Update repo owner (#331)

tritonbench was moved from pytorch-labs/tritonbench to
meta-pytorch/tritonbench. This should allow CI to run.

Author: davidberard98

.ci/test_infra/oss_ci_benchmark_v3.py

@@ -34,7 +34,7 @@ def parse_dependencies(envs: Dict[str, str]) -> Dict[str, Dict[str, Any]]:
     dependencies = {
         "pytorch": "pytorch/pytorch",
         "triton": "triton-lang/triton",
-        "tritonbench": "pytorch-labs/tritonbench",
+        "tritonbench": "meta-pytorch/tritonbench",
     }
     out = {}
     for dep in dependencies:

.github/workflows/_linux-benchmark-abtest-h100.yml

@@ -37,7 +37,7 @@ on:
 
 jobs:
   linux-benchmark-h100:
-    if: github.repository_owner == 'pytorch-labs'
+    if: github.repository_owner == 'meta-pytorch'
     runs-on: [gcp-h100-runner]
     timeout-minutes: 240
     environment: docker-s3-upload

.github/workflows/_linux-benchmark-h100.yml

@@ -30,7 +30,7 @@ on:
 
 jobs:
   linux-benchmark-h100:
-    if: github.repository_owner == 'pytorch-labs'
+    if: github.repository_owner == 'meta-pytorch'
     runs-on: [gcp-h100-runner]
     timeout-minutes: 240
     environment: docker-s3-upload

.github/workflows/_linux-test-h100.yml

@@ -10,7 +10,7 @@ on:
 
 jobs:
   linux-test-h100:
-    if: github.repository_owner == 'pytorch-labs'
+    if: github.repository_owner == 'meta-pytorch'
     runs-on: [gcp-h100-runner]
     timeout-minutes: 240
     environment: docker-s3-upload

.github/workflows/docker-rocm.yaml

@@ -15,7 +15,7 @@ env:
 
 jobs:
   build-push-docker:
-    if: ${{ github.repository_owner == 'pytorch-labs' }}
+    if: ${{ github.repository_owner == 'meta-pytorch' }}
     runs-on: 32-core-ubuntu
     environment: docker-s3-upload
     steps:

.github/workflows/docker.yaml

@@ -25,7 +25,7 @@ env:
 
 jobs:
   build-push-docker:
-    if: ${{ github.repository_owner == 'pytorch-labs' }}
+    if: ${{ github.repository_owner == 'meta-pytorch' }}
     runs-on: 32-core-ubuntu
     environment: docker-s3-upload
     steps:

README.md

@@ -12,7 +12,7 @@ The benchmark suite should be self-contained of its dependencies. To install, fo
 Step 1: clone the repository and checkout all submodules
 
 ```
-$ git clone https://github.com/pytorch-labs/tritonbench.git
+$ git clone https://github.com/meta-pytorch/tritonbench.git
 $ git submodule update --init --recursive
 ```
 

docker/infra/values.yaml

@@ -1,6 +1,6 @@
 ## githubConfigUrl is the GitHub url for where you want to configure runners
 ## ex: https://github.com/myorg/myrepo or https://github.com/myorg
-githubConfigUrl: "https://github.com/pytorch-labs/tritonbench"
+githubConfigUrl: "https://github.com/meta-pytorch/tritonbench"
 
 ## githubConfigSecret is the k8s secrets to use when auth with GitHub API.
 ## You can choose to use GitHub App or a PAT token

docker/tritonbench-nightly.dockerfile

@@ -28,7 +28,7 @@ RUN sudo mkdir -p /workspace; sudo chown runner:runner /workspace
 # We assume that the host NVIDIA driver binaries and libraries are mapped to the docker filesystem
 # Install CUDA 12.8 build toolchains
 RUN cd /workspace; mkdir -p pytorch-ci; cd pytorch-ci; wget https://raw.githubusercontent.com/pytorch/pytorch/main/.ci/docker/common/install_cuda.sh
-RUN cd /workspace/pytorch-ci; wget https://raw.githubusercontent.com/pytorch/pytorch/main/.ci/docker/common/install_cudnn.sh && \
+RUN cd /workspace/pytorch-ci; wget https://raw.githubusercontent.com/pytorch/pytorch/main/.ci/docker/common/install_cudnn.sh || true && \
     wget https://raw.githubusercontent.com/pytorch/pytorch/main/.ci/docker/common/install_nccl.sh && \
     wget https://raw.githubusercontent.com/pytorch/pytorch/main/.ci/docker/common/install_cusparselt.sh && \
     mkdir ci_commit_pins && cd ci_commit_pins && \
@@ -59,7 +59,7 @@ RUN echo ". /workspace/setup_instance.sh\n" >> ${HOME}/.bashrc
 
 # Checkout TritonBench and submodules
 RUN git clone --recurse-submodules -b "${TRITONBENCH_BRANCH}" --single-branch \
-    https://github.com/pytorch-labs/tritonbench /workspace/tritonbench
+    https://github.com/meta-pytorch/tritonbench /workspace/tritonbench
 
 # Setup conda env and CUDA
 RUN cd /workspace/tritonbench && \

docker/tritonbench-rocm-nightly.dockerfile

@@ -22,7 +22,7 @@ RUN echo ". /workspace/setup_instance.sh\n" >> ${HOME}/.bashrc
 
 # Checkout TritonBench and submodules
 RUN git clone --recurse-submodules -b "${TRITONBENCH_BRANCH}" --single-branch \
-    https://github.com/pytorch-labs/tritonbench /workspace/tritonbench
+    https://github.com/meta-pytorch/tritonbench /workspace/tritonbench
 
 # Setup conda env
 RUN cd /workspace/tritonbench && \