Incorrect QuantifiedConstraints parenthesization in type classes

(Originally noticed here.)
Take the following code:
{-# LANGUAGE ConstraintKinds #-}
{-# LANGUAGE FlexibleInstances #-}
{-# LANGUAGE MultiParamTypeClasses #-}
{-# LANGUAGE QuantifiedConstraints #-}
{-# LANGUAGE UndecidableInstances #-}
module Bug where

class    (c => d) => Implies c d
instance (c => d) => Implies c d

And run haddock Bug.hs --html on it. Trying this with a Haddock built from the ghc-head branch (commit a31b562f3f3a33ae2b08f9173ea08506b357f3a5) yields this:

This is missing the required parentheses around c => d in both the class and instance declarations.

@RyanGlScott Are you already fixing this? If not, I can get a patch up shortly.
In any case, thanks for the bug report (and for always including screenshots and test cases ❤)!

Well, my first inclination was to see how GHC is handling this, because clearly GHC must do this correctly, right? Sadly, the reality much harsher than I expected:
λ> ; $([d| class (c => d) => Implies c d; instance (c => d) => Implies c d |])
<interactive>:8:5-74: Splicing declarations
    [d| class (c_a4GK => d_a4GL) => Implies_a4GJ c_a4GK d_a4GL

        instance (c_a4GM => d_a4GN) => Implies_a4GJ c_a4GM d_a4GN |]
  ======>
    class c_a4HC => d_a4HD => Implies_a4HB c_a4HC d_a4HD
    instance c_a4HE => d_a4HF => Implies_a4HB c_a4HE d_a4HF

Yikes! The bottom part of the -ddump-splices output is also incorrect. So it appears that there may be something afoot in GHC as well. (I'm as of yet unclear if this buglet is related to the Haddock one observed above.)
I'll try to diagnose this issue first.

Your ddump-splices bug is separate and GHC's fault. The Haddock output is Haddock's fault. The reason for matching bugs is that Haddock ported the precedence logic for pretty-printing from GHC, so I'm not surprised GHC has this issue too. 😄

Yes, upon further thought, I believe that bug is entirely unrelated to what's going on in GHC, which appears to be a Convert-specific (i.e., Template Haskell–specific) issue.
As for what the culprit in Haddock might be, I have a hunch. Here is the function which parenthesizes contexts in the HTML backend:
https://github.com/haskell/haddock/blob/a31b562f3f3a33ae2b08f9173ea08506b357f3a5/haddock-api/src/Haddock/Backends/Xhtml/Decl.hs#L476-L479
In particular, single-predicate contexts go through this auxiliary ppCtxType function:
https://github.com/haskell/haddock/blob/a31b562f3f3a33ae2b08f9173ea08506b357f3a5/haddock-api/src/Haddock/Backends/Xhtml/Decl.hs#L1109-L1110
That, in turn, invokes reparenTypePrec PREC_CTX. What is the reparenTypePrec case for HsQualTy? As it turns out, it's this:
https://github.com/haskell/haddock/blob/a31b562f3f3a33ae2b08f9173ea08506b357f3a5/haddock-api/src/Haddock/GhcUtils.hs#L279-L280
It's guarded by paren p PREC_FUN, which means that it will only be parenthesized if the supplied Precedence is at least as great as PREC_FUN. But the definition of Precendence shows that PREC_CTX is less than PREC_FUN, according to its derived Ord instance:
https://github.com/haskell/haddock/blob/a31b562f3f3a33ae2b08f9173ea08506b357f3a5/haddock-api/src/Haddock/GhcUtils.hs#L240-L253

What to do? We could just merge PREC_CTX and PREC_FUN, as I'm unclear on what utility it brings to make a distinction between the two. Disclaimer: I haven't tested this change, so I don't know yet if this would cause any other adverse changes.

Yep, you found the right place. Perhaps we need another precedence level? I have no time right now, but I'll look again tomorrow morning at this.

FWIW, if I remove the PREC_CXT constructor and simply replace all occurrences of it with PREC_FUN then the test suite passes save for two tests:
Diff for file "TypeOperators.html":
144c144
<           > :: (a ~ b) => a -> b            > :: a ~ b => a -> b <a href="#" class="selflink"
160c160
<           > :: ((a            > :: (a <a href="#" title="TypeOperators"
166c166
<           > a)) => a            > a) => a <a href="#" class="selflink"
Diff for file "FunArgs.html":
221c221
<                 > (b :: ()). (d ~ '                 > (b :: ()). d ~ '<a href="#" title="GHC.Tuple"
223c223
<                 >)                 > Blah to be rendered as a ~ b => Blah instead. Both are valid GHC, although I don't know if you'd prefer to keep the parentheses in this situation.

I have no personal preference for (a ~ b) => Blah or a ~ b => Blah, but it would be nice to have a good reason to change the current behaviour if we are going to do so. I picked the current behaviour based on what GHC does:
λ> ; $([d| a :: (Int ~ b) => b -> Int; a = id |])
<interactive>:18:5-45: Splicing declarations
    [d| a_a6ay :: (Int ~ b_a6az) => b_a6az -> Int
        a_a6ay = id |]
  ======>
    a_a6bf :: Int ~ b_a6be => b_a6be -> Int
    a_a6bf = id

When trying out these sorts of changes, you may want to rebuild boot lib docs and diff -rq the new and old docs, just to make sure nothing big has been broken. The testsuite is great for preventing regressions, but unfortunately still has pretty poor coverage.
I haven't checked, but I suspect the changes you propose might have some pretty large effects.

I don't have a personal preference either. In fact, #1064 looks much less invasive than what I was proposing, so I'd be perfectly content with that.

Fixed in 384577e862171bdedc9311c9d17f7ad3a4a33456.


Upgrade moment javascript package

Fixes https://github.com/jupyter/nbclassic/issues/183

Thx @RRosio

Hello - thank you for maintaining this repo @echarles and @RRosio.
Would it be possible to get a patch release containing this commit?  The CVE is impacting some users and their ability to comfortably use nbclassic.

Awesome Eric - thank you!

+1 for a new release, thank you!

nbclassic 0.5.1 is released


Catch accidental use of concrete type in abstract type signature

This should not be allowed:
from metagraph import abstract_algorithm, PluginRegistry
from metagraph.plugins.core.types import Vector
from metagraph.plugins.numpy.types import NumpyVectorType

@abstract_algorithm('testing.scale')
def testing_scale(a: Vector, scale: float)->NumpyVectorType:  # oops, bad return type
    pass

registry = PluginRegistry('test_registry')
registry.register(testing_scale)  # this should raise an error

Actually, I think it might make more sense for the error to be raised when passing the registry to a Resolver.  The PluginRegistry right now does not do any validation (and the Resolver does), and I would rather not split validation into two places.

https://github.com/metagraph-dev/metagraph/pull/176 addresses this issue.


CLI uses underscore and not dash (vscode_cli_darwin_x64_cli)

All our other assets use dashes, such as vscode-server-darwin-x64

Our other assets do use underscores as well in the CI pipeline -- are you looking somewhere different?

@connor4312 yeah I am looking here: https://builds.code.visualstudio.com/builds/insider

All the builds there are using dashes 🤔

Ok then feel free to close, not sure what I was seeing. I think I reported this when I sanity tested during endgame.


CAD-370 cleanly setup & shutdown logging

clean shutdown of logging feature in cardano-cli
filter out message from #messagescounters

bors r+


Add loading sign when application gets loaded

Issue Template
Description
Add a loading indicator that displays while the application is loading, providing users with visual feedback until the content is fully rendered.This enhances user experience by clearly signaling that content is being fetched, reducing uncertainty during load times.
It is done to enhance the UI and will look good.
Steps to Reproduce
Please provide step-by-step instructions on how to reproduce the issue:

Go to site'
See loading.

Expected Behavior
When the application is opened, a loading indicator (e.g., spinner or progress bar) should appear immediately, signaling that the app is processing or fetching data. The loading indicator should remain visible until all essential content is fully loaded and ready for user interaction, at which point it should disappear smoothly, allowing the user to engage with the application seamlessly.
Actual Behavior
When the application is opened, a loading indicator which will enhance the UI

@yashmandi kindly assign this issue to me. Would be really great of you.
Thank you

thanks for raising the issue, but there's already a loading animation when the page loads ;)


infinite loop (freeze) when setState is called

🐛 Bug Report
This is really weird and I'm not sure if it's a bug or just wrong example but I think it should work because await should be resolved in the next tick but it doesn't seem to be.
To Reproduce
Steps to reproduce the behavior:

useSpring() with infinite promise generating new spring state (just like the one from examples)
add extra useState()
call that setState during onClick

Expected behavior
I think it should not cause infinite loop (I'd understand if it kept spinning but it freezes other
Link to repro (highly encouraged)
https://codesandbox.io/s/practical-mountain-ps9sc

Additional context
I've tried this outside of code-sandbox and for some reason, no other event loop callback gets called (it will freeze the window), it's almost like if some V8 optimization kicked in and suddenly turned async iteration into a sync one. But it happens in Firefox too so I'm really not sure what's going on here.
You can test this easily with setInterval(() => console.log('tick'), 1000) but you need to do it locally, without codesandbox checks.
Environment

react-spring v8.x.x
react v16.8.x

Seems like a duplicate of #591
Please try with v9:
npm install react-spring@next

works, thx


chore: ci reorganize dag

Right we essentially compile four or five times (build+2 bindings+unit-tests+clippy). and they can't usefully share artifacts, but we insert a dependency between the build step and everything else so that if compile breaks we don't run anything else. A lot of things (including, I believe, the unit-tests) depend on the glaredb binary, so that makes sense but the bindings can build in parallel with the main cli binary.
The challenge/impediment, now, is the unit-test->glaredb dependency (integration tests in the glaredb crate). If that can be built and run separately, we can run it with the pytests or a new task and wall clock times would be in the 5-7 minute range for the entire pipeline.
The big downside is that if you push a broken compile that doesn't also break the formater (so many typos and syntax issues will still be caught,) then it has to fail four times, but this is classically a good trade in terms of increasing developer responsiveness. The other downside, is the first build after a Cargo.lock change (so no cache hits) will take more build time.

The last build in this branch exhibits some more worst-case behavior: the main build takes closer to 5 minutes (cache is less relevant because other branches are building concurrently.)
Seeing these results makes me inclined to do per-branch caches, but need to experiment in practice.


User should be able to change the order of team members in Team module

User should be able to change the order of team members in Team module

Working on it.

Fixed.


Add Autotel.co site to ring

added my portfolio website, which I just tested to make sure that complies with what's required
link is at the bottom of index page.

I'm having a really hard time loading your website with our crappy internet connection, I'll have another look when we sail closer to the cell towers. How large is the index page just out of curiosity?

12 mb :)

The design is too hard to use and the website is too slow to be a good candidate for the webring at this time, sorry.


Learn more link broken

in the connect screen, the learn more link is broken:
1- hard to click, needs to hover on top part of text
2- when you click, it redirects you to home page.

Hey @LuizAsFight
I have raised a PR addressing the issue you mentioned. Kindly review the PR. As I am a first-time contributor to this repo, please let me know if I have done everything correctly. I will make the required changes if necessary.


Add NVRTC Runner

Closes: #7

Locally I get this error:
[mborland@DESKTOP-F265CLN build]$ cmake --build . --target tests -j $(nproc) --clean-first
[ 33%] Building CXX object libs/random/CMakeFiles/boost_random.dir/src/random_device.cpp.o
[  0%] Building CXX object libs/container/CMakeFiles/boost_container.dir/src/dlmalloc.cpp.o
[ 33%] Building C object libs/container/CMakeFiles/boost_container.dir/src/alloc_lib.c.o
[ 33%] Building CXX object libs/container/CMakeFiles/boost_container.dir/src/monotonic_buffer_resource.cpp.o
[ 66%] Building CXX object libs/container/CMakeFiles/boost_container.dir/src/synchronized_pool_resource.cpp.o
[ 66%] Building CXX object libs/container/CMakeFiles/boost_container.dir/src/pool_resource.cpp.o
[ 66%] Building CXX object libs/container/CMakeFiles/boost_container.dir/src/global_resource.cpp.o
[ 66%] Building CXX object libs/container/CMakeFiles/boost_container.dir/src/unsynchronized_pool_resource.cpp.o
[ 66%] Linking CXX static library ../../stage/lib/libboost_container.a
[ 66%] Built target boost_container
[ 66%] Linking CXX static library ../../stage/lib/libboost_random.a
[ 66%] Built target boost_random
[100%] Building CXX object libs/cuda-math/test/CMakeFiles/boost_cuda_math-test_beta_nvrtc.dir/test_beta_nvrtc.cpp.o
[100%] Linking CXX executable ../../../stage/bin/boost_cuda_math-test_beta_nvrtc
[100%] Built target boost_cuda_math-test_beta_nvrtc
[100%] Built target tests
[mborland@DESKTOP-F265CLN build]$ ctest --output-on-failure --no-tests=error
Test project /home/mborland/Documents/boost/build
    Start 1: run-boost_cuda_math-test_beta_nvrtc
1/1 Test #1: run-boost_cuda_math-test_beta_nvrtc ...***Failed    0.02 sec
Compilation failed:
/usr/include/c++/11/vector(58): warning #161-D: unrecognized #pragma
  #pragma GCC system_header
          ^

Remark: The warnings can be suppressed with "-diag-suppress <warning-number>"

/usr/include/c++/11/x86_64-redhat-linux/bits/c++config.h(284): error: identifier "__SIZE_TYPE__" is undefined
    typedef __SIZE_TYPE__ 	size_t;
            ^

/usr/include/c++/11/x86_64-redhat-linux/bits/c++config.h(285): error: identifier "__PTRDIFF_TYPE__" is undefined
    typedef __PTRDIFF_TYPE__	ptrdiff_t;
            ^

/usr/include/c++/11/bits/functexcept.h(48): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
    __throw_bad_exception(void) __attribute__((__noreturn__));
    ^

/usr/include/c++/11/bits/functexcept.h(52): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
    __throw_bad_alloc(void) __attribute__((__noreturn__));
    ^

/usr/include/c++/11/bits/functexcept.h(55): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
    __throw_bad_array_new_length(void) __attribute__((__noreturn__));
    ^

/usr/include/c++/11/bits/functexcept.h(59): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
    __throw_bad_cast(void) __attribute__((__noreturn__));
    ^

/usr/include/c++/11/bits/functexcept.h(62): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
    __throw_bad_typeid(void) __attribute__((__noreturn__));
    ^

/usr/include/c++/11/bits/functexcept.h(66): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
    __throw_logic_error(const char*) __attribute__((__noreturn__));
    ^

/usr/include/c++/11/bits/functexcept.h(69): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
    __throw_domain_error(const char*) __attribute__((__noreturn__));
    ^

/usr/include/c++/11/bits/functexcept.h(72): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
    __throw_invalid_argument(const char*) __attribute__((__noreturn__));
    ^

/usr/include/c++/11/bits/functexcept.h(75): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
    __throw_length_error(const char*) __attribute__((__noreturn__));
    ^

/usr/include/c++/11/bits/functexcept.h(78): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
    __throw_out_of_range(const char*) __attribute__((__noreturn__));
    ^

/usr/include/c++/11/bits/functexcept.h(81): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
    __throw_out_of_range_fmt(const char*, ...) __attribute__((__noreturn__))
    ^

/usr/include/c++/11/bits/functexcept.h(85): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
    __throw_runtime_error(const char*) __attribute__((__noreturn__));
    ^

/usr/include/c++/11/bits/functexcept.h(88): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
    __throw_range_error(const char*) __attribute__((__noreturn__));
    ^

/usr/include/c++/11/bits/functexcept.h(91): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
    __throw_overflow_error(const char*) __attribute__((__noreturn__));
    ^

/usr/include/c++/11/bits/functexcept.h(94): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
    __throw_underflow_error(const char*) __attribute__((__noreturn__));
    ^

/usr/include/c++/11/bits/functexcept.h(98): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
    __throw_ios_failure(const char*) __attribute__((__noreturn__));
    ^

/usr/include/c++/11/bits/functexcept.h(101): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
    __throw_ios_failure(const char*, int) __attribute__((__noreturn__));
    ^

/usr/include/c++/11/bits/functexcept.h(105): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
    __throw_system_error(int) __attribute__((__noreturn__));
    ^

/usr/include/c++/11/bits/functexcept.h(109): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
    __throw_future_error(int) __attribute__((__noreturn__));
    ^

/usr/include/c++/11/bits/functexcept.h(113): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
    __throw_bad_function_call() __attribute__((__noreturn__));
    ^

/usr/include/c++/11/bits/cpp_type_traits.h(35): warning #161-D: unrecognized #pragma
  #pragma GCC system_header
          ^

/usr/include/c++/11/bits/cpp_type_traits.h(560): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
      __miter_base(_Iterator __it)
      ^

/usr/include/c++/11/ext/type_traits.h(32): warning #161-D: unrecognized #pragma
  #pragma GCC system_header
          ^

/usr/include/c++/11/ext/type_traits.h(152): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
      __is_null_pointer(_Type* __ptr)
      ^

/usr/include/c++/11/ext/type_traits.h(157): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
      __is_null_pointer(_Type)
      ^

/usr/include/c++/11/ext/type_traits.h(162): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
    __is_null_pointer(std::nullptr_t)
    ^

/usr/include/c++/11/ext/type_traits.h(201): error: expected a ")"
        typedef __typeof__(_Tp2() + _Up2()) __type;
                                  ^

/usr/include/c++/11/ext/type_traits.h(201): error: explicit type is missing ("int" assumed)
        typedef __typeof__(_Tp2() + _Up2()) __type;
                ^

/usr/include/c++/11/ext/type_traits.h(201): error: expected a ";"
        typedef __typeof__(_Tp2() + _Up2()) __type;
                                            ^

/usr/include/c++/11/ext/type_traits.h(210): error: expected a ")"
        typedef __typeof__(_Tp2() + _Up2() + _Vp2()) __type;
                                  ^

/usr/include/c++/11/ext/type_traits.h(210): error: explicit type is missing ("int" assumed)
        typedef __typeof__(_Tp2() + _Up2() + _Vp2()) __type;
                ^

/usr/include/c++/11/ext/type_traits.h(210): error: expected a ";"
        typedef __typeof__(_Tp2() + _Up2() + _Vp2()) __type;
                                                     ^

/usr/include/c++/11/ext/type_traits.h(220): error: expected a ")"
        typedef __typeof__(_Tp2() + _Up2() + _Vp2() + _Wp2()) __type;
                                  ^

/usr/include/c++/11/ext/type_traits.h(220): error: explicit type is missing ("int" assumed)
        typedef __typeof__(_Tp2() + _Up2() + _Vp2() + _Wp2()) __type;
                ^

/usr/include/c++/11/ext/type_traits.h(220): error: expected a ";"
        typedef __typeof__(_Tp2() + _Up2() + _Vp2() + _Wp2()) __type;
                                                              ^

/usr/include/c++/11/ext/numeric_traits.h(32): warning #161-D: unrecognized #pragma
  #pragma GCC system_header
          ^

/usr/include/c++/11/ext/numeric_traits.h(57): error: identifier "__CHAR_BIT__" is undefined
        enum { __width = __value ? sizeof(_Tp) * __CHAR_BIT__ : 0 };
                                                 ^

/usr/include/c++/11/ext/numeric_traits.h(159): error: identifier "__FLT_MANT_DIG__" is undefined
        static const int __max_digits10 = __glibcxx_max_digits10(_Value);
                                          ^

/usr/include/c++/11/ext/numeric_traits.h(163): error: identifier "__FLT_DIG__" is undefined
        static const int __digits10 = __glibcxx_digits10(_Value);
                                      ^

/usr/include/c++/11/ext/numeric_traits.h(164): error: identifier "__FLT_MAX_10_EXP__" is undefined
        static const int __max_exponent10 = __glibcxx_max_exponent10(_Value);
                                            ^

/usr/include/c++/11/bits/move.h(49): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
      __addressof(_Tp& __r) _GLIBCXX_NOEXCEPT
      ^

/usr/include/c++/11/type_traits(32): warning #161-D: unrecognized #pragma
  #pragma GCC system_header
          ^

/usr/include/c++/11/type_traits(70): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
        constexpr operator value_type() const noexcept { return value; }
                  ^

/usr/include/c++/11/type_traits(75): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
        constexpr value_type operator()() const noexcept { return value; }
                             ^

/usr/include/c++/11/type_traits(228): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
      constexpr true_type __is_complete_or_unbounded(__type_identity<_Tp>)
                          ^

/usr/include/c++/11/type_traits(238): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
      >::type __is_complete_or_unbounded(_TypeIdentity)
              ^

/usr/include/c++/11/type_traits(431): error: template parameter "_Tp" is not used in or cannot be deduced from the template argument list of class template "std::is_array<<error-type>>"
    template<typename _Tp, std::size_t _Size>
                      ^

/usr/include/c++/11/type_traits(431): error: constant "_Size" is not used in or cannot be deduced from the template argument list of class template "std::is_array<<error-type>>"
    template<typename _Tp, std::size_t _Size>
                                       ^

/usr/include/c++/11/type_traits(808): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
      __declval(int);
      ^

/usr/include/c++/11/type_traits(812): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
      __declval(long);
      ^

/usr/include/c++/11/type_traits(816): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
      auto declval() noexcept -> decltype(__declval<_Tp>(0));
           ^

/usr/include/c++/11/type_traits(845): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
        static true_type __test(int);
                         ^

/usr/include/c++/11/type_traits(848): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
        static false_type __test(...);
                          ^

/usr/include/c++/11/type_traits(899): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
        __test(int);
        ^

/usr/include/c++/11/type_traits(902): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
        static false_type __test(...);
                          ^

/usr/include/c++/11/type_traits(1211): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
      static void __helper(const _Tp&);
                  ^

/usr/include/c++/11/type_traits(1214): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
      static true_type __test(const _Tp&,
                       ^

/usr/include/c++/11/type_traits(1217): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
      static false_type __test(...);
                        ^

/usr/include/c++/11/type_traits(1372): error: template parameter "_Tp" is not used in or cannot be deduced from the template argument list of class template "std::rank<<error-type>>"
    template<typename _Tp, std::size_t _Size>
                      ^

/usr/include/c++/11/type_traits(1372): error: constant "_Size" is not used in or cannot be deduced from the template argument list of class template "std::rank<<error-type>>"
    template<typename _Tp, std::size_t _Size>
                                       ^

/usr/include/c++/11/type_traits(1385): error: template parameter "_Tp" is not used in or cannot be deduced from the template argument list of class template "std::extent<<error-type>, _Uint>"
    template<typename _Tp, unsigned _Uint, std::size_t _Size>
                      ^

/usr/include/c++/11/type_traits(1385): error: constant "_Size" is not used in or cannot be deduced from the template argument list of class template "std::extent<<error-type>, _Uint>"
    template<typename _Tp, unsigned _Uint, std::size_t _Size>
                                                       ^

/usr/include/c++/11/type_traits(1433): warning #161-D: unrecognized #pragma
  #pragma GCC diagnostic push
          ^

/usr/include/c++/11/type_traits(1434): warning #161-D: unrecognized #pragma
  #pragma GCC diagnostic ignored "-Wctor-dtor-privacy"
          ^

/usr/include/c++/11/type_traits(1439): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
  	static void __test_aux(_To1) noexcept;
  	            ^

/usr/include/c++/11/type_traits(1444): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
  	__test(int);
  	^

/usr/include/c++/11/type_traits(1448): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
  	__test(...);
  	^

/usr/include/c++/11/type_traits(1453): warning #161-D: unrecognized #pragma
  #pragma GCC diagnostic pop
          ^

/usr/include/c++/11/type_traits(1473): warning #161-D: unrecognized #pragma
  #pragma GCC diagnostic push
          ^

/usr/include/c++/11/type_traits(1474): warning #161-D: unrecognized #pragma
  #pragma GCC diagnostic ignored "-Wctor-dtor-privacy"
          ^

/usr/include/c++/11/type_traits(1479): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
  	static void __test_aux(_To1) noexcept;
  	            ^

/usr/include/c++/11/type_traits(1484): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
  	__test(int);
  	^

/usr/include/c++/11/type_traits(1488): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
  	__test(...);
  	^

/usr/include/c++/11/type_traits(1493): warning #161-D: unrecognized #pragma
  #pragma GCC diagnostic pop
          ^

/usr/include/c++/11/type_traits(1764): error: constant "_Sz" is not used in or cannot be deduced from the template argument list of class template "std::__make_unsigned_selector_base::__select<<error-constant>, std::__make_unsigned_selector_base::_List<_Uint, _UInts...>, true>"
      template<size_t _Sz, typename _Uint, typename... _UInts>
                      ^

/usr/include/c++/11/type_traits(1768): error: constant "_Sz" is not used in or cannot be deduced from the template argument list of class template "std::__make_unsigned_selector_base::__select<<error-constant>, std::__make_unsigned_selector_base::_List<_Uint, _UInts...>, false>"
      template<size_t _Sz, typename _Uint, typename... _UInts>
                      ^

/usr/include/c++/11/type_traits(1783): error: incomplete type "std::__make_unsigned_selector_base::__select<<error-constant>, std::__make_unsigned_selector<char16_t, false, true>::_UInts, <error-constant>>" (aka "std::__make_unsigned_selector_base::__select<<error-constant>, std::__make_unsigned_selector_base::_List<unsigned char, unsigned short, unsigned int, unsigned long, unsigned long long>, <error-constant>>") is not allowed
        using __unsigned_type = typename __select<sizeof(_Tp), _UInts>::__type;
                                         ^
          detected during instantiation of class "std::__make_unsigned_selector<_Tp, false, true> [with _Tp=char16_t]" at line 1816

/usr/include/c++/11/type_traits(1682): error: incomplete type "std::__cv_selector<std::__make_unsigned_selector<char16_t, false, true>::__unsigned_type, false, false>" is not allowed
        typedef typename __match::__type __type;
                         ^
          detected during:
            instantiation of class "std::__match_cv_qualifiers<_Qualified, _Unqualified, _IsConst, _IsVol> [with _Qualified=char16_t, _Unqualified=<error-type>, _IsConst=false, _IsVol=false]" at line 1787
            instantiation of class "std::__make_unsigned_selector<_Tp, false, true> [with _Tp=char16_t]" at line 1816

/usr/include/c++/11/type_traits(1783): error: incomplete type "std::__make_unsigned_selector_base::__select<<error-constant>, std::__make_unsigned_selector<char16_t, false, true>::_UInts, <error-constant>>" (aka "std::__make_unsigned_selector_base::__select<<error-constant>, std::__make_unsigned_selector_base::_List<unsigned char, unsigned short, unsigned int, unsigned long, unsigned long long>, <error-constant>>") is not allowed
        using __unsigned_type = typename __select<sizeof(_Tp), _UInts>::__type;
                                         ^
          detected during instantiation of class "std::__make_unsigned_selector<_Tp, false, true> [with _Tp=char32_t]" at line 1823

/usr/include/c++/11/type_traits(1682): error: incomplete type "std::__cv_selector<std::__make_unsigned_selector<char16_t, false, true>::__unsigned_type, false, false>" is not allowed
        typedef typename __match::__type __type;
                         ^
          detected during:
            instantiation of class "std::__match_cv_qualifiers<_Qualified, _Unqualified, _IsConst, _IsVol> [with _Qualified=char32_t, _Unqualified=<error-type>, _IsConst=false, _IsVol=false]" at line 1787
            instantiation of class "std::__make_unsigned_selector<_Tp, false, true> [with _Tp=char32_t]" at line 1823

/usr/include/c++/11/type_traits(1915): error: incomplete type "std::__make_signed_selector<std::__make_signed_selector<char16_t, false, true>::__unsigned_type, false, <error-constant>>" is not allowed
        typedef typename __make_signed_selector<__unsigned_type>::__type __type;
                         ^
          detected during instantiation of class "std::__make_signed_selector<_Tp, false, true> [with _Tp=char16_t]" at line 1944

/usr/include/c++/11/type_traits(1915): error: incomplete type "std::__make_signed_selector<std::__make_signed_selector<char16_t, false, true>::__unsigned_type, false, <error-constant>>" is not allowed
        typedef typename __make_signed_selector<__unsigned_type>::__type __type;
                         ^
          detected during instantiation of class "std::__make_signed_selector<_Tp, false, true> [with _Tp=char32_t]" at line 1951

/usr/include/c++/11/type_traits(1984): error: template parameter "_Tp" is not used in or cannot be deduced from the template argument list of class template "std::remove_extent<<error-type>>"
    template<typename _Tp, std::size_t _Size>
                      ^

/usr/include/c++/11/type_traits(1984): error: constant "_Size" is not used in or cannot be deduced from the template argument list of class template "std::remove_extent<<error-type>>"
    template<typename _Tp, std::size_t _Size>
                                       ^

/usr/include/c++/11/type_traits(1997): error: template parameter "_Tp" is not used in or cannot be deduced from the template argument list of class template "std::remove_all_extents<<error-type>>"
    template<typename _Tp, std::size_t _Size>
                      ^

/usr/include/c++/11/type_traits(1997): error: constant "_Size" is not used in or cannot be deduced from the template argument list of class template "std::remove_all_extents<<error-type>>"
    template<typename _Tp, std::size_t _Size>
                                       ^

/usr/include/c++/11/type_traits(2132): error: template argument list must match the parameter list
      const size_t aligned_union<_Len, _Types...>::alignment_value;
                   ^

/usr/include/c++/11/type_traits(2245): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
        _S_test(int);
        ^

/usr/include/c++/11/type_traits(2257): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
        _S_test_2(...);
        ^

/usr/include/c++/11/type_traits(2261): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
        _S_test(...);
        ^

/usr/include/c++/11/type_traits(2358): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
      auto declval() noexcept -> decltype(__declval<_Tp>(0))
           ^

/usr/include/c++/11/type_traits(2391): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
        ), __invoke_memfun_ref> _S_test(int);
                                ^

/usr/include/c++/11/type_traits(2394): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
        static __failure_type _S_test(...);
                              ^

/usr/include/c++/11/type_traits(2410): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
        ), __invoke_memfun_deref> _S_test(int);
                                  ^

/usr/include/c++/11/type_traits(2413): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
        static __failure_type _S_test(...);
                              ^

/usr/include/c++/11/type_traits(2429): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
        ), __invoke_memobj_ref> _S_test(int);
                                ^

/usr/include/c++/11/type_traits(2432): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
        static __failure_type _S_test(...);
                              ^

/usr/include/c++/11/type_traits(2448): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
        ), __invoke_memobj_deref> _S_test(int);
                                  ^

/usr/include/c++/11/type_traits(2451): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
        static __failure_type _S_test(...);
                              ^

/usr/include/c++/11/type_traits(2531): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
        ), __invoke_other> _S_test(int);
                           ^

/usr/include/c++/11/type_traits(2534): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
        static __failure_type _S_test(...);
                              ^

/usr/include/c++/11/type_traits(2676): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
      swap(_Tp&, _Tp&)
      ^

/usr/include/c++/11/type_traits(2684): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
      swap(_Tp (&__a)[_Nm], _Tp (&__b)[_Nm])
      ^

/usr/include/c++/11/type_traits(2695): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
          static true_type __test(int);
                           ^

/usr/include/c++/11/type_traits(2698): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
          static false_type __test(...);
                            ^

/usr/include/c++/11/type_traits(2706): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
          > __test(int);
            ^

/usr/include/c++/11/type_traits(2709): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
          static false_type __test(...);
                            ^

/usr/include/c++/11/type_traits(2783): error: A function without execution space annotations (__host__/__device__/__global__) is considered a host function, and host functions are not allowed in JIT mode. Consider using -default-device flag to process unannotated functions as __device__ functions in JIT mode
          static true_type __test(int);
                           ^

Error limit reached.
100 errors detected in the compilation of "test_beta_kernel.cu".
Compilation terminated.

0% tests passed, 1 tests failed out of 1

Total Test time (real) =   0.02 sec

The following tests FAILED:
	  1 - run-boost_cuda_math-test_beta_nvrtc (Failed)
Errors while running CTest
[mborland@DESKTOP-F265CLN build]$

It looks like cupy does not use any of the STL so this path may be a non-starter


Initial Logic and System Architecture: Create tiles backend structure (service, entity, repository)

New PR of the backend for tiles, as I rebased it for master. Apologies for the confusions.

Will look at it today👍

Thanks to the previous great reviews. @paul891112 @Twhining @Croxsy

Love it! Looks good to me. Thanks!

Thanks for the positive notes, really boosts my moral 🥺❤


Added comments are not displayed in Dev Portal overview page

Added comments are not displayed in overview page:

This issue is fixed with https://github.com/wso2/carbon-apimgt/pull/7490


Add a new template for the file editing page.

We previously were serving the file editing page using the
built-in Jupyter UI. That meant that it looked wildly different
from the rest of Datalab, and was missing the Datalab-specific
UI elements like the sign-in and feedback buttons.
This version of the editor page is functional, but not yet
feature complete. The remaining missing features will be added
in later commits.

A few observations. Thanks!

LGTM!


Main Thread Crash

When i use self.stopAnimating(), i got "This application is modifying the autolayout engine from a background thread after the engine was accessed from the main thread. This can lead to engine corruption and weird crashes." crash. And xcode shows 3 main thread issue on NVActivityIndicatorPresenter.swift line 258, 260 and 262. Is anyone got this crash?

@berkerbilgi: Are you calling stopAnimating() on the main thread?

Close this, reopen if need be.


Function to define the current limit of a EVSE

Is there any function in the C API of this library that allows to change the current limit of the EVSE? I understood that "ocpp_setSmartChargingCurrentOutput" uses a function to tell when the limit has changed by the car, but what about the limit of the EVSE itself?

In the standard Smart Charging scenario, the OCPP server sends charging limits to the EVSE which MicroOcpp forwards to your application via the ocpp_setSmartChargingCurrentOutput callback function.
The EVSE can report back the actual charging limit (resulting from local load balancing restrictions, cable capacity, ect.) over MeterValues with the Measurand Current.Offered. To add a new measurand, use
https://github.com/matth-x/MicroOcpp/blob/c0732dccacd13a7b2a091272b0eaf92be26a5c30/src/MicroOcpp_c.h#L137
For example:
float my_charging_limit() {
    return 16.f; // TODO replace with the actual charging limit of the EVSE
}

// register callback (somewhere in the setup function):
ocpp_addMeterValueInputFloat(my_charging_limit, "Current.Offered", "A", NULL, NULL);

I understood this callback, but what i am trying to do is set the maximum current that the evse can supply the vehicle with. In the Schneider evlink park EVSE, this setting can be changed through ocpp, as shown in the picture (Page 32 of the evlink comissioning guide).

From: Matthias Akstaller @.>
Sent: Saturday, May 18, 2024 3:23:26 PM
To: matth-x/MicroOcpp @.>
Cc: p-r-m-n @.>; Author @.>
Subject: Re: [matth-x/MicroOcpp] Function to define the current limit of a EVSE (Issue #300)
In the standard Smart Charging scenario, the OCPP server sends charging limits to the EVSE which MicroOcpp forwards to your application via the ocpp_setSmartChargingCurrentOutput callback function.
The EVSE can report back the actual charging limit (resulting from local load balancing restrictions, cable capacity, ect.) over MeterValues with the Measurand Current.Offered. To add a new measurand, use
https://github.com/matth-x/MicroOcpp/blob/c0732dccacd13a7b2a091272b0eaf92be26a5c30/src/MicroOcpp_c.h#L137
For example:
float my_charging_limit() {
return 16.f; // TODO replace with the actual charging limit of the EVSE
}
// register callback (somewhere in the setup function):
ocpp_addMeterValueInputFloat(my_charging_limit, "Current.Offered", "A", NULL, NULL);
—
Reply to this email directly, view it on GitHubhttps://github.com/matth-x/MicroOcpp/issues/300#issuecomment-2118909948, or unsubscribehttps://github.com/notifications/unsubscribe-auth/AV6JPUWPWEJNWRGDZGYGOZDZC6MB5AVCNFSM6AAAAABH4GQK2CVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDCMJYHEYDSOJUHA.
You are receiving this because you authored the thread.Message ID: @.***>

I see. It's possible to register custom Configurations as described here: https://github.com/matth-x/MicroOcpp/issues/248#issuecomment-1883585103 The approach works the same for accessing built-in Configs as for declaring new, custom Configs.
Having a Config for the maximum current, you can read its value in the firmware integration and make sure that your charger never exceeds that level manually.

I see. It's possible to register custom Configurations as described here: #248 (comment) The approach works the same for accessing built-in Configs as for declaring new, custom Configs.
Having a Config for the maximum current, you can read its value in the firmware integration and make sure that your charger never exceeds that level manually.

thanks, i will try and post the results here.

I tried to connect a esp to a EVSE but apparently i had it wrong, this library should connect to a ocpp server as the EVSE does, not the other way. There are any functions in this library to implement a ocpp server on the esp32?

No, it's not supported at the moment. I did build a proof of concept for this once, but didn't go any further that direction.

thanks for the support!

No, it's not supported at the moment. I did build a proof of concept for this once, but didn't go any further that direction.


🦑 Cache RPMs with squid

Various osbuild-composer tests require downloads from various dnf
mirrors and these can take time on slow network links. Also, it puts
undue strain on mirrors when we run a lot of tests.
Use a small squid proxy on the CI machine to cache these packages, speed
up image tests, reduce mirror strain, and potentially save a little
money in some clouds.
Signed-off-by: Major Hayden<EMAIL_ADDRESS>

Sounds good! @dvdhrm is working on a long-term solution to this, but for the time being a proxy sounds like it would help a lot.


Question : Problem with OSGP Platform set up

Question:
Stuck while setting up OSGP Platform. Need help.
background:
Hi,
I am new to OSGP. I have done the installation with vagrant and virtual box. There were no errors in "vagrant up". While setting up the platform as per https://documentation.opensmartgridplatform.org/Userguide/Installation/setupOSGP.html, I am getting 2 errors listed below with SmartMeteringMonitoring.wsdl file in Eclipse. Looks like the build is incomplete due to this. When I right click on the Tomcat server and select 'Add and Remove',  I get an error message: "There are no resources that can be added or removed from the server". BTW, I am also getting 468 warnings and 1 info. Not sure if this is normal. Please help me in getting OSGP up and running.
The part 'GetPowerQualityProfileRequest' has an invalid value 'GetPowerQualityProfileRequest' defined for its element. Element declarations must refer to valid values defined in a schema.	SmartMeteringMonitoring.wsdl	/osgp-ws-smartmetering/src/main/resources	line 157	WSDL Problem
The part 'GetPowerQualityProfileResponse' has an invalid value 'GetPowerQualityProfileResponse' defined for its element. Element declarations must refer to valid values defined in a schema.	SmartMeteringMonitoring.wsdl	/osgp-ws-smartmetering/src/main/resources	line 163	WSDL Problem
Thanks,
Rama
**

Update: Looks like the 2 WSDL errors are not related to Tomcat server "Add and Remove" issue I reported earlier. I pulled release-5.1.0 branch (thinking it would be more stable than developer branch) and followed the same steps of setting up the platform as per https://documentation.opensmartgridplatform.org/Userguide/Installation/setupOSGP.html. I still get those 2 WSDL errors. But, I am able to add resources, except for 3 resources related to protocol simulators (iec60870, iec61850 and mqtt). So, it looks like the issue has been introduced in developer branch. Is it ok if I continue with 5.1.0 branch? I am yet to complete remaining steps of platform setup as per the document mentioned above.
Thanks,
Rama

Hello @ramams,
Thank you for reporting this issue. I created a new development environment using Vagrant/VirtualBox. I see the errors you mentioned. Deploying the components to Tomcat 9 works fine. As you describe in your second comment, there is no relation between deploying to Tomcat and those WSDL/XSD errors.
If you prefer using the release branch, you certainly can use that version of the code. You should be able to complete the setup steps as described in the documentation.
I will have a look at the errors in WSDL/XSD.

Hi @kevinsmeets,
Thank you for your quick response. I was able to setup release branch and run the demo app successfully. I will continue to use the release branch for now. I will keep this issue open, so that I will know when the WSDL errors get resolved. We are interested in smart meter domain.
Regards,
Rama


TinyAdventure Tutorial

A little tutorial using a PDA to save game data.
For some reason it does not shop up in the Tutorials tab.
Could you maybe have a look why that is?

ran yarn format 💪 🧹

It won't format .raw files. Looks good now!


freetube: 0.15.1 -> 0.16.0

Automatic update generated by nixpkgs-update tools. This update was made based on information from https://repology.org/metapackage/freetube/versions.
meta.description for freetube is: "An Open Source YouTube app for privacy"
meta.homepage for freetube is: "https://freetubeapp.io/"
meta.changelog for freetube is: ""
Updates performed

Version update

To inspect upstream changes

Release on GitHub

Compare changes on GitHub

Impact

Checks done (click to expand)

built on NixOS
The tests defined in passthru.tests, if any, passed
Warning: no invocation of /nix/store/1skdflrzjcslj5xhc138mfx5c66kjn30-freetube-0.16.0/bin/freetube had a zero exit code or showed the expected version
0 of 1 passed binary check by having a zero exit code.
0 of 1 passed binary check by having the new version present in output.
found 0.16.0 with grep in /nix/store/1skdflrzjcslj5xhc138mfx5c66kjn30-freetube-0.16.0
found 0.16.0 in filename of file in /nix/store/1skdflrzjcslj5xhc138mfx5c66kjn30-freetube-0.16.0

Rebuild report (if merged into master) (click to expand)

1 total rebuild path(s)

1 package rebuild(s)

1 x86_64-linux rebuild(s)
0 x86_64-darwin rebuild(s)

First fifty rebuilds by attrpath
freetube

Instructions to test this update (click to expand)

Either download from Cachix:
nix-store -r /nix/store/1skdflrzjcslj5xhc138mfx5c66kjn30-freetube-0.16.0 \
  --option binary-caches 'https://cache.nixos.org/ https://nix-community.cachix.org/' \
  --option trusted-public-keys '
  nix-community.cachix.org-1:mB9FSh9qf2dCimDSUo8Zy7bkq5CX+/rkCWyvRCYg3Fs=
  cache.nixos.org-1:6NCHdD59X431o0gWypbMrAURkbJ16ZPMQFGspcDShjY=
  '

(The Cachix cache is only trusted for this store-path realization.)
For the Cachix download to work, your user must be in the trusted-users list or you can use sudo since root is effectively trusted.
Or, build yourself:
nix-build -A freetube https://github.com/r-ryantm/nixpkgs/archive/0b47c3e7ae20fefc2dc4a2858ede262218ad11c5.tar.gz

After you've downloaded or built it, look at the files and if there are any, run the binaries:
ls -la /nix/store/1skdflrzjcslj5xhc138mfx5c66kjn30-freetube-0.16.0
ls -la /nix/store/1skdflrzjcslj5xhc138mfx5c66kjn30-freetube-0.16.0/bin

Pre-merge build results
We have automatically built all packages that will get rebuilt due to
this change.
This gives evidence on whether the upgrade will break dependent packages.
Note sometimes packages show up as failed to build independent of the
change, simply because they are already broken on the target branch.
Result of nixpkgs-review run on x86_64-linux 1

1 package built:

freetube

Maintainer pings
cc @ryneeverett @alyaeanyx for testing.

Tested and works for me


Render storylines as array in seed data

Unify interface to allow generic handling of storylines just like any
other collection.

Coverage increased (+8.0e-05%) to 99.053% when pulling 3cea2634075606255e58280271191eb9effecff7 on tf:storylines-seed into 0024e057d72d774fbd5aebecf365ee09fb1c0816 on codevise:master.

Coverage increased (+8.0e-05%) to 99.053% when pulling 3cea2634075606255e58280271191eb9effecff7 on tf:storylines-seed into 0024e057d72d774fbd5aebecf365ee09fb1c0816 on codevise:master.

Coverage increased (+8.0e-05%) to 99.053% when pulling 3cea2634075606255e58280271191eb9effecff7 on tf:storylines-seed into 0024e057d72d774fbd5aebecf365ee09fb1c0816 on codevise:master.


pkg/gadgets: Add unit test for trace oomkill.

Unit tests are frozen for this. Should we also implement the timeout for proc.Wait() in trace signal test?


💯 coverage

Objective
This PR brings test coverage back to 100%. Those tests are not strictly necessary but as they were the only missing lines from the entire code I figure we could quickly implement them.
Checklist

[x] I have read the CONTRIBUTING document.
[x] I have created a Codelog changefile with the changes made to the branch.
[x] I have created a test proving that my feature/fix does what it intends to do.
[x] I have updated the documentation accordingly. (If needed)

@emilianoLeite I tried rewriting the test without the stub to make it more representative, take a look at the changes and tell me what you think about!


Encrypt an accounts password before storing it

At the moment, all user passwords are stored as clear text. This needs to be changed.
Probably BCryptPasswordEncoder will help doing this. It can be defined as a bean and also used in Oauth2Configuration.

Not necessary any longer since Auth0 was chosen as authentication provider.


[BUG] Unable to build extension "transformer_inference"

Describe the bug
A clear and concise description of what the bug is.
After installing deepspeed, I try to run very basic inference with the transformers library but it seems that there is no way to install the transformer_inference extension necessary for inference. This is even after adding the flag for DS_BUILD_TRANSFORMER_INFERENCE=1 to the install process. I can get around this problem by just running init_inference twice and catching the first error, but this seems wrong.
To Reproduce
Steps to reproduce the behavior:

Simple inference script to reproduce
What packages are required and their versions
How to run the script
...

DS_BUILD_OPS=1 DS_BUILD_TRANSFORMER_INFERENCE=1 pip install deepspeed
python -c """
import deepspeed
import transformers
import os
model = transformers.AutoModelForCausalLM.from_pretrained('gpt2')
world_size = int(os.getenv('WORLD_SIZE', '1'))
model = deepspeed.init_inference(
            model,
            mp_size=world_size,
            replace_with_kernel_inject=True,
            replace_method='auto',
        )
"""

Error:
File "~/.conda/envs/py3/lib/python3.8/site-packages/deepspeed/module_inject/replace_module.py", line 468, in replace_with_policy
    new_module = transformer_inference.DeepSpeedTransformerInference(
  File "~/.conda/envs/py3/lib/python3.8/site-packages/deepspeed/model_implementations/transformers/ds_transformer.py", line 53, in __init__
    inference_cuda_module = builder.load()
  File "~/.conda/envs/py3/lib/python3.8/site-packages/deepspeed/ops/op_builder/builder.py", line 460, in load
    return self.jit_load(verbose)
  File "~/.conda/envs/py3/lib/python3.8/site-packages/deepspeed/ops/op_builder/builder.py", line 495, in jit_load
    op_module = load(
  File "~/.conda/envs/py3/lib/python3.8/site-packages/torch/utils/cpp_extension.py", line 986, in load
    return _jit_compile(
  File "~/.conda/envs/py3/lib/python3.8/site-packages/torch/utils/cpp_extension.py", line 1193, in _jit_compile
    _write_ninja_file_and_build_library(
  File "~/.conda/envs/py3/lib/python3.8/site-packages/torch/utils/cpp_extension.py", line 1297, in _write_ninja_file_and_build_library
    _run_ninja_build(
  File "~/.conda/envs/py3/lib/python3.8/site-packages/torch/utils/cpp_extension.py", line 1555, in _run_ninja_build
    raise RuntimeError(message) from e
RuntimeError: Error building extension 'transformer_inference'

Expected behavior
A clear and concise description of what you expected to happen.
Expected to see transformer and transformer_inference in the output of the ds_report command.
ds_report output
Please run ds_report to give us details about your setup.
--------------------------------------------------
DeepSpeed C++/CUDA extension op report
--------------------------------------------------
NOTE: Ops not installed will be just-in-time (JIT) compiled at
      runtime if needed. Op compatibility means that your system
      meet the required dependencies to JIT install the op.
--------------------------------------------------
JIT compiled ops requires ninja
ninja .................. [OKAY]
--------------------------------------------------
op name ................ installed .. compatible
--------------------------------------------------
cpu_adam ............... [NO] ....... [OKAY]
cpu_adagrad ............ [NO] ....... [OKAY]
fused_adam ............. [NO] ....... [OKAY]
fused_lamb ............. [NO] ....... [OKAY]
sparse_attn ............ [NO] ....... [OKAY]
transformer ............ [NO] ....... [OKAY]
stochastic_transformer . [NO] ....... [OKAY]
 [WARNING]  async_io requires the dev libaio .so object and headers but these wer
e not found.
 [WARNING]  async_io: please install the libaio-devel package with yum
 [WARNING]  If libaio is already installed (perhaps from source), try setting the
 CFLAGS and LDFLAGS environment variables to where it can be found.
async_io ............... [NO] ....... [NO]
utils .................. [NO] ....... [OKAY]
quantizer .............. [NO] ....... [OKAY]
fused_adam ............. [NO] ....... [OKAY]
fused_lamb ............. [NO] ....... [OKAY]
sparse_attn ............ [NO] ....... [OKAY]
transformer ............ [NO] ....... [OKAY]
stochastic_transformer . [NO] ....... [OKAY]
 [WARNING]  async_io requires the dev libaio .so object and headers but these wer
e not found.
 [WARNING]  async_io: please install the libaio-devel package with yum
 [WARNING]  If libaio is already installed (perhaps from source), try setting the
 CFLAGS and LDFLAGS environment variables to where it can be found.
async_io ............... [NO] ....... [NO]
utils .................. [NO] ....... [OKAY]
quantizer .............. [NO] ....... [OKAY]
transformer_inference .. [NO] ....... [OKAY]
spatial_inference ...... [NO] ....... [OKAY]
--------------------------------------------------
DeepSpeed general environment info:
torch install path ............... ['~/.conda/envs/py3/lib/python3.8/site-
packages/torch']
torch version .................... 1.7.1+cu110
torch cuda version ............... 11.0
torch hip version ................ None
nvcc version ..................... 11.3
deepspeed install path ........... ['~/.conda/envs/py3/lib/python3.8/site-
packages/deepspeed']
deepspeed info ................... 0.7.7, unknown, unknown
deepspeed wheel compiled w. ...... torch 1.7, cuda 11.0

Screenshots
If applicable, add screenshots to help explain your problem.
System info (please complete the following information):

OS: Ubuntu
GPU count and types: A100 machine with 8 GPUs
(if applicable) what DeepSpeed-MII version are you using: 0.7.7
(if applicable) Hugging Face Transformers/Accelerate/etc. versions: 4.24.0
Python version: 3.8.15
Any other relevant info about your setup

Docker context
Are you using a specific docker image that you can share?
Additional context
Add any other context about the problem here.

Hi @ianbstewart,
Can you please show me the whole stack trace, it seems there is compilation error?
Thanks,
Reza

Sure, here is the traceback from the error:
Traceback (most recent call last):
  File "<string>", line 7, in <module>
  File "~/.conda/envs/py3/lib/python3.8/site-packages/deepspeed/__init__.py", line 311, in init_inference
    engine = InferenceEngine(model, config=ds_inference_config)
  File "~/.conda/envs/py3/lib/python3.8/site-packages/deepspeed/inference/engine.py", line 124, in __init__
    self._apply_injection_policy(config)
  File "~/.conda/envs/py3/lib/python3.8/site-packages/deepspeed/inference/engine.py", line 349, in _apply_injection_policy
    replace_transformer_layer(client_module,
  File "~/.conda/envs/py3/lib/python3.8/site-packages/deepspeed/module_inject/replace_module.py", line 899, in replace_transformer_layer
    replaced_module = replace_module(model=model,
  File "~/.conda/envs/py3/lib/python3.8/site-packages/deepspeed/module_inject/replace_module.py", line 1168, in replace_module
    replaced_module, _ = _replace_module(model, policy)
  File "~/.conda/envs/py3/lib/python3.8/site-packages/deepspeed/module_inject/replace_module.py", line 1195, in _replace_module
    _, layer_id = _replace_module(child, policies, layer_id=layer_id)
  File "~/.conda/envs/py3/lib/python3.8/site-packages/deepspeed/module_inject/replace_module.py", line 1195, in _replace_module
    _, layer_id = _replace_module(child, policies, layer_id=layer_id)
  File "~/.conda/envs/py3/lib/python3.8/site-packages/deepspeed/module_inject/replace_module.py", line 1185, in _replace_module
    replaced_module = policies[child.__class__][0](child,
  File "~/.conda/envs/py3/lib/python3.8/site-packages/deepspeed/module_inject/replace_module.py", line 889, in replace_fn
    new_module = replace_with_policy(child,
  File "~/.conda/envs/py3/lib/python3.8/site-packages/deepspeed/module_inject/replace_module.py", line 468, in replace_with_policy
    new_module = transformer_inference.DeepSpeedTransformerInference(
  File "~/.conda/envs/py3/lib/python3.8/site-packages/deepspeed/model_implementations/transformers/ds_transformer.py", line 53, in __init__
    inference_cuda_module = builder.load()
  File "~/.conda/envs/py3/lib/python3.8/site-packages/deepspeed/ops/op_builder/builder.py", line 460, in load
    return self.jit_load(verbose)
  File "~/.conda/envs/py3/lib/python3.8/site-packages/deepspeed/ops/op_builder/builder.py", line 495, in jit_load
    op_module = load(
  File "~/.conda/envs/py3/lib/python3.8/site-packages/torch/utils/cpp_extension.py", line 986, in load
    return _jit_compile(
  File "~/.conda/envs/py3/lib/python3.8/site-packages/torch/utils/cpp_extension.py", line 1193, in _jit_compile
    _write_ninja_file_and_build_library(
  File "~/.conda/envs/py3/lib/python3.8/site-packages/torch/utils/cpp_extension.py", line 1297, in _write_ninja_file_and_build_library
    _run_ninja_build(
  File "~/.conda/envs/py3/lib/python3.8/site-packages/torch/utils/cpp_extension.py", line 1555, in _run_ninja_build
    raise RuntimeError(message) from e
RuntimeError: Error building extension 'transformer_inference'

Sorry, but it seems the compilation error happens before this, can I see the whole output log?

See below:
~/.conda/envs/py3/lib/python3.8/site-packages/torch/utils/cpp_extension.py:266: UserWarning:

                               !! WARNING !!

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
Your compiler (/share/apps/nvhpc/22.3/Linux_x86_64/22.3/compilers/bin/nvc++) is not compatible with the compiler Pytorch was
built with for this platform, which is g++ on linux. Please
use g++ to to compile your extension. Alternatively, you may
compile PyTorch from source using /share/apps/nvhpc/22.3/Linux_x86_64/22.3/compilers/bin/nvc++, and then you can also use
/share/apps/nvhpc/22.3/Linux_x86_64/22.3/compilers/bin/nvc++ to compile your extension.

See https://github.com/pytorch/pytorch/blob/master/CONTRIBUTING.md for help
with compiling PyTorch from source.
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

                              !! WARNING !!

  warnings.warn(WRONG_COMPILER_WARNING.format(
Traceback (most recent call last):
  File "~/.conda/envs/py3/lib/python3.8/site-packages/torch/utils/cpp_extension.py", line 1533, in _run_ninja_build
    subprocess.run(
  File "~/.conda/envs/py3/lib/python3.8/subprocess.py", line 516, in run
    raise CalledProcessError(retcode, process.args,
subprocess.CalledProcessError: Command '['ninja', '-v']' returned non-zero exit status 1.

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "debug_deepspeed_inference.py", line 6, in <module>
    model = deepspeed.init_inference(
  File "~/.conda/envs/py3/lib/python3.8/site-packages/deepspeed/__init__.py", line 311, in init_inference
    engine = InferenceEngine(model, config=ds_inference_config)
  File "~/.conda/envs/py3/lib/python3.8/site-packages/deepspeed/inference/engine.py", line 124, in __init__
    self._apply_injection_policy(config)
  File "~/.conda/envs/py3/lib/python3.8/site-packages/deepspeed/inference/engine.py", line 349, in _apply_injection_policy
    replace_transformer_layer(client_module,
  File "~/.conda/envs/py3/lib/python3.8/site-packages/deepspeed/module_inject/replace_module.py", line 899, in replace_transformer_layer
    replaced_module = replace_module(model=model,
  File "~/.conda/envs/py3/lib/python3.8/site-packages/deepspeed/module_inject/replace_module.py", line 1168, in replace_module
    replaced_module, _ = _replace_module(model, policy)
  File "~/.conda/envs/py3/lib/python3.8/site-packages/deepspeed/module_inject/replace_module.py", line 1195, in _replace_module
    _, layer_id = _replace_module(child, policies, layer_id=layer_id)
  File "~/.conda/envs/py3/lib/python3.8/site-packages/deepspeed/module_inject/replace_module.py", line 1195, in _replace_module
    _, layer_id = _replace_module(child, policies, layer_id=layer_id)
  File "~/.conda/envs/py3/lib/python3.8/site-packages/deepspeed/module_inject/replace_module.py", line 1185, in _replace_module
    replaced_module = policies[child.__class__][0](child,
  File "~/.conda/envs/py3/lib/python3.8/site-packages/deepspeed/module_inject/replace_module.py", line 889, in replace_fn
    new_module = replace_with_policy(child,
  File "~/.conda/envs/py3/lib/python3.8/site-packages/deepspeed/module_inject/replace_module.py", line 468, in replace_with_policy
    new_module = transformer_inference.DeepSpeedTransformerInference(
  File "~/.conda/envs/py3/lib/python3.8/site-packages/deepspeed/model_implementations/transformers/ds_transformer.py", line 53, in __init__
    inference_cuda_module = builder.load()
  File "~/.conda/envs/py3/lib/python3.8/site-packages/deepspeed/ops/op_builder/builder.py", line 460, in load
    return self.jit_load(verbose)
  File "~/.conda/envs/py3/lib/python3.8/site-packages/deepspeed/ops/op_builder/builder.py", line 495, in jit_load
    op_module = load(
  File "~/.conda/envs/py3/lib/python3.8/site-packages/torch/utils/cpp_extension.py", line 986, in load
    return _jit_compile(
  File "~/.conda/envs/py3/lib/python3.8/site-packages/torch/utils/cpp_extension.py", line 1193, in _jit_compile
    _write_ninja_file_and_build_library(
  File "~/.conda/envs/py3/lib/python3.8/site-packages/torch/utils/cpp_extension.py", line 1297, in _write_ninja_file_and_build_library
    _run_ninja_build(
  File "~/.conda/envs/py3/lib/python3.8/site-packages/torch/utils/cpp_extension.py", line 1555, in _run_ninja_build
    raise RuntimeError(message) from e
RuntimeError: Error building extension 'transformer_inference'

[2022-12-14 14:08:34,996] [WARNING] [runner.py:179:fetch_hostfile] Unable to find hostfile, will proceed with training with local resources only.
Detected CUDA_VISIBLE_DEVICES=0,2 but ignoring it because one or several of --include/--exclude/--num_gpus/--num_nodes cl args were used. If you want to use CUDA_VISIBLE_DEVICES don't pass any of these arguments to deepspeed.
[2022-12-14 14:08:35,277] [INFO] [runner.py:508:main] cmd = ~/.conda/envs/py3/bin/python -u -m deepspeed.launcher.launch --world_info=eyJsb2NhbGhvc3QiOiBbMCwgMV19 --master_addr=<IP_ADDRESS> --master_port=29500 debug_deepspeed_inference.py
[2022-12-14 14:08:36,468] [INFO] [launch.py:142:main] WORLD INFO DICT: {'localhost': [0, 1]}
[2022-12-14 14:08:36,469] [INFO] [launch.py:148:main] nnodes=1, num_local_procs=2, node_rank=0
[2022-12-14 14:08:36,469] [INFO] [launch.py:161:main] global_rank_mapping=defaultdict(<class 'list'>, {'localhost': [0, 1]})
[2022-12-14 14:08:36,469] [INFO] [launch.py:162:main] dist_world_size=2
[2022-12-14 14:08:36,469] [INFO] [launch.py:164:main] Setting CUDA_VISIBLE_DEVICES=0,1
[2022-12-14 14:08:43,175] [INFO] [logging.py:68:log_dist] [Rank -1] DeepSpeed info: version=0.7.7, git-hash=unknown, git-branch=unknown
[2022-12-14 14:08:43,176] [WARNING] [config_utils.py:67:_process_deprecated_field] Config parameter mp_size is deprecated use tensor_parallel.tp_size instead
[2022-12-14 14:08:43,176] [INFO] [logging.py:68:log_dist] [Rank -1] quantize_bits = 8 mlp_extra_grouping = False, quantize_groups = 1
[2022-12-14 14:08:43,189] [INFO] [logging.py:68:log_dist] [Rank -1] DeepSpeed info: version=0.7.7, git-hash=unknown, git-branch=unknown
[2022-12-14 14:08:43,189] [WARNING] [config_utils.py:67:_process_deprecated_field] Config parameter mp_size is deprecated use tensor_parallel.tp_size instead
[2022-12-14 14:08:43,190] [INFO] [logging.py:68:log_dist] [Rank -1] quantize_bits = 8 mlp_extra_grouping = False, quantize_groups = 1
[2022-12-14 14:08:43,365] [INFO] [comm.py:654:init_distributed] Initializing TorchBackend in DeepSpeed with backend nccl
Installed CUDA version 11.3 does not match the version torch was compiled with 11.0 but since the APIs are compatible, accepting this combination
Installed CUDA version 11.3 does not match the version torch was compiled with 11.0 but since the APIs are compatible, accepting this combination
Using ~/.cache/torch_extensions as PyTorch extensions root...
Using ~/.cache/torch_extensions as PyTorch extensions root...
Detected CUDA files, patching ldflags
Emitting ninja build file ~/.cache/torch_extensions/transformer_inference/build.ninja...
Building extension module transformer_inference...

Loading extension module transformer_inference...
Time to load transformer_inference op: 0.6002025604248047 seconds
Installed CUDA version 11.3 does not match the version torch was compiled with 11.0 but since the APIs are compatible, accepting this combination
Using ~/.cache/torch_extensions as PyTorch extensions root...
No modifications detected for re-loaded extension module transformer_inference, skipping build step...
Loading extension module transformer_inference...
Time to load transformer_inference op: 0.06150174140930176 seconds
Installed CUDA version 11.3 does not match the version torch was compiled with 11.0 but since the APIs are compatible, accepting this combination
Using ~/.cache/torch_extensions as PyTorch extensions root...
No modifications detected for re-loaded extension module transformer_inference, skipping build step...
Loading extension module transformer_inference...
Time to load transformer_inference op: 0.06500792503356934 seconds
[2022-12-14 14:08:52,499] [INFO] [launch.py:318:sigkill_handler] Killing subprocess 149933
[2022-12-14 14:08:52,499] [INFO] [launch.py:318:sigkill_handler] Killing subprocess 149934
[2022-12-14 14:08:52,742] [ERROR] [launch.py:324:sigkill_handler] ['~/.conda/envs/py3/bin/python', '-u', 'debug_deepspeed_inference.py', '--local_rank=1'] exits with return code = 1

Hi @ianbstewart
I just checked on my side, and I see that the compiler chosen by torch is different between use. I am seeing nvcc for the CUDA files such as gelu.cu,  however I see c++ for the cpp files like pt_biniding.cpp:
[6/9] /usr/local/cuda/bin/nvcc  -DTORCH_EXTENSION_NAME=transformer_inference -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -I/home/reyazda/DeepSpeed/deepspeed/ops/csrc/transformer/inference/includes -I/home/reyazda/DeepSpeed/deepspeed/ops/csrc/includes -isystem /opt/conda/lib/python3.8/site-packages/torch/include -isystem /opt/conda/lib/python3.8/site-packages/torch/include/torch/csrc/api/include -isystem /opt/conda/lib/python3.8/site-packages/torch/include/TH -isystem /opt/conda/lib/python3.8/site-packages/torch/include/THC -isystem /usr/local/cuda/include -isystem /opt/conda/include/python3.8 -D_GLIBCXX_USE_CXX11_ABI=0 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr -gencode=arch=compute_70,code=compute_70 -gencode=arch=compute_70,code=sm_70 --compiler-options '-fPIC' -O3 --use_fast_math -std=c++14 -U__CUDA_NO_HALF_OPERATORS__ -U__CUDA_NO_HALF_CONVERSIONS__ -U__CUDA_NO_HALF2_OPERATORS__ -gencode=arch=compute_70,code=sm_70 -gencode=arch=compute_70,code=compute_70 -c /home/reyazda/DeepSpeed/deepspeed/ops/csrc/transformer/inference/csrc/gelu.cu -o gelu.cuda.o

[8/9] c++ -MMD -MF pt_binding.o.d -DTORCH_EXTENSION_NAME=transformer_inference -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -I/home/reyazda/DeepSpeed/deepspeed/ops/csrc/transformer/inference/includes -I/home/reyazda/DeepSpeed/deepspeed/ops/csrc/includes -isystem /opt/conda/lib/python3.8/site-packages/torch/include -isystem /opt/conda/lib/python3.8/site-packages/torch/include/torch/csrc/api/include -isystem /opt/conda/lib/python3.8/site-packages/torch/include/TH -isystem /opt/conda/lib/python3.8/site-packages/torch/include/THC -isystem /usr/local/cuda/include -isystem /opt/conda/include/python3.8 -D_GLIBCXX_USE_CXX11_ABI=0 -fPIC -std=c++14 -O3 -std=c++14 -g -Wno-reorder -c /home/reyazda/DeepSpeed/deepspeed/ops/csrc/transformer/inference/csrc/pt_binding.cpp -o pt_binding.o

I am not sure how this is set as nvcc++ on your side (/share/apps/nvhpc/22.3/Linux_x86_64/22.3/compilers/bin/nvc++)! There must be some way to change this to point to the right compiler for the cpp files at torch.
@jeffra, do you have any idea how to resolve this issue?
Thanks,
Reza

@ianbstewart I've had this issue as well when trying to run txt2img with pytorch 1.13. I've fixed it (but not the subsequent errors :) ) by using pytorch 1.12.1 (conda install pytorch==1.12.1 torchvision==0.13.1 torchaudio==0.12.1 cudatoolkit=11.3 -c pytorch -y).

Thanks. I was able to get around this issue as well, forgot the exact fix but I think it was downgrading torch in the same way.

Any update on this?

I've had the same issue now(torch 2.3). What should I do?


Testing, please ignore. (mamiwo)

Please ignore.. Please DO NOT APPROVE THIS! (mamiwo)

Hi @helumanxa,
Thank you for contributing this pull request!
Please sign the Kaltura CLA so we can review and merge your contribution.
Learn more at http://bit.ly/KalturaContrib


Warn if multiple .ahk files exist in startup folders

If the user chooses to launch at startup, check if there are already .ahk files in the startup directory and warn the user (possibly offer to delete those or open the folder in Explorer).
Further, the save-to folder should be blank by default, and a blank value means not to save the script.

Going to remove startup stuff and simply document how to do this for users


Prompt can't be saved anymore

It seems tabs updates from React Bootstrap to Shadcn ui broke the prompt saving.

Tabs content is removed when not selected but precisely tabs content is collected by the form to get all the data.
By using default values, we could fix the bug but that is not the way the app works initially.


scour: Fix another variant of the crash from #260

"Stealing" a child from another node does not work as intended.
Instead, we use a "add clone, remove original"-flow instead.
Signed-off-by: Niels Thykier<EMAIL_ADDRESS>

Any plans on merging this?

Thanks for the fix Nils and sorry for the delayed review!
I believe the important thing here is to avoid attempting to modify the list directly and remember to use xml.dom, methods like appendChild or removeChild.
With this in mind, I assume we can avoid cloning said nodes only to discard the originals later. A simple appendChild should be enough (it even removes the node from the original parent for us as as per documentation)
Would you be willing to give this approach another try before I merge this @nthykier ?

@Ede123: Rebased.

Codecov Report

Merging #264 (0a06895) into master (92e64f0) will increase coverage by 0.04%.
The diff coverage is 100.00%.

@@            Coverage Diff             @@
##           master     #264      +/-   ##
==========================================
+ Coverage   94.09%   94.14%   +0.04%
==========================================
  Files           5        5
  Lines        2271     2272       +1
==========================================
+ Hits         2137     2139       +2
+ Misses        134      133       -1

Impacted Files
Coverage Δ

scour/scour.py
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Thanks a lot!


use a print statement to show the user that the app is loading

{'ADMIN0': {'name': 'Country/Province', 'type': 'Administrative definitions'}, 'ADMIN1': {'name': 'Admin level 1', 'type': 'Administrative definitions'}, 'ADMIN2': {'name': 'Admin level 2', 'type': 'Administrative definitions'}, 'SHAPE': {'name': 'Vector file', 'type': 'Custom geometries'}, 'DRAW': {'name': 'Drawn shapes', 'type': 'Custom geometries'}}

I manage to add the statement, but once it's their It create a cell output in voila i.e. a huge padding in the viewport that I cannot overlay. As it makes all the tile go down few centimeters I won't keep this solution for now.
I also tried to use a vuetify widget but it taks as much time to load as the others.


Add deps to colab notebook

Need to fix a weird issue with this still but this is the gist

Link to test PR:
https://colab.research.google.com/github/OpenFreeEnergy/kartograf/blob/fea%2Fupdate_notebook/examples/kartograf_example.ipynb

:rocket:

viz is working on colab


Add Cloud Firestore for state

Describe the proposal
Add support for Cloud Firestore (in datastore mode) as a state component.

I started working on this

Thanks, will be great to see this.


Use the ESPM to Manage Orders and Stock Information

Tutorial URL: https://developers.sap.com/tutorials/cp-java-reference-app-manage-orders.html
Please specify the step you are referring to Step 1,
hello I cant check out the Notebook, I became the Information "Check your Input and try again".
Regards

Hello,
Can you perform a fresh deployment, as it is working from our side.
Thanks.
Regards,
Simona

I stet up a new Database and a new Binding etc... I cant check out... Wich Credit Card had I to Use?

Hello,
There is no need for any card at all. This is a reference application that shows the capabilities of SAP Cloud Platform.
The tutorial you are referring to only aims to demonstrate how you can create a sales order, how to approve it, and how to update stock information.
Regards,
Simona

Thank you for your feedback. We haven't heard from you in a while, so we are closing the issue.
If you still have questions, feel free to reopen the issue.


assign tag to image in dockerfile

For users who pulled ubuntu image long ago, it will not update this image version.
And the commands in this dockerfile seems like only works in 16.04 or above.
By assign a tag to the docker image, every one will use the same version of ubuntu.

111


[Bug]: Failing to initialize Hydrogen project  with latest hydrogen cli

Please confirm that you have:

[X] Searched existing issues to see if your issue is a duplicate. (If you’ve found a duplicate issue, feel free to add additional information in a comment on it.)
[X] Reproduced the issue in the latest CLI version.

In which of these areas are you experiencing a problem?
Hydrogen custom storefront
Expected behavior
Should be able to initialize a new project by running the  npm create @shopify/hydrogen@latest
Actual behavior
I was presented with the following error:
Error: Access denied for hydrogenStorefrontCreate field. Required access:   │
│  User must have full access to apps or access to the Hydrogen channel.:      │
│  {"response":{"data":{"hydrogenStorefrontCreate":null},"errors":[{"message"  │
│  :"Access denied for hydrogenStorefrontCreate field. Required access: User   │
│  must have full access to apps or access to the Hydrogen                     │
│  channel.","locations":[{"line":3,"column":5}],"path":["hydrogenStorefrontC  │
│  reate"],"extensions":{"code":"ACCESS_DENIED","documentation":"https://shop  │
│  ify.dev/api/usage/access-scopes","requiredAccess":"User must have full      │
│  access to apps or access to the Hydrogen channel."}}],"extensions":{"cost"  │
│  :{"requestedQueryCost":10,"actualQueryCost":10,"throttleStatus":{"maximumA  │
│  vailable":1000,"currentlyAvailable":990,"restoreRate":50}}},"status":200,"  │
│  headers":{}},"request":{"query":"#graphql\n  mutation                       │
│  CreateStorefront($title: String!) {\n    hydrogenStorefrontCreate(title:    │
│  $title) {\n      hydrogenStorefront {\n        id\n        title\n          │
│  productionUrl\n      }\n      userErrors {\n        code\n        field\n   │
│         message\n      }\n      jobId\n    }\n                               │
│  }\n","variables":{"title":"My First Hydrogen App"}}}                        │
│      at makeRequest                                                          │
│  (file:///home/admir/.npm/_npx/e1eac94ad41cc36f/node_modules/@shopify/cli-k  │
│  it/node_modules/graphql-request/build/esm/index.js:284:15)                  │
│      at process.processTicksAndRejections                                    │
│  (node:internal/process/task_queues:95:5)                                    │
│      at async debugLogResponseInfo (file:///home/admir/.npm/_npx/e1eac94ad4  │
│  1cc36f/node_modules/@shopify/cli-kit/dist/private/node/api.js:12:20)        │
│      at async graphqlRequest (file:///home/admir/.npm/_npx/e1eac94ad41cc36f  │
│  /node_modules/@shopify/cli-kit/dist/public/node/api/graphql.js:20:22)       │
│      at async adminRequest (file:///home/admir/.npm/_npx/e1eac94ad41cc36f/n  │
│  ode_modules/@shopify/cli-hydrogen/dist/lib/graphql/admin/client.js:8:12)    │
│      at async createStorefront                                               │
│  (file:///home/admir/.npm/_npx/e1eac94ad41cc36f/node_modules/@shopify/cli-h  │
│  ydrogen/dist/lib/graphql/admin/create-storefront.js:24:7)                   │
│      at async Promise.all (index 2)

Reproduction steps

run npm create @shopify/hydrogen@latest
when prompted Link your Shopify account
select Hydrogen App
enter Storefront name

Operating System
Windows 10
Shopify CLI version (check your project's package.json if you're not sure)
5
Shell
zsh
Node version (run node -v if you're not sure)
No response
What language and version are you using in your application?
No response

You cannot install the Hydrogen sales channel on a development store
You can select mock.shop and then replace the tokens with ones you generate yourself, though


ARROW-637: [Format] Add timezone to Timestamp metadata, comments describing the semantics

cc @julianhyde @julienledem for comment. This makes Arrow semantically equivalent to datetime objects in Python, and I believe the SQL standard

Sounds good!


File uploaded twice from client creates duplicates

Hi,
when uploading the same file twice, two entries will be created and uploaded to the server. From a disk space perspective it would be nice, if the two files would point to one file on disk or return the object already in the db. Obviously, we need to check first if that file already exists and this could be done by either comparing the parameters or a hash value of the file. I would like to help to work on such a feature. What do you think? I guess the ID today results from the insert in the mongoDB here
Regards

Hi @rockhouse, I've noticed this since I am facing the same issue, but it was not a priority for me.
As you suggested, a hash of the file is the best way to do this, but it requires the file to be uploaded completely, so you still have to use bandwidth to transfer the file before knowing if the file exists or not on the server.
You could use the store.onFinishUpload(callback) method that is called with the file object as first argument (from ufs v0.7.4_2 not yet published) and read the file stream to calculate the hash with store.getReadStream(fileId, file), but it won't work without modifying existing code.
From there you would have the hash of the file and you would still need to check that hash before saving the file in the store, currently there is no "hook" (callback) that allows custom operations at this moment of the process. Since the hash computing should run async, we maybe need to use promises instead of cascading callbacks.
For example :

user uploads the file
the hash is computed in the on finishUpload() callback and added to the file document (eg: file.md5), then you return a promise
after the hash has been computed, the file is saved to the store
if later the user re-uploads the same file
the hash is computed and compared to existing hashes in database
if the hash exists, the existing file document is returned and the file data is not saved to the store

In all cases, this should be optional since computing checksum can lower performances and not everybody needs it (even if very useful).

How about we create just a link instead of file when it is a duplicate? This seems easier to implement. I would use the following library for the hash value for the file: https://www.npmjs.com/package/spark-md5. It allows us to incrementally update the hash which is very efficient especially for large files.
So the flow would look like this:

get the temp file incrementally and create a hash for the file
lookup the hash of the temp file in the store
if hash exists do not write the temp file but create a link instead
if hash does not exist go on and write the file
file is added to the store as usual

The advantage is that the complete logic for the stores would stay the same, just the call to the file system is adjusted. I can also add a flag to make this optional.


Bugfix #13. Table creation throws exception when class has no public properties.

Issue #13 describes a bug that can result in unwanted behavior. Classes which serve as data models for table creation and lack public properties would result in the construction of an empty and deformed table. A preferable behavior, as mentioned in the original issue, is to throw an exception which can be properly handled.
Now when an empty list of class properties is returned, and exception is thrown.  In order for the exception to be descriptive, a custom exception PublicPropertiesNotFoundException was created. This has been tested and is passing.
Additionally, when browsing files to familiarize myself with the program I unconsciously allowed ReSharper to implement some best practice changes to the code (variable names, etc). I apologize if this is unappreciated. This is my first contribution to an open source project, and I wasn't being thoughtful in that regard.

Hi @geekmdio.
Thanks for your commits here. @rahl0b10 has closed this PR and opened a new one: #18
It looks like this new PR will fix the issues. If you'd like to have a go at fixing another issue, there are lots on the list to pick from at the moment.
Thanks again for your commits!
Tom


v1.0 of nmfs-opensci contributor guide

@k-doering-NOAA @jmlondon First stab at a very simple and to the point GH org contributor guide. https://nmfs-opensci.github.io/Contributor-Guide/. Idea is to edit this and to have it (or a copy) be a template that other GH org admin can use as a simple template for their orgs.
To do

[ ] Edit and improve content
[ ] Decide on a better set of sections
[ ] Add links to GGT content when we get that done
[ ] Add links and instructions for using template for creating repos with the basic content (disclaimers, license, coc)

@k-doering-NOAA Thanks for catching the old CoC. I updated to the newest one.
Re

The nmfs-opensci GitHub organization is not intended for official NOAA communications and NOAA logos should not generally be used on repositories.

GitHub use is covered under the Social Media policy per the last GitHub policy, and use of logos requires applying to use those, which I have not done. https://www.commerce.gov/about/policies/social-media.  So I didn't want us to run afoul of that.  My take-home from the social media policy is that one needs to be careful not to present content on social media as an official communication from NOAA.
Also technically NMFS Open Science has not been announced yet, so we are not a NOAA initiative yet. I need to work with my OST contact about getting a webpage up on fisheries.noaa.gov, which will make it feel more official.

The following would be good feedback. Viewing this as a "template" of a minimal GH org Contributor Guide:

what tabs are needed? The ones I have now are a first start.
should content be added or moved around?