Java-eeWhat is GraphPipe?
GraphPipe is a protocol and collection of software designed to simplify machine learning model deployment and decouple it from framework-specific model implementations.
GraphPipe is a tool in the Development & Training Tools category of a tech stack.
Key Features
A minimalist machine learning transport specification based on flatbuffersSimple, efficient reference model servers for Tensorflow, Caffe2, and ONNX.Efficient client implementations in Go, Python, and Java.
GraphPipe Pros & Cons
Pros of GraphPipe
No pros listed yet.
Cons of GraphPipe
No cons listed yet.
GraphPipe Alternatives & Comparisons
What are some alternatives to GraphPipe?
TensorFlow
TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
PyTorch
PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.
scikit-learn
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
