diff --git a/.github/workflows/cron.yml b/.github/workflows/cron.yml index c1015cd541..e986a27670 100644 --- a/.github/workflows/cron.yml +++ b/.github/workflows/cron.yml @@ -15,8 +15,8 @@ jobs: environment: - "PT191+CUDA113" - "PT110+CUDA113" - - "PT112+CUDA113" - - "PTLATEST+CUDA118" + - "PT113+CUDA113" + - "PTLATEST+CUDA121" include: # https://docs.nvidia.com/deeplearning/frameworks/pytorch-release-notes - environment: PT191+CUDA113 @@ -25,12 +25,12 @@ jobs: - environment: PT110+CUDA113 pytorch: "torch==1.10.2 torchvision==0.11.3 --extra-index-url https://download.pytorch.org/whl/cu113" base: "nvcr.io/nvidia/pytorch:21.06-py3" # CUDA 11.3 - - environment: PT112+CUDA113 - pytorch: "torch==1.12.1 torchvision==0.13.1 --extra-index-url https://download.pytorch.org/whl/cu113" + - environment: PT113+CUDA113 + pytorch: "torch==1.13.1 torchvision==0.14.1 --extra-index-url https://download.pytorch.org/whl/cu113" base: "nvcr.io/nvidia/pytorch:21.06-py3" # CUDA 11.3 - - environment: PTLATEST+CUDA118 + - environment: PTLATEST+CUDA121 pytorch: "-U torch torchvision --extra-index-url https://download.pytorch.org/whl/cu118" - base: "nvcr.io/nvidia/pytorch:23.03-py3" # CUDA 11.8 + base: "nvcr.io/nvidia/pytorch:23.06-py3" # CUDA 12.1 container: image: ${{ matrix.base }} options: "--gpus all" @@ -76,7 +76,7 @@ jobs: if: github.repository == 'Project-MONAI/MONAI' strategy: matrix: - container: ["pytorch:22.09", "pytorch:22.11", "pytorch:23.03"] + container: ["pytorch:22.10", "pytorch:23.06"] container: image: nvcr.io/nvidia/${{ matrix.container }}-py3 # testing with the latest pytorch base image options: "--gpus all" @@ -121,7 +121,7 @@ jobs: if: github.repository == 'Project-MONAI/MONAI' strategy: matrix: - container: ["pytorch:22.09", "pytorch:22.11", "pytorch:23.03"] + container: ["pytorch:23.06"] container: image: nvcr.io/nvidia/${{ matrix.container }}-py3 # testing with the latest pytorch base image options: "--gpus all" @@ -221,7 +221,7 @@ jobs: if: github.repository == 'Project-MONAI/MONAI' needs: cron-gpu # so that monai itself is verified first container: - image: nvcr.io/nvidia/pytorch:23.03-py3 # testing with the latest pytorch base image + image: nvcr.io/nvidia/pytorch:23.06-py3 # testing with the latest pytorch base image options: "--gpus all --ipc=host" runs-on: [self-hosted, linux, x64, integration] steps: diff --git a/.github/workflows/pythonapp-gpu.yml b/.github/workflows/pythonapp-gpu.yml index 723e060d11..65ee29f4e3 100644 --- a/.github/workflows/pythonapp-gpu.yml +++ b/.github/workflows/pythonapp-gpu.yml @@ -25,7 +25,7 @@ jobs: - "PT110+CUDA111" - "PT112+CUDA118DOCKER" - "PT113+CUDA116" - - "PT114+CUDA120DOCKER" + - "PT210+CUDA121DOCKER" include: # https://docs.nvidia.com/deeplearning/frameworks/pytorch-release-notes - environment: PT19+CUDA114DOCKER @@ -42,10 +42,10 @@ jobs: - environment: PT113+CUDA116 pytorch: "torch==1.13.1 torchvision==0.14.1" base: "nvcr.io/nvidia/cuda:11.6.1-devel-ubuntu18.04" - - environment: PT114+CUDA120DOCKER - # 23.03: 2.0.0a0+1767026 + - environment: PT210+CUDA121DOCKER + # 23.06: 2.1.0a0+4136153 pytorch: "-h" # we explicitly set pytorch to -h to avoid pip install error - base: "nvcr.io/nvidia/pytorch:23.03-py3" + base: "nvcr.io/nvidia/pytorch:23.06-py3" container: image: ${{ matrix.base }} options: --gpus all --env NVIDIA_DISABLE_REQUIRE=true # workaround for unsatisfied condition: cuda>=11.6 diff --git a/Dockerfile b/Dockerfile index 653dd1571c..adfa5390ed 100644 --- a/Dockerfile +++ b/Dockerfile @@ -11,7 +11,7 @@ # To build with a different base image # please run `docker build` using the `--build-arg PYTORCH_IMAGE=...` flag. -ARG PYTORCH_IMAGE=nvcr.io/nvidia/pytorch:23.03-py3 +ARG PYTORCH_IMAGE=nvcr.io/nvidia/pytorch:23.06-py3 FROM ${PYTORCH_IMAGE} LABEL maintainer="monai.contact@gmail.com" diff --git a/tests/test_grid_distortion.py b/tests/test_grid_distortion.py index d776d49f4d..1a698140af 100644 --- a/tests/test_grid_distortion.py +++ b/tests/test_grid_distortion.py @@ -81,7 +81,7 @@ ) TESTS.append( [ - dict(num_cells=2, distort_steps=[(1.25,) * 3] * 3, mode="nearest", padding_mode="zeros"), + dict(num_cells=2, distort_steps=[(1.26,) * 3] * 3, mode="nearest", padding_mode="zeros"), p(np.indices([3, 3, 3])[:1].astype(np.float32)), p( np.array(