# `TestTaskEnd`

### *class* capymoa.ocl.evaluation.events.TestTaskEnd[[source]](https://github.com/adaptive-machine-learning/CapyMOA/blob/3e255b1/src/capymoa/ocl/evaluation/events.py#L92)

Bases: [`TestTaskBegin`](capymoa.ocl.evaluation.events.TestTaskBegin.md#capymoa.ocl.evaluation.events.TestTaskBegin)

On evaluation end for a task.

#### \_\_init_\_(train_task: [int](https://docs.python.org/3/builtins/functions.html#int), test_task: [int](https://docs.python.org/3/builtins/functions.html#int), continual_eval: [int](https://docs.python.org/3/builtins/functions.html#int), global_step: [int](https://docs.python.org/3/builtins/functions.html#int)) → [None](https://docs.python.org/3/builtins/constants.html#None)

#### continual_eval *: [int](https://docs.python.org/3/builtins/functions.html#int)*

If multiple evaluations are performed during each training task, this counts
which evaluation pass is being performed. Otherwise will be 0.

#### global_step *: [int](https://docs.python.org/3/builtins/functions.html#int)*

A monotonically increasing integer that counts training and evaluation steps.

#### test_task *: [int](https://docs.python.org/3/builtins/functions.html#int)*

The ID of the test task that has begun.

#### train_task *: [int](https://docs.python.org/3/builtins/functions.html#int)*

The ID of the training task that is being evaluated.