infra: CI updates

Author: narendasan

Diff for: .gitignore

@@ -74,4 +74,5 @@ tests/py/dynamo/models/*.ts
 tests/py/dynamo/models/*.ep
 *.deb
 *.tar.xz
-MODULE.bazel.lock
+MODULE.bazel.lock
+*.whl

Diff for: MODULE.bazel

@@ -69,7 +69,6 @@ http_archive(
     urls = ["https://download.pytorch.org/libtorch/nightly/cu128/libtorch-cxx11-abi-shared-with-deps-latest.zip"],
 )
 
-
 http_archive(
     name = "libtorch_win",
     build_file = "@//third_party/libtorch:BUILD",
@@ -81,13 +80,13 @@ http_archive(
 # It is possible to specify a wheel file to use as the libtorch source by providing the URL below and
 # using the build flag `--//toolchains/dep_src:torch="whl"`
 
-http_archive(
-    name = "torch_whl",
-    build_file = "@//third_party/libtorch:BUILD",
-    strip_prefix = "torch",
-    type = "zip",
-    urls = ["https://pypi.jetson-ai-lab.dev/jp6/cu126/+f/52c/2cbdd62b78f32/torch-2.7.0-cp310-cp310-linux_aarch64.whl#sha256=52c2cbdd62b78f32c51fa178212e4721241a2ba9e0c4d7d690dd808bd890d51b"],
-)
+# http_archive(
+#     name = "torch_whl",
+#     build_file = "@//third_party/libtorch:BUILD",
+#     strip_prefix = "torch",
+#     type = "zip",
+#     urls = ["https://pypi.jetson-ai-lab.dev/jp6/cu126/+f/52c/2cbdd62b78f32/torch-2.7.0-cp310-cp310-linux_aarch64.whl#sha256=52c2cbdd62b78f32c51fa178212e4721241a2ba9e0c4d7d690dd808bd890d51b"],
+# )
 
 # Download these tarballs manually from the NVIDIA website
 # Either place them in the distdir directory in third_party and use the --distdir flag

Diff for: toolchains/ci_workspaces/MODULE.bazel.tmpl

@@ -4,10 +4,10 @@ module(
     version = "${BUILD_VERSION}"
 )
 
-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")
+bazel_dep(name = "googletest", version = "1.16.0")
+bazel_dep(name = "platforms", version = "0.0.11")
+bazel_dep(name = "rules_cc", version = "0.1.1")
+bazel_dep(name = "rules_python", version = "1.3.0")
 
 python = use_extension("@rules_python//python/extensions:python.bzl", "python")
 python.toolchain(
@@ -27,7 +27,7 @@ local_repository = use_repo_rule("@bazel_tools//tools/build_defs/repo:local.bzl"
 # 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",
+    path = "/opt/conda/lib/python3.10/site-packages/torch_tensorrt",
 )
 
 
@@ -40,6 +40,15 @@ new_local_repository(
     path = "${CUDA_HOME}",
 )
 
+# Server Arm (SBSA) and Jetson Jetpack (L4T) use different versions of CUDA and TensorRT
+# These versions can be selected using the flag `--//toolchains/dep_collection:compute_libs="jetpack"`
+
+new_local_repository(
+    name = "cuda_l4t",
+    build_file = "@//third_party/cuda:BUILD",
+    path = "/usr/local/cuda-12.6",
+)
+
 new_local_repository(
     name = "cuda_win",
     build_file = "@//third_party/cuda:BUILD",
@@ -53,12 +62,31 @@ http_archive = use_repo_rule("@bazel_tools//tools/build_defs/repo:http.bzl", "ht
 # Tarballs and fetched dependencies (default - use in cases when building from precompiled bin and tarballs)
 #############################################################################################################
 
-http_archive(
-    name = "libtorch",
-    build_file = "@//third_party/libtorch:BUILD",
-    strip_prefix = "libtorch",
-    urls = ["https://download.pytorch.org/libtorch/${CHANNEL}/${CU_VERSION}/libtorch-cxx11-abi-shared-with-deps-latest.zip"],
-)
+# http_archive(
+#    name = "libtorch",
+#    build_file = "@//third_party/libtorch:BUILD",
+#    strip_prefix = "libtorch",
+#    urls = ["https://download.pytorch.org/libtorch/${CHANNEL}/${CU_VERSION}/libtorch-cxx11-abi-shared-with-deps-latest.zip"],
+# )
+
+# http_archive(
+#    name = "libtorch_win",
+#    build_file = "@//third_party/libtorch:BUILD",
+#    strip_prefix = "libtorch",
+#    urls = ["https://download.pytorch.org/libtorch//${CHANNEL}/${CU_VERSION}/libtorch-win-shared-with-deps-latest.zip"],
+# )
+
+
+# It is possible to specify a wheel file to use as the libtorch source by providing the URL below and
+# using the build flag `--//toolchains/dep_src:torch="whl"`
+
+# http_archive(
+#     name = "torch_whl",
+#     build_file = "@//third_party/libtorch:BUILD",
+#     strip_prefix = "torch",
+#     type = "zip",
+#     urls = ["file:///${TORCH_WHL_PATH}"],
+# )
 
 # Download these tarballs manually from the NVIDIA website
 # Either place them in the distdir directory in third_party and use the --distdir flag
@@ -73,6 +101,24 @@ http_archive(
     ],
 )
 
+http_archive(
+    name = "tensorrt_sbsa",
+    build_file = "@//third_party/tensorrt/archive:BUILD",
+    strip_prefix = "TensorRT-10.9.0.34",
+    urls = [
+        "https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.9.0/tars/TensorRT-10.9.0.34.Linux.aarch64-gnu.cuda-12.8.tar.gz",
+    ],
+)
+
+http_archive(
+    name = "tensorrt_l4t",
+    build_file = "@//third_party/tensorrt/archive:BUILD",
+    strip_prefix = "TensorRT-10.3.0.26",
+    urls = [
+        "https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.3.0/tars/TensorRT-10.3.0.26.l4t.aarch64-gnu.cuda-12.6.tar.gz",
+    ],
+)
+
 http_archive(
     name = "tensorrt_win",
     build_file = "@//third_party/tensorrt/archive:BUILD",
@@ -95,13 +141,13 @@ http_archive(
 # for both versions here and do not use --config=pre-cxx11-abi
 
 new_local_repository(
-    name = "libtorch_win",
+    name = "libtorch",
     path = "${TORCH_INSTALL_PATH}",
     build_file = "third_party/libtorch/BUILD"
 )
 
 new_local_repository(
-    name = "libtorch_pre_cxx11_abi",
+    name = "libtorch_win",
     path = "${TORCH_INSTALL_PATH}",
     build_file = "third_party/libtorch/BUILD"
 )