Masonmason
080eb5b887
Major Features: • Advanced topological sorting algorithm with cycle detection and resolution • Intelligent pipeline optimization with parallelization analysis • Critical path analysis and performance metrics calculation • Comprehensive .mflow file converter for seamless UI-to-API integration • Complete modular UI framework with node-based pipeline editor • Enhanced model node properties (scpu_fw_path, ncpu_fw_path) • Professional output formatting without emoji decorations Technical Improvements: • Graph theory algorithms (DFS, BFS, topological sort) • Automatic dependency resolution and conflict prevention • Multi-criteria pipeline optimization • Real-time stage count calculation and validation • Comprehensive configuration validation and error handling • Modular architecture with clean separation of concerns New Components: • MFlow converter with topology analysis (core/functions/mflow_converter.py) • Complete node system with exact property matching • Pipeline editor with visual node connections • Performance estimation and dongle management panels • Comprehensive test suite and demonstration scripts 🤖 Generated with Claude Code (https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
55 lines
1.4 KiB
Python
55 lines
1.4 KiB
Python
"""
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Cluster4NPU UI - Modular PyQt5 Application for ML Pipeline Design
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This package provides a comprehensive, modular user interface for designing,
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configuring, and deploying high-performance ML inference pipelines optimized
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for Kneron NPU dongles.
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Main Modules:
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- config: Theme and settings management
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- core: Business logic and node implementations
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- ui: User interface components and windows
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- utils: Utility functions and helpers
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- resources: Static resources and assets
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Key Features:
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- Visual node-based pipeline designer
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- Multi-stage inference workflow support
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- Hardware-aware resource allocation
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- Real-time performance estimation
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- Export to multiple deployment formats
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Usage:
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# Run the application
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from cluster4npu_ui.main import main
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main()
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# Or use individual components
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from cluster4npu_ui.core.nodes import ModelNode, InputNode
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from cluster4npu_ui.config.theme import apply_theme
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Author: Cluster4NPU Team
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Version: 1.0.0
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License: MIT
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"""
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__version__ = "1.0.0"
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__author__ = "Cluster4NPU Team"
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__email__ = "team@cluster4npu.com"
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__license__ = "MIT"
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# Package metadata
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__title__ = "Cluster4NPU UI"
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__description__ = "Modular PyQt5 Application for ML Pipeline Design"
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__url__ = "https://github.com/cluster4npu/ui"
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# Import main components for convenience
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from .main import main
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__all__ = [
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"main",
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"__version__",
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"__author__",
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"__title__",
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"__description__"
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] |