fei-nn: Train a neural network with MXNet in Haskell.

[ ai, bsd3, library, machine-learning ] [ Propose Tags ]

High level APIs to rain a neural network with MXNet in Haskell.

Modules

  • MXNet
    • MXNet.NN
      • MXNet.NN.Callback
      • DataIter
        • MXNet.NN.DataIter.Class
        • MXNet.NN.DataIter.Conduit
        • MXNet.NN.DataIter.ConduitAsync
        • MXNet.NN.DataIter.Streaming
        • MXNet.NN.DataIter.Vec
      • MXNet.NN.EvalMetric
      • MXNet.NN.Initializer
      • MXNet.NN.Layer
      • MXNet.NN.LrScheduler
      • MXNet.NN.Module
      • MXNet.NN.Optimizer
      • MXNet.NN.Session
      • MXNet.NN.TaggedState
      • MXNet.NN.Types
      • MXNet.NN.Utils
        • MXNet.NN.Utils.GraphViz
        • MXNet.NN.Utils.Render
        • MXNet.NN.Utils.Repa

Flags

Automatic Flags
NameDescriptionDefault
mxnet_geq_10600

MXNet >= 1.6.0

Disabled
neptune

Integrate Neptune

Disabled

Use -f <flag> to enable a flag, or -f -<flag> to disable that flag. More info

Downloads

Maintainer's Corner

Package maintainers

For package maintainers and hackage trustees

Candidates

  • No Candidates
Versions [RSS] 0.2.0, 1.0.0
Dependencies aeson (>=1.2), base (>=4.7 && <5.0), conduit (>=1.2 && <1.4), conduit-combinators (>=1.1.2 && <1.4), containers (>=0.5), fei-base, FontyFruity, formatting, graphviz, JuicyPixels, lens (>=4.12), neptune-backend (<0.2), Rasterific, repa, resourcet (>=1.1.8), rio, stm-conduit, streaming (>=0.1.4.5), template-haskell (>=2.12), time (<2.0), transformers-base (>=0.4.4), type-combinators, uuid, wl-pprint-text [details]
License BSD-3-Clause
Copyright Copyright: (c) 2020 Jiasen Wu
Author Jiasen Wu
Maintainer jiasenwu@hotmail.com
Category Machine Learning, AI
Home page http://github.com/pierric/fei-nn
Uploaded by JiasenWu at 2020-12-20T20:24:59Z
Distributions
Reverse Dependencies 3 direct, 1 indirect [details]
Downloads 616 total (0 in the last 30 days)
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Status Docs not available [build log]
All reported builds failed as of 2020-12-20 [all 3 reports]