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### Description 1. Renames all references of on device training to training apis. This is to keep the naming general. Nothing really prevents us from using the same apis on servers\non-edge devices. 2. Update ENABLE_TRAINING option: With this PR when this option is enabled, training apis and torch interop is also enabled. 3. Refactoring for onnxruntime_ENABLE_TRAINING_TORCH_INTEROP option: - Removed user facing option - Setting onnxruntime_ENABLE_TRAINING_TORCH_INTEROP to ON when onnxruntime_ENABLE_TRAINING is ON as we always build with torch interop. Once this PR is merged when --enable_training is selected we will do a "FULL Build" for training (with all the training entry points and features). Training entry points include: 1. ORTModule 2. Training APIs Features include: 1. ATen Fallback 2. All Training OPs includes communication and collectives 3. Strided Tensor Support 4. Python Op (torch interop) 5. ONNXBlock (Front end tools for training artifacts prep when using trianing apis) ### Motivation and Context Intention is to simply the options for building training enabled builds. This is part of the larger work item to create dedicated build for learning on the edge scenarios with just training apis enabled. |
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| .. | ||
| github | ||
| __init__.py | ||
| amd_hipify.py | ||
| build.py | ||
| clean_docker_image_cache.py | ||
| coverage.py | ||
| gen_def.py | ||
| get_docker_image.py | ||
| logger.py | ||
| op_registration_utils.py | ||
| op_registration_validator.py | ||
| policheck_exclusions.xml | ||
| reduce_op_kernels.py | ||
| replace_urls_in_deps.py | ||
| requirements.txt | ||
| update_tsaoptions.py | ||
| upload_python_package_to_azure_storage.py | ||