NeuropodWhat is Neuropod?
It is a library that provides a uniform interface to run deep learning models from multiple frameworks in C++ and Python. It makes it easy for researchers to build models in a framework of their choosing while also simplifying productionization of these models.
Neuropod is a tool in the Development & Training Tools category of a tech stack.
Key Features
Run models from any supported framework using one APIBuild generic tools and pipelinesFully self-contained modelsEfficient zero-copy operations
Neuropod Pros & Cons
Pros of Neuropod
No pros listed yet.
Cons of Neuropod
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Neuropod Alternatives & Comparisons
What are some alternatives to Neuropod?
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.
