Merge pull request #3113 from Luka12-dev/skip-packaging-option

High-performance deep learning framework built on PyTorch with CUDA

Author: geekcomputers

ML/.gitignore

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+__pycache__/
+*.py[cod]
+*$py.class
+*.so
+*.o
+*.obj
+*.exe
+*.out
+*.app
+build/
+dist/
+*.egg-info/
+.eggs/
+*.pt
+*.pth
+models/*.pt
+logs/*.log
+logs/*.json
+data/cache/
+.vscode/
+.idea/
+*.swp
+*.swo
+*~
+.DS_Store
+*.cuda
+*.ptx
+cmake-build-*/
+CMakeFiles/
+CMakeCache.txt

ML/CLI_USAGE_SUMMARY.md

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+# NeuralForge CLI - Quick Reference
+
+## Installation
+
+```bash
+# Install the package
+pip install -e .
+
+# Verify installation
+NeuralForgeAI --help
+```
+
+## Available Commands
+
+| Command | Description | Example |
+|---------|-------------|---------|
+| `NeuralForgeAI` | Train neural networks | `NeuralForgeAI --dataset cifar10 --model resnet18 --epochs 50` |
+| `neuralforge` | Same as NeuralForgeAI | `neuralforge --dataset stl10 --model resnet18` |
+| `neuralforge-train` | Explicit training | `neuralforge-train --dataset mnist --epochs 20` |
+| `neuralforge-test` | Test models | `neuralforge-test --help` |
+| `neuralforge-gui` | Launch GUI | `neuralforge-gui` |
+| `neuralforge-nas` | Architecture search | `neuralforge-nas --help` |
+
+## Quick Examples
+
+### Basic Training
+```bash
+# CIFAR-10 with ResNet18
+NeuralForgeAI --dataset cifar10 --model resnet18 --epochs 50 --batch-size 64
+
+# STL-10 with custom settings
+NeuralForgeAI --dataset stl10 --model resnet18 --epochs 100 --lr 0.001 --batch-size 64
+
+# MNIST quick test
+NeuralForgeAI --dataset mnist --model simple --epochs 10
+```
+
+### Advanced Usage
+```bash
+# Full customization
+NeuralForgeAI --dataset cifar100 --model resnet18 --epochs 100 \
+              --batch-size 128 --lr 0.001 --optimizer adamw \
+              --scheduler cosine --device cuda --seed 42
+
+# Using config file
+NeuralForgeAI --config my_config.json
+
+# Synthetic data for testing
+NeuralForgeAI --dataset synthetic --num-samples 1000 --epochs 5
+```
+
+## Common Arguments
+
+| Argument | Type | Default | Description |
+|----------|------|---------|-------------|
+| `--dataset` | str | synthetic | Dataset name (cifar10, mnist, stl10, etc.) |
+| `--model` | str | simple | Model architecture (simple, resnet18, efficientnet, vit) |
+| `--epochs` | int | 50 | Number of training epochs |
+| `--batch-size` | int | 32 | Batch size for training |
+| `--lr` | float | 0.001 | Learning rate |
+| `--optimizer` | str | adamw | Optimizer (adamw, adam, sgd) |
+| `--scheduler` | str | cosine | LR scheduler (cosine, onecycle, none) |
+| `--device` | str | auto | Device (cuda, cpu) |
+| `--seed` | int | 42 | Random seed |
+
+## Supported Datasets
+
+- `cifar10` - CIFAR-10 (60K images, 10 classes, 32x32)
+- `cifar100` - CIFAR-100 (60K images, 100 classes, 32x32)
+- `mnist` - MNIST (70K images, 10 classes, 28x28)
+- `fashion_mnist` - Fashion-MNIST (70K images, 10 classes, 28x28)
+- `stl10` - STL-10 (13K images, 10 classes, 96x96)
+- `tiny_imagenet` - Tiny ImageNet (200 classes, 64x64)
+- `synthetic` - Synthetic data for testing
+
+## Comparison: CLI vs Python Script
+
+### Using CLI (After pip install)
+```bash
+# Use from anywhere
+NeuralForgeAI --dataset stl10 --model resnet18 --epochs 50 --batch-size 64
+```
+
+**Pros:**
+- ✅ Use from any directory
+- ✅ Clean, simple syntax
+- ✅ No need to write Python code
+- ✅ Easy to integrate in scripts/workflows
+
+### Using Python Script (Traditional)
+```bash
+# Must be in NeuralForge directory
+python train.py --dataset stl10 --model resnet18 --epochs 50 --batch-size 64
+```
+
+**Pros:**
+- ✅ Works without installation
+- ✅ Easy to modify for custom needs
+
+## Getting Help
+
+```bash
+# Show all available options
+NeuralForgeAI --help
+
+# Get help for specific commands
+neuralforge-train --help
+neuralforge-test --help
+neuralforge-nas --help
+```
+
+## Documentation
+
+- **[README.md](README.md)** - Overview and features
+- **[INSTALL_CLI.md](INSTALL_CLI.md)** - Detailed installation guide
+- **[QUICKSTART.md](QUICKSTART.md)** - Quick start guide with examples
+- **[DOCUMENTATION.md](DOCUMENTATION.md)** - Complete API reference
+- **[DATASETS.md](DATASETS.md)** - Dataset information
+
+## Troubleshooting
+
+### Command not found
+If `NeuralForgeAI` is not recognized:
+1. Make sure you installed the package: `pip install -e .`
+2. Check pip's scripts are in PATH
+3. Use full Python path: `python -m neuralforge.cli.train`
+
+### Import errors
+Install required dependencies:
+```bash
+pip install torch torchvision numpy matplotlib tqdm pillow scipy tensorboard
+```
+
+### CUDA issues
+For CPU-only installation:
+```bash
+pip install --no-build-isolation -e .
+```

ML/CMakeLists.txt

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+cmake_minimum_required(VERSION 3.18)
+project(NeuralForge LANGUAGES CXX CUDA)
+
+set(CMAKE_CXX_STANDARD 17)
+set(CMAKE_CUDA_STANDARD 17)
+set(CMAKE_EXPORT_COMPILE_COMMANDS ON)
+
+find_package(CUDA REQUIRED)
+find_package(Python3 COMPONENTS Interpreter Development REQUIRED)
+
+set(CMAKE_CUDA_ARCHITECTURES 70 75 80)
+
+include_directories(
+    ${CUDA_INCLUDE_DIRS}
+    ${Python3_INCLUDE_DIRS}
+    src/cpp/include
+)
+
+set(CUDA_NVCC_FLAGS ${CUDA_NVCC_FLAGS};-O3;--use_fast_math)
+set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -O3 -march=native")
+
+add_library(neuralforge_core SHARED
+    src/cpp/extension.cpp
+    src/cpp/operators.cpp
+    src/cuda/kernels.cu
+    src/cuda/matmul.cu
+    src/cuda/activations.cu
+    src/cuda/optimizers.cu
+)
+
+set_target_properties(neuralforge_core PROPERTIES
+    CUDA_SEPARABLE_COMPILATION ON
+    POSITION_INDEPENDENT_CODE ON
+)
+
+target_link_libraries(neuralforge_core
+    ${CUDA_LIBRARIES}
+    ${Python3_LIBRARIES}
+)