Hype
Hype is a proof-of-concept deep learning library, where you can perform optimization on compositional machine learning systems of many components, even when such components themselves internally perform optimization. This is enabled by nested automatic differentiation (AD) giving you access to the automatic exact derivative of any floating-point value in your code with respect to any other. Underlying computations are run by a BLAS/LAPACK backend (OpenBLAS by default).
Activity
- Latest release
- 10y ago
- Total releases
- 4
- Cadence
- ~10 days
- Last 12 months
- 0
Details
- First release
- Nov 16, 2015
| Version | Released | |
|---|---|---|
0.1.3
patch
|
0.1.3
patch
Dependencies (1)
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0.1.2
patch
|
0.1.2
patch
Dependencies (1)
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0.1.1
patch
|
0.1.1
patch
Dependencies (1)
|
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0.1.0
initial
|
0.1.0
initial
Dependencies (1)
|