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chore: bump deps for default workspace file #2786

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Apr 26, 2024
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chore: bump deps for default workspace file #2786

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6 changes: 3 additions & 3 deletions WORKSPACE
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Original file line number Diff line number Diff line change
Expand Up @@ -81,10 +81,10 @@ http_archive(
http_archive(
name = "tensorrt",
build_file = "@//third_party/tensorrt/archive:BUILD",
sha256 = "0f8157a5fc5329943b338b893591373350afa90ca81239cdadd7580cd1eba254",
strip_prefix = "TensorRT-8.6.1.6",
sha256 = "0e35729954681411a79ccf31df089523caa11838095fbd025ddc7cd6f73f02de",
strip_prefix = "TensorRT-10.0.0.6",
urls = [
"https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/secure/8.6.1/tars/TensorRT-8.6.1.6.Linux.x86_64-gnu.cuda-12.0.tar.gz",
"https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.0.0/TensorRT-10.0.0.6.Linux.x86_64-gnu.cuda-12.4.tar.gz",
],
)

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25 changes: 15 additions & 10 deletions docsrc/getting_started/installation.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -87,15 +87,16 @@ Dependencies for Compilation
* Specify your CUDA version here if not the version used in the branch being built: https://github.com/pytorch/TensorRT/blob/4e5b0f6e860910eb510fa70a76ee3eb9825e7a4d/WORKSPACE#L46


* The correct **LibTorch** version will be pulled down for you by bazel.
* The correct **LibTorch**, **cuDNN** and **TensorRT** versions will be pulled down for you by bazel.

NOTE: By default bazel will pull the latest nightly from pytorch.org. For building main, this is usually sufficient however if there is a specific PyTorch you are targeting,
edit these locations with updated URLs/paths:

* https://github.com/pytorch/TensorRT/blob/4e5b0f6e860910eb510fa70a76ee3eb9825e7a4d/WORKSPACE#L53C1-L53C1


* **cuDNN and TensorRT** are not required to be installed on the system to build Torch-TensorRT, in fact this is preferable to ensure reproducable builds. Download the tarballs for cuDNN and TensorRT from https://developer.nvidia.com and update the paths in the WORKSPACE file here https://github.com/pytorch/TensorRT/blob/4e5b0f6e860910eb510fa70a76ee3eb9825e7a4d/WORKSPACE#L71
* **cuDNN and TensorRT** are not required to be installed on the system to build Torch-TensorRT, in fact this is preferable to ensure reproducable builds. If versions other than the default are needed
point the WORKSPACE file to the URL of the tarball or download the tarballs for cuDNN and TensorRT from https://developer.nvidia.com and update the paths in the WORKSPACE file here https://github.com/pytorch/TensorRT/blob/4e5b0f6e860910eb510fa70a76ee3eb9825e7a4d/WORKSPACE#L71

For example:

Expand All @@ -104,25 +105,29 @@ Dependencies for Compilation
http_archive(
name = "cudnn",
build_file = "@//third_party/cudnn/archive:BUILD",
sha256 = "79d77a769c7e7175abc7b5c2ed5c494148c0618a864138722c887f95c623777c",
strip_prefix = "cudnn-linux-x86_64-8.8.1.3_cuda12-archive",
sha256 = "<CUDNN SHA256>", # Optional but recommended
strip_prefix = "cudnn-linux-x86_64-<CUDNN VERSION>_<CUDA VERSION>-archive",
urls = [
#"https://developer.nvidia.com/downloads/compute/cudnn/secure/8.8.1/local_installers/12.0/cudnn-linux-x86_64-8.8.1.3_cuda12-archive.tar.xz",
"file:///<ABSOLUTE PATH TO FILE>/cudnn-linux-x86_64-8.8.1.3_cuda12-archive.tar.xz"
"https://developer.nvidia.com/downloads/compute/cudnn/<CUDNN DOWNLOAD PATH>",
# OR
"file:///<ABSOLUTE PATH TO FILE>/cudnn-linux-x86_64-<CUDNN VERSION>_<CUDA VERSION>-archive.tar.xz"
],
)

http_archive(
name = "tensorrt",
build_file = "@//third_party/tensorrt/archive:BUILD",
sha256 = "0f8157a5fc5329943b338b893591373350afa90ca81239cdadd7580cd1eba254",
strip_prefix = "TensorRT-8.6.1.6",
sha256 = "<TENSORRT SHA256>", # Optional but recommended
strip_prefix = "TensorRT-<TENSORRT VERSION>",
urls = [
#"https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/secure/8.6.1/tars/TensorRT-8.6.1.6.Linux.x86_64-gnu.cuda-12.0.tar.gz",
"file:///<ABSOLUTE PATH TO FILE>/TensorRT-8.6.1.6.Linux.x86_64-gnu.cuda-12.0.tar.gz"
"https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/<TENSORRT DOWNLOAD PATH>",
# OR
"file:///<ABSOLUTE PATH TO FILE>/TensorRT-<TENSORRT VERSION>.Linux.x86_64-gnu.cuda-<CUDA VERSION>.tar.gz"
],
)

Remember at runtime, these libraries must be added to your ``LD_LIBRARY_PATH`` explicity

If you have a local version of cuDNN and TensorRT installed, this can be used as well by commenting out the above lines and uncommenting the following lines https://github.com/pytorch/TensorRT/blob/4e5b0f6e860910eb510fa70a76ee3eb9825e7a4d/WORKSPACE#L114C1-L124C3


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