File size: 7,749 Bytes
f206b57 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 | # TorchForge - Windows Installation & Usage Guide
Complete guide for setting up and running TorchForge on Windows Dell Laptop.
## Prerequisites
### System Requirements
- Windows 10/11 (64-bit)
- Python 3.8 or higher
- 8GB RAM minimum (16GB recommended)
- 10GB free disk space
- Git for Windows
### Optional for GPU Support
- NVIDIA GPU with CUDA 11.8 or higher
- NVIDIA CUDA Toolkit
- cuDNN library
## Installation Steps
### 1. Install Python
Download and install Python from [python.org](https://www.python.org/downloads/)
```powershell
# Verify installation
python --version
pip --version
```
### 2. Install Git
Download and install Git from [git-scm.com](https://git-scm.com/download/win)
```powershell
# Verify installation
git --version
```
### 3. Clone TorchForge Repository
```powershell
# Open PowerShell or Command Prompt
cd C:\Users\YourUsername\Projects
# Clone repository
git clone https://github.com/anilprasad/torchforge.git
cd torchforge
```
### 4. Create Virtual Environment
```powershell
# Create virtual environment
python -m venv venv
# Activate virtual environment
.\venv\Scripts\activate
# You should see (venv) in your prompt
```
### 5. Install TorchForge
```powershell
# Install in development mode
pip install -e .
# Or install specific extras
pip install -e ".[all]"
# Verify installation
python -c "import torchforge; print(torchforge.__version__)"
```
## Running Examples
### Basic Example
```powershell
# Navigate to examples directory
cd examples
# Run comprehensive examples
python comprehensive_examples.py
```
Expected output:
```
==========================================================
TorchForge - Comprehensive Examples
Author: Anil Prasad
==========================================================
Example 1: Basic Classification
...
✓ Example 1 completed successfully!
```
### Custom Model Example
Create a file `my_model.py`:
```python
import torch
import torch.nn as nn
from torchforge import ForgeModel, ForgeConfig
# Define your PyTorch model
class MyModel(nn.Module):
def __init__(self):
super().__init__()
self.fc1 = nn.Linear(10, 64)
self.fc2 = nn.Linear(64, 2)
self.relu = nn.ReLU()
def forward(self, x):
x = self.relu(self.fc1(x))
return self.fc2(x)
# Create TorchForge configuration
config = ForgeConfig(
model_name="my_custom_model",
version="1.0.0",
enable_monitoring=True,
enable_governance=True
)
# Wrap with TorchForge
model = ForgeModel(MyModel(), config=config)
# Use the model
x = torch.randn(32, 10)
output = model(x)
print(f"Output shape: {output.shape}")
# Get metrics
metrics = model.get_metrics_summary()
print(f"Metrics: {metrics}")
```
Run it:
```powershell
python my_model.py
```
## Running Tests
```powershell
# Install test dependencies
pip install pytest pytest-cov
# Run all tests
pytest tests/ -v
# Run with coverage
pytest tests/ --cov=torchforge --cov-report=html
# View coverage report
start htmlcov\index.html
```
## Docker Deployment on Windows
### 1. Install Docker Desktop
Download from [docker.com](https://www.docker.com/products/docker-desktop)
### 2. Build Docker Image
```powershell
# Build image
docker build -t torchforge:1.0.0 .
# Verify image
docker images | findstr torchforge
```
### 3. Run Container
```powershell
# Run container
docker run -p 8000:8000 torchforge:1.0.0
# Run with volume mounts
docker run -p 8000:8000 `
-v ${PWD}\models:/app/models `
-v ${PWD}\logs:/app/logs `
torchforge:1.0.0
```
### 4. Run with Docker Compose
```powershell
# Start services
docker-compose up -d
# Check status
docker-compose ps
# View logs
docker-compose logs -f
# Stop services
docker-compose down
```
## Cloud Deployment
### AWS Deployment
```python
from torchforge import ForgeModel, ForgeConfig
from torchforge.cloud import AWSDeployer
# Create model
config = ForgeConfig(model_name="my_model", version="1.0.0")
model = ForgeModel(MyModel(), config=config)
# Deploy to AWS SageMaker
deployer = AWSDeployer(model)
endpoint = deployer.deploy_sagemaker(
instance_type="ml.m5.large",
endpoint_name="torchforge-prod"
)
print(f"Model deployed: {endpoint.url}")
```
### Azure Deployment
```python
from torchforge.cloud import AzureDeployer
deployer = AzureDeployer(model)
service = deployer.deploy_aks(
cluster_name="ml-cluster",
cpu_cores=4,
memory_gb=16
)
```
### GCP Deployment
```python
from torchforge.cloud import GCPDeployer
deployer = GCPDeployer(model)
endpoint = deployer.deploy_vertex(
machine_type="n1-standard-4",
accelerator_type="NVIDIA_TESLA_T4"
)
```
## Common Issues & Solutions
### Issue: ModuleNotFoundError
**Solution:**
```powershell
# Ensure virtual environment is activated
.\venv\Scripts\activate
# Reinstall TorchForge
pip install -e .
```
### Issue: CUDA Not Available
**Solution:**
```powershell
# Install PyTorch with CUDA support
pip install torch torchvision --index-url https://download.pytorch.org/whl/cu118
```
### Issue: Permission Denied
**Solution:**
```powershell
# Run PowerShell as Administrator
# Or add current user to docker-users group
net localgroup docker-users "%USERDOMAIN%\%USERNAME%" /ADD
```
### Issue: Port Already in Use
**Solution:**
```powershell
# Find process using port 8000
netstat -ano | findstr :8000
# Kill process (replace PID)
taskkill /PID <PID> /F
```
## Performance Optimization
### Enable GPU Support
```python
import torch
# Check CUDA availability
if torch.cuda.is_available():
device = torch.device("cuda")
model = model.to(device)
print(f"Using GPU: {torch.cuda.get_device_name(0)}")
else:
print("CUDA not available, using CPU")
```
### Memory Optimization
```python
# Enable memory optimization
config.optimization.memory_optimization = True
# Enable quantization
config.optimization.quantization = "int8"
```
## Development Workflow
### 1. Setup Development Environment
```powershell
# Install dev dependencies
pip install -e ".[dev]"
# Install pre-commit hooks
pre-commit install
```
### 2. Run Code Formatters
```powershell
# Format code with black
black torchforge/
# Sort imports
isort torchforge/
# Check style
flake8 torchforge/
```
### 3. Type Checking
```powershell
# Run mypy
mypy torchforge/
```
## Monitoring in Production
### View Metrics
```python
# Get metrics summary
metrics = model.get_metrics_summary()
print(f"Total Inferences: {metrics['inference_count']}")
print(f"Mean Latency: {metrics['latency_mean_ms']:.2f}ms")
print(f"P95 Latency: {metrics['latency_p95_ms']:.2f}ms")
```
### Export Compliance Report
```python
from torchforge.governance import ComplianceChecker
checker = ComplianceChecker()
report = checker.assess_model(model)
# Export reports
report.export_json("compliance_report.json")
report.export_pdf("compliance_report.pdf")
```
## Support & Resources
- **GitHub Issues**: https://github.com/anilprasad/torchforge/issues
- **Documentation**: https://torchforge.readthedocs.io
- **LinkedIn**: [Anil Prasad](https://www.linkedin.com/in/anilsprasad/)
- **Email**: anilprasad@example.com
## Next Steps
1. Try the comprehensive examples
2. Build your own model with TorchForge
3. Deploy to production
4. Check compliance and governance
5. Monitor in real-time
6. Contribute to the project!
---
**Built with ❤️ by Anil Prasad**
|