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T2R2: Train, test, record, repeat - incremental environment for testing AI models

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Description

TODO


Quick start


Basic training loop

TODO


Implement your own selector

We give you an opportunity to use your own selectors.

  1. Prepare a class you want to use - it should inherit from Selector class from t2r2.selector. Implement its select method.
  2. When declarating your own selector - provide module_path as one of the arguments.

Below we present a simple example how to do it.

config.yaml part

  selectors:
    - name: UserSelector
      args: 
        module_path: ./my_selector.py

my_selector.py code

import pandas as pd
from t2r2.selector import Selector

class UserSelector(Selector):
    def select(self, dataset: pd.DataFrame) -> pd.DataFrame:
        return dataset[:5]

Curriculum learning

To force specific order in which examples will be passed during training:

training:
  curriculum_learning: True

Then you also need to provide the order column in your training data.

Basically, the examples will be sorted according to order column and won't be shuffled.

You can also use the custom selector to dynamically provide the order of your training examples. For example, to pass examples in the order of increasing lenght of text:

class ClSelector(Selector):
    def select(self, dataset: pd.DataFrame) -> pd.DataFrame:
        dataset["order"] = [len(i) for i in dataset["text"]]
        return dataset

Metadata

Release files for t2r2 0.0.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

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Source distribution for t2r2 0.0.1
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Table of built distributions (wheels) for t2r2 0.0.1
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t2r2-0.0.1-py3-none-any.whl Python 3 none any Details

Total release size: 48.9 kB

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