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version: "1.0"
# =============================================================================
# Ascend Docker Factory - Base and Framework Images
# =============================================================================
# This file contains ONLY base and framework-level images:
# - Base: Python, Ubuntu
# - Framework: CANN, PyTorch, ML libraries
# - Inference Runtimes: vLLM
# - Framework-level tools: msit-msmodelslim
#
# App-specific images (YOLO, Flask, Chronos, etc.) are in projects/ directory.
# See README.md for building app-specific images.
# =============================================================================
images:
# ================= Base Images =================
python:
matrix:
PYTHON_VERSION: ["3.10", "3.11"]
build:
context: .
dockerfile: dockerfiles/python.dockerfile
args:
BASE_IMAGE: "ubuntu:22.04"
PIP_INDEX_URL: "https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple"
INCLUDE_DEBUG_TOOLS: "true"
tags:
- "quay.io/service-delivery-hub/python:{PYTHON_VERSION}"
# ================= Machine Learning Images =================
ml-basic:
purpose: training # training, inference, or both
app_type: ml-basic
app_name: "ML Basic"
description: "Scikit-learn, XGBoost, traditional ML algorithms"
depends_on:
- python-3.10
build:
context: .
dockerfile: dockerfiles/ml-basic.dockerfile
tags:
- "quay.io/service-delivery-hub/ml-basic:latest"
# ================= PyTorch Images =================
pytorch-cpu:
purpose: both
app_type: pytorch
app_name: "PyTorch Base"
description: "General-purpose deep learning framework"
depends_on:
- python-3.10
build:
context: .
dockerfile: dockerfiles/pytorch-cpu.dockerfile
args:
TORCH_VERSION: "2.7.1"
TORCH_VARIANT: "cpu"
tags:
- "quay.io/service-delivery-hub/pytorch:2.7.1-cpu"
# ================= CANN Images (≤8.3, offline install) =================
# Packages must be placed in packages/<CANN_VERSION>/ before building.
cann-8.0rc1-910b:
depends_on:
- python-3.10
build:
context: .
dockerfile: dockerfiles/cann.dockerfile
args:
CANN_VERSION: "8.0.RC1"
CHIP_TYPE: "910b"
DRIVER_VERSION: "24.1.1"
INSTALL_COMPONENTS: "toolkit,kernels"
tags:
- "quay.io/service-delivery-hub/cann:8.0rc1-910b"
cann-8.2rc1-910b:
depends_on:
- python-3.10
build:
context: .
dockerfile: dockerfiles/cann.dockerfile
args:
CANN_VERSION: "8.2.RC1"
CHIP_TYPE: "910b"
DRIVER_VERSION: "24.1.1"
INSTALL_COMPONENTS: "toolkit,kernels,nnal"
tags:
- "quay.io/service-delivery-hub/cann:8.2rc1-910b"
cann-8.3rc1-910b:
depends_on:
- python-3.10
build:
context: .
dockerfile: dockerfiles/cann.dockerfile
args:
CANN_VERSION: "8.3.RC1"
CHIP_TYPE: "910b"
DRIVER_VERSION: "24.1.1"
INSTALL_COMPONENTS: "toolkit,kernels,nnal"
tags:
- "quay.io/service-delivery-hub/cann:8.3rc1-910b"
cann-8.3rc1-310p:
depends_on:
- python-3.10
build:
context: .
dockerfile: dockerfiles/cann.dockerfile
args:
CANN_VERSION: "8.3.RC1"
CHIP_TYPE: "310p"
DRIVER_VERSION: "24.1.1"
INSTALL_COMPONENTS: "toolkit,kernels"
tags:
- "quay.io/service-delivery-hub/cann:8.3rc1-310p"
# ================= CANN Images (8.5+, online install) =================
# Packages are downloaded from Huawei OBS during build.
cann-8.5.0-910b:
purpose: both
app_type: cann
app_name: "CANN"
description: "CANN 8.5.0 with online installer, supports 910B chip"
depends_on:
- python-3.10
build:
context: .
dockerfile: dockerfiles/cann-8.5.dockerfile
args:
CANN_VERSION: "8.5.0"
CANN_BUILD_TAG: "8.5.T63"
CHIP_TYPE: "910b"
tags:
- "quay.io/service-delivery-hub/cann:8.5.0-910b"
pytorch-npu-910b-cann850:
purpose: training
app_type: pytorch
app_name: "PyTorch Base"
description: "General deep learning framework with NPU acceleration (910B, CANN 8.5)"
depends_on:
- cann-8.5.0-910b
build:
context: .
dockerfile: dockerfiles/pytorch-npu.dockerfile
args:
TORCH_VERSION: "2.5.1"
TORCH_NPU_VERSION: "2.5.1"
TORCHVISION_VERSION: "0.20.1"
tags:
- "quay.io/service-delivery-hub/pytorch:2.5.1-cann850-910b"
pytorch-npu-910b-cann850-torch290:
purpose: training
app_type: pytorch
app_name: "PyTorch Base"
description: "PyTorch 2.9.0 with NPU acceleration (910B, CANN 8.5)"
depends_on:
- cann-8.5.0-910b
build:
context: .
dockerfile: dockerfiles/pytorch-npu.dockerfile
args:
TORCH_VERSION: "2.9.0"
TORCH_NPU_VERSION: "2.9.0"
TORCHVISION_VERSION: "0.24.0"
tags:
- "quay.io/service-delivery-hub/pytorch:2.9.0-cann850-910b"
pytorch-npu-910b:
purpose: training
app_type: pytorch
app_name: "PyTorch Base"
description: "General deep learning framework with NPU acceleration (910B)"
depends_on:
- cann-8.3rc1-910b
build:
context: .
dockerfile: dockerfiles/pytorch-npu.dockerfile
args:
TORCH_VERSION: "2.5.1"
TORCH_NPU_VERSION: "2.5.1"
TORCHVISION_VERSION: "0.20.1"
tags:
- "quay.io/service-delivery-hub/pytorch:2.5.1-cann83rc1-910b"
pytorch-npu-310p:
purpose: inference
app_type: pytorch
app_name: "PyTorch Base"
description: "General deep learning framework with NPU acceleration (310P)"
depends_on:
- cann-8.3rc1-310p
build:
context: .
dockerfile: dockerfiles/pytorch-npu.dockerfile
args:
TORCH_VERSION: "2.5.1"
TORCH_NPU_VERSION: "2.5.1"
TORCHVISION_VERSION: "0.20.1"
tags:
- "quay.io/service-delivery-hub/pytorch:2.5.1-cann83rc1-310p"
# ================= Inference Runtimes =================
vllm-ascend:
purpose: inference
app_type: vllm
app_name: "vLLM Runtime"
description: "High-performance LLM inference framework"
standalone: true
matrix:
BASE_IMAGE: ["v0.13.0", "v0.14.0rc1", "v0.15.0rc1", "v0.16.0rc1", "v0.17.0rc1"]
build:
context: .
dockerfile: dockerfiles/vllm.dockerfile
args:
INCLUDE_DEBUG_TOOLS: "true"
tags:
- "quay.io/service-delivery-hub/vllm-ascend:{BASE_IMAGE}"
# ================= Projects =================
yolo-ascend:
purpose: training
app_type: yolo
app_name: "YOLO Ascend"
description: "Ultralytics YOLO with Ascend NPU support"
depends_on:
- pytorch-npu-910b
build:
context: .
dockerfile: projects/yolo/yolo.dockerfile
tags:
- "quay.io/service-delivery-hub/yolo-ascend:latest-torch251-cann83rc1-910b"
# ================= Framework-Level Tools =================
# Note: App-specific images (YOLO, Flask, Chronos, etc.) should be built
# manually from projects/ directory. See README.md for examples.
msmodelslim:
purpose: training
app_type: msmodelslim
app_name: "MSModelSlim"
description: "Model compression and pruning toolkit"
depends_on:
- pytorch-npu-910b
build:
context: .
dockerfile: dockerfiles/msmodelslim.dockerfile
tags:
- "quay.io/service-delivery-hub/msmodelslim:latest-npu-910b"