Welcome to txeo Library Documentation¶
txeo is a lightweight and intuitive C++ wrapper for TensorFlow, designed to simplify TensorFlow C++ development while preserving high performance and flexibility. Built entirely with Modern C++, txeo allows developers to use TensorFlow with the ease of a high-level API, eliminating the complexity of its low-level C++ interface.
txeo is an open-source library hosted at Github.
Main Features¶
- π¦ Intuitive API β A clean and modern C++ interface, simplifying TensorFlow C++ usage.
- π§ High-Level Tensor Abstraction β Easily create, manipulate, and operate on tensors.
- πΎ Flexible Tensor IO β Seamless reading and writing of tensors to text files.
- π Simplified Model Loading β Load and run saved TensorFlow models with minimal setup.
- β‘ XLA Acceleration β Effortlessly enable or disable TensorFlowβs XLA optimizations.
- π Near-Native Performance β Achieves 99.35% to 99.79% of native TensorFlow speed with negligible overhead.
- π‘ Encapsulated TensorFlow API β Fully abstracts TensorFlow internals for a cleaner, more maintainable experience.
Performance Comparison¶
txeo was benchmarked against the native TensorFlow C++ API using inference from a saved multiclassification convolution model.
- Model and other info:
- 279,610 parameters
- 1 Softmax Output Layer with 10 classes
- 3 Fully-Connected ReLU Convolutional Layers with 200 nodes each
- Input: 210,000 grayscale images (28Γ28).
- CPU: AMD Ryzen 7 5700X CPU
- TensorFlow: Compiled with CPU optimization
Results Overview¶
| Compiler | txeo (ΞΌs) | TensorFlow (ΞΌs) | Difference (%) |
|---|---|---|---|
| GCC | 233,994 | 232,494 | +0.65% |
| Intel | 234,489 | 232,683 | +0.78% |
| Clang | 236,858 | 234,016 | +1.21% |
- The performance overhead is negligible, ranging from 0.65% to 1.21%.
- txeoβs abstraction layer provides ease of use with almost no cost to performance.
Roadmap¶
txeo is actively evolving! Here are some of the upcoming features:
ποΈ Training Capabilities¶
- Model Training - Enable training models using TensorFlow C++.
- Backpropagation Support - Implement automatic differentiation.
- Gradient Descent & Optimizers - Integrate optimizers like SGD and Adam.
π’ Advanced Tensor Operations¶
- Linear Algebra Functions (SVD, QR decomposition) - Matrix Computations on tensors.
π Model Saving & Loading Enhancements¶
- Checkpointing - Save model weights at different training stages.
- Frozen Graph Support - Load & optimize frozen models for inference.
π¬ Contact¶
For any inquiries or contributions:
- GitHub Discussions: Start a discussion
- Issue Reporting: Open an issue
- Email: robertodias70@outlook.com (for serious inquiries only)
License¶
txeo is licensed under the Apache License 2.0, meaning it is open-source, free to use, modify, and distribute, while requiring proper attribution.
π Third-Party Licenses¶
txeo depends on third-party libraries that have their own licenses:
- TensorFlow C++ - Licensed under Apache License 2.0
- π TensorFlow License
- π TensorFlow GitHub
- Protobuf - Licensed under BSD 3-Clause
- π Protobuf License
π Note: The precompiled binaries of TensorFlow and Protobuf provided in the releases section are unmodified versions of the official source code.