feat: Add complete requirements and installation scripts
- requirements.txt: Added all dependencies including PyTorch, torch-geometric, tensorboard for neural network training - install.bat: One-click installation script that installs all dependencies with proper version constraints - train_neural.bat: Training script that runs parametric neural network training on collected FEA data Usage: 1. Double-click install.bat to install dependencies 2. Double-click train_neural.bat to train on bracket study 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
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install.bat
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install.bat
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@echo off
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REM ============================================================================
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REM Atomizer Installation Script
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REM ============================================================================
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REM This script installs all dependencies for Atomizer including neural networks
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REM
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REM Prerequisites:
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REM - Python 3.10+ installed
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REM - pip available in PATH
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REM
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REM For GPU support, run this BEFORE the script:
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REM pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121
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REM ============================================================================
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echo.
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echo ============================================================================
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echo ATOMIZER INSTALLATION
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echo ============================================================================
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echo.
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REM Check Python
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python --version >nul 2>&1
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if errorlevel 1 (
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echo ERROR: Python not found in PATH
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echo Please install Python 3.10+ and add it to PATH
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pause
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exit /b 1
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)
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echo Found Python:
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python --version
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echo.
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REM Upgrade pip
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echo Upgrading pip...
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python -m pip install --upgrade pip
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echo.
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REM Install core dependencies
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echo Installing core dependencies...
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python -m pip install numpy">=1.24.0,<2.0.0" scipy pandas scikit-learn
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echo.
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REM Install optimization framework
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echo Installing optimization framework...
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python -m pip install optuna plotly matplotlib
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echo.
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REM Install FEA tools
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echo Installing FEA/Nastran tools...
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python -m pip install "pyNastran>=1.4.0,<1.5.0" h5py
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echo.
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REM Install web framework
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echo Installing web framework...
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python -m pip install fastapi uvicorn websockets pydantic python-multipart jinja2
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echo.
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REM Install utilities
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echo Installing utilities...
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python -m pip install psutil tqdm
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echo.
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REM Install PyTorch (CPU version by default)
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echo.
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echo ============================================================================
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echo Installing PyTorch...
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echo ============================================================================
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echo.
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echo NOTE: Installing CPU version. For GPU support, run:
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echo pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121
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echo.
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python -m pip install torch
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echo.
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REM Install PyTorch Geometric
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echo Installing PyTorch Geometric (Graph Neural Networks)...
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python -m pip install torch-geometric
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echo.
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REM Install TensorBoard
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echo Installing TensorBoard...
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python -m pip install tensorboard
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echo.
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REM Verify installation
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echo.
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echo ============================================================================
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echo Verifying installation...
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echo ============================================================================
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echo.
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python -c "import numpy; import optuna; import torch; import torch_geometric; print('All core imports OK!')"
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if errorlevel 1 (
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echo.
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echo WARNING: Some packages may not have installed correctly
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echo Please check the error messages above
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) else (
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echo.
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echo ============================================================================
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echo INSTALLATION COMPLETE!
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echo ============================================================================
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echo.
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echo Atomizer is ready to use.
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echo.
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echo To train a neural network:
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echo train_neural.bat
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echo.
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echo To run an optimization study:
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echo cd studies\your_study
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echo python run_optimization.py --run --trials 100
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echo.
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)
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pause
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@@ -1,13 +1,52 @@
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# Core Dependencies
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optuna>=3.5.0
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pandas>=2.0.0
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numpy>=1.24.0
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scipy>=1.10.0
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scikit-learn>=1.3.0
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pyNastran>=1.4.0
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plotly>=5.18.0
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# Atomizer - Complete Requirements
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# =================================
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# LLM-native FEA optimization framework with Neural Network acceleration
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#
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# Installation:
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# pip install -r requirements.txt
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#
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# For GPU support (recommended for neural training):
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# pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121
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# pip install torch-geometric
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#
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# Note: numpy<2.0 required for pyNastran compatibility
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# Web Framework
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# ============================================================================
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# Core Scientific Computing
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# ============================================================================
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numpy>=1.24.0,<2.0.0
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scipy>=1.10.0
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pandas>=2.0.0
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scikit-learn>=1.3.0
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# ============================================================================
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# Optimization Framework
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# ============================================================================
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optuna>=3.5.0
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plotly>=5.18.0
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matplotlib>=3.5.0
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# ============================================================================
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# FEA/Nastran Integration
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# ============================================================================
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pyNastran>=1.4.0,<1.5.0
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h5py>=3.0.0
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# ============================================================================
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# Neural Network / AtomizerField
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# ============================================================================
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# PyTorch - Deep learning framework
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torch>=2.0.0
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# PyTorch Geometric - Graph neural networks
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torch-geometric>=2.3.0
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# TensorBoard - Training visualization
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tensorboard>=2.13.0
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# ============================================================================
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# Web Framework (Dashboard/API)
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# ============================================================================
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fastapi>=0.109.0
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uvicorn>=0.27.0
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websockets>=12.0
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@@ -15,7 +54,15 @@ pydantic>=2.5.0
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python-multipart>=0.0.6
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jinja2>=3.1.3
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# ============================================================================
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# System Utilities
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# ============================================================================
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psutil>=5.9.0
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tqdm>=4.65.0
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# ============================================================================
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# Development Tools (optional)
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# ============================================================================
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pytest>=7.4.0
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pytest-cov>=4.1.0
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black>=23.12.0
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115
train_neural.bat
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115
train_neural.bat
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@echo off
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REM ============================================================================
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REM Atomizer Neural Network Training Script
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REM ============================================================================
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REM Trains a parametric neural network on collected FEA data
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REM
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REM Usage:
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REM train_neural.bat (uses default: bracket study)
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REM train_neural.bat study_name (specify study name)
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REM train_neural.bat study_name 200 (specify epochs)
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REM ============================================================================
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echo.
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echo ============================================================================
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echo ATOMIZER NEURAL NETWORK TRAINING
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echo ============================================================================
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echo.
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REM Set defaults
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set STUDY_NAME=bracket_stiffness_optimization_atomizerfield
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set EPOCHS=100
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REM Parse arguments
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if not "%~1"=="" set STUDY_NAME=%~1
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if not "%~2"=="" set EPOCHS=%~2
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set TRAIN_DIR=atomizer_field_training_data\%STUDY_NAME%
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set OUTPUT_DIR=atomizer-field\runs\%STUDY_NAME%
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echo Study: %STUDY_NAME%
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echo Epochs: %EPOCHS%
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echo Train Dir: %TRAIN_DIR%
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echo Output: %OUTPUT_DIR%
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echo.
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REM Check training data exists
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if not exist "%TRAIN_DIR%" (
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echo ERROR: Training data not found at %TRAIN_DIR%
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echo.
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echo Available training data directories:
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dir atomizer_field_training_data /b 2>nul
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echo.
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pause
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exit /b 1
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)
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REM Count trials
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echo Counting training trials...
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set /a count=0
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for /d %%d in ("%TRAIN_DIR%\trial_*") do set /a count+=1
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echo Found %count% trials
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echo.
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if %count% LSS 20 (
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echo WARNING: Less than 20 trials. Training may not converge well.
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echo Consider running more FEA simulations first.
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echo.
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)
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REM Check PyTorch
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python -c "import torch; print(f'PyTorch {torch.__version__}')" 2>nul
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if errorlevel 1 (
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echo ERROR: PyTorch not installed
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echo Run install.bat first
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pause
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exit /b 1
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)
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REM Check for GPU
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echo.
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echo Checking for GPU...
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python -c "import torch; print(f'CUDA available: {torch.cuda.is_available()}'); print(f'Device: {torch.cuda.get_device_name(0) if torch.cuda.is_available() else \"CPU\"}')"
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echo.
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REM Start training
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echo ============================================================================
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echo Starting training...
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echo ============================================================================
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echo.
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echo Press Ctrl+C to stop training early (checkpoint will be saved)
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echo.
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cd atomizer-field
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python train_parametric.py ^
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--train_dir "..\%TRAIN_DIR%" ^
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--epochs %EPOCHS% ^
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--output_dir "runs\%STUDY_NAME%" ^
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--batch_size 16 ^
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--learning_rate 0.001 ^
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--hidden_channels 128 ^
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--num_layers 4
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if errorlevel 1 (
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echo.
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echo Training failed! Check error messages above.
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cd ..
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pause
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exit /b 1
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)
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cd ..
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echo.
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echo ============================================================================
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echo TRAINING COMPLETE!
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echo ============================================================================
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echo.
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echo Model saved to: %OUTPUT_DIR%\checkpoint_best.pt
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echo.
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echo To use the trained model in optimization:
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echo cd studies\%STUDY_NAME%
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echo python run_optimization.py --run --trials 100 --enable-nn --resume
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echo.
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pause
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