zip
+unzip bazel-$BAZEL_VERSION-dist.zip
+bash ./compile.sh
+cp output/bazel /usr/local/bin/
+```
 
 You will also need to have CUDA installed on the system (or if running in a container, the system must have
 the CUDA driver installed and the container must have CUDA)