Closed bob-carpenter closed 8 years ago
I'm reopening this issue because the pull request that was merged in only provides the infrastructure to test these vectorize functions. However, if you think that we should close this issue and open a new one, I can do that.
Either way is OK. You need to make the checklist of all unary functions to which this applies. You can probably knock them off in multiple issues.
On Mar 15, 2016, at 4:52 PM, rayleigh notifications@github.com wrote:
I'm reopening this issue because the pull request that was merged in only provides the infrastructure to test these vectorize functions. However, if you think that we should close this issue and open a new one, I can do that.
— You are receiving this because you were assigned. Reply to this email directly or view it on GitHub
Okay. Copying over your response to a question of where to put files:
stan/math/prim/mat/fun/<function-name>.hpp
This should declare all the basic vectorizations and perhaps up to 4 deep for arrays of all types.
Also, where should the test files go? Should they go in /test/unit/math/mix/mat/fun/<function-name>_test.hpp
?
Thanks and yes, that's the right place for the test files, because they depend on mix.
On Mar 17, 2016, at 10:30 AM, rayleigh notifications@github.com wrote:
Okay. Copying over your response to a question of where to put files:
• The function definitions so should go here: stan/math/prim/mat/fun/
.hpp • For functions already partly vectorized, you need to remove the original vectorized definitions (just get rid of them and their associated tests).
• The function signatures class is going to need a utility method to declare these, presumably something like ``add_unary_vectorized("exp") and so on.
This should declare all the basic vectorizations and perhaps up to 4 deep for arrays of all types.
• You're going to need to write (or have me write) a. a new intro section to the functions guide in the manual, with some new syntax for this vectorization, and b. update the doc for each of the added functions Also, where should the test files go? Should they go in /test/unit/math/mix/mat/fun/
_test.hpp? — You are receiving this because you were assigned. Reply to this email directly or view it on GitHub
Thanks. Looking through the 2.8.0 Stan manual, I noticed that abs
is to be deprecated. Should I vectorize it or should I only vectorize fabs
?
Ack, I think we undeprecated abs and are going to deprecate fabs (to make it more like math and less like C++). So go ahead and do both and we can see where the chips land.
On Mar 21, 2016, at 11:45 AM, rayleigh notifications@github.com wrote:
Thanks. Looking through the 2.8.0 Stan manual, I noticed that abs is to be deprecated. Should I vectorize it or should I only vectorize fabs?
— You are receiving this because you were assigned. Reply to this email directly or view it on GitHub
Sounds good; I vectorized both. I've been trying to vectorize the function cbrt
. It's defined for 0, but its derivatives aren't (it returns NaN). From this, I realized that the testing framework assumed that if a function is defined for a value, its derivatives are as well. To handle this, does the vectorize function throw an error if an user enters 0? Or, do I write separate code to test this case?
I think we should test derivatives.
We had this discussion in the past regarding defined values and undefined derivatives. I think the functions should trap that error and fail early if possible, even if it conflicts with other implementations of the function. If we're using these functions primarily where they need derivatives, it makes no sense to knowingly propagate NaNs.
On Mon, Mar 21, 2016 at 7:00 PM, rayleigh notifications@github.com wrote:
Sounds good; I vectorized both. I've been trying to vectorize the function cbrt. It's defined for 0, but its derivatives aren't (it returns NaN). From this, I realized that the testing framework assumed that if a function is defined for a value, its derivatives are as well. To handle this, does the vectorize function throw an error if an user enters 0? Or, do I write separate code to test this case?
— You are receiving this because you modified the open/close state. Reply to this email directly or view it on GitHub https://github.com/stan-dev/math/issues/202#issuecomment-199525782
Okay. Just to clarify, should the vectorize-all function or the individual scalar functions include the error checking? Or, both?
That was a general comment.
What test am I supposed to run? Can you provide the full path?
On Tue, Mar 22, 2016 at 11:34 AM, rayleigh notifications@github.com wrote:
Okay. Just to clarify, should the vectorize-all function or the individual scalar functions include the error checking? Or, both?
— You are receiving this because you modified the open/close state. Reply to this email directly or view it on GitHub https://github.com/stan-dev/math/issues/202#issuecomment-199868918
I pushed more changes to the branch feature/issue-202-vectorize-all
. However, I only wanted to commit things that worked. So, if you pull that branch, you'll need to change test/unit/math/mix/mat/fun/cbrt_test.cpp
before running it. In the function valid_inputs
, change any one of the values to 0.
I pushed the change to exp.hpp
to feature/issue-202-vectorize-all
. The test to run is test/unit/math/mix/mat/vectorize/foo_test.cpp
.
Is it only exp() that's causing the issue?
On Mar 22, 2016, at 2:28 PM, rayleigh notifications@github.com wrote:
I pushed the change to exp.hpp to feature/issue-202-vectorize-all. The test to run is test/unit/math/mix/mat/vectorize/foo_test.cpp.
— You are receiving this because you were assigned. Reply to this email directly or view it on GitHub
No. This isn't an include-order issue.
Here's where I'm at so far with exp:
stan::math::var exp(const stan::math::var& a)
in stan/math/rev/scal/fun/exp.hpp.In file included from test/unit/math/mix/mat/vectorize/foo_test.cpp:1:
In file included from ./stan/math/mix/mat.hpp:12:
In file included from ./stan/math/prim/mat.hpp:91:
In file included from ./stan/math/prim/mat/fun/exp.hpp:4:
./stan/math/prim/mat/vectorize/apply_scalar_unary.hpp:40:41: error:
implicit instantiation of
undefined template 'Eigen::internal::traits<stan::math::var>'
typedef typename Eigen::internal::traits<T>::Scalar scalar_t;
^
./stan/math/prim/mat/fun/exp.hpp:23:21: note: in instantiation of template
class
'stan::math::apply_scalar_unary<stan::math::exp_fun,
stan::math::var>' requested here
inline typename apply_scalar_unary<exp_fun, T>::return_t
^
./stan/math/rev/scal/fun/grad_inc_beta.hpp:28:16: note: while substituting
deduced template arguments
into function template 'exp' [with T = stan::math::var]
var c3 = exp(lbeta(a, b)) * inc_beta(a, b, z);
^
lib/eigen_3.2.4/Eigen/src/Core/util/ForwardDeclarations.h:17:29: note:
template is declared here
template<typename T> struct traits;
^
In file included from test/unit/math/mix/mat/vectorize/foo_test.cpp:1:
In file included from ./stan/math/mix/mat.hpp:12:
In file included from ./stan/math/prim/mat.hpp:91:
In file included from ./stan/math/prim/mat/fun/exp.hpp:4:
I think if I can figure out why that specialization is not being used, it would go a long way.
Daniel
On Tue, Mar 22, 2016 at 11:09 PM, Bob Carpenter notifications@github.com wrote:
Is it only exp() that's causing the issue?
- Bob
On Mar 22, 2016, at 2:28 PM, rayleigh notifications@github.com wrote:
I pushed the change to exp.hpp to feature/issue-202-vectorize-all. The test to run is test/unit/math/mix/mat/vectorize/foo_test.cpp.
— You are receiving this because you were assigned. Reply to this email directly or view it on GitHub
— You are receiving this because you modified the open/close state. Reply to this email directly or view it on GitHub https://github.com/stan-dev/math/issues/202#issuecomment-200146513
Ok. Those headers aren't included in stan/math/prim/mat.hpp or rev/mat.hpp or fwd/mat.hpp.
I'll fix that now.
On Tue, Mar 22, 2016 at 11:22 PM, Daniel Lee bearlee@alum.mit.edu wrote:
No. This isn't an include-order issue.
Here's where I'm at so far with exp:
- There's a definition of a struct exp_fun in stan/math/prim/scal/mat/fun/exp.hpp.
- There is a definition of a templated function exp that should handle the vectorization in stan/math/prim/mat/fun/exp.hpp.
- There is a definition of a
stan::math::var exp(const stan::math::var& a)
in stan/math/rev/scal/fun/exp.hpp.- When calling foo_test.cpp, which should really be changed to exp_test.cpp, with the appropriate changes, this is the compiler error message that crops up:
In file included from test/unit/math/mix/mat/vectorize/foo_test.cpp:1: In file included from ./stan/math/mix/mat.hpp:12: In file included from ./stan/math/prim/mat.hpp:91: In file included from ./stan/math/prim/mat/fun/exp.hpp:4: ./stan/math/prim/mat/vectorize/apply_scalar_unary.hpp:40:41: error: implicit instantiation of undefined template 'Eigen::internal::traits<stan::math::var>' typedef typename Eigen::internal::traits<T>::Scalar scalar_t; ^ ./stan/math/prim/mat/fun/exp.hpp:23:21: note: in instantiation of template class 'stan::math::apply_scalar_unary<stan::math::exp_fun, stan::math::var>' requested here inline typename apply_scalar_unary<exp_fun, T>::return_t ^ ./stan/math/rev/scal/fun/grad_inc_beta.hpp:28:16: note: while substituting deduced template arguments into function template 'exp' [with T = stan::math::var] var c3 = exp(lbeta(a, b)) * inc_beta(a, b, z); ^ lib/eigen_3.2.4/Eigen/src/Core/util/ForwardDeclarations.h:17:29: note: template is declared here template<typename T> struct traits; ^ In file included from test/unit/math/mix/mat/vectorize/foo_test.cpp:1: In file included from ./stan/math/mix/mat.hpp:12: In file included from ./stan/math/prim/mat.hpp:91: In file included from ./stan/math/prim/mat/fun/exp.hpp:4:
- That compiler error is coming from the template specialization of apply_scalar_unary() not being used from stan/math/rev/mat/vectorize/apply_scalar_unary.hpp.
I think if I can figure out why that specialization is not being used, it would go a long way.
Daniel
On Tue, Mar 22, 2016 at 11:09 PM, Bob Carpenter notifications@github.com wrote:
Is it only exp() that's causing the issue?
- Bob
On Mar 22, 2016, at 2:28 PM, rayleigh notifications@github.com wrote:
I pushed the change to exp.hpp to feature/issue-202-vectorize-all. The test to run is test/unit/math/mix/mat/vectorize/foo_test.cpp.
— You are receiving this because you were assigned. Reply to this email directly or view it on GitHub
— You are receiving this because you modified the open/close state. Reply to this email directly or view it on GitHub https://github.com/stan-dev/math/issues/202#issuecomment-200146513
I just pushed, but it's not working yet. Bob, I might need your help reasoning through this.
apply_scalar_unary() in prim is being called first. Even when the mix header is included. That gets instantiated with stan::math::var as its second argument instead of being found with argument dependent lookup. If you want more detail as to the include order, try running the test (it's ok if it doesn't compile), then open up test/unit/math/mix/vectorize/foo_test.d. That'll show you the order in which files get opened.
If you include the rev version as the first thing in the test file, it works.
I'm not sure how to get past this problem. I'm sure we've figured this out in the past.
On Tue, Mar 22, 2016 at 11:24 PM, Daniel Lee bearlee@alum.mit.edu wrote:
Ok. Those headers aren't included in stan/math/prim/mat.hpp or rev/mat.hpp or fwd/mat.hpp.
I'll fix that now.
On Tue, Mar 22, 2016 at 11:22 PM, Daniel Lee bearlee@alum.mit.edu wrote:
No. This isn't an include-order issue.
Here's where I'm at so far with exp:
- There's a definition of a struct exp_fun in stan/math/prim/scal/mat/fun/exp.hpp.
- There is a definition of a templated function exp that should handle the vectorization in stan/math/prim/mat/fun/exp.hpp.
- There is a definition of a
stan::math::var exp(const stan::math::var& a)
in stan/math/rev/scal/fun/exp.hpp.- When calling foo_test.cpp, which should really be changed to exp_test.cpp, with the appropriate changes, this is the compiler error message that crops up:
In file included from test/unit/math/mix/mat/vectorize/foo_test.cpp:1: In file included from ./stan/math/mix/mat.hpp:12: In file included from ./stan/math/prim/mat.hpp:91: In file included from ./stan/math/prim/mat/fun/exp.hpp:4: ./stan/math/prim/mat/vectorize/apply_scalar_unary.hpp:40:41: error: implicit instantiation of undefined template 'Eigen::internal::traits<stan::math::var>' typedef typename Eigen::internal::traits<T>::Scalar scalar_t; ^ ./stan/math/prim/mat/fun/exp.hpp:23:21: note: in instantiation of template class 'stan::math::apply_scalar_unary<stan::math::exp_fun, stan::math::var>' requested here inline typename apply_scalar_unary<exp_fun, T>::return_t ^ ./stan/math/rev/scal/fun/grad_inc_beta.hpp:28:16: note: while substituting deduced template arguments into function template 'exp' [with T = stan::math::var] var c3 = exp(lbeta(a, b)) * inc_beta(a, b, z); ^ lib/eigen_3.2.4/Eigen/src/Core/util/ForwardDeclarations.h:17:29: note: template is declared here template<typename T> struct traits; ^ In file included from test/unit/math/mix/mat/vectorize/foo_test.cpp:1: In file included from ./stan/math/mix/mat.hpp:12: In file included from ./stan/math/prim/mat.hpp:91: In file included from ./stan/math/prim/mat/fun/exp.hpp:4:
- That compiler error is coming from the template specialization of apply_scalar_unary() not being used from stan/math/rev/mat/vectorize/apply_scalar_unary.hpp.
I think if I can figure out why that specialization is not being used, it would go a long way.
Daniel
On Tue, Mar 22, 2016 at 11:09 PM, Bob Carpenter <notifications@github.com
wrote:
Is it only exp() that's causing the issue?
- Bob
On Mar 22, 2016, at 2:28 PM, rayleigh notifications@github.com wrote:
I pushed the change to exp.hpp to feature/issue-202-vectorize-all. The test to run is test/unit/math/mix/mat/vectorize/foo_test.cpp.
— You are receiving this because you were assigned. Reply to this email directly or view it on GitHub
— You are receiving this because you modified the open/close state. Reply to this email directly or view it on GitHub https://github.com/stan-dev/math/issues/202#issuecomment-200146513
Any luck getting past this problem?
Copying this over from an email chain because it might have the solution (I haven't tried yet):
If you edit out the very first include line in:
/test/unit/math/mix/mat/vectorize/foo_test.cpp,
everything passes. So the new file looks like:
---------------------
// #include <stan/math/mix/mat.hpp>
#include <gtest/gtest.h>
#include <test/unit/math/prim/mat/vectorize/prim_scalar_unary_test.hpp>
#include <test/unit/math/rev/mat/vectorize/rev_scalar_unary_test.hpp>
#include <test/unit/math/fwd/mat/vectorize/fwd_scalar_unary_test.hpp>
#include <test/unit/math/mix/mat/vectorize/mix_scalar_unary_test.hpp>
#include <test/unit/math/prim/mat/vectorize/foo_fun.hpp>
#include <test/unit/math/prim/mat/vectorize/vector_builder.hpp>
/**
* This is the structure for testing mock function foo (defined in the
* testing framework). See README.txt for more instructions.
*/
struct foo_test {
-------------------------------
This makes me think there may be a problem in the include order in mix/mat.hpp.
You might want to read this:
http://stackoverflow.com/questions/14626033/implicit-instantiation-of-undefined-template-class
It's all about steps 1, 2, and 3 in the answer.
Other questions:
1) I tried vectorizing trunc.hpp
, but the matrix tests fail to run for it. When I looked at boost/math/special_functions/trunc.hpp
, I saw the following comment:
// The following functions will not compile unless T has an
// implicit convertion to the integer types.
So, is trunc.hpp designed to work on matrix?
2) According to the manual, the function step
returns a real, but when I look at the prim/scal/fun/step.hpp
, it returns an int. Should I change the function to return a real?
3) For cbrt
, I know that I asked about it above, but I want to clarify what I should do about it. In the tests, should I allow the code to pass if both the expected and tested derivatives are NaN?
Listing why certain unary functions weren't vectorized: Unvectorized acosh and atanh because error handling isn't the same across all modes. Asinh looks to have similar coding problems as acosh and atanh, but it's defined for all values so I'm leaving it vectorized.
Unvectorized exp2, log2, and log1p because of an ambiguity error when making Stan model's C++ code for untemplated prim versions.
trunc and step aren't vectorized because both aren't compatible with matrices.
Other (real):real functions aren't vectorized because they're missing a mode and their prim version can't be untemplated.
Let's just get what you have working in and then create new issues for these other cases. The other four cases with solutions are as follows:
On Apr 11, 2016, at 2:50 PM, rayleigh notifications@github.com wrote:
Listing why certain unary functions weren't vectorized: Unvectorized acosh and atanh because error handling isn't the same across all modes. Asinh looks to have similar coding problems as acosh and atanh, but it's defined for all values so I'm leaving it vectorized.
Unvectorized exp2, log2, and log1p because of an ambiguity error when making Stan model's C++ code for untemplated prim versions.
trunc and step aren't vectorized because both aren't compatible with matrices.
Other (real):real functions aren't vectorized because they're missing a mode and their prim version can't be untemplated.
— You are receiving this because you were assigned. Reply to this email directly or view it on GitHub
Sounds good though I disagree about the solution to 1: 1) In the rev version of acosh.hpp, you have:
namespace { class acosh_vari : public op_v_vari { public: acosh_vari(double val, vari* avi) : op_v_vari(val, avi) { } void chain() { avi_->adj_ += adj_ / std::sqrt(avi_->val_ * avi_->val_ - 1.0); } }; }
In the rev version of digamma.hpp (which also uses code from boost/math/special_functions
), you have
namespace { class digamma_vari : public op_v_vari { public: explicit digamma_vari(vari* avi) : op_v_vari(digamma(avi->val_), avi) { } void chain() { avi_->adj_ += adj_ * trigamma(avi_->val_); } }; }
The vectorized version of digamma handles error consistently across all versions so I think the rev and fwd mode code needs to be fixed for acosh, atanh, and asinh.
Here's the actual function for acosh:
inline var acosh(const var& a) { if (boost::math::isinf(a.val()) && a > 0.0) return var(new acoshvari(a.val(), a.vi)); return var(new acoshvari(::acosh(a.val()), a.vi)); }
We could move the call to ::acosh() into acosh_vari constructor, but that wouldn't change the error handling. Or is it the conditioning on isinf that's the issue?
So I'm not sure what you're suggesting or where there is currently an inconsistency.
Thanks for pointing that out. I took another look and I think the includes might be the issue because for acosh.hpp
, the includes are:
#include <math.h>
#include <stan/math/rev/core.hpp>
#include <boost/math/special_functions/fpclassify.hpp>
#include <cmath>
#ifdef _MSC_VER
#include <boost/math/special_functions/acosh.hpp>
using boost::math::acosh;
#endif
So, unless it's being compiled on a Visual C++ compiler, I don't think it'll use acosh.hpp
from boost/math/special_functions
, which is providing the error handling. Because Stan doesn't use C++11 and acosh.hpp
is only available in C++11's cmath
library, the vectorized version of acosh.hpp
uses acosh.hpp
from boost/math/special_functions
as the base function. I think whether boost/math/special_functions/acosh.hpp
is included explains the inconsistency in error handling that I'm seeing.
That conditional include is nasty. Maybe we should just use boost::math::acosh independently of platform.
Is there ever a reason to include both
The error handling can be fixed by just adding it to the code, even if we do use Boost's definition for computing non-error inputs.
On Apr 11, 2016, at 5:40 PM, rayleigh notifications@github.com wrote:
Thanks for pointing that out. I took another look and I think the includes might be the issue because for acosh.hpp, the includes are:
include
include <stan/math/rev/core.hpp>
include <boost/math/special_functions/fpclassify.hpp>
include
ifdef _MSC_VER
include <boost/math/special_functions/acosh.hpp>
using boost::math::acosh;
endif
So, unless it's being compiled on a Visual C++ compiler, I don't think it'll use acosh.hpp from boost/math/special_functions, which is providing the error handling. Because Stan doesn't use C++11 and acosh.hpp is only available in C++11's cmath library, the vectorized version of acosh.hpp uses acosh.hpp from boost/math/special_functions as the base function. I think whether boost/math/special_functions/acosh.hpp is included explains the inconsistency in error handling that I'm seeing.
— You are receiving this because you were assigned. Reply to this email directly or view it on GitHub
@rayleigh Is the current checklist above up to date? Is there a reason the dozen or so (real): real
signature ones aren't implemented?
Closing in favor of newer issue #347 given that it's partially done.
Can we reopen this? The logical operators (at least) seem to remain un-vectorized
Binary infix operator == with functional interpretation logical_eq requires arguments of primitive type (int or real), found left type=int[ ], right arg type=int.
Thanks,
@jessexknight Probably better to start a new issue specifically or logical operations, because it's not immediately obvious how they should behave. This issue was specifically for real-valued operations and used a specific vectorization assuming real valued functions with autodiff---here there are no derivatives because we get integer values out.
I can imagine two alternatives for the logical operators:
int logical_eq(reals x, reals y);
which returns a single truth value conjoining the element wise result.
int[] logical_eq(reals x, reals y);
which returns a container of results element wise.
Both approaches can broadcast scalars to containers. If we go with (2), then we probably want functions all()
and any()
like in NumPy that return the conjunction and disjunction of a container.
This is related to the issue of comparing containers to elements to return booleans, the way that R allows. That'd give us something like this
int[] xs = { 1, 0, 2, 3, 0, -1};
int[] ys = (xs == 0); // after eval, ys = { 2, 5 }
Thanks, I've evidently added an issue...
Just want to add that I would strongly prefer (2) to allow more flexibility.
Not sure I follow the last issue you mentioned -- I'm not familiar with this behaviour in R, and personally wouldn't find this a priority vs the vectorization of the base logical functions.
Thanks for opening the issue. I edited it slightly to make it easier for our devs.
In R, you can do this:
> sex = c(0, 1, 1, 0, 0, 0, 1)
> age = c(23, 29, 30, 12, 15, 18)
> age[sex == 0]
[1] 23 12 15 18
> age[sex == 1]
[1] 29 30 NA
> age = c(23, 29, 30, 22, 25, 18, 31)
> sex = c(0, 1, 1 , 0, 0 , 0, 1)
> sex == 0
[1] TRUE FALSE FALSE TRUE TRUE TRUE FALSE
> age[sex == 0]
[1] 23 22 25 18
As you can see, it's useful for picking subgroups out of parallel sequences. But it relies on really odd behavior where if you give R a list of boolean arguments, it'll include the ones that are TRUE
in the result. This doesn't make much sense, as TRUE
evaluates to 1 and FALSE
evaluates to 0, but you get very different results if you replace the booleans with integers here.
> age[c(1, 0, 0, 1, 1, 1, 0)]
[1] 23 23 23 23
This is a very R result in that it seems to just ignore the out of range 0
inputs!
Oh, I see. I think this logical indexing is available in Numpy and Matlab too. In fact, I think logical indexing can be faster in Numpy, besides the fact that 0
is not out of bounds ;)
I suppose this raises the idea of a logical data type in Stan, but I think this type of indexing might be one of the only use cases ...
logical indexing can be faster in Numpy
It's always going to be bound by having to evaluate the condition for every element of the container. You could potentially do it without constructing the intermediate sex == 0
array by evaluating it lazily with an expression template, which would be more efficient.
I suppose this raises the idea of a logical data type in Stan
We've already committed to the C-style coding of 0 for false and everything else being true, so if we did go down the boolean route, we'd at least need the type to be promotable to int
.
As a bit of background for this:
Vectorize all functions for matching shapes and allow broadcasting of lower-dimensional types.
This will require
There is an example for the function
inv()
instan/math/prim/mat/fun/inv.hpp
in the branchfeature/issue-202-vectorize-all
.This issue involves the first step above for all of the Stan functions, so it may need to be broken down into stages, starting with unary functions.
For the stan-dev/stan issue: https://github.com/stan-dev/stan/issues/1683
For each of thee functions, we need (1) functor, (2) general template definition, (3) doc in manual, (4) signatures [need function for this], (5) signature tests for all instantiations.
When I did the example for
inv()
, I had to remove the templating forinv()
itself and replace it withdouble
to remove the ambiguity. For functions that only have a template version (i.e., there is not also a version forfwd
andrev
), I believe there will need to be anenable_if
on the base definition that restricts application to the base class.We'll also need a testing framework. This should be easy to do following the way
apply_scalar_unary
is defined (acrossprim
,rev
, andfwd
). It will require a simple templated testing functor for each function being tested.(int):int
abs
int_step
operator!
operator+
operator-
(int,int):int
max
min
operator*
operator+
operator-
operator/
operator<
operator<=
operator>
operator>=
operator==
operator&&
operator||
(int,real):real
bessel_first_kind
bessel_second_kind
modified_bessel_first_kind
modified_bessel_second_kind
(real):int
int_step
is_inf
is_nan
operator!
(real):real
abs
acos
acosh
asin
asinh
atan
atanh
cbrt
ceil
cos
cosh
digamma
erf
erfc
exp
exp2
expm1
fabs
floor
inv
inv_cloglog
inv_logit
inv_Phi
inv_sqrt
inv_square
lgamma
log
log10
log1m
log1m_exp
log1m_inv_logit
log1p
log1p_exp
log2
log_inv_logit
logit
Phi
Phi_approx
round
sin
sinh
sqrt
square
step
tan
tanh
tgamma
trigamma
trunc
(real,real):int
operator<
operator<=
operator>
operator>=
operator==
operator&&
operator||
(real,real):real
atan2
binomial_coefficient_log
falling_factorial
fdim
fmax
fmin
fmod
gamma_p
gamma_q
hypot
lbeta
log_diff_exp
log_falling_factorial
log_rising_factorial
log_sum_exp
max
min
multiply_log
operator*
operator+
operator-
operator/
operator^
owens_t
pow
rising_factorial
(int, real):real
binary_log_loss
lmgamma
(real,real,real):real
fma
log_mix
(int,real,real):real
if_else