Personally, I needed sorting channel axis of 4D CNN image tensor a while 
ago. It's about sorting large batches of short vectors (around 32~128 
channels). However this is just a corner case. I don't think I can tell 
what kind of sorting most needed.

Just a suggestion, what about posting this thread on some popular place 
such as /r/MachineLearning? So people using other frameworks can see this.

On Tuesday, June 20, 2017 at 6:16:41 AM UTC+8, nouiz wrote:
>
> Adam, what input shapes do you do sort on right now? What axis?
>
> This is to help to know which car to optimize.
>
> Fred
>
> Le mer. 14 juin 2017 22:03, Victor Campmany <[email protected] 
> <javascript:>> a écrit :
>
>> The implementation would be for *Gpuarray*, not Theano, I mixed things 
>> up sorry.
>>
>>
>> El miércoles, 14 de junio de 2017, 20:47:41 (UTC-4), Adam Becker escribió:
>>>
>>> I'd prefer a gpuarray implementation with similar interface as numpy:
>>>
>>> gpuarray.sort(arr, [axis=-1], [kind='radixsort'], [order='inc'])
>>>
>>> Deep Learning folks would need a fast batched version, especially 
>>> float32 / int32 tensors on GPU. But anyway there should be a general 
>>> algorithm deals with all cases, never know what kind of model would come up 
>>> in future. 
>>>
>>> On Thursday, June 15, 2017 at 4:01:00 AM UTC+8, Victor Campmany wrote:
>>>>
>>>> Hi,
>>>>
>>>> We are planning to implement a new GPU accelerated sorting algorithm. 
>>>> We'd like to know which are the most frequent sorting cases that you guys 
>>>> use and the data sizes you are dealing with. For example, sorting a large 
>>>> 1d array, sorting a given axis of a tensor or minibatch, or any other type 
>>>> of sorting you come up with.
>>>>
>>> -- 
>>
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