MXNet - Clojure API

MXNet supports the Clojure programming language. The MXNet Clojure package brings flexible and efficient GPU computing and state-of-art deep learning to Clojure. It enables you to write seamless tensor/matrix computation with multiple GPUs in Clojure. It also lets you construct and customize the state-of-art deep learning models in Clojure, and apply them to tasks, such as image classification and data science challenges.

See the MXNet Clojure API Documentation for detailed API information.

.. toctree::
   :maxdepth: 1

   kvstore.md
   module.md
   ndarray.md
   symbol_in_pictures.md
   symbol.md

Tensor and Matrix Computations

You can perform tensor or matrix computation in pure Clojure:

(def arr (ndarray/ones [2 3]))

arr ;=> #object[org.apache.mxnet.NDArray 0x597d72e "org.apache.mxnet.NDArray@e35c3ba9"]

(ndarray/shape-vec arr) ;=>  [2 3]

(-> (ndarray/* arr 2)
    (ndarray/->vec)) ;=> [2.0 2.0 2.0 2.0 2.0 2.0]

(ndarray/shape-vec (ndarray/* arr 2)) ;=> [2 3]

Clojure API Tutorials

• Module API is a flexible high-level interface for training neural networks.
• Symbolic API performs operations on NDArrays to assemble neural networks from layers.
• NDArray API performs vector/matrix/tensor operations.
• KVStore API performs multi-GPU and multi-host distributed training.

Related Resources

• MXNet Clojure API Documentation