Welcome to the Horovod TensorFlow examples section! These tutorials demonstrate how to leverage Horovod for distributed training with TensorFlow, enabling faster model development and scalability. 🧠💻

🔹 Key Examples

  1. MNIST Classification with Distributed Training
    A simple example showing how to train a CNN on MNIST using Horovod's distributed API.

    TensorFlow Workflow
    [Explore the full code](/en/tech/ai/horovod/docs/tutorials/tensorflow/overview)

  2. Image Augmentation with Horovod
    Demonstrates data parallelism for image processing tasks.

    Image Augmentation
    [View the implementation](/en/tech/ai/horovod/docs/tutorials/tensorflow/usage)

  3. Custom Training Loop Integration
    Shows how to integrate Horovod with custom TensorFlow training loops.

    Training Loop
    [Check advanced guides](/en/tech/ai/horovod/docs/tutorials/tensorflow/advanced)

📌 Tips for Success

  • Use tf.distribute.MirroredStrategy for multi-GPU setups
  • Monitor training with TensorBoard for distributed runs
  • Always validate model performance across devices

For more in-depth tutorials, visit our Horovod TensorFlow documentation to explore training best practices and optimization techniques. 📚✨