Various compiler warnings for clang

With the following example
#include <iostream>
#include <vector>
#include <xtensor/xarray.hpp>
#include <xtensor/xio.hpp>

int main()
{
  std::vector<size_t> shape = { 3, 2, 4 };
  xt::xarray<double> a(shape);

  return 0;
}

Compiling (on macOS) with
clang++ -std=c++14 -Wall -pedantic -Wsign-compare -I$HOME/miniconda3/envs/sim/include test.cpp

Gives the following warnings:
In file included from test.cpp:3:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xarray.hpp:19:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xcontainer.hpp:23:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xmath.hpp:26:
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xslice.hpp:108:50: warning: suggest braces around initialization of
      subobject [-Wmissing-braces]
        XTENSOR_GLOBAL_CONSTEXPR rangemaker<> _r{0, 0, 0};
                                                 ^~~~~~~
                                                 {      }
In file included from test.cpp:3:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xarray.hpp:19:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xcontainer.hpp:23:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xmath.hpp:27:
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xstrided_view.hpp:102:63: warning: extra ';' inside a class
      [-Wextra-semi]
        using strides_type = typename base_type::strides_type;;
                                                              ^
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xstrided_view.hpp:103:71: warning: extra ';' inside a class
      [-Wextra-semi]
        using backstrides_type = typename base_type::backstrides_type;;
                                                                      ^
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xstrided_view.hpp:486:25: warning: suggest braces around
      initialization of subobject [-Wmissing-braces]
                return {0, 0, 0};
                        ^~~~~~~
                        {      }
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xstrided_view.hpp:1061:72: warning: suggest braces around
      initialization of subobject [-Wmissing-braces]
        return squeeze(std::forward<E>(e), std::array<std::size_t, 1>{ axis }, check_policy);
                                                                       ^~~~
                                                                       {   }
In file included from test.cpp:3:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xarray.hpp:19:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xcontainer.hpp:23:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xmath.hpp:27:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xstrided_view.hpp:24:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xsemantic.hpp:15:
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xassign.hpp:495:19: warning: unused type alias 'size_type'
      [-Wunused-local-typedef]
            using size_type = typename E1::size_type;
                  ^
6 warnings generated.

Another simple example
#include <iostream>
#include <vector>
#include <xtensor/xarray.hpp>
#include <xtensor/xio.hpp>

int main()
{
  xt::xarray<double> a = xt::ones<double>({5,5});

  std::cout << a;
}

Gives
clang++ -std=c++14 -Wall -pedantic -Wsign-compare -I$HOME/miniconda3/envs/sim/include test.cpp -o test
In file included from test.cpp:3:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xarray.hpp:19:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xcontainer.hpp:23:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xmath.hpp:26:
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xslice.hpp:108:50: warning: suggest braces around initialization of subobject [-Wmissing-braces]
        XTENSOR_GLOBAL_CONSTEXPR rangemaker<> _r{0, 0, 0};
                                                 ^~~~~~~
                                                 {      }
In file included from test.cpp:3:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xarray.hpp:19:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xcontainer.hpp:23:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xmath.hpp:27:
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xstrided_view.hpp:102:63: warning: extra ';' inside a class [-Wextra-semi]
        using strides_type = typename base_type::strides_type;;
                                                              ^
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xstrided_view.hpp:103:71: warning: extra ';' inside a class [-Wextra-semi]
        using backstrides_type = typename base_type::backstrides_type;;
                                                                      ^
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xstrided_view.hpp:486:25: warning: suggest braces around initialization of subobject [-Wmissing-braces]
                return {0, 0, 0};
                        ^~~~~~~
                        {      }
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xstrided_view.hpp:1061:72: warning: suggest braces around initialization of subobject [-Wmissing-braces]
        return squeeze(std::forward<E>(e), std::array<std::size_t, 1>{ axis }, check_policy);
                                                                       ^~~~
                                                                       {   }
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xstrided_view.hpp:486:25: warning: suggest braces around initialization of subobject [-Wmissing-braces]
                return {0, 0, 0};
                        ^~~~~~~
                        {      }
/Users/tdegeus/miniconda3/envs/sim/include/xtl/xvariant_impl.hpp:546:18: note: in instantiation of function template specialization 'xt::detail::slice_getter_impl<xt::svector<unsigned long, 4,
      std::__1::allocator<unsigned long>, true> >::operator()<long>' requested here
          RETURN(lib::forward<F>(f)(lib::forward<As>(as)...))
                 ^
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xio.hpp:617:17: note: in instantiation of function template specialization
      'xt::detail::recurser_run<xt::detail::printer<xt::xarray_container<xt::uvector<double, std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned long, 4, std::__1::allocator<unsigned
      long>, true>, xt::xtensor_expression_tag>, void>, xt::xarray_container<xt::uvector<double, std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned long, 4,
      std::__1::allocator<unsigned long>, true>, xt::xtensor_expression_tag> >' requested here
        detail::recurser_run(p, d, sv, lim);
                ^
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xio.hpp:630:16: note: in instantiation of function template specialization 'xt::pretty_print<xt::xarray_container<xt::uvector<double,
      std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned long, 4, std::__1::allocator<unsigned long>, true>, xt::xtensor_expression_tag> >' requested here
        return pretty_print(e, out);
               ^
test.cpp:10:13: note: in instantiation of function template specialization 'xt::operator<<<xt::xarray_container<xt::uvector<double, std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned
      long, 4, std::__1::allocator<unsigned long>, true>, xt::xtensor_expression_tag> >' requested here
  std::cout << a;
            ^
In file included from test.cpp:3:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xarray.hpp:19:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xcontainer.hpp:23:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xmath.hpp:27:
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xstrided_view.hpp:493:25: warning: suggest braces around initialization of subobject [-Wmissing-braces]
                return {sl(0), sl.size(), sl.step_size()};
                        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
                        {                               }
/Users/tdegeus/miniconda3/envs/sim/include/xtl/xvariant_impl.hpp:546:18: note: in instantiation of function template specialization 'xt::detail::slice_getter_impl<xt::svector<unsigned long, 4,
      std::__1::allocator<unsigned long>, true> >::operator()<xt::placeholders::xtuph, long, long>' requested here
          RETURN(lib::forward<F>(f)(lib::forward<As>(as)...))
                 ^
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xio.hpp:617:17: note: in instantiation of function template specialization
      'xt::detail::recurser_run<xt::detail::printer<xt::xarray_container<xt::uvector<double, std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned long, 4, std::__1::allocator<unsigned
      long>, true>, xt::xtensor_expression_tag>, void>, xt::xarray_container<xt::uvector<double, std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned long, 4,
      std::__1::allocator<unsigned long>, true>, xt::xtensor_expression_tag> >' requested here
        detail::recurser_run(p, d, sv, lim);
                ^
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xio.hpp:630:16: note: in instantiation of function template specialization 'xt::pretty_print<xt::xarray_container<xt::uvector<double,
      std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned long, 4, std::__1::allocator<unsigned long>, true>, xt::xtensor_expression_tag> >' requested here
        return pretty_print(e, out);
               ^
test.cpp:10:13: note: in instantiation of function template specialization 'xt::operator<<<xt::xarray_container<xt::uvector<double, std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned
      long, 4, std::__1::allocator<unsigned long>, true>, xt::xtensor_expression_tag> >' requested here
  std::cout << a;
            ^
In file included from test.cpp:3:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xarray.hpp:19:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xcontainer.hpp:23:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xmath.hpp:27:
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xstrided_view.hpp:493:25: warning: suggest braces around initialization of subobject [-Wmissing-braces]
                return {sl(0), sl.size(), sl.step_size()};
                        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
                        {                               }
/Users/tdegeus/miniconda3/envs/sim/include/xtl/xvariant_impl.hpp:546:18: note: in instantiation of function template specialization 'xt::detail::slice_getter_impl<xt::svector<unsigned long, 4,
      std::__1::allocator<unsigned long>, true> >::operator()<long, xt::placeholders::xtuph, long>' requested here
          RETURN(lib::forward<F>(f)(lib::forward<As>(as)...))
                 ^
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xio.hpp:617:17: note: in instantiation of function template specialization
      'xt::detail::recurser_run<xt::detail::printer<xt::xarray_container<xt::uvector<double, std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned long, 4, std::__1::allocator<unsigned
      long>, true>, xt::xtensor_expression_tag>, void>, xt::xarray_container<xt::uvector<double, std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned long, 4,
      std::__1::allocator<unsigned long>, true>, xt::xtensor_expression_tag> >' requested here
        detail::recurser_run(p, d, sv, lim);
                ^
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xio.hpp:630:16: note: in instantiation of function template specialization 'xt::pretty_print<xt::xarray_container<xt::uvector<double,
      std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned long, 4, std::__1::allocator<unsigned long>, true>, xt::xtensor_expression_tag> >' requested here
        return pretty_print(e, out);
               ^
test.cpp:10:13: note: in instantiation of function template specialization 'xt::operator<<<xt::xarray_container<xt::uvector<double, std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned
      long, 4, std::__1::allocator<unsigned long>, true>, xt::xtensor_expression_tag> >' requested here
  std::cout << a;
            ^
In file included from test.cpp:3:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xarray.hpp:19:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xcontainer.hpp:23:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xmath.hpp:27:
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xstrided_view.hpp:493:25: warning: suggest braces around initialization of subobject [-Wmissing-braces]
                return {sl(0), sl.size(), sl.step_size()};
                        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
                        {                               }
/Users/tdegeus/miniconda3/envs/sim/include/xtl/xvariant_impl.hpp:546:18: note: in instantiation of function template specialization 'xt::detail::slice_getter_impl<xt::svector<unsigned long, 4,
      std::__1::allocator<unsigned long>, true> >::operator()<long, long, xt::placeholders::xtuph>' requested here
          RETURN(lib::forward<F>(f)(lib::forward<As>(as)...))
                 ^
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xio.hpp:617:17: note: in instantiation of function template specialization
      'xt::detail::recurser_run<xt::detail::printer<xt::xarray_container<xt::uvector<double, std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned long, 4, std::__1::allocator<unsigned
      long>, true>, xt::xtensor_expression_tag>, void>, xt::xarray_container<xt::uvector<double, std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned long, 4,
      std::__1::allocator<unsigned long>, true>, xt::xtensor_expression_tag> >' requested here
        detail::recurser_run(p, d, sv, lim);
                ^
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xio.hpp:630:16: note: in instantiation of function template specialization 'xt::pretty_print<xt::xarray_container<xt::uvector<double,
      std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned long, 4, std::__1::allocator<unsigned long>, true>, xt::xtensor_expression_tag> >' requested here
        return pretty_print(e, out);
               ^
test.cpp:10:13: note: in instantiation of function template specialization 'xt::operator<<<xt::xarray_container<xt::uvector<double, std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned
      long, 4, std::__1::allocator<unsigned long>, true>, xt::xtensor_expression_tag> >' requested here
  std::cout << a;
            ^
In file included from test.cpp:3:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xarray.hpp:19:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xcontainer.hpp:23:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xmath.hpp:27:
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xstrided_view.hpp:493:25: warning: suggest braces around initialization of subobject [-Wmissing-braces]
                return {sl(0), sl.size(), sl.step_size()};
                        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
                        {                               }
/Users/tdegeus/miniconda3/envs/sim/include/xtl/xvariant_impl.hpp:546:18: note: in instantiation of function template specialization 'xt::detail::slice_getter_impl<xt::svector<unsigned long, 4,
      std::__1::allocator<unsigned long>, true> >::operator()<long, xt::placeholders::xtuph, xt::placeholders::xtuph>' requested here
          RETURN(lib::forward<F>(f)(lib::forward<As>(as)...))
                 ^
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xio.hpp:617:17: note: in instantiation of function template specialization
      'xt::detail::recurser_run<xt::detail::printer<xt::xarray_container<xt::uvector<double, std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned long, 4, std::__1::allocator<unsigned
      long>, true>, xt::xtensor_expression_tag>, void>, xt::xarray_container<xt::uvector<double, std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned long, 4,
      std::__1::allocator<unsigned long>, true>, xt::xtensor_expression_tag> >' requested here
        detail::recurser_run(p, d, sv, lim);
                ^
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xio.hpp:630:16: note: in instantiation of function template specialization 'xt::pretty_print<xt::xarray_container<xt::uvector<double,
      std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned long, 4, std::__1::allocator<unsigned long>, true>, xt::xtensor_expression_tag> >' requested here
        return pretty_print(e, out);
               ^
test.cpp:10:13: note: in instantiation of function template specialization 'xt::operator<<<xt::xarray_container<xt::uvector<double, std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned
      long, 4, std::__1::allocator<unsigned long>, true>, xt::xtensor_expression_tag> >' requested here
  std::cout << a;
            ^
In file included from test.cpp:3:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xarray.hpp:19:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xcontainer.hpp:23:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xmath.hpp:27:
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xstrided_view.hpp:493:25: warning: suggest braces around initialization of subobject [-Wmissing-braces]
                return {sl(0), sl.size(), sl.step_size()};
                        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
                        {                               }
/Users/tdegeus/miniconda3/envs/sim/include/xtl/xvariant_impl.hpp:546:18: note: in instantiation of function template specialization 'xt::detail::slice_getter_impl<xt::svector<unsigned long, 4,
      std::__1::allocator<unsigned long>, true> >::operator()<xt::placeholders::xtuph, long, xt::placeholders::xtuph>' requested here
          RETURN(lib::forward<F>(f)(lib::forward<As>(as)...))
                 ^
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xio.hpp:617:17: note: in instantiation of function template specialization
      'xt::detail::recurser_run<xt::detail::printer<xt::xarray_container<xt::uvector<double, std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned long, 4, std::__1::allocator<unsigned
      long>, true>, xt::xtensor_expression_tag>, void>, xt::xarray_container<xt::uvector<double, std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned long, 4,
      std::__1::allocator<unsigned long>, true>, xt::xtensor_expression_tag> >' requested here
        detail::recurser_run(p, d, sv, lim);
                ^
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xio.hpp:630:16: note: in instantiation of function template specialization 'xt::pretty_print<xt::xarray_container<xt::uvector<double,
      std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned long, 4, std::__1::allocator<unsigned long>, true>, xt::xtensor_expression_tag> >' requested here
        return pretty_print(e, out);
               ^
test.cpp:10:13: note: in instantiation of function template specialization 'xt::operator<<<xt::xarray_container<xt::uvector<double, std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned
      long, 4, std::__1::allocator<unsigned long>, true>, xt::xtensor_expression_tag> >' requested here
  std::cout << a;
            ^
In file included from test.cpp:3:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xarray.hpp:19:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xcontainer.hpp:23:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xmath.hpp:27:
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xstrided_view.hpp:493:25: warning: suggest braces around initialization of subobject [-Wmissing-braces]
                return {sl(0), sl.size(), sl.step_size()};
                        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
                        {                               }
/Users/tdegeus/miniconda3/envs/sim/include/xtl/xvariant_impl.hpp:546:18: note: in instantiation of function template specialization 'xt::detail::slice_getter_impl<xt::svector<unsigned long, 4,
      std::__1::allocator<unsigned long>, true> >::operator()<xt::placeholders::xtuph, xt::placeholders::xtuph, long>' requested here
          RETURN(lib::forward<F>(f)(lib::forward<As>(as)...))
                 ^
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xio.hpp:617:17: note: in instantiation of function template specialization
      'xt::detail::recurser_run<xt::detail::printer<xt::xarray_container<xt::uvector<double, std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned long, 4, std::__1::allocator<unsigned
      long>, true>, xt::xtensor_expression_tag>, void>, xt::xarray_container<xt::uvector<double, std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned long, 4,
      std::__1::allocator<unsigned long>, true>, xt::xtensor_expression_tag> >' requested here
        detail::recurser_run(p, d, sv, lim);
                ^
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xio.hpp:630:16: note: in instantiation of function template specialization 'xt::pretty_print<xt::xarray_container<xt::uvector<double,
      std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned long, 4, std::__1::allocator<unsigned long>, true>, xt::xtensor_expression_tag> >' requested here
        return pretty_print(e, out);
               ^
test.cpp:10:13: note: in instantiation of function template specialization 'xt::operator<<<xt::xarray_container<xt::uvector<double, std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned
      long, 4, std::__1::allocator<unsigned long>, true>, xt::xtensor_expression_tag> >' requested here
  std::cout << a;
            ^
In file included from test.cpp:3:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xarray.hpp:19:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xcontainer.hpp:23:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xmath.hpp:27:
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xstrided_view.hpp:493:25: warning: suggest braces around initialization of subobject [-Wmissing-braces]
                return {sl(0), sl.size(), sl.step_size()};
                        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
                        {                               }
/Users/tdegeus/miniconda3/envs/sim/include/xtl/xvariant_impl.hpp:546:18: note: in instantiation of function template specialization 'xt::detail::slice_getter_impl<xt::svector<unsigned long, 4,
      std::__1::allocator<unsigned long>, true> >::operator()<long, long, long>' requested here
          RETURN(lib::forward<F>(f)(lib::forward<As>(as)...))
                 ^
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xio.hpp:617:17: note: in instantiation of function template specialization
      'xt::detail::recurser_run<xt::detail::printer<xt::xarray_container<xt::uvector<double, std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned long, 4, std::__1::allocator<unsigned
      long>, true>, xt::xtensor_expression_tag>, void>, xt::xarray_container<xt::uvector<double, std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned long, 4,
      std::__1::allocator<unsigned long>, true>, xt::xtensor_expression_tag> >' requested here
        detail::recurser_run(p, d, sv, lim);
                ^
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xio.hpp:630:16: note: in instantiation of function template specialization 'xt::pretty_print<xt::xarray_container<xt::uvector<double,
      std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned long, 4, std::__1::allocator<unsigned long>, true>, xt::xtensor_expression_tag> >' requested here
        return pretty_print(e, out);
               ^
test.cpp:10:13: note: in instantiation of function template specialization 'xt::operator<<<xt::xarray_container<xt::uvector<double, std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned
      long, 4, std::__1::allocator<unsigned long>, true>, xt::xtensor_expression_tag> >' requested here
  std::cout << a;
            ^
In file included from test.cpp:3:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xarray.hpp:19:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xcontainer.hpp:23:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xmath.hpp:27:
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xstrided_view.hpp:493:25: warning: suggest braces around initialization of subobject [-Wmissing-braces]
                return {sl(0), sl.size(), sl.step_size()};
                        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
                        {                               }
/Users/tdegeus/miniconda3/envs/sim/include/xtl/xvariant_impl.hpp:546:18: note: in instantiation of function template specialization 'xt::detail::slice_getter_impl<xt::svector<unsigned long, 4,
      std::__1::allocator<unsigned long>, true> >::operator()<xt::placeholders::xtuph, xt::placeholders::xtuph, xt::placeholders::xtuph>' requested here
          RETURN(lib::forward<F>(f)(lib::forward<As>(as)...))
                 ^
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xio.hpp:617:17: note: in instantiation of function template specialization
      'xt::detail::recurser_run<xt::detail::printer<xt::xarray_container<xt::uvector<double, std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned long, 4, std::__1::allocator<unsigned
      long>, true>, xt::xtensor_expression_tag>, void>, xt::xarray_container<xt::uvector<double, std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned long, 4,
      std::__1::allocator<unsigned long>, true>, xt::xtensor_expression_tag> >' requested here
        detail::recurser_run(p, d, sv, lim);
                ^
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xio.hpp:630:16: note: in instantiation of function template specialization 'xt::pretty_print<xt::xarray_container<xt::uvector<double,
      std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned long, 4, std::__1::allocator<unsigned long>, true>, xt::xtensor_expression_tag> >' requested here
        return pretty_print(e, out);
               ^
test.cpp:10:13: note: in instantiation of function template specialization 'xt::operator<<<xt::xarray_container<xt::uvector<double, std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned
      long, 4, std::__1::allocator<unsigned long>, true>, xt::xtensor_expression_tag> >' requested here
  std::cout << a;
            ^
In file included from test.cpp:3:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xarray.hpp:19:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xcontainer.hpp:23:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xmath.hpp:27:
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xstrided_view.hpp:486:25: warning: suggest braces around initialization of subobject [-Wmissing-braces]
                return {0, 0, 0};
                        ^~~~~~~
                        {      }
/Users/tdegeus/miniconda3/envs/sim/include/xtl/xvariant_impl.hpp:546:18: note: in instantiation of function template specialization 'xt::detail::slice_getter_impl<xt::svector<unsigned long, 4,
      std::__1::allocator<unsigned long>, true> >::operator()<xt::xall_tag>' requested here
          RETURN(lib::forward<F>(f)(lib::forward<As>(as)...))
                 ^
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xio.hpp:617:17: note: in instantiation of function template specialization
      'xt::detail::recurser_run<xt::detail::printer<xt::xarray_container<xt::uvector<double, std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned long, 4, std::__1::allocator<unsigned
      long>, true>, xt::xtensor_expression_tag>, void>, xt::xarray_container<xt::uvector<double, std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned long, 4,
      std::__1::allocator<unsigned long>, true>, xt::xtensor_expression_tag> >' requested here
        detail::recurser_run(p, d, sv, lim);
                ^
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xio.hpp:630:16: note: in instantiation of function template specialization 'xt::pretty_print<xt::xarray_container<xt::uvector<double,
      std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned long, 4, std::__1::allocator<unsigned long>, true>, xt::xtensor_expression_tag> >' requested here
        return pretty_print(e, out);
               ^
test.cpp:10:13: note: in instantiation of function template specialization 'xt::operator<<<xt::xarray_container<xt::uvector<double, std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned
      long, 4, std::__1::allocator<unsigned long>, true>, xt::xtensor_expression_tag> >' requested here
  std::cout << a;
            ^
In file included from test.cpp:3:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xarray.hpp:19:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xcontainer.hpp:23:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xmath.hpp:27:
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xstrided_view.hpp:486:25: warning: suggest braces around initialization of subobject [-Wmissing-braces]
                return {0, 0, 0};
                        ^~~~~~~
                        {      }
/Users/tdegeus/miniconda3/envs/sim/include/xtl/xvariant_impl.hpp:546:18: note: in instantiation of function template specialization 'xt::detail::slice_getter_impl<xt::svector<unsigned long, 4,
      std::__1::allocator<unsigned long>, true> >::operator()<xt::xellipsis_tag>' requested here
          RETURN(lib::forward<F>(f)(lib::forward<As>(as)...))
                 ^
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xio.hpp:617:17: note: in instantiation of function template specialization
      'xt::detail::recurser_run<xt::detail::printer<xt::xarray_container<xt::uvector<double, std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned long, 4, std::__1::allocator<unsigned
      long>, true>, xt::xtensor_expression_tag>, void>, xt::xarray_container<xt::uvector<double, std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned long, 4,
      std::__1::allocator<unsigned long>, true>, xt::xtensor_expression_tag> >' requested here
        detail::recurser_run(p, d, sv, lim);
                ^
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xio.hpp:630:16: note: in instantiation of function template specialization 'xt::pretty_print<xt::xarray_container<xt::uvector<double,
      std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned long, 4, std::__1::allocator<unsigned long>, true>, xt::xtensor_expression_tag> >' requested here
        return pretty_print(e, out);
               ^
test.cpp:10:13: note: in instantiation of function template specialization 'xt::operator<<<xt::xarray_container<xt::uvector<double, std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned
      long, 4, std::__1::allocator<unsigned long>, true>, xt::xtensor_expression_tag> >' requested here
  std::cout << a;
            ^
In file included from test.cpp:3:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xarray.hpp:19:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xcontainer.hpp:23:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xmath.hpp:27:
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xstrided_view.hpp:486:25: warning: suggest braces around initialization of subobject [-Wmissing-braces]
                return {0, 0, 0};
                        ^~~~~~~
                        {      }
/Users/tdegeus/miniconda3/envs/sim/include/xtl/xvariant_impl.hpp:546:18: note: in instantiation of function template specialization 'xt::detail::slice_getter_impl<xt::svector<unsigned long, 4,
      std::__1::allocator<unsigned long>, true> >::operator()<xt::xnewaxis_tag>' requested here
          RETURN(lib::forward<F>(f)(lib::forward<As>(as)...))
                 ^
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xio.hpp:617:17: note: in instantiation of function template specialization
      'xt::detail::recurser_run<xt::detail::printer<xt::xarray_container<xt::uvector<double, std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned long, 4, std::__1::allocator<unsigned
      long>, true>, xt::xtensor_expression_tag>, void>, xt::xarray_container<xt::uvector<double, std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned long, 4,
      std::__1::allocator<unsigned long>, true>, xt::xtensor_expression_tag> >' requested here
        detail::recurser_run(p, d, sv, lim);
                ^
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xio.hpp:630:16: note: in instantiation of function template specialization 'xt::pretty_print<xt::xarray_container<xt::uvector<double,
      std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned long, 4, std::__1::allocator<unsigned long>, true>, xt::xtensor_expression_tag> >' requested here
        return pretty_print(e, out);
               ^
test.cpp:10:13: note: in instantiation of function template specialization 'xt::operator<<<xt::xarray_container<xt::uvector<double, std::__1::allocator<double> >, xt::layout_type::row_major, xt::svector<unsigned
      long, 4, std::__1::allocator<unsigned long>, true>, xt::xtensor_expression_tag> >' requested here
  std::cout << a;
            ^
In file included from test.cpp:3:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xarray.hpp:19:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xcontainer.hpp:23:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xmath.hpp:27:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xstrided_view.hpp:24:
In file included from /Users/tdegeus/miniconda3/envs/sim/include/xtensor/xsemantic.hpp:15:
/Users/tdegeus/miniconda3/envs/sim/include/xtensor/xassign.hpp:495:19: warning: unused type alias 'size_type' [-Wunused-local-typedef]
            using size_type = typename E1::size_type;
                  ^
18 warnings generated.

I am on v.0.16.4 (the version I got from conda).

Hi,
I am fixing the valid issues. However, the missing braces one is invalid + wrong (as explained here: https://stackoverflow.com/a/48413842/1347553) and has been removed from Clang 6 as this is aggregate initialization :)
Cheers!

#990 has been merged! :tada:

Hi,
I understand. Note that mac users will see this bug for a long time, as the current Xcode appears to be based on clang 4.0.

actually the other option (briefly discussed on gitter: https://gitter.im/QuantStack/Lobby if you're interested!) would be to include xtensor as a system library from CMake. In that mode compilers supress warnings originating from the library, assuming that it's right. That doesn't mean we shouldn't attempt at keeping warnings low, but it would reduce the clutter of good (or bad) warnings on the enduser.

We could also switch to explicit instantiation with the type, e.g... would not be too much work
std::array<...>({...}) instead of just {...}

This is indeed what I often do (at least, I assume as I cannot directly find the discussion). This could be in documentation.
Still using other build tools (such as a setup.py) this will not help.
P.S. I tried 'installing' xtensor through
cmake /path/to/clone
make install

But this falls over the xtl dependency. Installing xtl the same way fails again over the JSON dependency. That, I think, does not come with a default CMake mechanism.

What is the proper way to install this way?
Can this be simplified, such that the installation of xtensor takes into account these dependencies automatically?

(I can use conda, but I'm not sure that will be favourable on our cluster, so installing this way may be relevant.)


[#148 Implement TES Task Runner] Implement SAS resolution strategy for DRS

Overview
The TES Task Runner provides an extensibility mechanism to enable just-in-time SAS token resolution on the Batch Nodes. The goal of this story is to implement a new SAS resolution strategy when DRS URLs are provided.
AC:

Must implement the current DRS approach as SAS resolution strategy in the runner.
Should consider removing the dependency with DRS downloader and perform the resolution calls directly.
Must add options to the runner to enable DRS SAS resolution .
Must refactor the scheduler to use this strategy when applicable.

DoD:

Code merge into main, with unit tests that demonstrate the functionality.
Documented options for the runner and the API if applicable,

Notes: Consider the following WRT the DRS Localizer (which is the current DRS approach):

Due to the reason for #391 & #390 some of the command-line options we are using are no longer valid (specifically --vault-name and --secret-name. Both should be removed, along with all the configuration that drives them. See #392.
The DRS Localizer actually allows all of the DRS downloads to be passed via the command-line in just one call (rather than serially calling the localizer repeatedly for each call). That option is named --manifest-path and requires one argument, a CSV file with two columns (Url, Path) and one row per input file. The file should be without headers and should follow RFC-4180 formatting.
The DRS Localizer uses another option (--identity-client-id) for authorization (pass the ClientId of the azure managed identity) which we should be setting. This means that the container running the localizer needs to not be blocked.
The DRS Localizer uses the following environment variables we have not been using: DRS_RESOLVER_NUM_RETRIES, DRS_RESOLVER_WAIT_INITIAL_SECONDS, DRS_RESOLVER_WAIT_MAXIMUM_SECONDS, DRS_RESOLVER_WAIT_MULTIPLIER, DRS_RESOLVER_WAIT_RANDOMIZATION_FACTOR. We should consider whether we should provide any of these, or simply continue to use the defaults.

The following is provided because it is no longer showing up in the source code:
DRS files are identified via this line of code: task.Inputs.Where(f => f?.Url?.StartsWith("drs://", StringComparison.OrdinalIgnoreCase) == true)
The docker image is available in BatchScheduler as cromwellDrsLocalizerImageName, the resolver URL (found currently in Options.MarthaOptions.Url) is passed double-quoted via the DRS_RESOLVER_URL environment variable, the command-line option --access-token-strategy azure is always provided, and the container should run with the same volume mounts options as the executor. When not using the manifest file, the Url and Path should be passed as command-line arguments in that same order.


Update sponsors and Socratic 14 date

v. confused why I had a few old commits come over into this PR. My fork of master is updated and when I try to rebase, it says everything is up to date.
Diff is accurate though!

I didn't know that file existed! Ty and fixed! Merging.


Python 3.9 support

does phusion supports python 3.9?
I'm unable to install

There should be no reason why you cannot install Python 3.9 -- perhaps if you were more specific with your particular issue, we could provide possible solutions.

There should be no reason why you cannot install Python 3.9 -- perhaps if you were more specific with your particular issue, we could provide possible solutions.


SAM-2540 joda 2.4 -> joda 2.7

http://www.joda.org/joda-time/upgradeto270.html
http://www.joda.org/joda-time/upgradeto260.html
http://www.joda.org/joda-time/upgradeto250.html

This was merged as part of PR #393.


[DBASE] Add support for Spring Data Functionalities

All services have backend in-memory database support. We're using H2 to support database operations for the time being. Later, postgres should be implemented. Closing this issue.


Fix Reshape copy condition

Copies were made by chainerx::Reshape where views would suffice, due to an unnecessarily strict check. This PR fixes that check.
A side note. chainerx::ExpandDims simply calls chainexr::Reshape to add an axis. This should in practice not incur a copy. However, it could in certain cases. The following assertion would e.g. fail. This is fixed and tested in this PR.
import chainerx as chx

a = chx.random.uniform(-1, 1, (2, 1, 3)).T
b = a.reshape(1, 3, 1, 2)  # Just an "expand dims".
assert a.data_ptr == b.data_ptr  # Would fail, meaning a copy was created.

Jenkins, test this please.

Jenkins CI test (for commit c31abb8a172dfd2c668f02c1912522d9bd3d59d8, target branch master) succeeded!

LGTM.


Validation of pubsub messages?

As I understand agregore browser enables pubsub subscriptions through fetch API.
I'm planning to use agregore for my project, but in addition to using pubsub it will eventually need to validate messages received through pubsub. I read that it is possible to tell libp2p which messages are valid so that invalid ones are not propagated. This would be useful for my use case. Searching around, I found that the way to do it in js is probably through datastore-pubsub.
I could probably add a dependency to js-datastore-pubsub for my webapp, but I see agregore already depends on ipfs-core, which depends on datastore-pubsub. And I was planning to use fetch API provided by agregore anyway.
Would it make sense for agregore to provide datastore-pubsub like API? Any advice for a solution in the short-term?

At this stage, I would just perform the validation of the data upon receiving it in your JavaScript once you get the message in your EventSource.
Getting the validation logic from JS into the p2p protocol handler is a bit hard to do at the moment. We're making use of js-ipfs-core for wrapping over libp2p's pubsub right now and it looks like there's no interface there for doing extra validation the way there is in Go. https://github.com/ipfs/js-ipfs/blob/master/docs/core-api/PUBSUB.md
What sort of validation logic were you hoping to do? Checking that the structure makes sense?

I can do the validation after getting the message from EventSource. I'm more worried about the propagation of messages. Pubsub topic strings will be public and I'm wondering what will happen if someone starts spamming with invalid messages to that topic.
Does the ipfs node within agregore automatically propagate messages they subscribe to? If detect invalid only in my logic that won't stop the propagation of the messages I imagine, right?

To answer your question about validation logic: validation might depend on some objects which will have to be fetched from IPFS by some peers. Some peers might already have it. I'd like peers who already have to not propagate invalid messages, so as to not make new peers do unecessary fetching and validation.

Do you have any thoughts on what the fetch/EventSource interface should do to enable this?
It feels like we would need to add some way to execute arbitrary code that gets passed in from JS (maybe WASM?) but that also feels like major overkill.
Is this a major blocker for getting your app started / do you anticipate it being mandatory for things to work within the next 6 months or so?

It's definitely not a blocker to get started. I just suspect it might become an issue later. I'm also considering some workarounds using IPNS.


Merge ROTATE_LEFT and ROTATE_RIGHT gestures into one ROTATE gesture

@auras Please update the test cases using the same commit. Right they won't compile.

Please merge all 3 commits into a single commit as the first commit doesn't compile the tests.

Done

Good job!


How to fix "expected a borrowed string" issue on custom deserializer when migrating from 0.5.x to 0.7.x?

I've recently tried upgrade from toml 0.5 to 0.7, and getting some errors when trying to use custom deserializers in serde that used to work with 0.5.x. I've read the changelog and can see some things related to that changed, but I couldn't figure out what was needed to fix it.
I've got a struct that can be deserialized from a bunch of different formats (including JSON and TOML). Here's a minimal example of the sort of thing that worked in 0.5, but gives me an error on 0.7:
playground link
use serde::{Deserialize, de::Deserializer};

#[derive(Deserialize)]
struct Config {
    #[allow(dead_code)]
    #[serde(deserialize_with = "deserialize_enabled_field")]
    enabled: bool,
}

fn deserialize_enabled_field<'de, D: Deserializer<'de>>(
    deserializer: D,
) -> Result<bool, D::Error> {
    let s: &str = Deserialize::deserialize(deserializer)?;
    Ok(match s {
        "yes" | "y" | "true" | "t" => true,
        _ => false
    })
}

fn main() {
    let json_data = r#" {"enabled": "true"} "#;
    let _: Config = serde_json::from_str(json_data).unwrap();

    let toml_data = r#" "enabled" = "true" "#;
    let _: Config = toml::from_str(toml_data).unwrap();
}

This gives the error:
thread 'main' panicked at 'called `Result::unwrap()` on an `Err` value: Error { inner: Error { inner: TomlError { message: "invalid type: string \"true\", expected a borrowed string", original: Some(" \"enabled\" = \"true\" "), keys: ["enabled"], span: Some(13..19) } } }', src/main.rs:25:47

You'll likely need to change
let s: &str = Deserialize::deserialize(deserializer)?;

to
let s: String = Deserialize::deserialize(deserializer)?;

Thanks, I'll do some testing around that. In the real app the custom deserializer gets called millions of times (mostly from JSON), so I'll check if there's any performance impact from the switch.

If so, you likely can improve the performance by using a custom deserialize visitor.


May I ask where to configure Webhooks callbacks for Docker deployment

Why this feature?
May I ask where to configure Webhooks callbacks for Docker deployment
Suggested Solution
May I ask where to configure Webhooks callbacks for Docker deployment
Additional Information
No response

https://github.com/openimsdk/openim-docker/issues/136

#136

The configuration method for deploying the source code in this is not found for Docker deployment

Please use environment variables, for more details refer to this issue
https://github.com/openimsdk/openim-docker/issues/136


cargo run --example winit_imgui

After apply the patch https://github.com/aclysma/skulpin/pull/73
C:\Users\hunt\source\repos\skulpin>cargo run --example winit_imgui
   Compiling skulpin-app-winit v0.4.0 (C:\Users\hunt\source\repos\skulpin\skulpin-app-winit)
   Compiling skulpin v0.10.0 (C:\Users\hunt\source\repos\skulpin)
error[E0308]: mismatched types
   --> examples\imgui_support\mod.rs:113:57
    |
113 |                 platform.handle_event(context.io_mut(), &window, event);
    |                                                         ^^^^^^^ expected struct `winit::window::Window`, found `&skulpin_renderer_winit::winit::window::Window`
    |
    = note: expected reference `&winit::window::Window`
               found reference `&&skulpin_renderer_winit::winit::window::Window`

error[E0308]: mismatched types
   --> examples\imgui_support\mod.rs:113:66
    |
113 |                 platform.handle_event(context.io_mut(), &window, event);
    |                                                                  ^^^^^ expected enum `winit::event::Event`, found enum `skulpin_renderer_winit::winit::event::Event`
    |
    = note: expected reference `&winit::event::Event<'_, _>`
               found reference `&skulpin_renderer_winit::winit::event::Event<'_, T>`
    = note: perhaps two different versions of crate `winit` are being used?

error[E0308]: mismatched types
   --> examples\imgui_support\mod.rs:187:52
    |
187 |             .prepare_frame(inner.context.io_mut(), window)
    |                                                    ^^^^^^ expected struct `winit::window::Window`, found struct `skulpin_renderer_winit::winit::window::Window`
    |
    = note: expected reference `&winit::window::Window`
               found reference `&skulpin_renderer_winit::winit::window::Window`
    = note: perhaps two different versions of crate `winit` are being used?

error[E0308]: mismatched types
   --> examples\imgui_support\mod.rs:225:48
    |
225 |             inner.platform.prepare_render(&ui, window);
    |                                                ^^^^^^ expected struct `winit::window::Window`, found struct `skulpin_renderer_winit::winit::window::Window`
    |
    = note: expected reference `&winit::window::Window`
               found reference `&skulpin_renderer_winit::winit::window::Window`
    = note: perhaps two different versions of crate `winit` are being used?

error[E0308]: mismatched types
   --> examples\imgui_support\mod.rs:299:9
    |
299 |         window,
    |         ^^^^^^ expected struct `winit::window::Window`, found struct `skulpin_renderer_winit::winit::window::Window`
    |
    = note: expected reference `&winit::window::Window`
               found reference `&skulpin_renderer_winit::winit::window::Window`
    = note: perhaps two different versions of crate `winit` are being used?

error: aborting due to 5 previous errors

For more information about this error, try `rustc --explain E0308`.
error: could not compile `skulpin`.

To learn more, run the command again with --verbose.

C:\Users\hunt\source\repos\skulpin>

https://github.com/Gekkio/imgui-rs/pull/371


Enable Python CHIP Controller on Raspbian

Problem

Make Python CHIP Controller build and run on Raspberry Pi 4 with Raspbian

Change overview
Minor build changes that was made to make it build and start on Raspbian
Testing

Sections "Building and installing" and "Running the tool" from:
https://github.com/project-chip/connectedhomeip/blob/e5bd5f3703b45b43b4cee4a5178586ca9fc01610/docs/guides/python_chip_controller_building.md

 Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.You have signed the CLA already but the status is still pending? Let us recheck it.


Add .token.class-name to rest of themes

Hi, thanks for taking care of this.
I noticed the Tomorrow Night theme and the Coy theme already have the class-name handled actually, so there should be nothing to change in these files.
On the contrary, we should add support for it in the Solarized Light theme.
The change in the Okaidia theme looks good to me.

@paladox Would love to get this in. Would you be able to make the minor changes requested here?

Done.

@mAAdhaTTah No, the changes in  themes/prism-coy.css and themes/prism-tomorrow.css need to be reverted. Those themes already handle the class-name token (line 149 in Coy, and 79 in Tomorrow).

@Golmote done.

@paladox Thank you!

your welcome :).


Please invite me to the GitHub Community Organization

Name
Rajaniraiyn
Discord Username (if applicable)
No response
Additional Context
I am an open-source freak. Currently I am working on a very large Project Raj Lang, for that I need a lot of friends. I have a goal to achieve tech self-sustainability. I come to know that this organization has done a great job on promoting opensource around the world. I have a desire to contribute to the world.

Welcome to the community 😄 Check your default GitHub Email for an invite


Respond to Global media shortcut keys

It's great if the program can respond to Global media shortcut keys.
python-xlib seems to be able to record key events when the window is not in focus.

Added global key function in #147 , please check it out

Closed via #147


[Web Application] - Implement Joystick

As a user, I would like to be able to move the car with precision, so that I can avoid obstacles and move according to my desired path.


emmet

Issue Type: Feature Request
i can not find emmet extension to download in vscode
VS Code version: Code 1.56.2 (054a9295330880ed74ceaedda236253b4f39a335, 2021-05-12T16:45:26.313Z)
OS version: Linux x64 5.8.0-53-generic

It is built in ;)


[ServiceBus] Fix typos

Had it search for typos in the solution. Then, I went through them and fixed them.
And yes, it is dead-letter: https://docs.microsoft.com/en-us/azure/service-bus-messaging/service-bus-dead-letter-queues

@pakrym - this has some doc fixes for Core as well.


Remove unused packages of patched legacy stdlibs

rm -rf core/http/{cookiejar cgi fcgi httptest httputil pprof testdata}
we don't need those packages and testdata as we never encourage others to use the core/http/** or run their tests.

LGTM, is travis borked?

yeah I can't tell what's going on even though I have org owner permissions.

amend/push -f triggered it now.


Blaze documentation: Install

Hello,
"Install" section of "Getting Started" needs to revised. There are four CDN links mentioned there, currently, but only first one is live:
http://blazecss.com/getting-started/install/

Ah yes. Thanks for the catch!


Call to a member function isLoggedIn() on a non-object when attempting to add a page

Attempting to add the page type "Blog" from the pages and navigation menu, got the following error:
"Call to a member function isLoggedIn() on a non-object"
When I switched the error messaging to verbose and tried again, I generated the attached
adding blog page error
error adding blog page 20160820.txt
One is a cut-pasted text file, the other is a screenshot of the top portion of the report.
If it's helpful, I am hosted on webhostingpad.com. The beta resides  in a subfolder to my main site (http://mileditors.com/beta). I installed the fully populated versions of Elemental and Stucco, then deleted all pages but Home.

I think this is an error of the Theme Stucco you are using. This GitHub repository is only for the core of concrete5.
You should contact the author of that theme here: https://www.concrete5.org/marketplace/themes/stucco/support


We are using the solutions which you have provided but the issue is still not resolved.

We are using the solutions which you have provided but the issue is still not resolved.

Not much to go on here.  Closing.  Feel free to open an issue that contains more information.


Dan/prototype infra changes dashboard

:nut_and_bolt: Description: What code changed, and why?
Thus far, it just adds the boilerplate needed to use Postgres to config-mgmt service.
:chains: Related Resources
:+1: Definition of Done
:athletic_shoe: How to Build and Test the Change
:white_check_mark: Checklist

[ ] I have read the CONTRIBUTING document.
[ ] Tests added/updated?
[ ] Docs added/updated?
[ ] All commits have been signed-off for the Developer Certification of Origin.

:camera: Screenshots, if applicable

The not-prototype implementation is being worked, see #4032 #3993 #3895 #3887 #3882 (so far)


Solidity Incompatible version error message - doing simple-nft-example branch yarn mint

Describe the bug

To Reproduce
VSCode - switched branch to simple-nft-example / ran instructions "as-is" / HOWEVER - wonder if doc should mention the user should cd back to scaffold-eth directory in order to run the yarn mint
Expected behavior
expected to NOT have a incompatible version of Solidity error
Screenshots
see above SS
Desktop (please complete the following information):

OS: Win X
Browser Brave 1.2=30.87

Smartphone (please complete the following information):
N/A
Additional context
I'm using WSL2 with VSCode / the doc is not clear on if and when switching "branches" / if and whether to "clone" to a sub-directory of the same parent project directory (i.e., sibling to scafold-eth).  This time (after having git issues on the later) - I followed the directions exactly - making the simple-nft-example a git into as a subdirectory of scaffold-eth.

The "doc" implies to be in the brach directory - in this case simple-nft-example.  Should the user/me be in the parent project directory?  (one level up = scaffold-eth).  So -yes, I was in simple-nft-example, when I ran the mint script.  Should I have been in scaffold-eth?  If so, then please change the doc.  Pls advise


[e2e]: docker-based schedule main gcp-workload-identity slsa3

Repo: https://github.com/slsa-framework/example-package/tree/main
Run: https://github.com/slsa-framework/example-package/actions/runs/5064275536
Workflow file: https://github.com/slsa-framework/example-package/tree/main/.github/workflows/e2e.docker-based.schedule.main.gcp-workload-identity.slsa3.yml
Workflow runs: https://github.com/slsa-framework/example-package/actions/workflows/e2e.docker-based.schedule.main.gcp-workload-identity.slsa3.yml
Trigger: schedule
Branch: main
Date: Wed May 24 03:11:11 UTC 2023

Repo: https://github.com/slsa-framework/example-package/tree/main
Run: https://github.com/slsa-framework/example-package/actions/runs/5075655541
Workflow file: https://github.com/slsa-framework/example-package/tree/main/.github/workflows/e2e.docker-based.schedule.main.gcp-workload-identity.slsa3.yml
Workflow runs: https://github.com/slsa-framework/example-package/actions/workflows/e2e.docker-based.schedule.main.gcp-workload-identity.slsa3.yml
Trigger: schedule
Branch: main
Date: Thu May 25 03:09:49 UTC 2023

Repo: https://github.com/slsa-framework/example-package/tree/main
Run: https://github.com/slsa-framework/example-package/actions/runs/5086785164
Workflow file: https://github.com/slsa-framework/example-package/tree/main/.github/workflows/e2e.docker-based.schedule.main.gcp-workload-identity.slsa3.yml
Workflow runs: https://github.com/slsa-framework/example-package/actions/workflows/e2e.docker-based.schedule.main.gcp-workload-identity.slsa3.yml
Trigger: schedule
Branch: main
Date: Fri May 26 03:09:41 UTC 2023

Passing after rename: https://github.com/slsa-framework/example-package/actions/runs/5117196968


使用paddledetection 训练faster_rcnn_r50_fpn_2x  转ONNX报错，提示Exception: ONNX model is not valid

使用paddledetection 训练faster_rcnn_r50_fpn_2x  转ONNX报错，提示Exception: ONNX model is not valid，是有不支持的OP吗
C:\PaddleDetection\inference_model>paddle2onnx --model_dir haidaipianyi --model_filename model.pdmodel --params_filename model.pdiparams --save_file model.onnx  --enable_dev_version False --opset_version 16
c:\program files\python39\lib\site-packages\onnx\mapping.py:27: DeprecationWarning: np.object is a deprecated alias for the builtin object. To silence this warning, use object by itself. Doing this will not modify any behavior and is safe.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
int(TensorProto.STRING): np.dtype(np.object)
c:\program files\python39\lib\site-packages\paddle\fluid\layers\math_op_patch.py:336: UserWarning: c:\program files\python39\lib\site-packages\paddle2onnx\op_mapper\custom_paddle_op\generate_proposals.py:107
The behavior of expression A - B has been unified with elementwise_sub(X, Y, axis=-1) from Paddle 2.0. If your code works well in the older versions but crashes in this version, try to use elementwise_sub(X, Y, axis=0) instead of A - B. This transitional warning will be dropped in the future.
warnings.warn(
c:\program files\python39\lib\site-packages\paddle\fluid\layers\math_op_patch.py:336: UserWarning: c:\program files\python39\lib\site-packages\paddle2onnx\op_mapper\custom_paddle_op\generate_proposals.py:108
The behavior of expression A - B has been unified with elementwise_sub(X, Y, axis=-1) from Paddle 2.0. If your code works well in the older versions but crashes in this version, try to use elementwise_sub(X, Y, axis=0) instead of A - B. This transitional warning will be dropped in the future.
warnings.warn(
c:\program files\python39\lib\site-packages\paddle\fluid\layers\math_op_patch.py:336: UserWarning: c:\program files\python39\lib\site-packages\paddle2onnx\op_mapper\custom_paddle_op\generate_proposals.py:109
The behavior of expression A + B has been unified with elementwise_add(X, Y, axis=-1) from Paddle 2.0. If your code works well in the older versions but crashes in this version, try to use elementwise_add(X, Y, axis=0) instead of A + B. This transitional warning will be dropped in the future.
warnings.warn(
c:\program files\python39\lib\site-packages\paddle\fluid\layers\math_op_patch.py:336: UserWarning: c:\program files\python39\lib\site-packages\paddle2onnx\op_mapper\custom_paddle_op\generate_proposals.py:110
The behavior of expression A + B has been unified with elementwise_add(X, Y, axis=-1) from Paddle 2.0. If your code works well in the older versions but crashes in this version, try to use elementwise_add(X, Y, axis=0) instead of A + B. This transitional warning will be dropped in the future.
warnings.warn(
c:\program files\python39\lib\site-packages\paddle\fluid\layers\math_op_patch.py:336: UserWarning: c:\program files\python39\lib\site-packages\paddle2onnx\op_mapper\custom_paddle_op\generate_proposals.py:116
The behavior of expression A * B has been unified with elementwise_mul(X, Y, axis=-1) from Paddle 2.0. If your code works well in the older versions but crashes in this version, try to use elementwise_mul(X, Y, axis=0) instead of A * B. This transitional warning will be dropped in the future.
warnings.warn(
c:\program files\python39\lib\site-packages\paddle\fluid\layers\math_op_patch.py:336: UserWarning: c:\program files\python39\lib\site-packages\paddle2onnx\op_mapper\custom_paddle_op\generate_proposals.py:116
The behavior of expression A + B has been unified with elementwise_add(X, Y, axis=-1) from Paddle 2.0. If your code works well in the older versions but crashes in this version, try to use elementwise_add(X, Y, axis=0) instead of A + B. This transitional warning will be dropped in the future.
warnings.warn(
c:\program files\python39\lib\site-packages\paddle\fluid\layers\math_op_patch.py:336: UserWarning: c:\program files\python39\lib\site-packages\paddle2onnx\op_mapper\custom_paddle_op\generate_proposals.py:117
The behavior of expression A * B has been unified with elementwise_mul(X, Y, axis=-1) from Paddle 2.0. If your code works well in the older versions but crashes in this version, try to use elementwise_mul(X, Y, axis=0) instead of A * B. This transitional warning will be dropped in the future.
warnings.warn(
c:\program files\python39\lib\site-packages\paddle\fluid\layers\math_op_patch.py:336: UserWarning: c:\program files\python39\lib\site-packages\paddle2onnx\op_mapper\custom_paddle_op\generate_proposals.py:117
The behavior of expression A + B has been unified with elementwise_add(X, Y, axis=-1) from Paddle 2.0. If your code works well in the older versions but crashes in this version, try to use elementwise_add(X, Y, axis=0) instead of A + B. This transitional warning will be dropped in the future.
warnings.warn(
c:\program files\python39\lib\site-packages\paddle\fluid\layers\math_op_patch.py:336: UserWarning: c:\program files\python39\lib\site-packages\paddle2onnx\op_mapper\custom_paddle_op\generate_proposals.py:120
The behavior of expression A * B has been unified with elementwise_mul(X, Y, axis=-1) from Paddle 2.0. If your code works well in the older versions but crashes in this version, try to use elementwise_mul(X, Y, axis=0) instead of A * B. This transitional warning will be dropped in the future.
warnings.warn(
c:\program files\python39\lib\site-packages\paddle\fluid\layers\math_op_patch.py:336: UserWarning: c:\program files\python39\lib\site-packages\paddle2onnx\op_mapper\custom_paddle_op\generate_proposals.py:118
The behavior of expression A * B has been unified with elementwise_mul(X, Y, axis=-1) from Paddle 2.0. If your code works well in the older versions but crashes in this version, try to use elementwise_mul(X, Y, axis=0) instead of A * B. This transitional warning will be dropped in the future.
warnings.warn(
c:\program files\python39\lib\site-packages\paddle\fluid\layers\math_op_patch.py:336: UserWarning: c:\program files\python39\lib\site-packages\paddle2onnx\op_mapper\custom_paddle_op\generate_proposals.py:123
The behavior of expression A * B has been unified with elementwise_mul(X, Y, axis=-1) from Paddle 2.0. If your code works well in the older versions but crashes in this version, try to use elementwise_mul(X, Y, axis=0) instead of A * B. This transitional warning will be dropped in the future.
warnings.warn(
c:\program files\python39\lib\site-packages\paddle\fluid\layers\math_op_patch.py:336: UserWarning: c:\program files\python39\lib\site-packages\paddle2onnx\op_mapper\custom_paddle_op\generate_proposals.py:121
The behavior of expression A * B has been unified with elementwise_mul(X, Y, axis=-1) from Paddle 2.0. If your code works well in the older versions but crashes in this version, try to use elementwise_mul(X, Y, axis=0) instead of A * B. This transitional warning will be dropped in the future.
warnings.warn(
c:\program files\python39\lib\site-packages\paddle\fluid\layers\math_op_patch.py:336: UserWarning: c:\program files\python39\lib\site-packages\paddle2onnx\op_mapper\custom_paddle_op\generate_proposals.py:126
The behavior of expression A - B has been unified with elementwise_sub(X, Y, axis=-1) from Paddle 2.0. If your code works well in the older versions but crashes in this version, try to use elementwise_sub(X, Y, axis=0) instead of A - B. This transitional warning will be dropped in the future.
warnings.warn(
c:\program files\python39\lib\site-packages\paddle\fluid\layers\math_op_patch.py:336: UserWarning: c:\program files\python39\lib\site-packages\paddle2onnx\op_mapper\custom_paddle_op\generate_proposals.py:127
The behavior of expression A - B has been unified with elementwise_sub(X, Y, axis=-1) from Paddle 2.0. If your code works well in the older versions but crashes in this version, try to use elementwise_sub(X, Y, axis=0) instead of A - B. This transitional warning will be dropped in the future.
warnings.warn(
c:\program files\python39\lib\site-packages\paddle\fluid\layers\math_op_patch.py:336: UserWarning: c:\program files\python39\lib\site-packages\paddle2onnx\op_mapper\custom_paddle_op\generate_proposals.py:128
The behavior of expression A + B has been unified with elementwise_add(X, Y, axis=-1) from Paddle 2.0. If your code works well in the older versions but crashes in this version, try to use elementwise_add(X, Y, axis=0) instead of A + B. This transitional warning will be dropped in the future.
warnings.warn(
c:\program files\python39\lib\site-packages\paddle\fluid\layers\math_op_patch.py:336: UserWarning: c:\program files\python39\lib\site-packages\paddle2onnx\op_mapper\custom_paddle_op\generate_proposals.py:129
The behavior of expression A + B has been unified with elementwise_add(X, Y, axis=-1) from Paddle 2.0. If your code works well in the older versions but crashes in this version, try to use elementwise_add(X, Y, axis=0) instead of A + B. This transitional warning will be dropped in the future.
warnings.warn(
c:\program files\python39\lib\site-packages\paddle\fluid\layers\math_op_patch.py:336: UserWarning: c:\program files\python39\lib\site-packages\paddle2onnx\op_mapper\custom_paddle_op\generate_proposals.py:72
The behavior of expression A - B has been unified with elementwise_sub(X, Y, axis=-1) from Paddle 2.0. If your code works well in the older versions but crashes in this version, try to use elementwise_sub(X, Y, axis=0) instead of A - B. This transitional warning will be dropped in the future.
warnings.warn(
c:\program files\python39\lib\site-packages\paddle\fluid\layers\math_op_patch.py:336: UserWarning: c:\program files\python39\lib\site-packages\paddle2onnx\op_mapper\custom_paddle_op\generate_proposals.py:73
The behavior of expression A - B has been unified with elementwise_sub(X, Y, axis=-1) from Paddle 2.0. If your code works well in the older versions but crashes in this version, try to use elementwise_sub(X, Y, axis=0) instead of A - B. This transitional warning will be dropped in the future.
warnings.warn(
c:\program files\python39\lib\site-packages\paddle\fluid\framework.py:744: DeprecationWarning: np.bool is a deprecated alias for the builtin bool. To silence this warning, use bool by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use np.bool_ here.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
elif dtype == np.bool:
c:\program files\python39\lib\site-packages\paddle\fluid\layers\math_op_patch.py:336: UserWarning: c:\program files\python39\lib\site-packages\paddle2onnx\op_mapper\custom_paddle_op\distribute_fpn_proposals.py:38
The behavior of expression A - B has been unified with elementwise_sub(X, Y, axis=-1) from Paddle 2.0. If your code works well in the older versions but crashes in this version, try to use elementwise_sub(X, Y, axis=0) instead of A - B. This transitional warning will be dropped in the future.
warnings.warn(
c:\program files\python39\lib\site-packages\paddle\fluid\layers\math_op_patch.py:336: UserWarning: c:\program files\python39\lib\site-packages\paddle2onnx\op_mapper\custom_paddle_op\distribute_fpn_proposals.py:39
The behavior of expression A - B has been unified with elementwise_sub(X, Y, axis=-1) from Paddle 2.0. If your code works well in the older versions but crashes in this version, try to use elementwise_sub(X, Y, axis=0) instead of A - B. This transitional warning will be dropped in the future.
warnings.warn(
c:\program files\python39\lib\site-packages\paddle\fluid\layers\math_op_patch.py:336: UserWarning: c:\program files\python39\lib\site-packages\paddle2onnx\op_mapper\custom_paddle_op\distribute_fpn_proposals.py:40
The behavior of expression A * B has been unified with elementwise_mul(X, Y, axis=-1) from Paddle 2.0. If your code works well in the older versions but crashes in this version, try to use elementwise_mul(X, Y, axis=0) instead of A * B. This transitional warning will be dropped in the future.
warnings.warn(
c:\program files\python39\lib\site-packages\onnx\helper.py:343: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working
is_iterable = isinstance(value, collections.Iterable)
2022-05-23 20:36:45 [WARNING]   Due to the operator:multiclass_nms3, the converted ONNX model will only supports input[batch_size] == 1.
2022-05-23 20:36:48 [INFO]      ONNX model generated is valid.
Traceback (most recent call last):
File "c:\program files\python39\lib\site-packages\paddle2onnx\utils.py", line 43, in check_model
onnx.checker.check_model(onnx_model)
File "c:\program files\python39\lib\site-packages\onnx\checker.py", line 104, in check_model
C.check_model(protobuf_string)
onnx.onnx_cpp2py_export.checker.ValidationError: Nodes in a graph must be topologically sorted, however input 'S' of node:
name: NonMaxSuppression_5 OpType: NonMaxSuppression
is not output of any previous nodes.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "c:\program files\python39\lib\runpy.py", line 197, in _run_module_as_main
return _run_code(code, main_globals, None,
File "c:\program files\python39\lib\runpy.py", line 87, in run_code
exec(code, run_globals)
File "C:\Program Files\Python39\Scripts\paddle2onnx.exe_main.py", line 7, in
File "c:\program files\python39\lib\site-packages\paddle2onnx\command.py", line 273, in main
program2onnx(
File "c:\program files\python39\lib\site-packages\paddle2onnx\command.py", line 200, in program2onnx
p2o.program2onnx(
File "c:\program files\python39\lib\site-packages\paddle2onnx\convert.py", line 95, in program2onnx
return export_onnx(
File "c:\program files\python39\lib\site-packages\paddle2onnx\convert.py", line 40, in export_onnx
onnx_proto = onnx_graph.export_proto(enable_onnx_checker, output_names)
File "c:\program files\python39\lib\site-packages\paddle2onnx\graph\onnx_graph.py", line 313, in export_proto
check_model(onnx_proto)
File "c:\program files\python39\lib\site-packages\paddle2onnx\utils.py", line 45, in check_model
raise Exception('ONNX model is not valid.')
Exception: ONNX model is not valid.

将你的onnx版本升级至最新试下
pip install onnx --upgrade

已经是最新的版本了

是指升级onnx，而非paddle2onnx

确实使用的都是最新版本，并且更换了一台设备之后报同样的错误

您好，为了快速解决这个问题，麻烦将要转换的Paddle模型上传到网盘，然后给我一个链接吧，谢谢

另外请问你转到ONNX的原因是？用什么推理引擎部署呢？

您好，为了快速解决这个问题，麻烦将要转换的Paddle模型上传到网盘，然后给我一个链接吧，谢谢

模型在这里，希望能够移植到xbox上，使用onnxruntime directML部署
链接：https://pan.baidu.com/s/158Xvm9xkdBAyL0OgVwtUZg
提取码：wzq5
--来自百度网盘超级会员V5的分享

你好，请使用这个PR进行测试：https://github.com/PaddlePaddle/Paddle2ONNX/pull/756

你好，请使用这个PR进行测试：#756

太好了，问题解决了，辛苦


Service seems offline

Hello. Working on that.

On 13 Mar 2021, at 17:34, Shyim @.***> wrote:
https://user-images.githubusercontent.com/6224096/111035274-f2f31d80-8419-11eb-8ac5-bb0a6487218a.png
—
You are receiving this because you are subscribed to this thread.
Reply to this email directly, view it on GitHub https://github.com/neoascetic/rawgithack/issues/60, or unsubscribe https://github.com/notifications/unsubscribe-auth/AAFRGTACZ5N6TKOQXGSKXALTDOAYPANCNFSM4ZD5TGZA.

Seems to be fixed. Sorry for inconvenience. There were problems with the network on the hosting side.

no problem. thanks for hosting it! 😊


SidebarLinks unnecessary re-renders

Problem:
When we open a report, we end up re-rendering parts of the UI that are not visible, specifically the SidebarLinks. This re-rendering of SidebarLinks is costly and negatively affects performance. Additionally, the re-rendering is unnecessary because it doesn't change anything in the UI. It only occurs because there are changes in the lastRead timestamp and the lastMentionedTime fields of the report that we just opened.
Importance:
When we measure performance, we observe a significant improvement when we optimize SidebarLinks to avoid unnecessary re-rendering (see screenshots).
Solution:
Certain parts of the UI require these specific fields, such as the LHNOptionRow, to be rendered as unread. However, it is not necessary to pass these fields to the entire list. Instead, we can link the OptionRows to the relevant section of the Onyx state to retrieve that information. (We need to measure if this approach of connecting each OptionRow to Onyx introduces any new performance issues.)
Upwork Automation - Do Not Edit

Upwork Job URL: https://www.upwork.com/jobs/~015effa438f02c3652
Upwork Job ID:<PHONE_NUMBER>755038208
Last Price Increase: 2023-06-19

👋

Unassigning as @0xmiroslav can handle the convo and I will be ooo next week

Proposal
Please re-state the problem that we are trying to solve in this issue.
When opening a report the SidebarLinks component is re-rendering at least twice, which is unnecessary work we want to avoid in order to gain better performance.
What is the root cause of that problem?
The SidebarLinks component is subscribed to the onyx data of the reports. It uses a selector to only pick the data necessary for the UI output. It selects the lastReadTime and lastMentionedTime properties, which are getting updated when opening a report:
https://github.com/Expensify/App/blob/1096b6e9cdbdf62a882d29d853a04257d14858fb/src/pages/home/sidebar/SidebarLinks.js#L272-L292
When running a diff in componentDidUpdate we can see that SidebarLinks is re-rendering due to these prop changes.
First lastReadTime changes causing a re-render and then lastMentionedTime changes as it can be seen here:

What changes do you think we should make in order to solve the problem?

The SidebarLinks itself doesn't need these two properties in order to do its job. When we look at what it does, it's just getting a list of report IDs and passing that to a list. The ID is then forwarded to each item of the list so that the item can take care of itself to get the data it needs for rendering.
So the SidebarLinks is only concerned with the order of the report IDs. For the order, the two named properties are however irrelevant.
Thus we shouldn't re-render the SidebarLinks only because these two properties have changed. So we remove the two properties from the selector.
When we look at how the OptionRowLHN component (the one that's rendered by SidebarLinks) is getting their data we understand why we currently connect these two properties to SidebarLinks:
https://github.com/Expensify/App/blob/40ece2391721d98b0207ebd1d32bfdc17dfe1342/src/components/LHNOptionsList/OptionRowLHN.js#L57-L62
Instead of connecting the onyx data directly to the component, we are using a utility module. This utility module loads the onyx data statically. It can't however notify the react component on data changes, thus the component wouldn't re-render when the data changes. That's the reason why at the parent level of SidebarLinks we are causing a re-render.
We can circumvent this by mapping the data directly to the OptionRowLHN component like this:
export default withOnyx({
        optionItem: {
            // ⚡ Notice how we are using the reportID from the props here to connect to the collection entry
            key: (props) => ONYXKEYS.COLLECTION.REPORT + props.reportID,
            // 👀 Instead of using the data statically retrieved in the utility, we pass it the data from onyx in a selector
            selector: (report) => SidebarUtils.getOptionData(report),
        },
    })(OptionRowLHN);

Notice how I didn't do SidebarUtils.getOptionData(props.reportID);.
This means the component will directly receive the props it needs for rendering, and not a pre-stage type of data that it needs to transform (because it might not need all the data from the pre-stage type, and thus might re-render unnecessarily).
I general i propose that when we can we get rid of that pattern as well. We are connecting multiple times unnecessarily to onyx and in general its against reacts patterns.
Instead, when we connect to onyx we should also forward that data directly to our utility functions.
(By transforming the data in the selector we are also preventing the component from re-rendering when the lastMentionedTime changes as it is transformed to another value).

@0xmiroslav Hm, looking at the I don't think the two tasks conflict with each other too much. So it's fine making this performance change without prior refactoring to FC, as the change isn't about anything that happens inside the component.
As I am by now quite familiar with the component I can take it however for a refactor later on.

Proposal part 2
Please re-state the problem that we are trying to solve in this issue.
When opening a report the SidebarLinks component is re-rendering at least twice, which is unnecessary work we want to avoid in order to gain better performance.
What is the root cause of that problem?
Another cause is that the SidebarLinks are re-rendering due to currentReportId changing (from the withCurrentReportId HOC).
This information is only needed to highlight the currently active report item.
What changes do you think we should make in order to solve the problem?
Again, we don't need to connect the whole list to this state, but should connect each item individually to that piece of state.

Here are two screenshots of the android release build before and after these changes:

Thanks for the proposal. @0xmiroslav any concerns?

This is being actively worked on now

PR in an active review

Still in review


feat: add 996-icu group in playground

This PR followed tutorial "Create your ZK Badge in 15 Minutes", and add 996-icu group in playground.

Hey @996icu, thanks for this ZK Badge! It should be deployed on playground.sismo.io in 5mn

@996fighter :-)


custom model does not work !

Hi @spring98 ,
I have fine tuned yolov5s.pt over a custom dataset, the resulting best.pt when loaded in the example app is not able to perform detection. Is there anything I am missing ? I have read the docs head to toe, followed the instructions on how to export the models. Though I must say, I have not yet exported the .mlmodel.
Any help or advice on how to make it work ?

Thank you for your interest in my plugin.
It would be great if you could provide some information!

Are you using it on Android? Are you using it on iOS?
mlmodel is for iOS only, so it is not needed if you do not use iOS.

Did you export the .pt file through modified_export.py?

You must use the exported torchscript.
That is, best.pt > best.torchscript (export and using)
Afterwards, just change the name of the best.torchscript file to best.pt.
Sorry for confusing you. If you have any further problems, please reply!!

Hey @spring98 , thanks for the prompt response!
Ah got it, I am trying that now.
Will keep you updated.
Thanks.

The app crashes on inferences. don't know why that happens though.

Does the code in the basic example not work?
And I think it would be helpful to have an image of the inference failure!!

The code in the example works fine with its weights.
On start of the app, it crashes 3 seconds, there are no error logs in my console either. I've had delete my build folder and rebuilt the app, but it still occurs. I am using an honor x6a for this project with a mediatek helio chipset.
I will get a different device and try a new build. All the same, I will keep this issue alive and updated until fully resolved. I love the learnings from the experiments!
Thank you.

It's a little strange that the log doesn't appear.
Have you made sure you set List active Classes, List full Classes to match your custom model?
Anyway, I support your spirit of challenge, and if there are any other issues, please let me know!!

@spring98 , I solved the hassle.
During the conversion from best.pt > best.torchscript, one has to make sure they take note of the --img flag. The compatible img size of the raw best.pt must be exactly the same as that of the expected best.torchscript. And always remember to set the androidModelHeight and androidModelWidth to the same size as that of best.pt.

Thank you for your hard work. Thank you for sharing!!

Thank you taking time to work on this to. Great plugin by all standards.


conda env

Hi,
Can I know why if I used conda to set the env, it will a long time to setup?
Thx

Hi, thanks for your interest in our work. I'm also confusing with this issue. Maybe I just install too many things based on ZoeDepth env

I mean if use conda to install the env, how long it approximately take?

:D Sometimes, it stuck forever...


Is this a problem of concurrency ?

the error log
createToken() for room<PHONE_NUMBER>772695
createToken() for room<PHONE_NUMBER>428408
2015-12-08 14:55:40.387  - INFO: RoomsResource - Representing rooms for service  5559463f78645fae6c9c5065
2015-12-08 14:55:40.610  - INFO: RoomsResource - Representing rooms for service  5559463f78645fae6c9c5065
room length 14291
room length 14291
2015-12-08 14:55:41.091  - INFO: RoomsResource - Room created<PHONE_NUMBER>772695 (roomName) for service superService , p2p =  false
Created room  56667eec81fe34e116d1f9e3
2015-12-08 14:55:41.485  - INFO: RoomsResource - Room created<PHONE_NUMBER>428408 (roomName) for service superService , p2p =  false
Created room  56667eed81fe34e116d1f9e4
2015-12-08 14:55:41.751  - INFO: TokensResource - Room  56667eed81fe34e116d1f9e4  does not exist
/server/licode/node_modules/mongojs/node_modules/mongodb/lib/mongodb/connection/base.js:246
throw message;
^
TypeError: Cannot read property '_id' of undefined
at /server/licode/nuve/nuveAPI/resource/tokensResource.js:176:73
at /server/licode/nuve/nuveAPI/resource/tokensResource.js:141:17
at /server/licode/nuve/nuveAPI/mdb/tokenRegistry.js:59:9
at callback (/server/licode/node_modules/mongojs/index.js:371:7)
at /server/licode/node_modules/mongojs/node_modules/mongodb/lib/mongodb/collection/core.js:482:9
at /server/licode/node_modules/mongojs/node_modules/mongodb/lib/mongodb/collection/core.js:128:9
at /server/licode/node_modules/mongojs/node_modules/mongodb/lib/mongodb/db.js:1195:7
at /server/licode/node_modules/mongojs/node_modules/mongodb/lib/mongodb/db.js:1903:9
at Server.Base._callHandler (/server/licode/node_modules/mongojs/node_modules/mongodb/lib/mongodb/connection/base.js:453:41)
at /server/licode/node_modules/mongojs/node_modules/mongodb/lib/mongodb/connection/server.js:487:18
why the get rooms list the “ Representing rooms for service 5559463f78645fae6c9c5065 ”  twice.

You are calling createToken twice, that's why you are getting the "Representing rooms" message twice.
Otherwise I would need more information on what you are trying to do... Are you creatingTokens for rooms before creating them?


Consolidate arduino.py files

It would be nice to combine the arduino.py files into a single file that is referenced in each sub module.

Agreed.  I'm contemplating how to add some jupyter notebooks to the repo, and am considering a new folder labeled 'notebooks' that would then import arduino.py   For this purpose, I'd suggest a new top-level folder labeled 'lib'  to hold arduino, then import from there for all other uses.  Does that make sense?

The arduino.py file is removed and the package is replaced by tclab that is now available from 'pip install tclab'.


{SQL} Update help text for ltr/geo restore params

Related command
az sql db
Description
Made help clearer about what service objective applies to.
Testing Guide
Tested that the new help text appears.

sql

/azp run


SelectedPosition problem when config generateInDates or generateOutDates

with these configuration of calendar:
ConfigurationParameters(startDate: startDate, endDate: endDate, generateInDates: .off, generateOutDates: .off)
then cellState.selectedPosition() returns wrong response in start and end of month.
you have an 2tapRangedSelection example, you can edit it and see wrong result.

in my app i set this generateOutDates: .tillEndOfRow
and as you can see if month day ends at middle of the week, everything works great:

but if a month day ends at end of the week, so it will break. like Jun 2021 and Jul 2021

or in April 2022 and May 2022:

when i set generateOutDates: .off, it will be like this: ( end of the month day is in middle )

this ?
calendarView.rangeSelectionMode = .continuous
calendarView.rangeSelectionMode = .segmented

with . continuous it works correctly
thank you

oops!
with generateOutDates: .tillEndOfRow and calendarView.rangeSelectionMode = .continuous look likes great!
but with generateOutDates: .off and calendarView.rangeSelectionMode = .continuous, last day of month does not have correct SelectedPosition state
( i selected from 22 Jun to 31 Jun )

The behaviour you are seeing is not a bug. It is behaving as intended. It appears that way on your screen because you have hidden the outdates.
The real issue here seems to be this --> I do not have a have to code the library that will satisfy every developer for ranged selection.
There are many conditions that have to be considered.
I will list them later today.

ok. I see an edge case fix that i can apply.
Let me test it.

Keep in mind, i know how to fix your issue.
However, if i code it the way you want, then other developers might not like the new behavior.  Therefore, let me test an edgecase fix for this case when the final day lands on end of index. Be right back.

Ok yea, the fix will work. But other developers wont be happy.
Therefore i have determined the ultimate solution for this.
This library needs to create a new set of functions.
calendarView.showIndates()
calendarView.hideIndates()
calendarView.showoutDates()
calendarView.hideOutDates()

The problem is that i let the developers determine when to show or hide the indates/outDates.
Because of this, the library does not know when a developer has done this. And because I do not know, I cannot suggest the best visual way the range selection should look.
However, if this library now begins to manage the visibility/invisibility of the inDates/OutDates, Then can will know how to adjust what the ranged left, right, middle should look like.

greaaaat!!!
when we can use this?

I didnt want this library to "hold the developers" hand so much however.....
But it seems that i locked my self into this problem the moment i introduced the selectedPosition feature

it's not possible to handle it with generateOutDates parameters?

if generateOutDates is .off then handle it like calendarView.hideOutDates()

How do you suggest?
This is the problem with selecting dates 26 - 31 with outdates/indates hidden.

If i unhide it, you can see that the library correctly does it as continuous.
The 2nd row of selected dates in the indates you hid.  You can see it is correctly continous.

But because it is hidden. The library does not know about it. And therefore cannot tell you to make the 31 to be red color.

but i think developer hide outDate and inDate dates. we always have one 31 which is shown and it's not hidden. so you can decide selectedPosition on visible date.
as you said above if you want to add these functions in library:
calendarView.showIndates()
calendarView.hideIndates()
calendarView.showoutDates()
calendarView.hideOutDates()

i think you can handle it with generateInDates and generateOutDates. like this: ( i think these are equal )
{ calendarView.showIndates() } == { generateInDates: .forFirstMonthOnly, .forAllMonths }
{ calendarView.hideIndates() } == { generateInDates: .off }
{ calendarView.showoutDates() } == { generateOutDates: .tillEndOfRow, .tillEndOfGrid }
{ calendarView.hideoutDates() } == { generateOutDates: .off }

Ah.
Let me clear it up.
Here indates/outdates are generated and visible.

Here indates/outdates are generated and hidden.

Here indates/outdates are not generated. And therefore are not visible.

So there is difference between generating them and hiding them.
With the solution i plan to implement, I will be the visibility (not the generation).
Based on the visibility, i can fix how the range looks. The decision to generate/not generate will not be handled by the library.

how to config like this

Hi @patchthecode @SajjadKharrazi , I face the same problem, any workaround for this situation? 🙏


hypervisor: add performance counter delta registers

It has been requested that we add htimedelta[h] CSRs so that hosts can
lie to guests about the current time, without requiring trapping and
emulating. cycle is also included, since the SBI set timer callback has
absolute cycles as the argument.  There is no intent to add equivalent
CSRs for instret and performance counters.
Fixes: #298

For the reason I mentioned in #298, I would prefer to add only the time-delta CSR.

Sorry, I was confused by Linux code that does rdtime and calls it get_cycles...
I would like to have cycles as well but I will remove it so that we can progress on this missing feature.

Ah, yes, that API name mismatch is unfortunate.  Thank you.

One detail is this register should be HSXLEN bits wide, not VSXLEN bits wide.  If the host is RV64 and the guest is RV32, the host shouldn't have to use two CSRs to maintain the delta.  I will fix this, and a couple other stylistic things, and merge this in.

Merged manually via 4bfae7862e436ce67c1aebaf2d95f0d35c658c51.
Note we've also changed the CSR assignment to keep the h* registers in the 0x6xx range, and to reflect that we will not add delta registers for other counters.  (Time is special because it is global. The other counters are per-hart, so it is practical to migrate them on VM migration even without delta registers.)


quotecast timeouting

Dear community,
I'm facing an issue with vwdservices to get stock prices since last Friday. Since then, seeking for a solution, I've updated all the outdated packages (didn't work). Here is the log when I try to run the realtime_one_shot.py example:
INFO:degiro_connector.quotecast.api:Connection required.
CRITICAL:degiro_connector.quotecast.actions.action_connect:HTTPSConnectionPool(host='degiro.quotecast.vwdservices.com', port=443): Max retries exceeded with url: /CORS/request_session?version=1.0.20201211&userToken=[REDACTEDTOKEN](Caused by ConnectTimeoutError(<urllib3.connection.HTTPSConnection object at 0x0000020B17A4EE30>, 'Connection to degiro.quotecast.vwdservices.com timed out. (connect timeout=None)'))
At first, I thought that I was banned or something like that, however, I can connect normally to "https://business-customer.vwd.com/chartanalyse/web/?config=degiro&[ETC.ETC.ETC]"
Does anyone have a clue?
Thanks in advance :)

Hello @pereira1408,
realtime data are still working on my side.
Maybe it was a connection or server issue.
An alternative is to use the Chart methods.
Closing the issue for now, feel free to reopen it or create a new one if you still have this issue.
Thanks


[Bug Report] SubsequenceNode IndexError

Hey, I found one bug when using the SubsequenceNode because of the inconsistency of the residue_mask and node_mask.
The residue number and node number is not the same without using layers.GraphConstruction to transform the original protein view into the residue-level graph.

Thanks for pointing out the bug! This has been fixed in 4e76c30.

Thank you for your work !


Generates code from imported types

When running zenrpc in a package that both defines and imports a zenrpc.Service type, then it will generate (incorrect) code for the imported services.
I.e. if having:
cmd/mycmd
    main_zenrpc.go -- generated
    service.go -- defines FooService
    server.go -- register FooService and pkg/bar.Service
pkg/bar
   bar_zenrpc.go -- generated
   service.go -- defines Service

When generating the code in cmd/mycmd then it will generate code for Service (which does not exist in the package) as well as FooService, which does exist. It will also, for some reason, import encoding/json twise. Either way, the result is invalid code.
Maybe related with #35?

Should be working now, please confirm

Sorry for the late update. It seams that we no longer get the additional Service generation. However, we still get a duplicated import:
Import:
import (
	"context"
	"encoding/json"

	"github.com/semrush/zenrpc/v2"
	"github.com/semrush/zenrpc/v2/smd"

	"encoding/json"
)


[Feat] - Add Caching Capabilities to Workflow

Description:
The Deploy script here,  can be improved by adding caching capabilities to the workflow to reduce the CI time.

Hello!
I'd like to work on this, how do I get started?

Closed this issue because #24 has solved it.


[DO_NOT_MERGE] Tests before sync with develop

This PR is for generating a preview url from Vercel to test on recent changes.

Tests done, closing the PR.

Tests done, closing the PR.


Simplify update-site tested cases

Simplify update-site tested cases
This is intended to be a minimal acceptance test, not a detailed validation test of the update center rules.
We may want to drop this test completely since the update center is already very well tested by @daniel-beck .  The test runs at https://ci.jenkins.io/job/Infra/job/acceptance-tests/ .  Tests from that repository have been helpful detecting repository signing issues, but are not frequently monitored by anyone other than me.

Interesting, I didn't know this existed.
FTR the redirects are testable by https://github.com/jenkins-infra/update-center2/blob/master/site/test/test.sh which has the benefit of not requiring constant updates since the (supposed to be) supported version tiers are passed as arguments.
OTOH it can only test redirects, not actual files, and works with fake data as well.

Closing because I believe this branch should be replaced with a call to a modified form of the tests that Daniel mentioned in his comments.  I'll propose extensions to those tests when time allows so that they can be used with the production server in addition to their current use with a local server.


[Event Request]Application “Tests-Workflow”, 134172 "WF Demo Sales Quote Approvals"

[Event Request]Application “Tests-Workflow”, 134172 "WF Demo Sales Quote Approvals"
Could you please insert the OnTestInitialize Event at the beginning of Initialize procedure:

Thanks for reporting this. We agree, and we’ll publish a fix asap, either in an update for the current version or in the next major release. We will update this issue with information about availability.


Auth.signUp() fails with error - Unable to verify secret hash for client - missing AppClientSecret in awsconfiguration.json

Describe the bug
Note: possible duplicate bug: Missing AppClientSecret from awsconfiguration.json file after amplify add auth
I recently upgraded to the latest Amplify tools (version 4.35.0).
Now when I add Auth to an IOS project, the amplify configuration tools no longer adds a AppClientSecret key / value to the awsconfiguration.json file.  The result of this is that when performing Amplify.Auth.signUp(...) in the app, it fails with the following error:
AuthError: Unable to verify secret hash for client xxxxxxxx
To Reproduce
Steps to reproduce the behavior:

At prompt: % amplify init
At prompt: % amplify auth add (with default values)
At prompt: % amplify push
Check the awsconfiguration.json file to confirm if the AppClientSecret key exists.

Expected behavior
I expect that the awsconfiguration.json file should contain the following:
"CognitoUserPool": {
        "Default": {
            "PoolId": "ap-southeast-2_xxxxxxx",
            "AppClientId": "xxxxxxxxxxxxxx",
            "AppClientSecret": "xxxxxxxxxxxxxxxx",
            "Region": "ap-southeast-2"
        }
    }

Instead the file just contains the following:
"CognitoUserPool": {
        "Default": {
            "PoolId": "ap-southeast-2_xxxxxxx",
            "AppClientId": "xxxxxxxxxxxxxx",
            "Region": "ap-southeast-2"
        }
    }

This problem does not occur when using older Amplify CLI - version 4.29.0.
Environment(please complete the following information):

Amplify Framework Version: [4.35.0]
Dependency Manager: [Cocoapods]
Swift Version : [5.0]

Device Information (please complete the following information):

Device: [any]
iOS Version: [iOS 14]

this is an issue with the amplify-cli and not with the sdk... so closing

duplicate of https://github.com/aws-amplify/amplify-cli/issues/5976