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Validating Accelerator Class Implementations in DeepSpeed

This test suite validates the implementation of accelerator classes in DeepSpeed, ensuring all required abstract methods are properly defined and accelerator modules can be correctly imported. It provides comprehensive testing of accelerator class definitions and module loading mechanisms.

Test Coverage Overview

The test suite provides systematic coverage of accelerator class implementations in DeepSpeed.

Key areas tested include:

Dynamic module importing and class discovery
Validation of accelerator class naming conventions
Verification of abstract method implementations
Module dependency handling and mocking

Implementation Analysis

The testing approach uses pytest’s parametrization to dynamically test all accelerator implementations. It employs sophisticated module importing mechanisms with mock capabilities to handle missing dependencies.

Key patterns include:

Dynamic test parameterization based on filesystem discovery
Fixture-based class name resolution
Automated cleanup of mocked modules

Technical Details

Testing infrastructure includes:

pytest framework for test organization
Python’s importlib for dynamic module loading
Regular expressions for error handling
Custom fixtures for test setup and teardown
Module-level mocking capabilities

Best Practices Demonstrated

The test suite exemplifies high-quality testing practices through careful organization and robust implementation.

Notable practices include:

Systematic validation of all accelerator implementations
Clean handling of environmental dependencies
Proper test isolation and cleanup
Effective use of pytest fixtures and parameterization

microsoft/deepspeed

tests/unit/accelerator/test_accelerator.py

            
# Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0

# DeepSpeed Team

import pytest

import os
import sys
import importlib
import re

import deepspeed

DS_ACCEL_PATH = "deepspeed.accelerator"
IGNORE_FILES = ["abstract_accelerator.py", "real_accelerator.py"]


@pytest.fixture
def accel_class_name(module_name):
    class_list = []
    mocked_modules = []

    # Get the accelerator class name for a given module
    while True:
        try:
            module = importlib.import_module(module_name)
            break
        except ModuleNotFoundError as e:
            # If the environment is missing a module, mock it so we can still
            # test importing the accelerator class
            missing_module = re.search(r"\'(.*)\'", e.msg).group().strip("'")
            sys.modules[missing_module] = lambda x: None
            mocked_modules.append(missing_module)
    for name in dir(module):
        if name.endswith("_Accelerator"):
            class_list.append(name)

    assert len(class_list) == 1, f"Multiple accelerator classes found in {module_name}"

    yield class_list[0]

    # Clean up mocked modules so as to not impact other tests
    for module in mocked_modules:
        del sys.modules[module]


@pytest.mark.parametrize(
    "module_name",
    [
        DS_ACCEL_PATH + "." + f.rstrip(".py") for f in os.listdir(deepspeed.accelerator.__path__[0])
        if f.endswith("_accelerator.py") and f not in IGNORE_FILES
    ],
)
def test_abstract_methods_defined(module_name, accel_class_name):
    module = importlib.import_module(module_name)
    accel_class = getattr(module, accel_class_name)
    accel_class.__init__ = lambda self: None
    _ = accel_class()