fix that UI cannot get the error when tensor is too large and skip

add info when crc check failed.

1. add cli entry
2. add more validation for hyper config
3. add validator for config dict
4. add st for optimizer config validator
5. add custom lineage for hyper config

1. add functions for calculating target buckets and params importances
2. add restful api for target buckets, importances and metadata

fix npu timeout mechanism

sum not used and not available to others

add new field of success

Main features:

1. Use the ComputingResourceManager to manage all computing workers.
2. Ensure fair worker number between summary directories at first. So every summary directories in cache will be loaded simultaneously.
3. When a summary directory is loaded, it's worker will be released, and other unfinished summary directories can use the released workers to speed up. This way we solved the slow worker problem.

Code changes:

1. Added computing_resource_mgr.py
2. Passed ComputingResourceManager instances instead of workers_count
3. Simplified the _load_single_fine() function a bit.

Use the AST replaces the importlib/inspect modules to analyze and modify network definition script.
The importlib/inspect must load python script to analyze, but AST analysis is static code analysis and is very secure.