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Difference between revisions of "SW:Magenta"

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(Created page with "== Magenta == "[https://magenta.tensorflow.org/ Magenta] is distributed as an open source Python library, powered by TensorFlow. This library includes utilities for manipulati...")
 
(Magenta on HPRC Clusters)
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"[https://magenta.tensorflow.org/ Magenta] is distributed as an open source Python library, powered by TensorFlow. This library includes utilities for manipulating source data (primarily music and images), using this data to train machine learning models, and finally generating new content from these models."
 
"[https://magenta.tensorflow.org/ Magenta] is distributed as an open source Python library, powered by TensorFlow. This library includes utilities for manipulating source data (primarily music and images), using this data to train machine learning models, and finally generating new content from these models."
  
=== Magenta on HPRC Clusters ===
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=== Magenta on HPRC clusters ===
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==== Magenta module ====
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Ideally we would rebuild everything needed for Magenta to optimize for our clusters but this is a significant and less than straightforward task.  So for now we recommend the Python solution below.
 +
==== Magenta via an Anaconda virtual environment ====
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A lot of what is described below is probably easily adapted to [[SW:Anaconda | Anaconda]], but we are going to use a plain Python for now
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==== Magenta via a Python virtual environment

Revision as of 04:59, 6 December 2018

Magenta

"Magenta is distributed as an open source Python library, powered by TensorFlow. This library includes utilities for manipulating source data (primarily music and images), using this data to train machine learning models, and finally generating new content from these models."

Magenta on HPRC clusters

Magenta module

Ideally we would rebuild everything needed for Magenta to optimize for our clusters but this is a significant and less than straightforward task. So for now we recommend the Python solution below.

Magenta via an Anaconda virtual environment

A lot of what is described below is probably easily adapted to Anaconda, but we are going to use a plain Python for now ==== Magenta via a Python virtual environment