EuroPy 1.0.0

EuroPy testing framework for Machine Learning

EuroPy

EuroPy is a declarative python testing framework designed for the machine learning (ML) pipeline. Inspired by other testing frameworks (such as JUnit and NUnit) EuroPy uses test decorators to register and execute tests.

EuroPy is designed to work within an Iron Python interactive environment (i.e. Jupyter Notebook) as well as within the typical python kernel.

Philosophy

TODO: Fill this in

Usage

Creating a test function is accomplished by simply decorating any function with decorators from europy.decorators. This will register your test function with the EuroPy lifecycle. In order to execute all registered tests you simply need to execute the europy.lifecycle.reporting.execute_tests function. Any parameters passed to the execute_tests function will also be passed to all registered functions.

from europy.decorator import bias, fairness
from europy.lifecycle.reporting import execute_tests

@bias("My example bias test", "Lorem ipsum dolor sit amet, consectetur adipiscing elit.")
def foo(input):
    assert input % 2 == 0
    return input

@fairness("My example fairness test that fails")
@bias()
def foo_failure(input): 
    assert input % 2 == 1
    return input


execute_tests(100)

Example Notebook Output

Example Standard Output

Testing Report

TODO: Fill me in after this is incorporated

Model Card

EuroPy can also help with generating high level details of your model for use in the report. This is included with the @model_details() decorator which reads data from .yaml or .json file. An example can be found at tests/model_details_example.[yml|json].

Simple Model Card Example

@model_details('model_details.yml') # will load details from file and pass into train
def train(details: ModelDetails=None):
    # train
    details.description = "something computed"

@model_details() # will load existing details from the current report
def test(detail: ModelDetails=None):
    pass

Hyper-Parameters

Keeping track of hyper-parameter tuning can be accomplished in configuration .yml or .json files and loaded into your code with the decorator using_params() or globally with load_global_params(). Doing so will automatically add the parameter details to your report. Parameters are loaded from

Example Param Usage

global:
    num_epochs: 4
    batch_size: 128
    learning_rate: 0.0001
train: 
    test_split: 0.2
test:
    title: "Testing Run 01"
    batch_size: 256

@using_params('params.yml')
def train(num_epochs: int=None, batch_size: int=None, learning_rate: float=None, test_split: float=None):
    # will load global params first, then params matching func name
    pass

@using_params('params.yml')
def test(title: str="", batch_size: int=None):
    # will load batch_size from test, overriding the global definition
    pass 

Example Notebook Output

Test Decorators

EuroPy supports a number of test classes out of the box. These test classes have been created by surveying industry practitioners and creating a list of well known testing labels. When defining a testing function you may pass two optional parameters to any decorator: name and description. These parameters are used as metadata and will be included in the resulting test report. The supported labels are listed below.

• @bias()
• @data_bias()
• @fairness()
• @transparency()
• @accountability()
• @accuracy()
• @unit()
• @integration()
• @minimum_functionality()

Custom Test Decorators

While we believe these decorators should be comprehensive we have provided two ways in which you can add your own custom label to the test reports. For the examples below we will be adding a custom "end-to-end" testing label to our testing function.

• Using the generic @test() decorator you can provide a custom string label

  from europy.decorator import test
  from europy.lifecycle.reporting import execute_tests
  
  EXAMPLE_LABEL_NAME = "end-to-end"
  
  @test(EXAMPLE_LABEL_NAME, "My custom label test")
  def foo(input):
      assert input % 2 == 0
      return input
  
  execute_tests(100)
  

• Defining your own test decorator using the decorator_factory

  from europy.decorator import decorator_factory
  from europy.lifecycle.reporting import execute_tests
  
  def end_to_end(name: str = ""):
      # here you can add multiple labels if you wish
      labels = ["end-to-end"]
      return decorator_factory(labels, name)
  
  
  @end_to_end("Test with custom decorator")
  def foo(input):
      assert input % 2 == 0
      return input
  
  execute_tests(100)