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From "Piyush Ghai (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (MXNET-1286) Train a Float64 model in Python in order to verify MXNET-1278
Date Wed, 02 Jan 2019 22:55:00 GMT

    [ https://issues.apache.org/jira/browse/MXNET-1286?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16732495#comment-16732495
] 

Piyush Ghai commented on MXNET-1286:
------------------------------------

An easy workaround is to take any pre-trained model, and use the Cast operator of MXNet to
cast it to a different DType. 

 

Example snippet : [https://github.com/apache/incubator-mxnet/pull/12412/files#diff-33e25bba6c65aa67b8d00cb07bd7fc4cR206]

 

> Train a Float64 model in Python in order to verify MXNET-1278
> -------------------------------------------------------------
>
>                 Key: MXNET-1286
>                 URL: https://issues.apache.org/jira/browse/MXNET-1286
>             Project: Apache MXNet
>          Issue Type: Sub-task
>          Components: Apache MXNet Scala API
>            Reporter: Piyush Ghai
>            Assignee: Piyush Ghai
>            Priority: Minor
>
> To load a pre-trained model, we need to access a model or try to train a simple model
using Float64 as the input types. 



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