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Merged
merged 1 commit into from
Jul 31, 2024
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refactor: Upgrade bazel and move to MODULE.bazel #3012

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9 changes: 5 additions & 4 deletions .bazelrc
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Original file line number Diff line number Diff line change
Expand Up @@ -20,10 +20,11 @@
# +------------------------------------------------------------+
# | Build Configurations |
# +------------------------------------------------------------+
# Enable colorful output of GCC
build:default --cxxopt="-fdiagnostics-color=always"
build:default --cxxopt='-std=c++17'
#build:default --linkopt="-Wl,--no-as-needed"

common --enable_platform_specific_config

build:linux --cxxopt="-std=c++17"
build:linux --cxxopt="-fdiagnostics-color=always"

build:windows --cxxopt="/GS-" --cxxopt="/std:c++17" --cxxopt="/permissive-"
build:windows --cxxopt="/wd4244" --cxxopt="/wd4267" --cxxopt="/wd4819"
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2 changes: 1 addition & 1 deletion .bazelversion
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Original file line number Diff line number Diff line change
@@ -1 +1 @@
6.3.2
7.2.1
66 changes: 23 additions & 43 deletions WORKSPACE → MODULE.bazel
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@@ -1,44 +1,37 @@
workspace(name = "Torch-TensorRT")

load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive")

http_archive(
name = "rules_python",
sha256 = "863ba0fa944319f7e3d695711427d9ad80ba92c6edd0b7c7443b84e904689539",
strip_prefix = "rules_python-0.22.0",
url = "https://github.com/bazelbuild/rules_python/releases/download/0.22.0/rules_python-0.22.0.tar.gz",
module(
name = "torch_tensorrt",
version = "2.5.0a0",
repo_name = "org_pytorch_tensorrt",
)

load("@rules_python//python:repositories.bzl", "py_repositories")

py_repositories()
bazel_dep(name = "googletest", version = "1.14.0")
bazel_dep(name = "platforms", version = "0.0.10")
bazel_dep(name = "rules_cc", version = "0.0.9")
bazel_dep(name = "rules_python", version = "0.34.0")

http_archive(
name = "rules_pkg",
sha256 = "8f9ee2dc10c1ae514ee599a8b42ed99fa262b757058f65ad3c384289ff70c4b8",
urls = [
"https://mirror.bazel.build/github.com/bazelbuild/rules_pkg/releases/download/0.9.1/rules_pkg-0.9.1.tar.gz",
"https://github.com/bazelbuild/rules_pkg/releases/download/0.9.1/rules_pkg-0.9.1.tar.gz",
],
python = use_extension("@rules_python//python/extensions:python.bzl", "python")
python.toolchain(
ignore_root_user_error = True,
python_version = "3.11",
)

load("@rules_pkg//:deps.bzl", "rules_pkg_dependencies")

rules_pkg_dependencies()

http_archive(
name = "googletest",
sha256 = "755f9a39bc7205f5a0c428e920ddad092c33c8a1b46997def3f1d4a82aded6e1",
strip_prefix = "googletest-5ab508a01f9eb089207ee87fd547d290da39d015",
urls = ["https://github.com/google/googletest/archive/5ab508a01f9eb089207ee87fd547d290da39d015.zip"],
bazel_dep(name = "rules_pkg", version = "1.0.1")
git_override(
module_name = "rules_pkg",
commit = "17c57f4",
remote = "https://github.com/narendasan/rules_pkg",
)
Comment on lines +19 to +22
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Any reason for overriding specific commit and for usage of your own repo ?

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@narendasan narendasan Jul 31, 2024 •
edited
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Theres an issue with building as root in the container without the patches in my fork


local_repository = use_repo_rule("@bazel_tools//tools/build_defs/repo:local.bzl", "local_repository")

# External dependency for torch_tensorrt if you already have precompiled binaries.
local_repository(
name = "torch_tensorrt",
path = "/opt/conda/lib/python3.8/site-packages/torch_tensorrt",
)
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Should this still be python3.8?

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I think we just use this for DLFW CI so @apbose might know

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@apbose apbose Jul 17, 2024 •
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The DLFW CI uses the WORKSPACE.ngc within the docker folder. python3.10 is used there-

# External dependency for torch_tensorrt if you already have precompiled binaries.
# This is currently used in pytorch NGC container CI testing.
local_repository(
    name = "torch_tensorrt",
    path = "/usr/local/lib/python3.10/dist-packages/torch_tensorrt/"
)

@narendasan based on the MODULE.bazel it will use bazel_dep to handle torchTRT dependencies. So what are the use cases when it will use the local_repository rule as compared to the bazel_dep dependencies?

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Local repositories still exist for MODULE.bazel, there is just now a bazel package repository for common packages that we use


new_local_repository = use_repo_rule("@bazel_tools//tools/build_defs/repo:local.bzl", "new_local_repository")

# CUDA should be installed on the system locally
new_local_repository(
name = "cuda",
Expand All @@ -52,6 +45,8 @@ new_local_repository(
path = "C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v12.4/",
)

http_archive = use_repo_rule("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive")

#############################################################################################################
# Tarballs and fetched dependencies (default - use in cases when building from precompiled bin and tarballs)
#############################################################################################################
Expand Down Expand Up @@ -129,18 +124,3 @@ http_archive(
# path = "/usr/",
# build_file = "@//third_party/tensorrt/local:BUILD"
#)

#########################################################################
# Development Dependencies (optional - comment out on aarch64)
#########################################################################

load("@rules_python//python:pip.bzl", "pip_parse")

pip_parse(
name = "devtools_deps",
requirements = "//:requirements-dev.txt",
)

load("@devtools_deps//:requirements.bzl", "install_deps")

install_deps()
127 changes: 127 additions & 0 deletions MODULE.bazel.lock
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2 changes: 1 addition & 1 deletion cpp/include/torch_tensorrt/macros.h
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Expand Up @@ -24,7 +24,7 @@
#define STR(x) XSTR(x)

#define TORCH_TENSORRT_MAJOR_VERSION 2
#define TORCH_TENSORRT_MINOR_VERSION 4
#define TORCH_TENSORRT_MINOR_VERSION 5
#define TORCH_TENSORRT_PATCH_VERSION 0
#define TORCH_TENSORRT_VERSION \
STR(TORCH_TENSORRT_MAJOR_VERSION) \
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3 changes: 2 additions & 1 deletion packaging/pre_build_script.sh
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Expand Up @@ -8,6 +8,7 @@ wget https://github.com/bazelbuild/bazelisk/releases/download/v1.17.0/bazelisk-l
&& chmod +x /usr/bin/bazel

export TORCH_BUILD_NUMBER=$(python -c "import torch, urllib.parse as ul; print(ul.quote_plus(torch.__version__))")
export TORCH_INSTALL_PATH=$(python -c "import torch, os; print(os.path.dirname(torch.__file__))")

cat toolchains/ci_workspaces/WORKSPACE.x86_64.release.rhel.tmpl | envsubst > WORKSPACE
cat toolchains/ci_workspaces/MODULE.bazel.tmpl | envsubst > MODULE.bazel
export CI_BUILD=1
6 changes: 3 additions & 3 deletions packaging/pre_build_script_windows.sh
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Expand Up @@ -8,11 +8,11 @@ pip install tensorrt==${TRT_VERSION} tensorrt-${CU_VERSION::4}-bindings==${TRT_V

choco install bazelisk -y

curl -Lo TensorRT.zip https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.1.0/zip/TensorRT-10.1.0.27.Windows.win10.cuda-12.4.zip
unzip -o TensorRT.zip -d C:/
#curl -Lo TensorRT.zip https://developer.download.nvidia.com/compute/machine-learning/tensorrt/10.0.1/zip/TensorRT-10.0.1.6.Windows10.win10.cuda-12.4.zip
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doesn't need to change to TRT 10.0 I think, although it's commented out.

#unzip -o TensorRT.zip -d C:/

export CUDA_HOME="$(echo ${CUDA_PATH} | sed -e 's#\\#\/#g')"

cat toolchains/ci_workspaces/WORKSPACE.win.release.tmpl | envsubst > WORKSPACE
cat toolchains/ci_workspaces/MODULE.bazel.tmpl | envsubst > MODULE.bazel

echo "RELEASE=1" >> ${GITHUB_ENV}
2 changes: 1 addition & 1 deletion py/torch_tensorrt/dynamo/_compiler.py
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Expand Up @@ -651,6 +651,6 @@ def convert_module_to_trt_engine(

with io.BytesIO() as engine_bytes:
engine_bytes.write(interpreter_result.engine)
engine_bytearray = engine_bytes.getvalue()
engine_bytearray: bytes = engine_bytes.getvalue()

return engine_bytearray
21 changes: 20 additions & 1 deletion setup.py
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Expand Up @@ -202,7 +202,7 @@ def build_libtorchtrt_pre_cxx11_abi(
if IS_WINDOWS:
cmd.append("--config=windows")
else:
cmd.append("--config=default")
cmd.append("--config=linux")

if JETPACK_VERSION == "4.5":
cmd.append("--platforms=//toolchains:jetpack_4.5")
Expand Down Expand Up @@ -482,6 +482,23 @@ def run(self):
package_data = {}

if not (PY_ONLY or NO_TS):
tensorrt_linux_external_dir = (
lambda: subprocess.check_output(
["bazel", "query", "@tensorrt//:nvinfer", "--output", "location"]
)
.decode("ascii")
.strip()
.split("/BUILD.bazel")[0]
)
tensorrt_windows_external_dir = (
lambda: subprocess.check_output(
["bazel", "query", "@tensorrt_win//:nvinfer", "--output", "location"]
)
.decode("ascii")
.strip()
.split("/BUILD.bazel")[0]
)

ext_modules += [
CUDAExtension(
"torch_tensorrt._C",
Expand Down Expand Up @@ -513,13 +530,15 @@ def run(self):
+ "/../bazel-Torch-TensorRT/external/tensorrt_win/include",
dir_path + "/../bazel-TensorRT/external/tensorrt_win/include",
dir_path + "/../bazel-tensorrt/external/tensorrt_win/include",
f"{tensorrt_windows_external_dir()}/include",
]
if IS_WINDOWS
else [
dir_path + "/../bazel-TRTorch/external/tensorrt/include",
dir_path + "/../bazel-Torch-TensorRT/external/tensorrt/include",
dir_path + "/../bazel-TensorRT/external/tensorrt/include",
dir_path + "/../bazel-tensorrt/external/tensorrt/include",
f"{tensorrt_linux_external_dir()}/include",
]
)
),
Expand Down
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