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A flexible deep learning framework supporting CUDA computation, multiple GPUs, and various network architectures including feed-forward nets, convnets, recurrent nets, recursive...
A flexible deep learning framework supporting CUDA computation, multiple GPUs, and various network architectures including feed-forward nets, convnets, recurrent nets, recursive nets, and per-batch architectures. Uses define-by-run approach for intuitive code and easy debugging.
Platforms, integrations, and language support vary by plan and region. Confirm final requirements with the vendor.
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Compliance claims are normalized from current vendor documentation and independently reviewed by SOTA2.