Urgh

Signed-off-by: Huy Do <huydhn@gmail.com>

Author: huydhn

.github/workflows/test_linux_job_v2.yml

@@ -36,24 +36,24 @@ jobs:
       matrix:
         runner_type: ["linux.g5.4xlarge.nvidia.gpu"]
     with:
-      job-name: "linux-py3.10-cu126"
+      job-name: "linux-py3.10-cu128"
       runner: ${{ matrix.runner_type }}
       test-infra-repository: ${{ github.repository }}
       test-infra-ref: ${{ github.ref }}
       submodules: ${{ 'true' }}
       gpu-arch-type: cuda
-      gpu-arch-version: "12.6"
+      gpu-arch-version: "12.8"
       timeout: 60
       script: |
         nvidia-smi
-        nvcc --version | grep "cuda_12.6"
+        nvcc --version | grep "cuda_12.8"
         conda create --yes --quiet -n test python=3.10
         conda activate test
-        python3 -m pip install --index-url https://download.pytorch.org/whl/nightly/cu126 --pre torch
+        python3 -m pip install --index-url https://download.pytorch.org/whl/nightly/cu128 --pre torch
         # Can import pytorch, cuda is available
         python3 -c 'import torch;cuda_avail = torch.cuda.is_available();print("CUDA available: " + str(cuda_avail));assert(cuda_avail)'
         python3 -c 'import torch;t = torch.ones([2,2], device="cuda:0");print(t);print("tensor device:" + str(t.device))'
-        python3 -c 'import torch;assert(torch.version.cuda == "12.6")'
+        python3 -c 'import torch;assert(torch.version.cuda == "12.8")'
   test-gpu-containers:
     uses: ./.github/workflows/linux_job_v2.yml
     permissions:
@@ -62,24 +62,24 @@ jobs:
       matrix:
         runner_type: ["linux.aws.a100"]
     with:
-      job-name: "linux-py3.10-cu128-container"
+      job-name: "linux-py3.10-cu126-container"
       runner: ${{ matrix.runner_type }}
       test-infra-repository: ${{ github.repository }}
       test-infra-ref: ${{ github.ref }}
       submodules: ${{ 'true' }}
       gpu-arch-type: cuda
-      gpu-arch-version: "12.8"
+      gpu-arch-version: "12.6"
       timeout: 60
       script: |
         nvidia-smi
-        nvcc --version | grep "cuda_12.8"
+        nvcc --version | grep "cuda_12.6"
         conda create --yes --quiet -n test python=3.10
         conda activate test
-        python3 -m pip install --index-url https://download.pytorch.org/whl/nightly/cu128 --pre torch
+        python3 -m pip install --index-url https://download.pytorch.org/whl/nightly/cu126 --pre torch
         # Can import pytorch, cuda is available
         python3 -c 'import torch;cuda_avail = torch.cuda.is_available();print("CUDA available: " + str(cuda_avail));assert(cuda_avail)'
         python3 -c 'import torch;t = torch.ones([2,2], device="cuda:0");print(t);print("tensor device:" + str(t.device))'
-        python3 -c 'import torch;assert(torch.version.cuda == "12.8")'
+        python3 -c 'import torch;assert(torch.version.cuda == "12.6")'
   test-docker-image:
     uses: ./.github/workflows/linux_job_v2.yml
     permissions: