Fix densenet pipeline: update EOL Docker images and DALI CUDA version#3864
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Chakradhar886 wants to merge 3 commits intomainfrom
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Fix densenet pipeline: update EOL Docker images and DALI CUDA version#3864Chakradhar886 wants to merge 3 commits intomainfrom
Chakradhar886 wants to merge 3 commits intomainfrom
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- 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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- 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) - Update image_cnn_train to openmpi5.0-cuda12.4-ubuntu22.04 (old CUDA 11.8 image EOL) - Upgrade PyTorch 1.8.1 -> 2.4.0 and torchvision 0.9.1 -> 0.19.0 for CUDA 12 compat - Update nvidia-dali-cuda100 -> nvidia-dali-cuda120 to match CUDA 12.4 base image - Update apex build: use pip install instead of deprecated setup.py, remove pinned commit - Bump Python 3.8 -> 3.10, numpy, pillow, tensorboard, protobuf, pandas versions - Apply all changes to both CLI and SDK versions
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- Switch image_cnn_train from openmpi5.0-cuda12.4-ubuntu22.04 to openmpi4.1.0-ubuntu22.04 (OpenMPI 5.0 PMIx causes PRTE ERROR: Bad parameter in odls_base_default_fns.c) - PyTorch 2.4.0 pip wheel bundles CUDA runtime, no CUDA base image needed - Install apex Python-only (no --cpp_ext/--cuda_ext) to avoid nvcc dependency - Apply to both CLI and SDK versions
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