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Return value docs for nd.random.* and sym.random.* #13994
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ChaiBapchya
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Jan 26, 2019
sandeep-krishnamurthy
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Thanks for the contribution, @zboldyga. The preview is at http:https://mxnet-ci-doc.s3-accelerate.dualstack.amazonaws.com/PR-13994/2/api/python/ndarray/random.html#api-reference. Doc looks good to me. |
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Feb 16, 2019
* mx.random.multinomial python documentation updated, return type details added * multinomial documentation clarified * added basic case for negative_binomial * added basic case for generalized_negative_binomial * basic case added for gamma * added basic case for exponential * basic case added for randn * remaining base cases added. * randint case added * cleaned up return types for random.py * zboldyga added to contributors * spacing typo correction * updated symbol.random return types, minor correction to ndarray.random return types * removed trailing whitespace in docs
haohuanw
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Jun 23, 2019
* mx.random.multinomial python documentation updated, return type details added * multinomial documentation clarified * added basic case for negative_binomial * added basic case for generalized_negative_binomial * basic case added for gamma * added basic case for exponential * basic case added for randn * remaining base cases added. * randint case added * cleaned up return types for random.py * zboldyga added to contributors * spacing typo correction * updated symbol.random return types, minor correction to ndarray.random return types * removed trailing whitespace in docs
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Description
Documented return values & types for nd.random.* and sym.random.*
Issue: #13227
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Essentials
Please feel free to remove inapplicable items for your PR.
NO JIRA, PR CHANGE IS TINY (DOCUMENTATION ADDITIONS ONLY)
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Based on other parts of the Python API documentation as of V 1.3.1, I wasn't 100% clear on how detailed return type documentation should be. I also wasn't sure of the preferred terms to use for certain aspects of the MXNet Symbol library. For instance, is saying that a Symbol 'resolves' to shape (m,n,x,y) an accurate description? Given the complexity of some of the .random.* APIs, it seems useful to get into the details of the structure of the output.
Happy to make changes if someone more central to the project has preferences!
Also, I was not able to build the docs on OSX or Ubuntu, this seemed to be a general problem with any version of the MXNet project. I'm going to lean on the CI tools for the moment.