306 lines
12 KiB
Python
306 lines
12 KiB
Python
#!/usr/bin/env python3
|
|
"""
|
|
🚀 智慧拓撲排序算法演示
|
|
|
|
這個演示展示了我們的進階pipeline拓撲分析和優化算法:
|
|
- 自動依賴關係分析
|
|
- 循環檢測和解決
|
|
- 並行執行優化
|
|
- 關鍵路徑分析
|
|
- 性能指標計算
|
|
|
|
適合進度報告展示！
|
|
"""
|
|
|
|
import json
|
|
from mflow_converter import MFlowConverter
|
|
|
|
def create_demo_pipeline() -> dict:
|
|
"""創建一個複雜的多階段pipeline用於演示"""
|
|
return {
|
|
"project_name": "Advanced Multi-Stage Fire Detection Pipeline",
|
|
"description": "Demonstrates intelligent topology sorting with parallel stages",
|
|
"nodes": [
|
|
# Input Node
|
|
{
|
|
"id": "input_001",
|
|
"name": "RGB Camera Input",
|
|
"type": "ExactInputNode",
|
|
"pos": [100, 200],
|
|
"properties": {
|
|
"source_type": "Camera",
|
|
"device_id": 0,
|
|
"resolution": "1920x1080",
|
|
"fps": 30
|
|
}
|
|
},
|
|
|
|
# Parallel Feature Extraction Stages
|
|
{
|
|
"id": "model_rgb_001",
|
|
"name": "RGB Feature Extractor",
|
|
"type": "ExactModelNode",
|
|
"pos": [300, 100],
|
|
"properties": {
|
|
"model_path": "rgb_features.nef",
|
|
"scpu_fw_path": "fw_scpu.bin",
|
|
"ncpu_fw_path": "fw_ncpu.bin",
|
|
"dongle_series": "520",
|
|
"port_id": "28,30"
|
|
}
|
|
},
|
|
|
|
{
|
|
"id": "model_edge_002",
|
|
"name": "Edge Feature Extractor",
|
|
"type": "ExactModelNode",
|
|
"pos": [300, 200],
|
|
"properties": {
|
|
"model_path": "edge_features.nef",
|
|
"scpu_fw_path": "fw_scpu.bin",
|
|
"ncpu_fw_path": "fw_ncpu.bin",
|
|
"dongle_series": "520",
|
|
"port_id": "32,34"
|
|
}
|
|
},
|
|
|
|
{
|
|
"id": "model_thermal_003",
|
|
"name": "Thermal Feature Extractor",
|
|
"type": "ExactModelNode",
|
|
"pos": [300, 300],
|
|
"properties": {
|
|
"model_path": "thermal_features.nef",
|
|
"scpu_fw_path": "fw_scpu.bin",
|
|
"ncpu_fw_path": "fw_ncpu.bin",
|
|
"dongle_series": "520",
|
|
"port_id": "36,38"
|
|
}
|
|
},
|
|
|
|
# Intermediate Processing Stages
|
|
{
|
|
"id": "model_fusion_004",
|
|
"name": "Feature Fusion",
|
|
"type": "ExactModelNode",
|
|
"pos": [500, 150],
|
|
"properties": {
|
|
"model_path": "feature_fusion.nef",
|
|
"scpu_fw_path": "fw_scpu.bin",
|
|
"ncpu_fw_path": "fw_ncpu.bin",
|
|
"dongle_series": "720",
|
|
"port_id": "40,42"
|
|
}
|
|
},
|
|
|
|
{
|
|
"id": "model_attention_005",
|
|
"name": "Attention Mechanism",
|
|
"type": "ExactModelNode",
|
|
"pos": [500, 250],
|
|
"properties": {
|
|
"model_path": "attention.nef",
|
|
"scpu_fw_path": "fw_scpu.bin",
|
|
"ncpu_fw_path": "fw_ncpu.bin",
|
|
"dongle_series": "720",
|
|
"port_id": "44,46"
|
|
}
|
|
},
|
|
|
|
# Final Classification Stage
|
|
{
|
|
"id": "model_classifier_006",
|
|
"name": "Fire Classifier",
|
|
"type": "ExactModelNode",
|
|
"pos": [700, 200],
|
|
"properties": {
|
|
"model_path": "fire_classifier.nef",
|
|
"scpu_fw_path": "fw_scpu.bin",
|
|
"ncpu_fw_path": "fw_ncpu.bin",
|
|
"dongle_series": "720",
|
|
"port_id": "48,50"
|
|
}
|
|
},
|
|
|
|
# Output Node
|
|
{
|
|
"id": "output_007",
|
|
"name": "Detection Output",
|
|
"type": "ExactOutputNode",
|
|
"pos": [900, 200],
|
|
"properties": {
|
|
"output_type": "Stream",
|
|
"format": "JSON",
|
|
"destination": "tcp://localhost:5555"
|
|
}
|
|
}
|
|
],
|
|
|
|
"connections": [
|
|
# Input to parallel feature extractors
|
|
{"output_node": "input_001", "output_port": "output", "input_node": "model_rgb_001", "input_port": "input"},
|
|
{"output_node": "input_001", "output_port": "output", "input_node": "model_edge_002", "input_port": "input"},
|
|
{"output_node": "input_001", "output_port": "output", "input_node": "model_thermal_003", "input_port": "input"},
|
|
|
|
# Feature extractors to fusion
|
|
{"output_node": "model_rgb_001", "output_port": "output", "input_node": "model_fusion_004", "input_port": "input"},
|
|
{"output_node": "model_edge_002", "output_port": "output", "input_node": "model_fusion_004", "input_port": "input"},
|
|
{"output_node": "model_thermal_003", "output_port": "output", "input_node": "model_attention_005", "input_port": "input"},
|
|
|
|
# Intermediate stages to classifier
|
|
{"output_node": "model_fusion_004", "output_port": "output", "input_node": "model_classifier_006", "input_port": "input"},
|
|
{"output_node": "model_attention_005", "output_port": "output", "input_node": "model_classifier_006", "input_port": "input"},
|
|
|
|
# Classifier to output
|
|
{"output_node": "model_classifier_006", "output_port": "output", "input_node": "output_007", "input_port": "input"}
|
|
],
|
|
|
|
"version": "1.0"
|
|
}
|
|
|
|
def demo_simple_pipeline():
|
|
"""演示簡單的線性pipeline"""
|
|
print("🎯 DEMO 1: Simple Linear Pipeline")
|
|
print("="*50)
|
|
|
|
simple_pipeline = {
|
|
"project_name": "Simple Linear Pipeline",
|
|
"nodes": [
|
|
{"id": "model_001", "name": "Detection", "type": "ExactModelNode", "properties": {"model_path": "detect.nef", "scpu_fw_path": "fw_scpu.bin", "ncpu_fw_path": "fw_ncpu.bin", "port_id": "28"}},
|
|
{"id": "model_002", "name": "Classification", "type": "ExactModelNode", "properties": {"model_path": "classify.nef", "scpu_fw_path": "fw_scpu.bin", "ncpu_fw_path": "fw_ncpu.bin", "port_id": "30"}},
|
|
{"id": "model_003", "name": "Verification", "type": "ExactModelNode", "properties": {"model_path": "verify.nef", "scpu_fw_path": "fw_scpu.bin", "ncpu_fw_path": "fw_ncpu.bin", "port_id": "32"}}
|
|
],
|
|
"connections": [
|
|
{"output_node": "model_001", "input_node": "model_002"},
|
|
{"output_node": "model_002", "input_node": "model_003"}
|
|
]
|
|
}
|
|
|
|
converter = MFlowConverter()
|
|
config = converter._convert_mflow_to_config(simple_pipeline)
|
|
print("\n")
|
|
|
|
def demo_parallel_pipeline():
|
|
"""演示並行pipeline"""
|
|
print("🎯 DEMO 2: Parallel Processing Pipeline")
|
|
print("="*50)
|
|
|
|
parallel_pipeline = {
|
|
"project_name": "Parallel Processing Pipeline",
|
|
"nodes": [
|
|
{"id": "model_001", "name": "RGB Processor", "type": "ExactModelNode", "properties": {"model_path": "rgb.nef", "scpu_fw_path": "fw_scpu.bin", "ncpu_fw_path": "fw_ncpu.bin", "port_id": "28"}},
|
|
{"id": "model_002", "name": "IR Processor", "type": "ExactModelNode", "properties": {"model_path": "ir.nef", "scpu_fw_path": "fw_scpu.bin", "ncpu_fw_path": "fw_ncpu.bin", "port_id": "30"}},
|
|
{"id": "model_003", "name": "Depth Processor", "type": "ExactModelNode", "properties": {"model_path": "depth.nef", "scpu_fw_path": "fw_scpu.bin", "ncpu_fw_path": "fw_ncpu.bin", "port_id": "32"}},
|
|
{"id": "model_004", "name": "Fusion Engine", "type": "ExactModelNode", "properties": {"model_path": "fusion.nef", "scpu_fw_path": "fw_scpu.bin", "ncpu_fw_path": "fw_ncpu.bin", "port_id": "34"}}
|
|
],
|
|
"connections": [
|
|
{"output_node": "model_001", "input_node": "model_004"},
|
|
{"output_node": "model_002", "input_node": "model_004"},
|
|
{"output_node": "model_003", "input_node": "model_004"}
|
|
]
|
|
}
|
|
|
|
converter = MFlowConverter()
|
|
config = converter._convert_mflow_to_config(parallel_pipeline)
|
|
print("\n")
|
|
|
|
def demo_complex_pipeline():
|
|
"""演示複雜的多層級pipeline"""
|
|
print("🎯 DEMO 3: Complex Multi-Level Pipeline")
|
|
print("="*50)
|
|
|
|
complex_pipeline = create_demo_pipeline()
|
|
|
|
converter = MFlowConverter()
|
|
config = converter._convert_mflow_to_config(complex_pipeline)
|
|
|
|
# 顯示額外的配置信息
|
|
print("🔧 Generated Pipeline Configuration:")
|
|
print(f" • Stage Configs: {len(config.stage_configs)}")
|
|
print(f" • Input Config: {config.input_config.get('source_type', 'Unknown')}")
|
|
print(f" • Output Config: {config.output_config.get('format', 'Unknown')}")
|
|
print("\n")
|
|
|
|
def demo_cycle_detection():
|
|
"""演示循環檢測和解決"""
|
|
print("🎯 DEMO 4: Cycle Detection & Resolution")
|
|
print("="*50)
|
|
|
|
# 創建一個有循環的pipeline
|
|
cycle_pipeline = {
|
|
"project_name": "Pipeline with Cycles (Testing)",
|
|
"nodes": [
|
|
{"id": "model_A", "name": "Model A", "type": "ExactModelNode", "properties": {"model_path": "a.nef", "scpu_fw_path": "fw_scpu.bin", "ncpu_fw_path": "fw_ncpu.bin", "port_id": "28"}},
|
|
{"id": "model_B", "name": "Model B", "type": "ExactModelNode", "properties": {"model_path": "b.nef", "scpu_fw_path": "fw_scpu.bin", "ncpu_fw_path": "fw_ncpu.bin", "port_id": "30"}},
|
|
{"id": "model_C", "name": "Model C", "type": "ExactModelNode", "properties": {"model_path": "c.nef", "scpu_fw_path": "fw_scpu.bin", "ncpu_fw_path": "fw_ncpu.bin", "port_id": "32"}}
|
|
],
|
|
"connections": [
|
|
{"output_node": "model_A", "input_node": "model_B"},
|
|
{"output_node": "model_B", "input_node": "model_C"},
|
|
{"output_node": "model_C", "input_node": "model_A"} # Creates cycle!
|
|
]
|
|
}
|
|
|
|
converter = MFlowConverter()
|
|
config = converter._convert_mflow_to_config(cycle_pipeline)
|
|
print("\n")
|
|
|
|
def demo_performance_analysis():
|
|
"""演示性能分析功能"""
|
|
print("🎯 DEMO 5: Performance Analysis")
|
|
print("="*50)
|
|
|
|
# 使用之前創建的複雜pipeline
|
|
complex_pipeline = create_demo_pipeline()
|
|
|
|
converter = MFlowConverter()
|
|
config = converter._convert_mflow_to_config(complex_pipeline)
|
|
|
|
# 驗證配置
|
|
is_valid, errors = converter.validate_config(config)
|
|
|
|
print("🔍 Configuration Validation:")
|
|
if is_valid:
|
|
print(" ✅ All configurations are valid!")
|
|
else:
|
|
print(" ⚠️ Configuration issues found:")
|
|
for error in errors[:3]: # Show first 3 errors
|
|
print(f" - {error}")
|
|
|
|
print(f"\n📦 Ready for InferencePipeline Creation:")
|
|
print(f" • Total Stages: {len(config.stage_configs)}")
|
|
print(f" • Pipeline Name: {config.pipeline_name}")
|
|
print(f" • Preprocessing Configs: {len(config.preprocessing_configs)}")
|
|
print(f" • Postprocessing Configs: {len(config.postprocessing_configs)}")
|
|
print("\n")
|
|
|
|
def main():
|
|
"""主演示函數"""
|
|
print("🚀 INTELLIGENT PIPELINE TOPOLOGY SORTING DEMONSTRATION")
|
|
print("="*60)
|
|
print("This demo showcases our advanced pipeline analysis capabilities:")
|
|
print("• Automatic dependency resolution")
|
|
print("• Parallel execution optimization")
|
|
print("• Cycle detection and prevention")
|
|
print("• Critical path analysis")
|
|
print("• Performance metrics calculation")
|
|
print("="*60 + "\n")
|
|
|
|
try:
|
|
# 運行所有演示
|
|
demo_simple_pipeline()
|
|
demo_parallel_pipeline()
|
|
demo_complex_pipeline()
|
|
demo_cycle_detection()
|
|
demo_performance_analysis()
|
|
|
|
print("🎉 ALL DEMONSTRATIONS COMPLETED SUCCESSFULLY!")
|
|
print("Ready for production deployment and progress reporting! 🚀")
|
|
|
|
except Exception as e:
|
|
print(f"❌ Demo error: {e}")
|
|
import traceback
|
|
traceback.print_exc()
|
|
|
|
if __name__ == "__main__":
|
|
main() |