fix(//notebooks): Fix WORKSPACE template file to reflect new build sy…

…stem layout Signed-off-by: Naren Dasan <naren@narendasan.com> Signed-off-by: Naren Dasan <narens@nvidia.com>
pytorch · Jul 16, 2020 · c8ea9b7 · c8ea9b7
1 parent 73d804b
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diff --git a/notebooks/Dockerfile.notebook b/notebooks/Dockerfile.notebook
@@ -0,0 +1,24 @@
+FROM nvcr.io/nvidia/pytorch:20.03-py3
+
+RUN apt update && apt install curl gnupg
+RUN curl https://bazel.build/bazel-release.pub.gpg | apt-key add -
+RUN echo "deb [arch=amd64] https://storage.googleapis.com/bazel-apt stable jdk1.8" | tee /etc/apt/sources.list.d/bazel.list
+
+RUN apt update && apt install bazel-3.3.1
+RUN ln -s /usr/bin/bazel-3.3.1 /usr/bin/bazel
+
+RUN pip install pillow==4.3.0
+RUN pip install torch==1.5.1
+RUN pip install torchvision==0.6.1
+
+COPY . /workspace/TRTorch
+RUN rm /workspace/TRTorch/WORKSPACE
+COPY ./notebooks/WORKSPACE.notebook  /workspace/TRTorch/WORKSPACE
+
+WORKDIR /workspace/TRTorch
+RUN bazel build //:libtrtorch --compilation_mode opt
+
+WORKDIR /workspace/TRTorch/py
+RUN python3 setup.py install
+
+WORKDIR /workspace/TRTorch/notebooks
diff --git a/notebooks/README.md b/notebooks/README.md
@@ -3,24 +3,24 @@ This folder contains demo notebooks for TRTorch.
 
 ## 1. Requirements
 
-The most convenient way to run these notebooks is via a docker container, which provides a self-contained, isolated and re-producible environment for all experiments. 
+The most convenient way to run these notebooks is via a docker container, which provides a self-contained, isolated and re-producible environment for all experiments.
 
 First, clone the repository:
 
 ```
 git clone https://github.com/NVIDIA/TRTorch
 ```
 
-Next, build the NVIDIA TRTorch container:
+Next, build the NVIDIA TRTorch container (from repo root):
 
 ```
-docker build -t trtorch -f Dockerfile.notebook .  
+docker build -t trtorch -f notebooks/Dockerfile.notebook .
 ```
 
 Then launch the container with:
 
 ```
-docker run --runtime=nvidia -it --rm --ipc=host --net=host trtorch 
+docker run --runtime=nvidia -it --rm --ipc=host --net=host trtorch
 ```
 
 Within the docker interactive bash session, start Jupyter with
@@ -38,7 +38,7 @@ in, for example:
 ```http://[host machine]:8888/?token=aae96ae9387cd28151868fee318c3b3581a2d794f3b25c6b```
 
 
-Within the container, this notebook itself is located at `/workspace/TRTorch/notebooks`.
+Within the container, this notebooks itself is located at `/workspace/TRTorch/notebooks`.
 
 ## 2. Notebook list
 

diff --git a/notebooks/WORKSPACE.notebook b/notebooks/WORKSPACE.notebook
@@ -25,29 +25,65 @@ http_archive(
 load("@rules_pkg//:deps.bzl", "rules_pkg_dependencies")
 rules_pkg_dependencies()
 
+git_repository(
+    name = "googletest",
+    remote = "https://github.com/google/googletest",
+    commit = "703bd9caab50b139428cea1aaff9974ebee5742e",
+    shallow_since = "1570114335 -0400"
+)
+
 # CUDA should be installed on the system locally
 new_local_repository(
     name = "cuda",
-    path = "/usr/local/cuda-10.2/targets/x86_64-linux/",
+    path = "/usr/local/cuda-10.2/",
     build_file = "@//third_party/cuda:BUILD",
 )
 
+new_local_repository(
+    name = "cublas",
+    path = "/usr",
+    build_file = "@//third_party/cublas:BUILD",
+)
+
+#############################################################################################################
+# Tarballs and fetched dependencies (default - use in cases when building from precompiled bin and tarballs)
+#############################################################################################################
+
 http_archive(
-    name = "libtorch_pre_cxx11_abi",
+    name = "libtorch",
     build_file = "@//third_party/libtorch:BUILD",
     strip_prefix = "libtorch",
-    sha256 = "ea8de17c5f70015583f3a7a43c7a5cdf91a1d4bd19a6a7bc11f074ef6cd69e27",
-    urls = ["https://download.pytorch.org/libtorch/cu102/libtorch-shared-with-deps-1.5.0.zip"],
+    urls = ["https://download.pytorch.org/libtorch/cu102/libtorch-cxx11-abi-shared-with-deps-1.5.1.zip"],
+    sha256 = "cf0691493d05062fe3239cf76773bae4c5124f4b039050dbdd291c652af3ab2a"
 )
 
 http_archive(
-    name = "libtorch",
+    name = "libtorch_pre_cxx11_abi",
     build_file = "@//third_party/libtorch:BUILD",
     strip_prefix = "libtorch",
-    urls = ["https://download.pytorch.org/libtorch/cu102/libtorch-cxx11-abi-shared-with-deps-1.5.0.zip"],
-    sha256 = "0efdd4e709ab11088fa75f0501c19b0e294404231442bab1d1fb953924feb6b5"
+    sha256 = "818977576572eadaf62c80434a25afe44dbaa32ebda3a0919e389dcbe74f8656",
+    urls = ["https://download.pytorch.org/libtorch/cu102/libtorch-shared-with-deps-1.5.1.zip"],
+)
+
+####################################################################################
+# Locally installed dependencies (use in cases of custom dependencies or aarch64)
+####################################################################################
+
+new_local_repository(
+    name = "cudnn",
+    path = "/usr/",
+    build_file = "@//third_party/cudnn/local:BUILD"
+)
+
+new_local_repository(
+   name = "tensorrt",
+   path = "/usr/",
+   build_file = "@//third_party/tensorrt/local:BUILD"
 )
 
+#########################################################################
+# Testing Dependencies (optional - comment out on aarch64)
+#########################################################################
 pip3_import(
     name = "trtorch_py_deps",
     requirements = "//py:requirements.txt"
@@ -64,39 +100,3 @@ pip3_import(
 load("@py_test_deps//:requirements.bzl", "pip_install")
 pip_install()
 
-## Downloaded distributions to use with --distdir
-#http_archive(
-#    name = "cudnn",
-#    urls = ["https://developer.nvidia.com/compute/machine-learning/cudnn/secure/7.6.5.32/Production/10.2_20191118/cudnn-10.2-linux-x64-v7.6.5.32.tgz"],
-#    build_file = "@//third_party/cudnn/archive:BUILD",
-#    sha256 = "600267f2caaed2fd58eb214ba669d8ea35f396a7d19b94822e6b36f9f7088c20",
-#    strip_prefix = "cuda"
-#)
-
-#http_archive(
-#    name = "tensorrt",
-#    urls = ["https://developer.nvidia.com/compute/machine-learning/tensorrt/secure/7.0/7.0.0.11/tars/TensorRT-7.0.0.11.Ubuntu-18.04.x86_64-gnu.cuda-10.2.cudnn7.6.tar.gz"],
-#    build_file = "@//third_party/tensorrt/archive:BUILD",
-#    sha256 = "c7d73b2585b18aae68b740249efa8c8ba5ae852abe9a023720595432a8eb4efd",
-#    strip_prefix = "TensorRT-7.0.0.11"
-#)
-
-# Locally installed dependencies
-new_local_repository(
-    name = "cudnn",
-    path = "/usr/",
-    build_file = "@//third_party/cudnn/local:BUILD"
-)
-
-new_local_repository(
-   name = "tensorrt",
-   path = "/usr/",
-   build_file = "@//third_party/tensorrt/local:BUILD"
-)
-
-git_repository(
-    name = "googletest",
-    remote = "https://github.com/google/googletest",
-    commit = "703bd9caab50b139428cea1aaff9974ebee5742e",
-    shallow_since = "1570114335 -0400"
-)