Neuropod
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About
Neuropod is a library designed to provide a unified interface for executing deep learning models from various frameworks, including TensorFlow, PyTorch, TorchScript, and Keras, in both C++ and Python environments. It simplifies the model productionization process for researchers by allowing them to build their models in a framework of their choice without being confined to its respective API for inference. Neuropod's features include the ability to run models from different frameworks using a single API, focusing on problem-solving rather than framework constraints, and enabling the construction of framework-agnostic tools and pipelines. With capabilities like out-of-process execution, zero-copy operations, and support for multiple model versions, Neuropod significantly enhances the ease of experimentation and deployment in deep learning.
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Task
Features
• efficient zero-copy operations
• supports tensorflow, pytorch, torchscript, and keras
• build generic tools and pipelines
• out-of-process execution
• model isolation for different framework versions
• define a problem api
• framework agnostic inference code
• unified interface for multiple frameworks
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