Running IR experiments

The module experimaestro.experiments contain code factorizing boilerplate for launching experiments, which is specialized in xpmir with specific experiment helpers.

For instance, one can define a standard IR experiments that learns (with tensorboard), evaluates a model on a different metrics and upload it to HuggingFace.

With full.yaml located in the same folder as experiment.py

file: experiment
learning_rate: 1e-4

The experiment can be started with

experimaestro run-experiment --run-mode normal full.yaml

Learning experiment

Generic learning experiments can be conducted with the :py:module:`xpmir.experiments.learning` module that allows to easily use a Tensorboard service.

from experimaestro.experiments import configuration
from xpmir.experiments.learning import PaperResults, learning_experiment, LearningExperimentHelper

@configuration
class Configuration:
    #: Default learning rate
    learning_rate: float = 1e-3

@learning_experiment()
def run(
    helper: LearningExperimentHelper, cfg: Configuration
) -> PaperResults:
    ...

IR experiment

Example

from experimaestro.experiments import configuration
from xpmir.experiments.ir import PaperResults, ir_experiment, IRExperimentHelper

@configuration
class Configuration:
    #: Default learning rate
    learning_rate: float = 1e-3

@ir_experiment()
def run(
    helper: IRExperimentHelper, cfg: Configuration
) -> PaperResults:
    ...

    return PaperResults(
        models={"my-model@RR10": outputs.listeners[validation.id]["RR@10"]},
        evaluations=tests,
        tb_logs={"my-model@RR10": learner.logpath},
    )

API

class xpmir.experiments.ir.IRExperimentHelper(callable: ExperimentCallable)

Bases: LearningExperimentHelper

Helper for IR experiments

callable: ExperimentCallable

Run function

property tensorboard_service

Returns a tensorboard service

xpmir.experiments.ir.ir_experiment(*args, **kwargs)

Uses an IR experiment helper that provides

1. Tensorboard service (from Learning) 1. Upload to HuggingFace 1. Printing the evaluation results