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@bioinformatist bioinformatist commented Sep 23, 2023

@lazyky 义父,please assist me in completing this PR. The tasks that need to be done are as follows:

  • Replace all instances of derive-builder with typed-builder.
  • Rewrite the unit test for the Inference trait to cover the scenario of two threads simultaneously operating on the same batch (you can refer to the Register trait for guidance).
  • Use tempfile::NamedTempFile for temporary files.
  • Replace the type of working_status, which is a property of TaskConfig, with &[&str], which is the same as the signature of Inference::inference.
  • Write a new simple test_task_running_in_parallel() (just leave the comments there, I'll add examples with Burn later).
  • The Metadata now uses Option<i64> instead of a regular i64 type for the model_update_time field. Please make sure to update this in the Inference trait accordingly.
  • The data_path field should be removed everywhere.
  • The number of fields and tags can be determined by Vec<T>, rendering the relative fields obsolete in both the Register and Inference trait.

@bioinformatist bioinformatist added the enhancement New feature or request label Sep 25, 2023
* test: add tests for Task and Inference

- add test_task_running_in_parallel()
- rewrite the test of Inference
- update deadpool
- change vec<&str> into &[&str]
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@lazyky There are still some issues with the unit test for Task. Using an async function is unnecessary in this case. Additionally, since we are using anyhow::Result, why not use ? everywhere?

bioinformatist and others added 7 commits October 7, 2023 14:52
* refactor: delete unnecessary code

- Use ? for `anyhow::Result`
- delete unnecessary `async`

* refactor: refactor the use of asynchronous
* feat: Optimize the timing of task run()

- Change model_update_time tag in Stable training_data to train_start_time
- Add update_train_start_time() to update by timestamp of latest available model
- Delete model_update_time in Metadata
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@lazyky It is recommended to merge structure TaskConfig into TDengine as other kind of database may need different configurations.

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3 participants