# Requirements for Local PyTorch Training

## Python Version
- Python >= 3.8

## Core Dependencies

### PyTorch (chọn một trong các tùy chọn dưới)

#### Option 1: CPU Only
```bash
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu
```

#### Option 2: GPU (CUDA 11.8)
```bash
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
```

#### Option 3: GPU (CUDA 12.1)
```bash
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121
```

#### Option 4: Apple Silicon (M1/M2/M3)
```bash
pip install torch torchvision torchaudio
```

### Data Processing
```bash
pip install numpy>=1.21.0
pip install xarray>=0.20.0
pip install netcdf4>=1.5.0
pip install geopandas>=0.10.0
pip install shapely>=1.7.0
pip install fiona>=1.8.0
```

### Machine Learning
```bash
pip install scikit-learn>=1.0.0
```

### Visualization
```bash
pip install matplotlib>=3.4.0
```

### GIS (optional, for GeoTIFF export)
```bash
pip install rasterio>=1.2.0
pip install rasterio[s3]  # Nếu cần S3 access
```

### Utils
```bash
pip install joblib>=1.0.0
```

---

## Installation Instructions

### 1. Create Virtual Environment
```bash
# Using venv
python -m venv pytorch_env
source pytorch_env/bin/activate  # On Windows: pytorch_env\Scripts\activate

# Or using conda
conda create -n pytorch_env python=3.10
conda activate pytorch_env
```

### 2. Install PyTorch (choose ONE)

**For GPU (recommended)**:
```bash
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
```

**For CPU only** (if no GPU):
```bash
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu
```

### 3. Install Other Dependencies
```bash
pip install numpy xarray netcdf4 geopandas shapely fiona
pip install scikit-learn matplotlib
pip install rasterio
pip install joblib
```

### 4. Verify Installation
```bash
python -c "import torch; print(f'PyTorch version: {torch.__version__}'); print(f'GPU available: {torch.cuda.is_available()}')"
```

---

## Complete Installation Script

### Linux/Mac:
```bash
#!/bin/bash

# Create virtual environment
python -m venv pytorch_env
source pytorch_env/bin/activate

# Upgrade pip
pip install --upgrade pip

# Install PyTorch (GPU)
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118

# Install dependencies
pip install numpy xarray netcdf4 geopandas shapely fiona scikit-learn matplotlib rasterio joblib

echo "✅ Installation complete!"
```

### Windows:
```bash
# Create virtual environment
python -m venv pytorch_env
pytorch_env\Scripts\activate

# Upgrade pip
python -m pip install --upgrade pip

# Install PyTorch (GPU)
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118

# Install dependencies
pip install numpy xarray netcdf4 geopandas shapely fiona scikit-learn matplotlib rasterio joblib

echo Installation complete!
```

---

## Quick Test

```python
import torch
import numpy as np
import xarray as xr
import geopandas as gpd

print(f"✅ PyTorch: {torch.__version__}")
print(f"✅ GPU available: {torch.cuda.is_available()}")
print(f"✅ NumPy: {np.__version__}")
print(f"✅ xarray: {xr.__version__}")
print(f"✅ GeoPandas: {gpd.__version__}")

# GPU test
if torch.cuda.is_available():
    x = torch.randn(3, 4).cuda()
    print(f"✅ GPU test passed! ({torch.cuda.get_device_name(0)})")
```

---

## System Requirements

### Minimum:
- RAM: 8GB
- Disk: 5GB (for data + model)
- Processor: Any modern CPU

### Recommended:
- RAM: 16GB
- Disk: 10GB
- GPU: NVIDIA (CUDA) or AMD (ROCm)

### GPU Support:
- **NVIDIA**: CUDA 11.8+ with cuDNN 8.0+
- **AMD**: ROCm 5.0+
- **Apple**: Metal Performance Shaders (automatic)

---

## Troubleshooting

### Issue 1: GPU not recognized
```
GPU available: False
```
**Solution**:
- Check NVIDIA drivers: `nvidia-smi`
- Reinstall PyTorch with correct CUDA version
- Verify CUDA compatibility

### Issue 2: Import errors
```
ModuleNotFoundError: No module named 'torch'
```
**Solution**:
- Check virtual environment is activated
- Reinstall: `pip install torch --force-reinstall`

### Issue 3: Out of memory
**Solution**:
- Use CPU instead: `device = torch.device('cpu')`
- Reduce batch_size in notebooks
- Reduce model complexity

---

## Next Steps

1. ✅ Install dependencies using one of the methods above
2. ✅ Run verification script
3. ✅ Download data from server
4. ✅ Run `02.train_CNN_PyTorch_local.ipynb`
5. ✅ Run `03.predict_CNN_PyTorch_local.ipynb`

Happy training! 🚀