Cluster/tests/test_final_implementation.py
2025-07-17 17:04:56 +08:00

180 lines
6.5 KiB
Python

#!/usr/bin/env python3
"""
Final test to verify the stage detection implementation works correctly.
"""
import sys
import os
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
# Set up Qt environment
os.environ['QT_QPA_PLATFORM'] = 'offscreen'
from PyQt5.QtWidgets import QApplication
app = QApplication(sys.argv)
from core.pipeline import (
is_model_node, is_input_node, is_output_node,
get_stage_count, get_pipeline_summary
)
from core.nodes.model_node import ModelNode
from core.nodes.input_node import InputNode
from core.nodes.output_node import OutputNode
from core.nodes.preprocess_node import PreprocessNode
from core.nodes.postprocess_node import PostprocessNode
class MockNodeGraph:
"""Mock node graph for testing."""
def __init__(self):
self.nodes = []
def all_nodes(self):
return self.nodes
def add_node(self, node):
self.nodes.append(node)
print(f"Added node: {node} (type: {type(node).__name__})")
def test_comprehensive_pipeline():
"""Test comprehensive pipeline functionality."""
print("Testing Comprehensive Pipeline...")
# Create mock graph
graph = MockNodeGraph()
# Test 1: Empty pipeline
print("\n1. Empty pipeline:")
stage_count = get_stage_count(graph)
print(f" Stage count: {stage_count}")
assert stage_count == 0, f"Expected 0 stages, got {stage_count}"
# Test 2: Add input node
print("\n2. Add input node:")
input_node = InputNode()
graph.add_node(input_node)
stage_count = get_stage_count(graph)
print(f" Stage count: {stage_count}")
assert stage_count == 0, f"Expected 0 stages, got {stage_count}"
# Test 3: Add model node (should create 1 stage)
print("\n3. Add model node:")
model_node = ModelNode()
graph.add_node(model_node)
stage_count = get_stage_count(graph)
print(f" Stage count: {stage_count}")
assert stage_count == 1, f"Expected 1 stage, got {stage_count}"
# Test 4: Add output node
print("\n4. Add output node:")
output_node = OutputNode()
graph.add_node(output_node)
stage_count = get_stage_count(graph)
print(f" Stage count: {stage_count}")
assert stage_count == 1, f"Expected 1 stage, got {stage_count}"
# Test 5: Add preprocess node
print("\n5. Add preprocess node:")
preprocess_node = PreprocessNode()
graph.add_node(preprocess_node)
stage_count = get_stage_count(graph)
print(f" Stage count: {stage_count}")
assert stage_count == 1, f"Expected 1 stage, got {stage_count}"
# Test 6: Add postprocess node
print("\n6. Add postprocess node:")
postprocess_node = PostprocessNode()
graph.add_node(postprocess_node)
stage_count = get_stage_count(graph)
print(f" Stage count: {stage_count}")
assert stage_count == 1, f"Expected 1 stage, got {stage_count}"
# Test 7: Add second model node (should create 2 stages)
print("\n7. Add second model node:")
model_node2 = ModelNode()
graph.add_node(model_node2)
stage_count = get_stage_count(graph)
print(f" Stage count: {stage_count}")
assert stage_count == 2, f"Expected 2 stages, got {stage_count}"
# Test 8: Add third model node (should create 3 stages)
print("\n8. Add third model node:")
model_node3 = ModelNode()
graph.add_node(model_node3)
stage_count = get_stage_count(graph)
print(f" Stage count: {stage_count}")
assert stage_count == 3, f"Expected 3 stages, got {stage_count}"
# Test 9: Get pipeline summary
print("\n9. Get pipeline summary:")
summary = get_pipeline_summary(graph)
print(f" Summary: {summary}")
expected_fields = ['stage_count', 'valid', 'total_nodes', 'model_nodes', 'input_nodes', 'output_nodes']
for field in expected_fields:
assert field in summary, f"Missing field '{field}' in summary"
assert summary['stage_count'] == 3, f"Expected 3 stages in summary, got {summary['stage_count']}"
assert summary['model_nodes'] == 3, f"Expected 3 model nodes in summary, got {summary['model_nodes']}"
assert summary['input_nodes'] == 1, f"Expected 1 input node in summary, got {summary['input_nodes']}"
assert summary['output_nodes'] == 1, f"Expected 1 output node in summary, got {summary['output_nodes']}"
assert summary['total_nodes'] == 7, f"Expected 7 total nodes in summary, got {summary['total_nodes']}"
print("✓ All comprehensive tests passed!")
def test_node_detection_robustness():
"""Test robustness of node detection."""
print("\nTesting Node Detection Robustness...")
# Test with actual node instances
model_node = ModelNode()
input_node = InputNode()
output_node = OutputNode()
preprocess_node = PreprocessNode()
postprocess_node = PostprocessNode()
# Test detection methods
assert is_model_node(model_node), "Model node not detected correctly"
assert is_input_node(input_node), "Input node not detected correctly"
assert is_output_node(output_node), "Output node not detected correctly"
# Test cross-detection (should be False)
assert not is_model_node(input_node), "Input node incorrectly detected as model"
assert not is_model_node(output_node), "Output node incorrectly detected as model"
assert not is_input_node(model_node), "Model node incorrectly detected as input"
assert not is_input_node(output_node), "Output node incorrectly detected as input"
assert not is_output_node(model_node), "Model node incorrectly detected as output"
assert not is_output_node(input_node), "Input node incorrectly detected as output"
print("✓ Node detection robustness tests passed!")
def main():
"""Run all tests."""
print("Running Final Implementation Tests...")
print("=" * 60)
try:
test_node_detection_robustness()
test_comprehensive_pipeline()
print("\n" + "=" * 60)
print("🎉 ALL TESTS PASSED! The stage detection implementation is working correctly.")
print("\nKey Features Verified:")
print("✓ Model node detection works correctly")
print("✓ Stage counting updates when model nodes are added")
print("✓ Pipeline summary provides accurate information")
print("✓ Node detection is robust and handles edge cases")
print("✓ Multiple stages are correctly counted")
except Exception as e:
print(f"\n❌ Test failed: {e}")
import traceback
traceback.print_exc()
sys.exit(1)
if __name__ == '__main__':
main()