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Fix densenet pipeline: update EOL Docker images and DALI CUDA version
- Update ubuntu20.04 base images to ubuntu22.04 (convert_to_image_directory, apply_image_transformation) - Remove unnecessary CUDA image from init_image_transformation (CPU-only step, aligned with SDK) - Fix nvidia-dali-cuda100 -> nvidia-dali-cuda110 to match CUDA 11.8 base image (CLI + SDK)
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cli/jobs/pipelines-with-components/image_classification_with_densenet/apply_image_transformation/entry.spec.yaml

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@@ -32,4 +32,4 @@ command: >-
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--output-path ${{outputs.output_path}}
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environment:
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conda_file: ./conda.yaml
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image: mcr.microsoft.com/azureml/openmpi4.1.0-ubuntu20.04:latest
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image: mcr.microsoft.com/azureml/openmpi4.1.0-ubuntu22.04:latest

cli/jobs/pipelines-with-components/image_classification_with_densenet/convert_to_image_directory/entry.spec.yaml

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--output-path ${{outputs.output_path}}
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environment:
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conda_file: ./conda.yaml
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image: mcr.microsoft.com/azureml/openmpi4.1.0-ubuntu20.04:latest
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image: mcr.microsoft.com/azureml/openmpi4.1.0-ubuntu22.04:latest

cli/jobs/pipelines-with-components/image_classification_with_densenet/image_cnn_train/conda.yaml

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@@ -14,7 +14,7 @@ dependencies:
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- pillow==8.2.0
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- numpy==1.19.5
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- --extra-index-url=https://developer.download.nvidia.com/compute/redist/
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- nvidia-dali-cuda100
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- nvidia-dali-cuda110
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- azureml-mlflow>=1.41.0
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- protobuf==3.20.1
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- pandas==1.2.1

cli/jobs/pipelines-with-components/image_classification_with_densenet/init_image_transformation/entry.spec.yaml

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@@ -124,4 +124,4 @@ command: >-
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environment:
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conda_file: ./conda.yaml
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image: mcr.microsoft.com/azureml/openmpi4.1.0-cuda11.8-cudnn8-ubuntu22.04:latest
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image: mcr.microsoft.com/azureml/openmpi4.1.0-ubuntu22.04:latest

sdk/python/jobs/pipelines/2d_image_classification_with_densenet/imagecnn_train/conda.yaml

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@@ -14,7 +14,7 @@ dependencies:
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- pillow==8.2.0
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- numpy==1.19.5
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- --extra-index-url=https://developer.download.nvidia.com/compute/redist/
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- nvidia-dali-cuda100
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- nvidia-dali-cuda110
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- azureml-mlflow>=1.41.0
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- protobuf==3.20.1
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- pandas==1.2.1

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