Addon to the Codegen section: With the example above of having an implemented function in some expression in sympy, assuming one can write the c-code equivalent, how would one link the c-code to the codegen process as opposed to having codegen generate it? Cheers, Guy
On Tuesday, August 6, 2013 11:04:33 AM UTC-4, Guy Parsey wrote: > > Hello, > > Theano/Sympy questions > Fred, in terms of replacing sympy.Pieceiwse with a Theano equivalent, > since sympy.Piecewise attempts each condition (from ExprCondPair) until one > is valid, I would think that the closest equivalent would be a recursive > theano ifelse (ie. sympy.Piecewise((expr1,cond1),(expr2,cond2)) ~ > theano.ifelse(cond1,expr1,theano.ifelse(cond2,expr2,None))) statement so > that the expressions are not evaluated until the condition is achieved. > This might be too much of a patch though and I am not sure how to implement > it with the same argument structure as sympy.Pieceiwse. > > With regards to using an externally defined theano graph or op (theano > wrapped sympy implementation), how would one pass them to theano_function? > It feels as though it would be analogous to the autowrap helpers argument, > or would this be an issue of merging graphs before calling theano.function? > If I can understand this step, I feel as though both of my problems would > be solvable (a wrapping of a piecewise along with a wrapping of an > interpolated function) > > In all of my simplified test cases (no pieceiwse or interpolations, 9 > heavily-linked non-linear ODEs), I also show that the lambdify function is > faster to evaluate than my created theano function. When passing a list of > expressions, if there is a commons subexpression that exists in two > expressions (not twice in the same expression), is it treated as such > during theano compilation or is each expression handled separately? > > Codegen questions (maybe a different topic): > Jason, I have started playing with the sympy.printing.codegen (C for now, > Fortran later) as an alternative to theano (I would very much like to get > multiple methods working, and GPU acceleration makes me want to keep theano > implementation). There is a size-able speedup relative to lambdify or > theano_function, which is to be expected, but I arrive at the same problem > as above with regards to interpolated or piecewise functions. The initial > crash from using Piecewise functions comes from Routine calling > sympy.tensor.index_methods get_contraction_structure which explicitly > states no support for Piecewise function types. In principle, if one made a > symbolic implemented function (preferably without an analytical > representation), could one link the python object to the compiled code? > What attributes would said implemented_function need to have? > > Thank you for your responses, I am glad to hear that at least I am not > completely missing something. > Cheers, > Guy > > On Tuesday, August 6, 2013 9:37:41 AM UTC-4, Jason Moore wrote: >> >> Fred, >> >> I think on_used_input=ignore should be a default in Matthew's theano >> printing code or that arg needs to be pushed up to his layer. I hit that >> issue too. >> >> The code I have is here: https://github.com/PythonDynamics/pydy-code-gen >> >> See the results.txt file for basic speed comparisons. I'm generating the >> ODEs for an n-link pendulum with mechanics and then see how fast it >> generates and simulates with scipy.odeint. >> >> The code doesn't work at the moment. I haven't touched it in a month and >> looks like some things have changed in sympy and/or theano. I'll work on >> the bugs now. >> >> But "python benchmark.py" should run it with sympy master and ?some? >> version of Theano. >> >> >> Jason >> moorepants.info >> +01 530-601-9791 >> >> >> On Tue, Aug 6, 2013 at 9:25 AM, Frédéric Bastien <no...@nouiz.org> wrote: >> >>> Hi, >>> >>> I don't know what is sympy.functions.elementary.piecewise. Do Jason >>> answered that part? If not, I'll look into it to know how to make Theano >>> reproduce it. About converting any Sympy symbol to Theano symbol, when >>> there isn't a one to one matching, you can create a one to a full Theano >>> graph conversion. When this is possible, it is probably the best, as if you >>> make a new Theano op, it work work on the GPU. But if you make a Theano >>> graph, there is good change that the graph will already work on the GPU. >>> >>> If it is not possible to make a Theano graph for a sympy symbol, it is >>> possible to make a new Theano op that just wrap the sympy implementation. >>> Also, if this is a bottleneck, I recently added an example that show how to >>> use numba with Theano so speed up the python code in a Theano op. >>> >>> >>> Theano do not parallelize on the CPU, except for the call to BLAS, when >>> the BLAS library is parallel. On the GPU, it is parallel. >>> >>> Having on_unused_input=ignore is normal for complicated generated code. >>> That is why it was added. But when the code is simpler and not generated, >>> but all user manually coded, most of time it mean the user didn't do what >>> he wanted. If you know it is normal that you have unused input, there is no >>> problem to use that flag. >>> >>> >>> Jason, about the case where Theano is slower, can you send me the Theano >>> code? I would like to look at it. I'm very surprised that Theano is slower >>> then Sympy in this case and would like to know why it is like this. >>> >>> Fred >>> >>> >>> On Mon, Aug 5, 2013 at 9:03 PM, Jason Moore <moore...@gmail.com> wrote: >>> >>>> Guy, >>>> >>>> We're working on the same problem for sympy.physics.mechanics. Matthew >>>> Rocklin added support for matrix conversions in the theano code that is in >>>> SymPy and I used that, but found that theano was slower that lambdify for >>>> most of my cases (I only have two cores, so I'm not taking advantage of >>>> the >>>> Theano parallel stuff). I think writing specific code gen for ode >>>> integration is going to be the best bet. I'm happy to collaborate on this >>>> with you. >>>> >>>> >>>> Jason >>>> moorepants.info >>>> +01 530-601-9791 >>>> >>>> >>>> On Mon, Aug 5, 2013 at 3:13 PM, Guy Parsey <guy.p...@gmail.com> wrote: >>>> >>>>> Hello Everyone, >>>>> Thank you in advance for reading through my problem and for any input >>>>> you may have. I must say that I still feel like a novice programmer and >>>>> my >>>>> problems may be easily solvable from a different mindset. My present >>>>> project entails time-integration of extremely stiff and non-linear ODEs >>>>> with regards to chemical kinetics (one derivative equation for each >>>>> variable species) and energy equations. Initially we were planning on >>>>> using >>>>> the sympy.lambdify function to create callable functions for the main >>>>> function along with the jacobian and passing said functions to >>>>> scipy.integrate.odeint, however this method only works for easier test >>>>> cases (fewer species and/or no energy equations) before being limited by >>>>> either the list recursion limit or segfaulting due to the limited stack >>>>> size. I know that both of these limits can be edited, but that fact that >>>>> I >>>>> am reaching them makes me feel as though I am doing something extremely >>>>> inefficiently. Outside of the documentation of SymPy and Theano, I have >>>>> also been heavily using the BlogPost by Matthew Rocklin >>>>> http://matthewrocklin.com/blog/work/2013/03/19/SymPy-Theano-part-1/ . >>>>> >>>>> Presently I am trying to use the mapping between Theano and SymPy >>>>> (sympy.printing.theanocode theano_function) to make my callable functions >>>>> and take advantage of the optimization routines. I have two major >>>>> problems >>>>> and a few questions: >>>>> >>>>> 1st major problem: Though piecewise functions exist in SymPy >>>>> (sympy.functions.elementary.piecewise) there is no counterpart in Theano. >>>>> Looking at the source of the inspiration for theanocode ( >>>>> https://github.com/nouiz/theano_sympy/ graph_translation.py) I see >>>>> that some of the SymPy equivalents were defined as lambda functions. Is >>>>> there an equivalent way to add Theano conditional expressions wrapped >>>>> into >>>>> a function to add to the mapping dictionary in theanocode.py? >>>>> >>>>> 2nd major problem: Similar to the problem above in that I am not sure >>>>> that the Theano counterpart is; some of the terms that I use are >>>>> interpolated functions (with one ODE variable as input) that we have >>>>> wrapped symbolically while providing a numerical implementation (so that >>>>> symbolic derivatives can be made, resulting in their own interpolations). >>>>> Is it possible to recreate the interpolation function as a Theano >>>>> operation >>>>> for use within the system of ODEs? >>>>> >>>>> Remain questions: >>>>> I presently have to flatten my input to theano_function to a list of >>>>> expressions and then wrap to return to a form (Jacobian is a matrix not a >>>>> vector); is it possible to have a matrix of different expressions as an >>>>> input to theano_function with a vector output? >>>>> >>>>> I know that a huge amount of Theano speed up is due to parallelization >>>>> of matrix operations (which I do not have), should I be focusing on SymPy >>>>> Autowrap/Ufuncify or my own code generation instead of trying to get >>>>> Theano >>>>> to play nicely? >>>>> >>>>> Stupid questions: >>>>> Does sympy.printing.theanocode.theano_function automatically optimize >>>>> the compiled graph? >>>>> >>>>> Minor comment: >>>>> Perhaps unnecessary for most uses of the theano_function, but I needed >>>>> to modify function inputs so as to be able to use the keyword argument >>>>> 'on_unused_input=ignore' as opposed to 'raise' so that I did not need to >>>>> have all symbols in all equations. This may be avoided by having the >>>>> unused >>>>> symbols somehow (I don't know how) included in each expression. >>>>> >>>>> Thank you again for your time in reading my problems and any potential >>>>> help you may think of. I can attach code if necessary, I just didn't want >>>>> to make my post more confusing. >>>>> Have an excellent day. >>>>> Sincerely, >>>>> Guy Parsey >>>>> >>>>> -- >>>>> You received this message because you are subscribed to the Google >>>>> Groups "sympy" group. >>>>> To unsubscribe from this group and stop receiving emails from it, send >>>>> an email to sympy+un...@googlegroups.com. >>>>> To post to this group, send email to sy...@googlegroups.com. >>>>> Visit this group at http://groups.google.com/group/sympy. >>>>> For more options, visit https://groups.google.com/groups/opt_out. >>>>> >>>>> >>>>> >>>> >>>> -- >>>> You received this message because you are subscribed to the Google >>>> Groups "sympy" group. >>>> To unsubscribe from this group and stop receiving emails from it, send >>>> an email to sympy+un...@googlegroups.com. >>>> To post to this group, send email to sy...@googlegroups.com. >>>> Visit this group at http://groups.google.com/group/sympy. >>>> For more options, visit https://groups.google.com/groups/opt_out. >>>> >>>> >>>> >>> >>> -- >>> You received this message because you are subscribed to the Google >>> Groups "sympy" group. >>> To unsubscribe from this group and stop receiving emails from it, send >>> an email to sympy+un...@googlegroups.com. >>> To post to this group, send email to sy...@googlegroups.com. >>> Visit this group at http://groups.google.com/group/sympy. >>> For more options, visit https://groups.google.com/groups/opt_out. >>> >>> >>> >> >> -- You received this message because you are subscribed to the Google Groups "sympy" group. 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