example1 | Sample application using sdk and creating your own online

It appears you forgot to tell rustc it was allowed to use AVX2 instructions everywhere, so it couldn't inline those functions. Instead, you get a total disaster where only the wrapper functions are compiled as AVX2-using functions, or something like that.

Works fine for me with -O -C target-cpu=skylake-avx512 (https://godbolt.org/z/csY5or43T) so it can inline even the AVX512VL load you used, _mm256_load_epi32¹, and then optimize it into a memory source operand for vpaddd ymm0, ymm0, ymmword ptr [rdi + 4*rax] (AVX2) inside a tight loop.

In GCC / clang, you get an error like "inlining failed in call to always_inline foobar" in this case, instead of working but slow asm. (See this for details). This is something Rust should probably sort out before this is ready for prime time, either be like MSVC and actually inline the instruction into a function using the intrinsic, or refuse to compile like GCC/clang.

Footnote 1: See How to emulate _mm256_loadu_epi32 with gcc or clang? if you didn't mean to use AVX512.

With -O -C target-cpu=skylake (just AVX2), it inlines everything else, including vpaddd ymm, but still calls out to a function that copies 32 bytes from memory to memory with AVX vmovaps. It requires AVX512VL to inline the intrinsic, but later in the optimization process it realizes that with no masking, it's just a 256-bit load it should do without a bloated AVX-512 instruction. It's kinda dumb that Intel even provided a no-masking version of _mm256_mask[z]_loadu_epi32 that requires AVX-512. Or dumb that gcc/clang/rustc consider it an AVX512 intrinsic.

My approach here would be to create a distributive object type (as coined in microsoft/TypeScript#47109) where we first create a mapped type over Keys where each key P has a property that is the first part of P if it ends in ".bar", or never otherwise. And then we immediately index into this object type with Keys to get the Namespace union type we want. This serves to distribute the operation of extracting the part before ".bar" over the union of entries in Keys:

You could simply define another model containing the items list as a field:

Maybe something like this:

It seems something has changed in the new version of ChromeDriver and it is no longer possible to send some special chars directly using send_keys method.

In this link you will see how it is solved (in C#) --> Selenium - SendKeys("@") write an "à"

And regarding python implementation, check this out --> https://www.geeksforgeeks.org/special-keys-in-selenium-python/

Specifically, my implementation was (using MAC):

This is a hard problem to solve in general, and even a fairly hard problem to solve in specific cases.

I think the difference arose between version 1.1.27.1 and 1.1.28, probably from this NEWS item:

construction of interacting factors (e.g. when f1:f2 or f1/f2 occur in random effects terms) is now more efficient for partially crossed designs (doesn't try to create all combinations of f1 and f2) (GH #635 and #636)

My guess is that this changes the ordering of the components in the Z matrix, which in turn means that results of various linear algebra operations are not identical (e.g. floating point arithmetic is not associative, so while binary addition is commutative (a + b == b + a), left-to-right evaluation of a sum may not be the same as right-to-left evaluation ((a+b) + c != a + (b+c)) ...)

My attempt at reproducing the problem uses the same version of R ("under development 2022-02-25 r81818") and compares only lme4 package versions 1.18.1 with 1.1.28.9000 (development); any upstream packages such as Rcpp, RcppEigen, Matrix use the same versions. (I had to backport a few changes from the development version of lme4 to 1.1.18.1 to get it to install under the most recent version of R, but I don't think any of those modifications would affect numerical results.)

I did the comparison by installing different versions of the lme4 package before running the code in a fresh R session. My results differed between versions 1.1.18.1 and 1.1.28 less than yours did (both fits were singular, and the relative differences in the theta estimates were of the order of 2e-7 — still greater than your desired 1e-8 tolerance but much smaller than 1e-4 ...)

The results from 1.1.18.1 and 1.1.27.1 were identical.

• Q1: Why are your results more different between versions than mine?
  • in general/anecdotally, numerical results on Windows are slightly more unstable/differ more from other platforms
  • there are more differences between your two test platforms than among mine: R version, upstream packages (Matrix/Rcpp/RcppEigen/minqa), possibly the compiler versions and settings used to build everything [all of which could make a difference]
• Q2: how should one deal with this kind of problem?
  • as a minor frame challenge, why (other than not understanding what's going on, which is a perfectly legitimate reason to be concerned) does this worry you? The differences in the results are way smaller than the magnitude of statistical uncertainty, and differences this large are also likely to occur across different platforms (OS/compiler version/etc.) even for otherwise identical environments (versions of R, lme4, and other packages).
  • you could revert to version 1.1.27.1 for now ...
  • I do take the differences between 1.1.27.1 as a bug, of sorts — at the very least it's an undocumented change in the package. If it were sufficiently high-priority I could investigate the code changes described above and see if there is a way to fix the problems they addressed without breaking backward compatibility (in theory this should be possible, but it could be annoyingly difficult ...)

You can not use vuejs-datepicker in Vue3, you can try with vue3datepicker :

For the first database schema, you need a pipeline that will first filter the translation array using the $filter operator. This will return an array with just the document that satisfies the filtering condition. So the expression:

Yes, the best fit is a line through the top two points. I do an argsort to find the top Ys, compute the slope and y-intercept, and off we go: