[Feat]Add the features for expanding and shrinking the number of tables in distributed training by independently saving files. #305
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…ible and concise.
…r=True in LoadFromFileSystem function.
…hen using DE BasicEmbedding.
…les in distributed training by independently saving files. User would be able to use DE filesystem KV files without any code changing. Just simply use savedmodel/checkpoint API to save and restore DE parameters. A better implementation for TFRA training in Horovod.
…attribute 'BatchNormalization'"
…pe to _init_from_args [fix] Compatible with TF 2.9 function read_value_no_copy.
…, because 'find_packages' has been deprecated.
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Description
Add the features for expanding and shrinking the number of tables in distributed training by independently saving files.
Also improve the performance of CPU table by using std::copy_n.
Also make genarating _DEFAULT_CUDA_COMPUTE_CAPABILITIES more compatible and concise in build_deps/toolchains/gpu/cuda_configure.bzl.
Also compatible with TF 2.9, which would pass parameter validate_shape to _init_from_args.
Also fix RedisTableOfTensors Node missing user-defined name.
Also fix problem with the parameter 'checkpoint' passing not working when using DE BasicEmbedding.
Also compatible with 'find_namespace_packages' when using setuptools, because 'find_packages' has been deprecated.
Type of change
Checklist:
How Has This Been Tested?
Read the doc(docs/api_docs/tfra/dynamic_embedding/FileSystemSaver.md) and run new tests.