c code generator from python
Hi, Is there any python framework or any tool as which can generate C code from python code as it is . Thanks, Kushal -- https://mail.python.org/mailman/listinfo/python-list
python to C code generator
Hi, Is there any python framework or any tool as which can generate C code from python code as it is . Thanks, Kushal -- https://mail.python.org/mailman/listinfo/python-list
Re: python to C code generator
Hi, Have a look at Cython. Best 2018-01-17 12:04 GMT+01:00 kushal bhattacharya : > Hi, > Is there any python framework or any tool as which can generate C code from > python code as it is . > > Thanks, > Kushal > -- > https://mail.python.org/mailman/listinfo/python-list -- https://mail.python.org/mailman/listinfo/python-list
Re: python to C code generator
On 17/01/2018 11:04, kushal bhattacharya wrote: Hi, Is there any python framework or any tool as which can generate C code from python code as it is . What C code would you expect to see from this line of Python: a = b + c ? -- https://mail.python.org/mailman/listinfo/python-list
Speeding up the implementation of Stochastic Gradient Ascent in Python
Hello everyone, I am implementing a time-dependent Recommender System which applies BPR (Bayesian Personalized Ranking), where Stochastic Gradient Ascent is used to learn the parameters of the model. Such that, one iteration involves sampling randomly the quadruple (i.e. userID, positive_item, negative_item, epoch_index) for n times, where n is the total number of positive feedbacks (i.e. the number of ratings given to all items). But, as my implementation takes too much time for learning the parameters (since it requires 100 iterations to learn the parameters), I was wondering if there is a way to improve my code and speed up the learning process of the parameters. Please find the code of my implementation (the update function named as updateFactors is the one that learns the parameters, and such that I guess is the one that should be improved in order to speed up the process of learning the parameter values) in the following link: https://codereview.stackexchange.com/questions/183707/speeding-up-the-implementation-of-stochastic-gradient-ascent-in-python -- https://mail.python.org/mailman/listinfo/python-list
Re: Speeding up the implementation of Stochastic Gradient Ascent in Python
On Wednesday, January 17, 2018 at 2:30:13 PM UTC, Leo wrote: > Hello everyone, > > I am implementing a time-dependent Recommender System which applies BPR > (Bayesian Personalized Ranking), where Stochastic Gradient Ascent is used to > learn the parameters of the model. Such that, one iteration involves sampling > randomly the quadruple (i.e. userID, positive_item, negative_item, > epoch_index) for n times, where n is the total number of positive feedbacks > (i.e. the number of ratings given to all items). But, as my implementation > takes too much time for learning the parameters (since it requires 100 > iterations to learn the parameters), I was wondering if there is a way to > improve my code and speed up the learning process of the parameters. > > Please find the code of my implementation (the update function named as > updateFactors is the one that learns the parameters, and such that I guess is > the one that should be improved in order to speed up the process of learning > the parameter values) in the following link: > https://codereview.stackexchange.com/questions/183707/speeding-up-the-implementation-of-stochastic-gradient-ascent-in-python You have a fair chunk of code so I've only taken a quick glance so this could just be the tip of the iceberg. You're clearly using Python 2 as you have print statements, not functions. If you can upgrade to Python 3 is it is superior, see e.g. https://www.youtube.com/watch?v=f_6vDi7ywuA for i in range(1, len(self.userItems[userID])): is a code smell, consider using for userItem in self.userItems[userID]: if len(pos_per_user[userID]) == 0: is written if pos_per_user[userID]: if userID == None: should be if userID is None: Profile your code with https://docs.python.org/3/library/profile.html to find where the hot spots are. Read https://wiki.python.org/moin/PythonSpeed/PerformanceTips for tips on how to up your code performance. -- Kindest regards. Mark Lawrence. -- https://mail.python.org/mailman/listinfo/python-list
Re: Speeding up the implementation of Stochastic Gradient Ascent in Python
On 1/17/18 9:29 AM, leutrim.kal...@gmail.com wrote: Hello everyone, I am implementing a time-dependent Recommender System which applies BPR (Bayesian Personalized Ranking), where Stochastic Gradient Ascent is used to learn the parameters of the model. Such that, one iteration involves sampling randomly the quadruple (i.e. userID, positive_item, negative_item, epoch_index) for n times, where n is the total number of positive feedbacks (i.e. the number of ratings given to all items). But, as my implementation takes too much time for learning the parameters (since it requires 100 iterations to learn the parameters), I was wondering if there is a way to improve my code and speed up the learning process of the parameters. Please find the code of my implementation (the update function named as updateFactors is the one that learns the parameters, and such that I guess is the one that should be improved in order to speed up the process of learning the parameter values) in the following link: https://codereview.stackexchange.com/questions/183707/speeding-up-the-implementation-of-stochastic-gradient-ascent-in-python It looks like you have lists that you are doing "in" and "remove" operations on. I don't know how long these lists are, but sets will be much faster in general. You'll have to replace random.choice() with random.choice(list(...)), since you can't random.choice from a set. That might negate the benefits, but it's worth a try. --Ned. -- https://mail.python.org/mailman/listinfo/python-list
Re: Speeding up the implementation of Stochastic Gradient Ascent in Python
On Thu, Jan 18, 2018 at 6:28 AM, Ned Batchelder wrote: > You'll have to replace random.choice() with > random.choice(list(...)), since you can't random.choice from a set. > Side point: why can't you? You can random.sample from a set, but random.choice requires a sequence. It seems perfectly sane to ask for a random element from a set. ChrisA -- https://mail.python.org/mailman/listinfo/python-list
Re: Speeding up the implementation of Stochastic Gradient Ascent in Python
On 1/17/18 2:45 PM, Chris Angelico wrote: On Thu, Jan 18, 2018 at 6:28 AM, Ned Batchelder wrote: You'll have to replace random.choice() with random.choice(list(...)), since you can't random.choice from a set. Side point: why can't you? You can random.sample from a set, but random.choice requires a sequence. It seems perfectly sane to ask for a random element from a set. You'd have to ask Raymond Hettinger I guess. random.sample works on a set because it starts with: if isinstance(population, _Set): population = tuple(population) So sample() is willing to listify (tuplify?) your set for you, but choice() is not. --Ned. -- https://mail.python.org/mailman/listinfo/python-list
Re: Speeding up the implementation of Stochastic Gradient Ascent in Python
On Thu, Jan 18, 2018 at 7:19 AM, Ned Batchelder wrote: > On 1/17/18 2:45 PM, Chris Angelico wrote: >> >> On Thu, Jan 18, 2018 at 6:28 AM, Ned Batchelder >> wrote: >>> >>> You'll have to replace random.choice() with >>> random.choice(list(...)), since you can't random.choice from a set. >>> >> Side point: why can't you? You can random.sample from a set, but >> random.choice requires a sequence. It seems perfectly sane to ask for >> a random element from a set. >> >> > > You'd have to ask Raymond Hettinger I guess. random.sample works on a set > because it starts with: > > if isinstance(population, _Set): > population = tuple(population) > > So sample() is willing to listify (tuplify?) your set for you, but choice() > is not. > Ah. So it's just as inefficient. (I should have looked.) So I guess what we really need is some lower-level support. There's no way in Python to pick a random element from a set in O(1) time. It could be done in O(n) time and O(1) space by iterating through the set until you hit the chosen random index, but you can't just say "grab me one of those". ChrisA -- https://mail.python.org/mailman/listinfo/python-list
Why does random.choice() reject sets? was Re: Speeding up the implementation of Stochastic Gradient Ascent in Python
Chris Angelico wrote: > On Thu, Jan 18, 2018 at 6:28 AM, Ned Batchelder > wrote: >> You'll have to replace random.choice() with >> random.choice(list(...)), since you can't random.choice from a set. >> > > Side point: why can't you? You can random.sample from a set, I'm not sure this was a good idea. > but > random.choice requires a sequence. It seems perfectly sane to ask for > a random element from a set. $ python3 -m timeit -s 'from random import sample; items = list(range(10))' 'sample(items, 5)' 10 loops, best of 3: 18 usec per loop $ python3 -m timeit -s 'from random import sample; items = set(range(10))' 'sample(items, 5)' 100 loops, best of 3: 7.27 msec per loop You would need access to the set implementation to get reasonable performance. As random.choice() is more likely to be called repeatedly with the same argument I'd rather not hide something like if isinstance(seq, set): seq = tuple(set) in its function body. -- https://mail.python.org/mailman/listinfo/python-list
Re: documentation on read.encode
On Tue, Jan 16, 2018 at 3:58 PM, MRAB wrote:
> On 2018-01-16 19:52, Larry Martell wrote:
>>
>> On Tue, Jan 16, 2018 at 2:35 PM, Gene Heskett
>> wrote:
>>>
>>> On Tuesday 16 January 2018 14:19:38 Larry Martell wrote:
>>>
On Tue, Jan 16, 2018 at 12:00 PM, Larry Martell
>>>
>>> wrote:
> Looking for 2.7 docs on read.encode - googling did not turn up
> anything.
>
> Specifically, looking for the supported options for base64, and how
> to specify them, e.g. Base64.NO_WRAP
So I just realized that encode() is not a method of read() it's a
string method. But I still have the same question - can I pass in any
flags?
My issue is that I am base64 encoding PNG images on linux and it's
putting a LF at the end of each line. If I do the same on Windows it's
putting CR/LF. I want the files to be encoded with no platform
dependences. Googling I found mention of Base64.NO_WRAP and I want to
pass that into encode() - can I do that?
>>>
>>>
>>> Di you not have the manpages installed?
>>>
>>> In my copy of the manpage:
>>> base64 [OPTION]... [FILE]
>>> where option is:
>>> -w, --wrap=COLS
>>> wrap encoded lines after COLS character (default 76). Use
>>> 0 to disable line wrapping.
>>>
>>> Seems pretty simple.
>>
>>
>> But how do I use that in read().encode('base64')?
>>
> Use the base64 module instead, which is also how you would do it in Python
> 3.
>
> If you're getting CR/LF on Windows, that's because you're opening the file
> in text mode. In both Python 2 and Python 3 the base64 string will be a
> bytestring, which you'd write out to a file opened in binary mode.
>
> That's an extra bit of future-proofing! :-)
Thanks. That's what it ended up being. The code that was receiving the
PNG was not reading and writing the file as binary. Strangely that
worked on Linux but not on Windows.
--
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Re: documentation on read.encode
On Wed, 17 Jan 2018 16:54:37 -0500, Larry Martell wrote: > The code that was receiving the > PNG was not reading and writing the file as binary. Strangely that > worked on Linux but not on Windows. Nothing strange about it -- on Unix and Linux systems (with the possible exception of Mac OS?) in Python 2 there's no difference between text and binary mode for ASCII-only files. In Python 2, strings are byte strings, not Unicode, and reading from files returns such sequences of bytes. On Windows, reading from files in text mode treats \r\n as the end of line, and converts[1] such \r\n pairs to \n; it also treats ^Z byte as the end of file[2], or at least it used to back in the 2.5 or so days. I haven't tested it in more recent versions. [1] Technically this is a build-time option, but as far as I know it is not just the default but pretty much universal. [2] https://blogs.msdn.microsoft.com/oldnewthing/20040316-00/?p=40233/ -- Steve -- https://mail.python.org/mailman/listinfo/python-list
