humigencev2 / tests /test_gpu_detection.py
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chore: initial public release of Humigence (CLI wizard + dual-GPU fine-tuning)
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#!/usr/bin/env python3
"""
Test GPU detection functionality
"""
import pytest
import sys
from pathlib import Path
# Add the parent directory to the path so we can import from cli
sys.path.insert(0, str(Path(__file__).parent.parent))
from cli.main import detect_gpus, choose_training_mode
def test_gpu_detection():
"""Test GPU detection returns valid results"""
gpu_count, gpus = detect_gpus()
# Should return valid results (even if 0 GPUs)
assert isinstance(gpu_count, int)
assert isinstance(gpus, list)
assert gpu_count >= 0
assert len(gpus) == gpu_count
# If GPUs are detected, they should have required fields
for gpu in gpus:
assert "index" in gpu
assert "name" in gpu
assert "memory" in gpu
assert isinstance(gpu["index"], int)
assert isinstance(gpu["name"], str)
assert isinstance(gpu["memory"], str)
def test_training_mode_selection():
"""Test training mode selection logic"""
# Test with no GPUs
result = choose_training_mode(0, [])
assert result is None
# Test with single GPU
single_gpu = [{"index": 0, "name": "Test GPU", "memory": "8GB"}]
result = choose_training_mode(1, single_gpu)
assert result == "single"
# Test with multiple GPUs (would prompt user in real usage)
multi_gpus = [
{"index": 0, "name": "GPU 0", "memory": "8GB"},
{"index": 1, "name": "GPU 1", "memory": "8GB"}
]
# This would normally prompt the user, so we can't test the full flow
# But we can test that the function can be called
try:
result = choose_training_mode(2, multi_gpus)
# If it returns without error, that's good
assert result is not None
except Exception:
# If it prompts for user input, that's expected in test environment
pass
if __name__ == "__main__":
pytest.main([__file__])