warmup | WarmuP - a simple templater / token replacement tool

It's my first Kafka program.

From a kafka_2.13-3.1.0 instance, I created a Kafka topic poids_garmin_brut and filled it with this csv:

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I have a dataset from participants that provided liking ratings (on a scale from 0-100) of stimuli associated with rewards of different magnitudes (factor pval, with levels small/medium/large) and delay (factor time, with levels delayed/immediate). A subset of the data looks like this:

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I have a function like this:

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I am using a C library which uses various fixed-sized unsigned char arrays with no null terminator as strings.

I've been converting them to std::string using the following function:

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I would like to know-how in my web app written in C#.NET5 (+React) call function after IIS server use setting for recycling Web data on IIS -> Application Pool -> Recycling (Regular Time Interval (In Minutes)) set on 1440.

I load over 6 GB to memory (IMemoryCache) and it takes over 6 minutes then all data is loaded, I would like to call the load function to cache automatically after each cycle of the recycling period, before waiting for the user interaction.

I try it call in StartUp, in Main, and also with use IHostetServices, but in each case, I got an error then called service (my class with load method) is not recognized

3 Ways to Run Code Once at Application Startup in ASP.NET Core

I got these errors: when I try to call

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I have the following toy data -

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I am trying an experiment to bring up a Drupal 7 installation in Repo authoritative mode under HHVM 3.21 (which still supported PHP - latest version does not). (May sound crazy, but bear with me here.) Server is Ubuntu 18.04 running apache2 with mod_proxy, mod_proxy_fcgi. I am new to HHVM, so I have probably made an obvious mistake.

I started with an index.php "hello world" to ensure that I had the general configuration working. That works fine, regardless of the contents of /var/www/html/index.php (per https://docs.hhvm.com/hhvm/advanced-usage/repo-authoritative)

I am using hhvm --hphp -thhbc -o /var/cache/hhvm file_list.txt to create the repo, which is then chown'ed to www-data. (The same file I copy to /var/www/.hhvm.hhbc, since it seems that the server wants a copy there... this question I will solve later...)

Problem #1: I have left the entire file tree in place in /var/www/html, but mod_rewrite is not working correctly. I can use the site without problems if I use the "unpretty" URLs (?q=admin/config), but not rewritten URLs.

Problem #2: In principle HHVM in repo authoritative mode should be able to serve the entire image from the repo file if only the index.php is in place or if I specify hhvm.server.allowed_files[] = index.php, but when I try this, the server 404's.

What follows is a ton of relevant info from config files. I am happy to add more information as needed to assist with finding my error/omission, in case I have forgotten anything here. Thank you for reading this far!

/etc/hhvm/server.ini:

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Consider the following code, running on an ARM Cortex-A72 processor (optimization guide here). I have included what I expect are resource pressures for each execution port:

Instruction B I0 I1 M L S F0 F1 .LBB0_1: ldr q3, [x1], #16 0.5 0.5 1 ldr q4, [x2], #16 0.5 0.5 1 add x8, x8, #4 0.5 0.5 cmp x8, #508 0.5 0.5 mul v5.4s, v3.4s, v4.4s 2 mul v5.4s, v5.4s, v0.4s 2 smull v6.2d, v5.2s, v1.2s 1 smull2 v5.2d, v5.4s, v2.4s 1 smlal v6.2d, v3.2s, v4.2s 1 smlal2 v5.2d, v3.4s, v4.4s 1 uzp2 v3.4s, v6.4s, v5.4s 1 str q3, [x0], #16 0.5 0.5 1 b.lo .LBB0_1 1 Total port pressure 1 2.5 2.5 0 2 1 8 1

Although uzp2 could run on either the F0 or F1 ports, I chose to attribute it entirely to F1 due to high pressure on F0 and zero pressure on F1 other than this instruction.

There are no dependencies between loop iterations, other than the loop counter and array pointers; and these should be resolved very quickly, compared to the time taken for the rest of the loop body.

Thus, my intuition is that this code should be throughput limited, and considering the worst pressure is on F0, run in 8 cycles per iteration (unless it hits a decoding bottleneck or cache misses). The latter is unlikely given the streaming access pattern, and the fact that arrays comfortably fit in L1 cache. As for the former, considering the constraints listed on section 4.1 of the optimization manual, I project that the loop body is decodable in only 8 cycles.

Yet microbenchmarking indicates that each iteration of the loop body takes 12.5 cycles on average. If no other plausible explanation exists, I may edit the question including further details about how I benchmarked this code, but I'm fairly certain the difference can't be attributed to benchmarking artifacts alone. Also, I have tried to increase the number of iterations to see if performance improved towards an asymptotic limit due to startup/cool-down effects, but it appears to have done so already for the selected value of 128 iterations displayed above.

Manually unrolling the loop to include two calculations per iteration decreased performance to 13 cycles; however, note that this would also duplicate the number of load and store instructions. Interestingly, if the doubled loads and stores are instead replaced by single LD1/ST1 instructions (two-register format) (e.g. ld1 { v3.4s, v4.4s }, [x1], #32) then performance improves to 11.75 cycles per iteration. Further unrolling the loop to four calculations per iteration, while using the four-register format of LD1/ST1, improves performance to 11.25 cycles per iteration.

In spite of the improvements, the performance is still far away from the 8 cycles per iteration that I expected from looking at resource pressures alone. Even if the CPU made a bad scheduling call and issued uzp2 to F0, revising the resource pressure table would indicate 9 cycles per iteration, still far from actual measurements. So, what's causing this code to run so much slower than expected? What kind of effects am I missing in my analysis?

EDIT: As promised, some more benchmarking details. I run the loop 3 times for warmup, 10 times for say n = 512, and then 10 times for n = 256. I take the minimum cycle count for the n = 512 runs and subtract from the minimum for n = 256. The difference should give me how many cycles it takes to run for n = 256, while canceling out the fixed setup cost (code not shown). In addition, this should ensure all data is in the L1 I and D cache. Measurements are taken by reading the cycle counter (pmccntr_el0) directly. Any overhead should be canceled out by the measurement strategy above.

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This question is the same with How can I check a confusion_matrix after fine-tuning with custom datasets?, on Data Science Stack Exchange.

Background

I would like to check a confusion_matrix, including precision, recall, and f1-score like below after fine-tuning with custom datasets.

Fine tuning process and the task are Sequence Classification with IMDb Reviews on the Fine-tuning with custom datasets tutorial on Hugging face.

After finishing the fine-tune with Trainer, how can I check a confusion_matrix in this case?

An image of confusion_matrix, including precision, recall, and f1-score original site: just for example output image

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