[jira] [Commented] (SINGA-445) can not run Singa module example

["Moaz Reyad (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SINGA-445?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16856599#comment-16856599 ] 

Moaz Reyad commented on SINGA-445:
----------------------------------

I think the [Three most important unfinished issues to address before graduating |https://cwiki.apache.org/confluence/display/INCUBATOR/June2019#three-most-important-unfinished-issues-to-address-before-graduating-18] section should contain issues related to graduating from the incubator and not general issues like website update and rafiki integration. These general issues do not block the graduation and they are independent from the graduation tasks.

The most important issues to address before graduation (in my opinion) are:
 1. [Choosing the project PMC chair|https://lists.apache.org/thread.html/ce3c626d22ecf520d73cd5add269cf1993f1d253dd6f6ce13446d44b@%3Cprivate.singa.apache.org%3E].
 2. Finalize the [Graduation Resolution|https://cwiki.apache.org/confluence/display/SINGA/Graduation+Resolution]. Missing parts are marked in red.
 3. [Discuss|https://lists.apache.org/thread.html/dc37e2c7614f0f7f0f91d0451ddeff1d253b1d05bfeb3c4797fefa0e@%3Cdev.singa.apache.org%3E] and Vote with mentors and team members on the mail list if there is any other missing issue before graduation.

> can not run Singa module example
> --------------------------------
>
>                 Key: SINGA-445
>                 URL: https://issues.apache.org/jira/browse/SINGA-445
>             Project: Singa
>          Issue Type: Bug
>          Components: Documentation
>         Environment: - Ubuntu 18.10
> - python 3.6
>            Reporter: thao p nguyen
>            Priority: Critical
>
> Following the latest Singa documentation's examples on running modules, below error was found  for running module Metric:
> >>> from singa import tensor
> >>> from singa import metric
> >>> x = tensor.Tensor((3, 5))
> >>> x.uniform(0, 1) # randomly generate the prediction activation
> >>> x = tensor.SoftMax # normalize the prediction into probabilities
> Traceback (most recent call last):
> File "<stdin>", line 1, in <module>
> AttributeError: module 'singa.tensor' has no attribute 'SoftMax'
> >>> y = tensor.from_numpy(np.array([0, 1, 3], dtype=np.int)) # set the truth
> Traceback (most recent call last):
> File "<stdin>", line 1, in <module>
> NameError: name 'np' is not defined
> >>>
> >>> f = metric.Accuracy()
> >>> acc = f.evaluate(x, y) # averaged accuracy over all 3 samples in x
>  



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