Schedule post

What is this feature?
Be able to schedule when a post goes live
How the feature should work?
make the published field accept not only a boolean in front matter, but also a datetime. If the datetime is bigger than the current datetime set is true in other case send false.
You have examples or an idea of how it can be implemented?
@ful1e5 do you mind if I do a PR for this?

Added a draft PR #239 for you to check the idea @ful1e5. Please let me know if it makes sense. I will finish the checklist tomorrow.


jpeg-turbo detection doesn't properly handle not finding it

The code here isn't good. It should error out if it can't find jpeg-turbo and not just fill in some randomness and result in a link failure halfway through building Vogl.
    else()
        if (BUILD_X64)
            set(BITS_STRING "x64")
        else()
            set(BITS_STRING "x86")
        endif()
        set(LibJpegTurbo_INCLUDE "${CMAKE_PREFIX_PATH}/libjpeg-turbo-2.1.3/include" PARENT_SCOPE)
        set(LibJpegTurbo_LIBRARY "${CMAKE_PREFIX_PATH}/libjpeg-turbo-2.1.3/lib_${BITS_STRING}/turbojpeg.lib" PARENT_SCOPE)
    endif()

I just hit this. Needed to install more dependencies, would have been nice if cmake would have failed instead of the make.
vogl/vogl_build/release64$ make
[ 27%] Built target voglcore
[ 27%] Built target voglgen
[ 28%] Built target voglgen_make_inc
[ 33%] Built target backtracevogl
[ 50%] Built target voglcommon
[ 54%] Built target vogl
[ 54%] Built target voglbench
make[2]: *** No rule to make target `/libjpeg-turbo-2.1.3/lib_x64/turbojpeg.lib', needed by `../libvogltrace64.so'. Stop.
make[1]: *** [src/vogltrace/CMakeFiles/vogltrace.dir/all] Error 2

@sstewartgallus It looks like the code that you quote is from src/build_options.cmake.
I'll quote the full function here:
function(require_libjpegturbo)
    find_library(LibJpegTurbo_LIBRARY
        NAMES libturbojpeg.so libturbojpeg.so.0 libturbojpeg.dylib
        PATHS /opt/libjpeg-turbo/lib
    )

    # On platforms that find this, the include files will have also been installed to the system
    # so we don't need extra include dirs.
    if (LibJpegTurbo_LIBRARY)
        set(LibJpegTurbo_INCLUDE "" PARENT_SCOPE)

    # On Darwin we assume a Homebrew install
    elseif (${CMAKE_SYSTEM_NAME} MATCHES "Darwin")
        set(LibJpegTurbo_INCLUDE "/usr/local/opt/jpeg-turbo/include"            PARENT_SCOPE)
        set(LibJpegTurbo_LIBRARY "/usr/local/opt/jpeg-turbo/lib/libturbojpeg.a" PARENT_SCOPE)

    else()
        if (BUILD_X64)
            set(BITS_STRING "x64")
        else()
            set(BITS_STRING "x86")
        endif()
        set(LibJpegTurbo_INCLUDE "${CMAKE_PREFIX_PATH}/libjpeg-turbo-2.1.3/include" PARENT_SCOPE)
        set(LibJpegTurbo_LIBRARY "${CMAKE_PREFIX_PATH}/libjpeg-turbo-2.1.3/lib_${BITS_STRING}/turbojpeg.lib" PARENT_SCOPE)
    endif()
endfunction()

CMake looks in /opt/libjpeg-turbo/lib in addition CMake associated paths (for the turbojpeg library). I believe the else section that you quote is a residual of the original build procedure (and is unlikely to find turbojpeg). I agree that it would be better to replace the else() with failing out with an error.
So, perhaps the else() above becomes:
message(FATAL_ERROR "Unable to find libturbojpeg")

In addition, the search for the header, /usr/include/turbojpeg.h should be made explicit (especially if header is placed in a path that is not being searched). The configuration process would succeed, but the build process would fail at the attempted to find turbojpeg.h during compilation of src/vogltrace/vogl_intercept.cpp.
# On platforms that find this, the include files will have also been installed to the system
# so we don't need extra include dirs.
if (LibJpegTurbo_LIBRARY)
   set(LibJpegTurbo_INCLUDE "" PARENT_SCOPE)

to something like (I haven't tested below, but I believe this should work):
if (LibJpegTurbo_LIBRARY)
   find_path(LIBJPEGTURBO_INCLUDE_DIR
                   NAME turbojpeg.h
                   PATHS /opt/libjpeg-turbo/inc)
   IF(NOT LIBJPEGTURBO_INCLUDE_DIR)
     message(FATAL_ERROR "Unable to find turbojpeg.h")
   ENDIF()
   include_directories(${LIBJPEGTURBO_INCLUDE_DIR})
ENDIF()

I would recommend an additional set of checks to see the library found by CMake has the appropriate set of symbols defined and the version of the found library is correct.


LEGO: Pull request from lego/hb_04604851-bac4-4681-9f74-73de611d6e48_20231202163910126 to main

LEGO: Pull request from lego/hb_04604851-bac4-4681-9f74-73de611d6e48_20231202163910126 to main with localized lcls

Pull Request Test Coverage Report for Build<PHONE_NUMBER>

0 of 0   changed or added relevant lines in 0 files are covered.
1 unchanged line in 1 file lost coverage.
Overall coverage decreased (-0.003%) to 41.604%

Files with Coverage Reduction
New Missed Lines
%

extensions/notebook/src/dialog/configurePython/configurePathPage.ts
1
57.02%

Totals

Change from base Build<PHONE_NUMBER>:
-0.003%

Covered Lines:
30818

Relevant Lines:
69389

💛  - Coveralls


[Bugfix]--Appropriately handle multiple meshes being assigned to the same transform node.

Motivation and Context
This PR fixes an issue with attempting to load an asset with multiple meshes assigned to the same MeshTransformNode.  A recent change to the loading mechanism ignored all subsequent meshes that were assigned to the same transform; this PR fixes this by assigning these subsequent meshes as children in the MeshTransformNode.  This is what was done originally in the Magnum Importer.

How Has This Been Tested
Locally; All c++ and python tests pass

Types of changes

[ ] Docs change / refactoring / dependency upgrade
[x] Bug fix (non-breaking change which fixes an issue)
[ ] New feature (non-breaking change which adds functionality)
[ ] Breaking change (fix or feature that would cause existing functionality to change)

Checklist

[x] My code follows the code style of this project.
[ ] My change requires a change to the documentation.
[ ] I have updated the documentation accordingly.
[x] I have read the CONTRIBUTING document.
[x] I have completed my CLA (see CONTRIBUTING)
[ ] I have added tests to cover my changes.
[x] All new and existing tests passed.

python lint is failing because the ci/config.yaml is not restricting mypy version to the one we use in pre-commit.


Development Build Need to be so Verbose?

It's almost a bit ridiculous...

@dav-is by development build do you mean
“yarn start” ?

Ok.. Figured out it was during yarn build thanks for pointing it out, updated the code for minimal warnings only.


pull request for e2e test at 12/25/2016 18:15:13

:white_check_mark: Validation status: passed
For more details, please refer to the build report.
Note: If you changed an existing file name or deleted a file, broken links in other files to the deleted or renamed file are listed only in the full build report.


log: println! implementation with no allocations

As noted in TODO, use esp_log_level_get to decide whether to log, then use println!() to directly write message, including no-alloc write of record.args().

The one problem I just realized is that println! drags in a hard dependency in STD. We have to think a bit how to do that in a no-std compatible way.

We probably need to implement the core::fmt::Write trait for the stdout file descriptor of ESP-IDF using unsafe code and from there we can use the write! macro instead.

First pass without handling errors:
use core::fmt::Write;

struct EspStdout;

impl core::fmt::Write for EspStdout {
    fn write_str(&mut self, s: &str) -> core::fmt::Result {
        let stdout = unsafe { __getreent().as_mut() }.unwrap()._stdout;
        let slice = s.as_bytes();
        unsafe {
            fwrite(
                slice.as_ptr() as *const _,
                1,
                slice.len() as u32,
                stdout
            );
        }
        Ok(())
    }
}

then in log(),
                write!(EspStdout,
                    "\x1b[0;{}m{} ({}) {}: {}\x1b[0m\n",
                    color,
                    Self::get_marker(record.metadata().level()),
                    unsafe { esp_log_timestamp() },
                    record.metadata().target(),
                    record.args(),
                )
                .unwrap();

Tested with rust-esp32-std-demo, working fine.
Do you know another way to grab stdout? getreent is inexpensive but a bit messy.

I think that's OK actually!

I've only tested on ESP32-C3 - if anyone can test on other platforms that would be good (just to be sure!)

@tcbennun Can you fix the fmt error so that I can merge?


Code snippet for establishing connection with MySQL database.

Since this is a Web Development Training repository it will be helpful if any code snippet is provided as a reference for establishing connection between MySQL database and PHP.

Please assign this issue to me.


Fix: namespace case

This PR

[x] Fix the namespace case.

Closes #387.

Thank you, @Lctrs!
The latest version is broken, I haven't had the time to fix it yet.
I currently use localheinz/github-changelog:0.6.1.

Okay. Will see if I find some time in the next days to look at it.

@Lctrs
Thank you, @Lctrs! I have been thinking about adjusting this so it can be used in the context of GitHub Actions, when creating a new release. Just haven't had time yet.


FIX: Repaired broken yaml parsing

pin to ruamel.yaml >= 0.16, < 0.17

On branch fix_deps
Changes to be committed:
modified:   recipe/meta.yaml

Checklist

[X] Used a personal fork of the feedstock to propose changes
[X] Bumped the build number (if the version is unchanged)
[ ] Re-rendered with the latest conda-smithy (Use the phrase @conda-forge-admin, please rerender in a comment in this PR for automated rerendering)
[X] Ensured the license file is being packaged.

Hi! This is the friendly automated conda-forge-linting service.
I just wanted to let you know that I linted all conda-recipes in your PR (recipe) and found it was in an excellent condition.

@conda-forge-admin, please rerender


Sampling chooses vocab index that does not exist with certain random seeds

Running into the following error while sampling with certain seeds:
Traceback (most recent call last):
  File "/usr/lib/python3.5/runpy.py", line 184, in _run_module_as_main
    "__main__", mod_spec)
  File "/usr/lib/python3.5/runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "/net/cephfs/scratch/mathmu/map-volatility/venvs/sockeye3/lib/python3.5/site-packages/sockeye/translate.py", line 269, in <module>
    main()
  File "/net/cephfs/scratch/mathmu/map-volatility/venvs/sockeye3/lib/python3.5/site-packages/sockeye/translate.py", line 46, in main
    run_translate(args)
  File "/net/cephfs/scratch/mathmu/map-volatility/venvs/sockeye3/lib/python3.5/site-packages/sockeye/translate.py", line 155, in run_translate
    input_is_json=args.json_input)
  File "/net/cephfs/scratch/mathmu/map-volatility/venvs/sockeye3/lib/python3.5/site-packages/sockeye/translate.py", line 237, in read_and_translate
    chunk_time = translate(output_handler, chunk, translator)
  File "/net/cephfs/scratch/mathmu/map-volatility/venvs/sockeye3/lib/python3.5/site-packages/sockeye/translate.py", line 260, in translate
    trans_outputs = translator.translate(trans_inputs)
  File "/net/cephfs/scratch/mathmu/map-volatility/venvs/sockeye3/lib/python3.5/site-packages/sockeye/inference.py", line 861, in translate
    results.append(self._make_result(trans_input, translation))
  File "/net/cephfs/scratch/mathmu/map-volatility/venvs/sockeye3/lib/python3.5/site-packages/sockeye/inference.py", line 963, in _make_result
    target_tokens = [self.vocab_target_inv[target_id] for target_id in target_ids]
  File "/net/cephfs/scratch/mathmu/map-volatility/venvs/sockeye3/lib/python3.5/site-packages/sockeye/inference.py", line 963, in <listcomp>
    target_tokens = [self.vocab_target_inv[target_id] for target_id in target_ids]
KeyError: 7525

I am calling Sockeye with a script such as
OMP_NUM_THREADS=1 python -m sockeye.translate \
                -i $data_sub/$corpus.pieces.src \
                -o $samples_sub_sub/$corpus.pieces.$seed.trg \
                -m $model_path \
                --sample \
                --seed $seed \
                --length-penalty-alpha 1.0 \
                --device-ids 0 \
                --batch-size 64 \
                --disable-device-locking

Sockeye and Mxnet versions:
[2020-08-25:17:03:03:INFO:sockeye.utils:log_sockeye_version] Sockeye version 2.1.17, commit 92a020a25cbe75935c700ce2f29b286b31a87189, path /net/cephfs/scratch/mathmu/map-volatility/venvs/sockeye3/lib/python3.5/site-packages/sockeye/__init__.py
[2020-08-25:17:03:03:INFO:sockeye.utils:log_mxnet_version] MXNet version 1.6.0, path /net/cephfs/scratch/mathmu/map-volatility/venvs/sockeye3/lib/python3.5/site-packages/mxnet/__init__.py

Details that may be relevant:

This only happens for certain random --seeds
Running on a Tesla V100
OS: Ubuntu 16.04.6 LTS
the MXnet version in the CUDA 10.2 requirements file (https://github.com/awslabs/sockeye/blob/master/requirements/requirements.gpu-cu102.txt) is no longer available on Pypi. I had to install mxnet-cu102mkl==1.6.0.post0.

The vocabulary does not have this index:

[INFO:sockeye.vocab] Vocabulary (7525 words) loaded from "/net/cephfs/scratch/mathmu/map-volatility/models/bel-eng/baseline/vocab.src.0.json"
[INFO:sockeye.vocab] Vocabulary (7525 words) loaded from "/net/cephfs/scratch/mathmu/map-volatility/models/bel-eng/baseline/vocab.trg.0.json"

I suspect that the sampling procedure somehow assumes 1-based indexing, whereas the vocabulary is 0-indexed. This would mean that there is a small chance that max_vocab_id+1 is picked as the next token.
Looking at the inference code, I am not sure yet why this happens.

Interesting, thanks for opening this issue. Can you disable hybridization and check for the presence of 7525 after this line? That is, see whether this value is sample there?

@fhieber I assume you mean something like this?
# Sample from the target distributions over words, then get the corresponding values from the cumulative scores
best_word_indices = F.random.multinomial(target_dists, get_prob=False)

# warn if 7525 was sampled here
if F.sum(best_word_indices == 7525) > 0:
    print("7525 actually in best_word_indices!")

Yes, 7525 is actually sampled there.

Very strange, what is the input shape of target_dists, specifically the size of the last dimension?

Shape of target_dists:
(320, 7525)

Which I think is correct and should mean that 7525 cannot be sampled

That points very much to a bug in the implementation of random.multinomial then. Do you want to submit an issue to mxnet?

Sure, I'll try to isolate the issue a bit more (= strip away Sockeye) and then open an issue

I am at a loss (not a benign cross-entropy one!) with this bug;

It only happens on GPU
It only happens with exactly this input file. If I split the file up into several parts, the error is not thrown for any chunk of the input, even though taken together, the lines are the same.
If I save the target_dists that causes the error, then load it in isolation and call random.multinomial, the error never happens, no matter the device context or random seed.

Here is a gist that I can run on a clean instance and that throws the error:
https://gist.github.com/bricksdont/58dfa0964201c83961a30f23406baa5d
I would be glad to know if someone can reproduce this error at all.

Is there a way to store the random generator state of MXNet somehow? I guess you cannot reproduce in isolation because it depends on the previous inputs. If you would run multinomial on smaller random input data, 1000k times and always check for sampled index not being out of bounds, would you see the error?

Finally found the problem I think: mx.random.multinomial consistently returns impossible values if inputs are not proper distributions. For instance:
>>> dist = mx.nd.array([1.2, 9.4, 8.8])
>>> mx.random.multinomial(dist)
[3]
<NDArray 1 @cpu(0)>

MXnet also does not check if inputs are indeed distributions. If I renormalize target_dists:
# Map the negative logprobs to probabilities so as to have a distribution
target_dists = F.exp(-target_dists)

# normalize to make sure values are proper distributions
target_dists = F.softmax(target_dists, axis=-1)

then the problem never occurs. Does that make sense as an explanation / is applying softmax in that spot a good solution?

Thats a good find! This is actually also part of the documentation for multinomial: ".. note:: The input distribution must be normalized, i.e. data must sum to 1 along its last dimension."
But what I don't understand yet is why target_dists does not contain proper distributions, i.e. summing up to 1? Isn't the line above exactly aimed at that?

Yes, it's a somewhat confusing implicit assumption of multinomial. But it's a reasonable one—you wouldn't want the code to have to waste time ensuring a slice sums to 1.
I haven't looked at the code (that I wrote :)), but it seems clear to me that you want to sample from the output distribution at the current step, and you should not be incorporating the summed scores so far. This might not actually be what I wrote. If that is the case, I don't know why I did it that way.

Thanks @mjpost. The code is correct, as far as I can tell. Given that this seems such an unlikely event, I would think this is a numerical precision issue.

"but it seems clear to me that you want to sample from the output distribution at the current step, and you should not be incorporating the summed scores so far"
@mjpost The shape of the distributions as input for multinomial sampling is exactly (batch_size * beam_size, target_vocab_size) in my case, which confirms that this is the correct array, i.e. distributions of the current time step.

"Edit: are you somehow skipping the softmax operation earlier (beam-size 1)?"
@fhieber beam_size is at its default value (5), but I'm not sure if the behaviour is different for sampling (if sampling skips softmax or assumes beam=1 that could be an explanation).
" I would think this is a numerical precision issue."
After I re-normalize with softmax, some distributions still do not sum to 1.0 exactly, but mx.random.multinomial does the right thing. This might mean that before my "second" softmax, values do not actually sum to 1.

@bricksdont Another thing to check—are the values sorted from highest to lowest? If the algorithm works the way I suspect, they would have to be sorted.
If so, then I'd be curious to see the cdf of the slice. Output distributions are typically pretty peaked, so it seems very unlikely the last item would get selected.

@mjpost It's not the last item that gets selected; if mx.random.multinomial is fed malformed input, it often returns max_possible_index+1, regardless of probability of the actual last entry in the input aray.
I can still check if values are sorted of course.

So, can you confirm that most distributions in your case significantly do not sum up to 1? Could you add a line that asserts on the sum with some epsilon?

All distributions are within a small tolerance of 1.0; the following print statement is never executed:
# Map the negative logprobs to probabilities so as to have a distribution
target_dists = F.exp(-target_dists)

# numpy isclose: absolute(a - b) <= (atol + rtol * absolute(b))
# b is the reference value = not symmetric
atol = 0.00000001
rtol = 0.00001
one_array = F.array([1.0])

target_dists_sums = F.sum(target_dists, axis=-1)

if any(F.abs(target_dists_sums - one_array) > (atol + rtol * F.abs(one_array))):
    print("target_dists_sums contains non-distributions")

Sorry for jumping to conclusions about this! A different explanation is that by re-normalizing the values (applying softmax in the SampleK function) they change slightly, which causes mx.random.multinomial to behave differently.

Update: the behaviour is exactly the same with MXnet 1.7.0

I came across the same error in Sockeye-1.18.115.
I've started to write a issue/ticket when I realize this one was about the same thing.  I'll add what I was in the process of writing here in case it helps.
Invalid token id during n-best translation
Hi,
I'm trying to perform translation to produce N-best and I occasionally encounter a keyError, a target token was produced that isn't in the target vocabulary.
To be more precise, that token is one past the last target token.
I'm using a beam size of 10, a N-best size of 10 and I want to sample 5.
Observations
While writing the bug report, I noticed that the target vocabulary has 15017 tokens, the KeyError is for 15018` but in the logs I see
[INFO:sockeye.vocab] Vocabulary (15018 words) loaded from "model/vocab.trg.0.json"

Translation Command
   time python \
      -m sockeye.translate \
         --disable-device-locking \
         --batch-size 32 \
         --strip-unknown-words \
         --models model/params/best \
         --input big_input \
         --beam-size=10 \
         --nbest-size=10 \
         --sample=5 \
      2> logs/log.trans.big_input \
	  > translation.json

Error Message
[INFO:__main__] Translating...
[ERROR:root] Uncaught exception
Traceback (most recent call last):
  File "/project/WMT20/opt/miniconda3/envs/sockeye-1.18.115_cu101/lib/python3.7/runpy.py", line 193, in _run_module_as_main
    "__main__", mod_spec)
  File "/project/WMT20/opt/miniconda3/envs/sockeye-1.18.115_cu101/lib/python3.7/runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "/project/WMT20/opt/miniconda3/envs/sockeye-1.18.115_cu101/lib/python3.7/site-packages/sockeye-1.18.115-py3.7.egg/sockeye/translate.py", line 273, in <module>
    main()
  File "/project/WMT20/opt/miniconda3/envs/sockeye-1.18.115_cu101/lib/python3.7/site-packages/sockeye-1.18.115-py3.7.egg/sockeye/translate.py", line 41, in main
    run_translate(args)
  File "/project/WMT20/opt/miniconda3/envs/sockeye-1.18.115_cu101/lib/python3.7/site-packages/sockeye-1.18.115-py3.7.egg/sockeye/translate.py", line 159, in run_translate
    input_is_json=args.json_input)
  File "/project/WMT20/opt/miniconda3/envs/sockeye-1.18.115_cu101/lib/python3.7/site-packages/sockeye-1.18.115-py3.7.egg/sockeye/translate.py", line 241, in read_and_translate
    chunk_time = translate(output_handler, chunk, translator)
  File "/project/WMT20/opt/miniconda3/envs/sockeye-1.18.115_cu101/lib/python3.7/site-packages/sockeye-1.18.115-py3.7.egg/sockeye/translate.py", line 264, in translate
    trans_outputs = translator.translate(trans_inputs)
  File "/project/WMT20/opt/miniconda3/envs/sockeye-1.18.115_cu101/lib/python3.7/site-packages/sockeye-1.18.115-py3.7.egg/sockeye/inference.py", line 1620, in translate
    results.append(self._make_result(trans_input, translation))
  File "/project/WMT20/opt/miniconda3/envs/sockeye-1.18.115_cu101/lib/python3.7/site-packages/sockeye-1.18.115-py3.7.egg/sockeye/inference.py", line 1733, in _make_result
    target_tokens_list = [[self.vocab_target_inv[id] for id in ids] for ids in nbest_target_ids]
  File "/project/WMT20/opt/miniconda3/envs/sockeye-1.18.115_cu101/lib/python3.7/site-packages/sockeye-1.18.115-py3.7.egg/sockeye/inference.py", line 1733, in <listcomp>
    target_tokens_list = [[self.vocab_target_inv[id] for id in ids] for ids in nbest_target_ids]
  File "/project/WMT20/opt/miniconda3/envs/sockeye-1.18.115_cu101/lib/python3.7/site-packages/sockeye-1.18.115-py3.7.egg/sockeye/inference.py", line 1733, in <listcomp>
    target_tokens_list = [[self.vocab_target_inv[id] for id in ids] for ids in nbest_target_ids]
KeyError: 15018

model/vocab.trg.0.json
{
    "<pad>": 0,
    "<unk>": 1,
    "<s>": 2,
    "</s>": 3,
    "<BT>": 4,
    "<TAG01>": 5,
	...
    "-RSB-": 15015,
    "-LCB-": 15016,
    "-RCB-": 15017
}

Translate Log
[INFO:sockeye.utils] Sockeye version 1.18.115, commit 41772bcb68b0e4bfb216f6541b5dde72c8c53f7a, path /project/WMT20/opt/miniconda3/envs/sockeye-1.18.115_cu101/lib/python3.7/site-packages/soc
keye-1.18.115-py3.7.egg/sockeye/__init__.py
[INFO:sockeye.utils] MXNet version 1.6.0, path /project/WMT20/opt/miniconda3/envs/sockeye-1.18.115_cu101/lib/python3.7/site-packages/mxnet/__init__.py
[INFO:sockeye.utils] Command: /project/WMT20/opt/miniconda3/envs/sockeye-1.18.115_cu101/lib/python3.7/site-packages/sockeye-1.18.115-py3.7.egg/sockeye/translate.py --disable-device-locking --batch-size 32 --strip-unknown-words --models model --input news.2019.de.shuffled.deduped_1200k.12/source.de.bpe --beam-size=10 --nbest-size=10 --sample=5
[INFO:sockeye.utils] Arguments: Namespace(avoid_list=None, batch_size=32, beam_prune=0, beam_search_stop='all', beam_size=10, brevity_penalty_constant_length_ratio=0.0, brevity_penalty_type='none', brevity_penalty_weight=1.0, bucket_width=10, checkpoints=None, chunk_size=None, config=None, device_ids=[-1], disable_device_locking=True, ensemble_mode='linear', input='news.2019.de.shuffled.deduped_1200k.02/source.de.bpe', input_factors=None, json_input=False, length_penalty_alpha=1.0, length_penalty_beta=0.0, lock_dir='/tmp', loglevel='INFO', max_input_len=None, max_output_length_num_stds=2, models=['model'], nbest_size=10, no_logfile=False, output=None, output_type='translation', override_dtype=None, quiet=False, restrict_lexicon=None, restrict_lexicon_topk=None, sample=5, seed=None, skip_topk=False, softmax_temperature=None, strip_unknown_words=False, sure_align_threshold=0.9, use_cpu=False)
[WARNING:__main__] For nbest translation, you must specify `--output-type 'json'; overriding your setting of 'translation'.
[WARNING:sockeye.utils] Sockeye currently does not respect CUDA_VISIBLE_DEVICE settings when locking GPU devices.
[INFO:sockeye.utils] Attempting to acquire 1 GPUs of 1 GPUs.
[INFO:__main__] Translate Device: gpu(0)
[INFO:sockeye.inference] Loading 1 model(s) from ['model'] ...

[ERROR:root] Uncaught exception
Traceback (most recent call last):
  File "/project/WMT20/opt/miniconda3/envs/sockeye-1.18.115_cu101/lib/python3.7/runpy.py", line 193, in _run_module_as_main
    "__main__", mod_spec)
  File "/project/WMT20/opt/miniconda3/envs/sockeye-1.18.115_cu101/lib/python3.7/runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "/project/WMT20/opt/miniconda3/envs/sockeye-1.18.115_cu101/lib/python3.7/site-packages/sockeye-1.18.115-py3.7.egg/sockeye/translate.py", line 273, in <module>
    main()
  File "/project/WMT20/opt/miniconda3/envs/sockeye-1.18.115_cu101/lib/python3.7/site-packages/sockeye-1.18.115-py3.7.egg/sockeye/translate.py", line 41, in main
    run_translate(args)
  File "/project/WMT20/opt/miniconda3/envs/sockeye-1.18.115_cu101/lib/python3.7/site-packages/sockeye-1.18.115-py3.7.egg/sockeye/translate.py", line 159, in run_translate
    input_is_json=args.json_input)
  File "/project/WMT20/opt/miniconda3/envs/sockeye-1.18.115_cu101/lib/python3.7/site-packages/sockeye-1.18.115-py3.7.egg/sockeye/translate.py", line 241, in read_and_translate
    chunk_time = translate(output_handler, chunk, translator)
  File "/project/WMT20/opt/miniconda3/envs/sockeye-1.18.115_cu101/lib/python3.7/site-packages/sockeye-1.18.115-py3.7.egg/sockeye/translate.py", line 264, in translate
    trans_outputs = translator.translate(trans_inputs)
  File "/project/WMT20/opt/miniconda3/envs/sockeye-1.18.115_cu101/lib/python3.7/site-packages/sockeye-1.18.115-py3.7.egg/sockeye/inference.py", line 1620, in translate
    results.append(self._make_result(trans_input, translation))
  File "/project/WMT20/opt/miniconda3/envs/sockeye-1.18.115_cu101/lib/python3.7/site-packages/sockeye-1.18.115-py3.7.egg/sockeye/inference.py", line 1733, in _make_result
    target_tokens_list = [[self.vocab_target_inv[id] for id in ids] for ids in nbest_target_ids]
  File "/project/WMT20/opt/miniconda3/envs/sockeye-1.18.115_cu101/lib/python3.7/site-packages/sockeye-1.18.115-py3.7.egg/sockeye/inference.py", line 1733, in <listcomp>
    target_tokens_list = [[self.vocab_target_inv[id] for id in ids] for ids in nbest_target_ids]
  File "/project/WMT20/opt/miniconda3/envs/sockeye-1.18.115_cu101/lib/python3.7/site-packages/sockeye-1.18.115-py3.7.egg/sockeye/inference.py", line 1733, in <listcomp>
    target_tokens_list = [[self.vocab_target_inv[id] for id in ids] for ids in nbest_target_ids]
KeyError: 15018

Sockeye Version
1.18.115
Conda Environment.yaml
name: sockeye-1.18.115_cu101
channels:
  - defaults
dependencies:
  - _libgcc_mutex=0.1=main
  - _tflow_select=2.3.0=mkl
  - absl-py=0.9.0=py37_0
  - alabaster=0.7.12=py37_0
  - asn1crypto=1.3.0=py37_0
  - astor=0.8.0=py37_0
  - babel=2.8.0=py_0
  - blas=1.0=mkl
  - blinker=1.4=py37_0
  - c-ares=1.15.0=h7b6447c_1001
  - ca-certificates=2020.1.1=0
  - cachetools=3.1.1=py_0
  - certifi=2<IP_ADDRESS>=py37_0
  - cffi=1.14.0=py37h2e261b9_0
  - chardet=3.0.4=py37_1003
  - click=7.1.1=py_0
  - cryptography=2.8=py37h1ba5d50_0
  - cudatoolkit=10.1.243=h6bb024c_0
  - cudnn=7.6.5=cuda10.1_0
  - cycler=0.10.0=py37_0
  - dbus=1.13.12=h746ee38_0
  - docutils=0.16=py37_0
  - expat=2.2.6=he6710b0_0
  - fontconfig=2.13.0=h9420a91_0
  - freetype=2.9.1=h8a8886c_1
  - gast=0.2.2=py37_0
  - glib=2.63.1=h5a9c865_0
  - google-auth=1.13.1=py_0
  - google-auth-oauthlib=0.4.1=py_2
  - google-pasta=0.2.0=py_0
  - grpcio=1.27.2=py37hf8bcb03_0
  - gst-plugins-base=1.14.0=hbbd80ab_1
  - gstreamer=1.14.0=hb453b48_1
  - h5py=2.10.0=py37h7918eee_0
  - hdf5=1.10.4=hb1b8bf9_0
  - icu=58.2=h9c2bf20_1
  - idna=2.9=py_1
  - imagesize=1.2.0=py_0
  - intel-openmp=2020.0=166
  - jinja2=2.11.1=py_0
  - jpeg=9b=h024ee3a_2
  - keras-applications=1.0.8=py_0
  - keras-preprocessing=1.1.0=py_1
  - kiwisolver=1.1.0=py37he6710b0_0
  - ld_impl_linux-64=2.33.1=h53a641e_7
  - libedit=3.1.20181209=hc058e9b_0
  - libffi=3.2.1=hd88cf55_4
  - libgcc-ng=9.1.0=hdf63c60_0
  - libgfortran-ng=7.3.0=hdf63c60_0
  - libpng=1.6.37=hbc83047_0
  - libprotobuf=3.11.4=hd408876_0
  - libstdcxx-ng=9.1.0=hdf63c60_0
  - libuuid=1.0.3=h1bed415_2
  - libxcb=1.13=h1bed415_1
  - libxml2=2.9.9=hea5a465_1
  - markdown=3.1.1=py37_0
  - markupsafe=1.1.1=py37h7b6447c_0
  - matplotlib=3.1.3=py37_0
  - matplotlib-base=3.1.3=py37hef1b27d_0
  - mkl=2020.0=166
  - mkl-service=2.3.0=py37he904b0f_0
  - mkl_fft=1.0.15=py37ha843d7b_0
  - mkl_random=1.1.0=py37hd6b4f25_0
  - ncurses=6.2=he6710b0_0
  - numpy=1.18.1=py37h4f9e942_0
  - numpy-base=1.18.1=py37hde5b4d6_1
  - oauthlib=3.1.0=py_0
  - openssl=1.1.1f=h7b6447c_0
  - opt_einsum=3.1.0=py_0
  - packaging=20.3=py_0
  - pcre=8.43=he6710b0_0
  - pip=20.0.2=py37_1
  - protobuf=3.11.4=py37he6710b0_0
  - pyasn1=0.4.8=py_0
  - pyasn1-modules=0.2.7=py_0
  - pycparser=2.20=py_0
  - pygments=2.6.1=py_0
  - pyjwt=1.7.1=py37_0
  - pyopenssl=19.1.0=py37_0
  - pyparsing=2.4.6=py_0
  - pyqt=5.9.2=py37h05f1152_2
  - pysocks=1.7.1=py37_0
  - python=3.7.7=hcf32534_0_cpython
  - python-dateutil=2.8.1=py_0
  - pytz=2019.3=py_0
  - qt=5.9.7=h5867ecd_1
  - readline=8.0=h7b6447c_0
  - requests=2.23.0=py37_0
  - requests-oauthlib=1.3.0=py_0
  - rsa=4.0=py_0
  - scipy=1.4.1=py37h0b6359f_0
  - setuptools=46.1.3=py37_0
  - sip=4.19.8=py37hf484d3e_0
  - six=1.14.0=py37_0
  - snowballstemmer=2.0.0=py_0
  - sphinx=2.4.4=py_0
  - sphinxcontrib-applehelp=1.0.2=py_0
  - sphinxcontrib-devhelp=1.0.2=py_0
  - sphinxcontrib-htmlhelp=1.0.3=py_0
  - sphinxcontrib-jsmath=1.0.1=py_0
  - sphinxcontrib-qthelp=1.0.3=py_0
  - sphinxcontrib-serializinghtml=1.1.4=py_0
  - sqlite=3.31.1=h7b6447c_0
  - tensorboard=2.1.0=py3_0
  - tensorflow=2.1.0=mkl_py37h80a91df_0
  - tensorflow-base=2.1.0=mkl_py37h6d63fb7_0
  - tensorflow-estimator=2.1.0=pyhd54b08b_0
  - termcolor=1.1.0=py37_1
  - tk=8.6.8=hbc83047_0
  - tornado=6.0.4=py37h7b6447c_1
  - urllib3=1.25.8=py37_0
  - werkzeug=1.0.1=py_0
  - wheel=0.34.2=py37_0
  - wrapt=1.12.1=py37h7b6447c_1
  - xz=5.2.4=h14c3975_4
  - zlib=1.2.11=h7b6447c_3
  - pip:
    - decorator==4.4.2
    - mxboard==0.1.0
    - mxnet-cu101mkl==1.6.0
    - mxnet-mkl==1.5.1
    - networkx==2.0
    - pillow==7.1.1
    - portalocker==1.7.0
    - pudb==2019.2
    - python-graphviz==0.8.4
    - sentencepiece==0.1.85
    - sockeye==1.18.115
    - subword-nmt==0.3.7
    - typing==<IP_ADDRESS>
    - urwid==2.1.0
prefix: /project/WMT20/opt/miniconda3/envs/sockeye-1.18.115_cu101

args.yaml
allow_missing_params: false
attention_based_copying: false
batch_size: 8192
batch_type: word
bucket_width: 10
checkpoint_interval: 4752
cnn_activation_type: glu
cnn_hidden_dropout: 0.2
cnn_kernel_width:
- 3
- 3
cnn_num_hidden: 512
cnn_positional_embedding_type: learned
cnn_project_qkv: false
config: model_config.yaml
conv_embed_add_positional_encodings: false
conv_embed_dropout: 0.0
conv_embed_max_filter_width: 8
conv_embed_num_filters:
- 200
- 200
- 250
- 250
- 300
- 300
- 300
- 300
conv_embed_num_highway_layers: 4
conv_embed_output_dim: null
conv_embed_pool_stride: 5
decode_and_evaluate: -1
decode_and_evaluate_device_id: null
decode_and_evaluate_use_cpu: false
decoder: transformer
decoder_only: false
device_ids:
- -4
disable_device_locking: true
dry_run: false
embed_dropout: &id001
- 0.0
- 0.0
embed_weight_init: default
encoder: transformer
fixed_param_names: []
fixed_param_strategy: null
gradient_clipping_threshold: 1.0
gradient_clipping_type: abs
gradient_compression_threshold: 0.5
gradient_compression_type: null
initial_learning_rate: 0.0001
keep_initializations: false
keep_last_params: 2
kvstore: device
label_smoothing: 0.1
layer_normalization: false
learning_rate_decay_optimizer_states_reset: 'off'
learning_rate_decay_param_reset: false
learning_rate_half_life: 10
learning_rate_reduce_factor: 0.7
learning_rate_reduce_num_not_improved: 8
learning_rate_schedule: null
learning_rate_scheduler_type: plateau-reduce
learning_rate_warmup: 0
length_task: null
length_task_layers: 1
length_task_weight: 1.0
lhuc: null
lock_dir: /tmp
loglevel: INFO
loss: cross-entropy
loss_normalization_type: valid
max_checkpoints: null
max_num_checkpoint_not_improved: 32
max_num_epochs: 1000
max_samples: null
max_seconds: null
max_seq_len:
- 200
- 200
max_updates: null
metrics:
- perplexity
- accuracy
min_num_epochs: null
min_samples: null
min_updates: null
momentum: null
monitor_pattern: null
monitor_stat_func: mx_default
no_bucketing: false
no_logfile: false
num_embed:
- null
- null
num_layers:
- 6
- 6
num_words:
- 0
- 0
optimized_metric: bleu
optimizer: adam
optimizer_params: null
output: model
overwrite_output: false
pad_vocab_to_multiple_of: null
params: ../../teacher.wmt.6.bpe-dr-t-src/de2cs.bpe.15k.bpe-dr/model/params.best
prepared_data: null
quiet: false
rnn_attention_coverage_max_fertility: 2
rnn_attention_coverage_num_hidden: 1
rnn_attention_coverage_type: count
rnn_attention_in_upper_layers: false
rnn_attention_mhdot_heads: null
rnn_attention_num_hidden: null
rnn_attention_type: mlp
rnn_attention_use_prev_word: false
rnn_cell_type: lstm
rnn_context_gating: false
rnn_decoder_hidden_dropout: 0.2
rnn_decoder_state_init: last
rnn_dropout_inputs: *id001
rnn_dropout_recurrent: *id001
rnn_dropout_states: *id001
rnn_enc_last_hidden_concat_to_embedding: false
rnn_encoder_reverse_input: false
rnn_first_residual_layer: 2
rnn_forget_bias: 0.0
rnn_h2h_init: orthogonal
rnn_num_hidden: 1024
rnn_residual_connections: false
rnn_scale_dot_attention: false
seed: 13
shared_vocab: false
source: ../../../corpora/preprocessing.multilingual.wmt.6/bpe.15k/bt.mono_hsb.backtrans.1/hsb-de_x12+witaj+si+web.bt_tag.bpe-dr-de/train.hsb-de.de.gz
source_factor_vocabs: []
source_factors: []
source_factors_combine: concat
source_factors_num_embed: []
source_vocab: ../../teacher.wmt.6.bpe-dr-t-src/de2cs.bpe.15k.bpe-dr/model/vocab.src.0.json
stop_training_on_decoder_failure: false
target: ../../../corpora/preprocessing.multilingual.wmt.6/bpe.15k/bt.mono_hsb.backtrans.1/hsb-de_x12+witaj+si+web.bt_tag.bpe-dr-de/train.hsb-de.hsb.gz
target_vocab: ../../teacher.wmt.6.bpe-dr-t-src/de2cs.bpe.15k.bpe-dr/model/vocab.trg.0.json
transformer_activation_type: relu
transformer_attention_heads:
- 8
- 8
transformer_dropout_act: 0.1
transformer_dropout_attention: 0.1
transformer_dropout_prepost: 0.1
transformer_feed_forward_num_hidden:
- 2048
- 2048
transformer_model_size:
- 512
- 512
transformer_positional_embedding_type: fixed
transformer_postprocess:
- dr
- dr
transformer_preprocess:
- n
- n
update_interval: 1
use_cpu: false
validation_source: ../../../corpora/preprocessing.multilingual.wmt.6/bpe.15k/bt.mono_hsb.backtrans.1/hsb-de_x12+witaj+si+web.bt_tag.bpe-dr-de/devel.hsb-de.de
validation_source_factors: []
validation_target: ../../../corpora/preprocessing.multilingual.wmt.6/bpe.15k/bt.mono_hsb.backtrans.1/hsb-de_x12+witaj+si+web.bt_tag.bpe-dr-de/devel.hsb-de.hsb
weight_decay: 0.0
weight_init: xavier
weight_init_scale: 3.0
weight_init_xavier_factor_type: avg
weight_init_xavier_rand_type: uniform
weight_normalization: false
weight_tying: false
weight_tying_type: trg_softmax
word_min_count:
- 1
- 1

I still believe this is an MXnet bug, but don't know how to reduce the problem to the single RNG state and input that cause random.multinomial to misbehave. As @fhieber said, that would be possible if the RNG state could be saved somehow.
@KellenSunderland we could need some MXnet expertise here, if you are interested in tackling this.

Closing for now as this applies to an older version of Sockeye.


[Spec Deviation] Strands created from named-worker-decls are scheduled in different threads

In the absence of annotations, the runtime scheduler should schedule strands created from named-worker-decls in the same thread.
Here is a sample code to reproduce this in jBallerina.
import ballerina/io;
import ballerinax/java;

public function main() {
    io:println("default: " + getCurrentThreadName());
    worker w1 {
        io:println("w1: " + getCurrentThreadName());
    }

    worker w2 {
        io:println("w2: " + getCurrentThreadName());
    }
}

function getCurrentThreadName() returns string {
    handle t = currentThread();
    handle tName = getName(t);
    return java:toString(tName) ?: "";
}

function currentThread() returns handle = @java:Method {
    class: "java.lang.Thread"
} external;

function getName(handle thread) returns handle = @java:Method {
    class: "java.lang.Thread"
} external;

Fix for this issue will be reverted by https://github.com/ballerina-platform/ballerina-lang/pull/20448


Custom Op Output Shape is Unknown in TF 1.15

Please make sure that this is a bug. As per our
GitHub Policy,
we only address code/doc bugs, performance issues, feature requests and
build/installation issues on GitHub. tag:bug_template
System information

Have I written custom code (as opposed to using a stock example script provided in TensorFlow): No
OS Platform and Distribution (e.g., Linux Ubuntu 16.04): SLES 12.2
Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue happens on mobile device:
TensorFlow installed from (source or binary): binary
TensorFlow version (use command below): 1.15.3
Python version: 3.5.2
Bazel version (if compiling from source):
GCC/Compiler version (if compiling from source): g++ 4.8 (for custom op)
CUDA/cuDNN version: 10.0 / 7.6
GPU model and memory: Tesla P100 / 12198MiB

You can collect some of this information using our environment capture
script
You can also obtain the TensorFlow version with:

TF 1.0: python -c "import tensorflow as tf; print(tf.GIT_VERSION, tf.VERSION)"
TF 2.0: python -c "import tensorflow as tf; print(tf.version.GIT_VERSION, tf.version.VERSION)"

Describe the current behavior
Custom Op compiled against TF 1.15 has unknown output shape (>>>print(repr(t.shape))  # TensorShape(None)) in following conditions:

Input tensor has a known shape.
Custom Op ShapeFn has been implemented to have the same output shape as input shape.

In TF 1.11, the output shape is identical to the input shape as expected.
Describe the expected behavior
Custom Op output shape should be identical to input shape (>>>print(repr(t.shape))  #TensorShape([6]))
Standalone code to reproduce the issue
Based on the "Zero Out" example from create an op. The following should get it up and running:

copy all files into the same directory
sh build.sh
python zero_out_shape_test.py

In TF 1.11 as_list will work and shape will be TensorShape([6]). In TF 1.15 as_list will fail (logs below) and shape will be TensorShape(None).
zero_out.cc
#include "tensorflow/core/framework/op.h"
#include "tensorflow/core/framework/shape_inference.h"
#include "tensorflow/core/framework/op_kernel.h"

using namespace tensorflow;

REGISTER_OP("ZeroOut")
    .Input("to_zero: int32")
    .Output("zeroed: int32")
    .SetShapeFn([](::tensorflow::shape_inference::InferenceContext* c) {
      c->set_output(0, c->input(0));
      return Status::OK();
    });

class ZeroOutOp : public OpKernel {
 public:
  explicit ZeroOutOp(OpKernelConstruction* context) : OpKernel(context) {}

  void Compute(OpKernelContext* context) override {
    // Grab the input tensor
    const Tensor& input_tensor = context->input(0);
    auto input = input_tensor.flat<int32>();

    // Create an output tensor
    Tensor* output_tensor = NULL;
    OP_REQUIRES_OK(context, context->allocate_output(0, input_tensor.shape(),
                                                     &output_tensor));
    auto output_flat = output_tensor->flat<int32>();

    // Set all but the first element of the output tensor to 0.
    const int N = input.size();
    for (int i = 1; i < N; i++) {
      output_flat(i) = 0;
    }

    // Preserve the first input value if possible.
    if (N > 0) output_flat(0) = input(0);
  }
};

REGISTER_KERNEL_BUILDER(Name("ZeroOut").Device(DEVICE_CPU), ZeroOutOp);

build.sh
TF_CFLAGS=( $(python -c 'import tensorflow as tf; print(" ".join(tf.sysconfig.get_compile_flags()))') )
TF_LFLAGS=( $(python -c 'import tensorflow as tf; print(" ".join(tf.sysconfig.get_link_flags()))') )
g++ -std=c++11 -shared zero_out.cc -o zero_out.so -fPIC ${TF_CFLAGS[@]} ${TF_LFLAGS[@]} -O2

zero_out_shape_test.py
import tensorflow as tf

_input = tf.constant([1, 2, 3, 4, 5, 6])
print('input shape:', _input.shape.as_list())

zero_out_module = tf.load_op_library('./zero_out.so')

zo_op = zero_out_module.zero_out(_input)
print(repr(zo_op.get_shape()))
print(zo_op.get_shape())
print(zo_op.get_shape().as_list())

Other info / logs Include any logs or source code that would be helpful to
TF 1.15 logs
input shape: [6]
TensorShape(None)
<unknown>
Traceback (most recent call last):
  File "zero_out_shape_test.py", line 11, in <module>
    print(zo_op.get_shape().as_list())
  File "******/python3.5/site-packages/tensorflow_core/python/framework/tensor_shape.py", line 1171, in as_list
    raise ValueError("as_list() is not defined on an unknown TensorShape.")
ValueError: as_list() is not defined on an unknown TensorShape.

TF 1.11 logs
input shape: [6]
TensorShape([Dimension(6)])
(6,)
[6]

@iandreariley,
TensorFlow 1.x is not actively supported. Could you please update TensorFlow to v2.3 and check if you are facing the same issue? Thanks!

@amahendrakar I'm unable to reproduce in v2.3. Thanks.


docs : Translated video_similarity_search.md into CN

docs : Translated video_similarity_search.md into CN
Fixes #548

Hi @Aryamanz29 , thank you for your contribution! I have reviewed your PR and it seems like that translation has not reached our standard for acceptance. I have left several comments and there are mainly 3 issues : 1) Inconsistency, 2) Translation does not follow our style guide, 3) Awkward sentence structure in Chinese (the last sentence).
We really appreciate your efforts, but you have to further edit and polish your translation in order for us to accept that.


[DNM][Frontend] Split -working-directory

Clang no longer supports -working-directory<path>. Split this argument into -working-directory <path> so that clients passing the old argument still work.

@swift-ci build toolchain


notmuch: add missing "patchShebangs configure"

This is on master as well, and fixes last failing notmuch test
"Ignore files and directories specified in new.ignore (regexp)"
Things done

[x] Tested using sandboxing (nix.useSandbox on NixOS, or option build-use-sandbox in nix.conf on non-NixOS)
Built on platform(s)

[x] NixOS
[ ] macOS
[ ] other Linux distributions

[ ] Tested via one or more NixOS test(s) if existing and applicable for the change (look inside nixos/tests)
[ ] Tested compilation of all pkgs that depend on this change using nix-shell -p nox --run "nox-review wip"
[x] Tested execution of all binary files (usually in ./result/bin/)
[x] Fits CONTRIBUTING.md.

Huh. What version of Nix this happens with?

Weird thing is, I could not reproduce the notmuch hydra failure locally on the staging-18.03 branch. Builds fine on my machine with or without this patch...

I was able to reproduce locally with a checkout of df29e697fde09363f7a2fbf6016986cd983f77b1, and a
nix-build -A notmuch -I nixpkgs=/path/to/checkout .

Nix 2.0.1 here.

I just did exactly the same and it succeded:
Notmuch test suite complete.
All 960 tests behaved as expected (4 expected failures).

Only difference is that I have nix (Nix) 2.0.

Success on x86_64-darwin (full log)
Attempted: notmuch
Partial log (click to expand)
/nix/store/6v3dva4yk0ahbz61zslv97s5dw6l19q7-notmuch-0.26/lib/libnotmuch.5.0.0.dylib: fixing dylib
/nix/store/6v3dva4yk0ahbz61zslv97s5dw6l19q7-notmuch-0.26/lib/libnotmuch.5.0.0.dylib: fixing dylib
/nix/store/6v3dva4yk0ahbz61zslv97s5dw6l19q7-notmuch-0.26/lib/libnotmuch.5.0.0.dylib: fixing dylib
/nix/store/6v3dva4yk0ahbz61zslv97s5dw6l19q7-notmuch-0.26/lib/libnotmuch.5.0.0.dylib: fixing dylib
/nix/store/6v3dva4yk0ahbz61zslv97s5dw6l19q7-notmuch-0.26/lib/libnotmuch.5.0.0.dylib: fixing dylib
/nix/store/6v3dva4yk0ahbz61zslv97s5dw6l19q7-notmuch-0.26/lib/libnotmuch.5.0.0.dylib: fixing dylib
/nix/store/6v3dva4yk0ahbz61zslv97s5dw6l19q7-notmuch-0.26/lib/libnotmuch.5.0.0.dylib: fixing dylib
/nix/store/6v3dva4yk0ahbz61zslv97s5dw6l19q7-notmuch-0.26/lib/libnotmuch.5.0.0.dylib: fixing dylib
/nix/store/6v3dva4yk0ahbz61zslv97s5dw6l19q7-notmuch-0.26/lib/libnotmuch.5.0.0.dylib: fixing dylib
/nix/store/6v3dva4yk0ahbz61zslv97s5dw6l19q7-notmuch-0.26

Success on aarch64-linux (full log)
Attempted: notmuch
Partial log (click to expand)
post-installation fixup
shrinking RPATHs of ELF executables and libraries in /nix/store/w2391clnxay9xra369gs533midiq20b1-notmuch-0.26
shrinking /nix/store/w2391clnxay9xra369gs533midiq20b1-notmuch-0.26/bin/notmuch
shrinking /nix/store/w2391clnxay9xra369gs533midiq20b1-notmuch-0.26/lib/libnotmuch.so.5.0.0
strip is /nix/store/lvx1acn1ig1j2km8jds5x3ggh3f2wa8v-binutils-2.28.1/bin/strip
stripping (with command strip and flags -S) in /nix/store/w2391clnxay9xra369gs533midiq20b1-notmuch-0.26/lib  /nix/store/w2391clnxay9xra369gs533midiq20b1-notmuch-0.26/bin
patching script interpreter paths in /nix/store/w2391clnxay9xra369gs533midiq20b1-notmuch-0.26
/nix/store/w2391clnxay9xra369gs533midiq20b1-notmuch-0.26/bin/notmuch-emacs-mua: interpreter directive changed from "/usr/bin/env bash" to "/nix/store/lnws52qanbi5vz8qg24v4ym57nznfndg-bash-4.4-p12/bin/bash"
checking for references to /build in /nix/store/w2391clnxay9xra369gs533midiq20b1-notmuch-0.26...
/nix/store/w2391clnxay9xra369gs533midiq20b1-notmuch-0.26

d97416198a035ed983e8195bca0493f6eee3f8ae (which seems to be this PR) speaks about /bin/sh impurity.

whatever, the patch shouldn't hurt and is consistent with master, so let's get this merged and see.

I don't know if it will help with the transient test failure (I was not able to reproduce it), but I suggest bumping notmuch to 0.26.1 at the same time. Builds ok for me against staging-18.03. See PR #39487


BrickSize public init

I forgot to add this in #26

Current coverage is 92.97% (diff: 100%)

No coverage report found for master at 19c524b.

Powered by Codecov. Last update 19c524b...25aeb9c


Inlay hints position

Hi,
Is it possible to show inlay hints inside the parenthesis of function call, Instead of at the end.
e.g:
fun(para1Hint: para1, para2Hint: para2)  >> returnParaHint
Thanks.

Update this plugin, switch to neovim nightly, then see :h vim.lsp.inlay_hint()


Max retries exceeded with url: /v2/_catalog (Caused by <class 'socket.error'>: [Errno 111] Connection refused)

Hi,
I'm using Docker Version:      1.11.2.
I'm using the two scripts you offer. The first one (delete_docker_registry_image) works fine. After doing the export I'm able to delete repo's.
But when I try to execute the second script (clean_old_versions) it does not work.
I've my registry (secured with a selfsigned cert) and I pushed:
myreg.com/busybox/busy:1
myreg.com/busybox/busy:2
myreg.com/busybox/busy:3
myreg.com/busybox/busy:4
myreg.com/busybox/busy:latest

Now I try to delete all images except the 4 newest:
./clean_old_versions --image 'busybox/busy' --include '*' -l 4
But this gave me:
Traceback (most recent call last):
  File "./clean_old_versions", line 86, in <module>
    main()
  File "./clean_old_versions", line 52, in main
    auth=auth, verify=args.no_check_certificate)
  File "/usr/lib/python2.7/dist-packages/requests/api.py", line 55, in get
    return request('get', url, **kwargs)
  File "/usr/lib/python2.7/dist-packages/requests/api.py", line 44, in request
    return session.request(method=method, url=url, **kwargs)
  File "/usr/lib/python2.7/dist-packages/requests/sessions.py", line 455, in request
    resp = self.send(prep, **send_kwargs)
  File "/usr/lib/python2.7/dist-packages/requests/sessions.py", line 558, in send
    r = adapter.send(request, **kwargs)
  File "/usr/lib/python2.7/dist-packages/requests/adapters.py", line 378, in send
    raise ConnectionError(e)
requests.exceptions.ConnectionError: HTTPConnectionPool(host='localhost', port=80): Max retries exceeded with url: /v2/_catalog (Caused by <class 'socket.error'>: [Errno 111] Connection refused)

Any help on this issue? Thanks

Hi, I can't help you with your original question but the registry does support garbage collection as of version 2.4 (2.5 is the current one). Maybe it is sufficient for your needs?
https://github.com/docker/distribution/blob/master/docs/garbage-collection.md

Thanks @donnex . I'm now exploring it. It seems to clean thins up in a nice way after I remove the manifest manually (rm -r inside the container). Do you know a better way how to delete a manifest of an image?. I saw this but it's unsupported:
curl -XDELETE http://myreg:5000/v2/proj1/base/manifests/1.0
{"errors":[{"code":"UNSUPPORTED","message":"The operation is unsupported."}]}

Yeah, you have to enable storage delete in the repository. I'm using env vars to enable it by setting REGISTRY_STORAGE_DELETE_ENABLED: "true".  It defaults to false, but it can be enabled by writing the following on the configuration file:
delete:
enabled: true

@donnex Thanks, I've started my registry with that variable.
Am I able to delete the image based on the tag? So deleting the manifest basedon the tag and than run the GC?
I tried:
curl -XDELETE http://my-reg:5000/v2/proj1/base/manifests/1.0
{"errors":[{"code":"DIGEST_INVALID","message":"provided digest did not match uploaded content"}]}
and

$ curl -XDELETE http://my-reg:5000/v2/proj1/base/manifests/tags/1.0
404 page not found


Feature: Added folder picker control

Q
A

Bug fix?
[ ]

New feature?
[y]

New sample?
[ ]

Related issues?
fixes #272

What's in this Pull Request?
Added new folder picker control.

Thank you @gautamdsheth for the new control!


State-dependent running cost

Is it possible to use state-dependent running costs?

In principle, yes, I just haven't implemented it yet. It would work exactly as outlined in the Quantum paper, so it's not that difficult. I can probably do it within the next couple of weeks.
As mentioned in https://github.com/JuliaQuantumControl/QuantumControl.jl/issues/38, it would be good to have an example to work with.


Do not force a favicon.ico

Do you want to request a feature or report a bug?
Bug.
What is the current behaviour?
Unless there's a src/assets/favicon.ico the current config will default to its own favicon.ico, as you can see here: https://github.com/developit/preact-cli/blob/6742f94664cf88ca0159f809e715fd441495e653/src/lib/webpack/render-html-plugin.js#L24
If the current behaviour is a bug, please provide the steps to reproduce.
Create a new preact-cli project. Delete src/assets/favicon.ico. Build. Now there is a favicon.ico at the root of the build directory, i.e. dist/favicon.ico.
What is the expected behaviour?
If I have no favicon.ico in my src/assets directory I expect to be there no favicon.ico in my build. Specially when the one provided is not blank and it impacts my branding. Specially when I have one coming from another directory which is being replaced by the one built-in.
If this is a feature request, what is motivation or use case for changing the behaviour?
To have more flexibility when dealing with static files I dropped the assets folder and used the copy plugin to have my files copied as is to the root of the build from a custom directory. e.g. src/static.
Please mention other relevant information.
N/A

Makes sense to me - if there's no favicon.ico we should omit the tag.

@JesseSingleton was absolutely right about that. That does indeed remove the favicon, and there was only a small adjustment of the specs required.


fix(child-process): require bridge rpc key

#132  👈
main

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Could not find zstdConfig.cmake error when using cpptrace

I compiled cpptrace with -DCPPTRACE_USE_EXTERNAL_LIBDWARF=On as I want to use the system libraries for zstd and libdwarf. cpptrace compiles and installs correctly.
Then, on my main project I added find_package(cpptrace REQUIRED) to the CMakeLists.txt file. When I try to configure it the next error is shown:

CMake Error at /usr/lib64/cmake/cpptrace/cpptrace-config.cmake:7 (find_package):
By not providing "Findzstd.cmake" in CMAKE_MODULE_PATH this project has
asked CMake to find a package configuration file provided by "zstd", but
CMake did not find one.
Could not find a package configuration file provided by "zstd" with any of
the following names:
zstdConfig.cmake
zstd-config.cmake

Add the installation prefix of "zstd" to CMAKE_PREFIX_PATH or set
"zstd_DIR" to a directory containing one of the above files.  If "zstd"
provides a separate development package or SDK, be sure it has been
installed.

If I remove the two find_dependency lines from cmake/in/cpptrace-config-cmake.in my project compiles, links and runs correctly. I think that probably the if(@CPPTRACE_GET_SYMBOLS_WITH_LIBDWARF@) should be changed so it also checks for CPPTRACE_USE_EXTERNAL_LIBDWARF in such a way that if it's enabled it should not try to find those dependencies as they are already linked to cpptrace.

Thanks for opening this, good catch

I think the original reason for adding the find_dependency was for package manger stuff. I will figure out how best to deal with this tomorrow.

I see. In my use case I created a cpptrace pacakge for Gentoo (that's why I turned on the settings to use system libraries) and then when using the installed package it failed bcause of that.

Oh awesome thanks so much for doing that! I have been looking at a similar issue today with the find_dependency(ZLIB) not working for someone else and I think I now better understand what’s going on with that issue and this one.
On your gentoo setup, is zstd installed but not zstd-dev (or similar) which would have the config files for the library or Findzstd.cmake?

I don't know the exact reason, but the zstd package only installs /usr/lib64/pkgconfig/libzstd.pc. It's libdwarf package the one which installs Findzstd.cmake (at /usr/lib64/cmake/libdwarf/Findzstd.cmake). I believe that cpptrace links against libdwarf and libdwarf links against zstd, so everything works fine. But when cpptrace tries to link explicetely with zstd it fails, as it can not find Findzstd.cmake (because it's installed in libdwarf path). Luckily, cpptrace doesn't actually needs to link against zstd, so when removing that part everything works fine.

Studying git blames a bit and playing around with removing the find_dependency(zstd) line I realized the reason it was needed is libdwarf's Findzstd.cmake script doesn't define zstd::libzstd_static / zstd::libzstd_shared targets. I think I've settled on a reasonable solution which is to provide a Findzstd.cmake script as part of cpptrace's installation and resolve the dependency that way. (reasonable in that I actually understand what's going on :P)
Please let me know if the setup in https://github.com/jeremy-rifkin/cpptrace/pull/115 works for your use case! I'll look to do a patch release soon.

Yep. Applying the patch seems to fix the issue. Given that cpptrace depends in libdwarf and this was a workaround for a libdwarf issue, I think it can make sense to submit your Findzstd.cmake to libdwarf?

Awesome thanks for confirming! I agree it would be good to apply upstream too.

On your gentoo setup, is zstd installed but not zstd-dev (or similar) which would have the config files for the library or Findzstd.cmake?

https://bugs.gentoo.org/872254
TL;DR: It depends on whether you build upstream zstd with CMake or not :(


IE11, ECMAScript Object property assignment problem

Hello,
On the PROD, Internet Explorer 11 doesn't work properly. I'm not having any issue when im working on localhost, but after i publish my app to PROD it gives me error below:
    SCRIPT1003: Expected ':'
    main-client.js (559,109)

I investigated to main-client.js, I found this:
    Pr={"ɵdefineBase":defineBase,
    "ɵdefineComponent":defineComponent,
    "ɵdefineDirective":H,
    defineInjectable, ## This is line:559 and column:109 ##

defineInjectable need to be "defineInjectable": defineInjectable. I've tested this in IE11 developer tool with following example,
   c = 3; d=4; values = {a:1, b:2, c, d} output is: Expected ':'
But this is what IE11 wants:
    c = 3; d=4; values = {a:1, b:2, c:c, d:d} outpus is: OK
Is it related with webpack? Any solution for this?
Thanks.

Hi @rcanpahali
I just addressed this issue today (exactly as you described... working local but not in a server). I solved by targeting ecmac 5 instead of 6 as described at https://github.com/MarkPieszak/aspnetcore-angular-universal/issues/666 . Hope it helps.
/Alex

Thank you so much mate, It solved my problem as well.


集成scrapy的pipeline时，运行save_item时候报错

Bug 描述
例如，当用v0.6版本集成scrapy的save_item到pipeline时候，运行报错
复现步骤
该 Bug 复现步骤如下

scrapy新项目，settings的ITEM_PIPELINES里加入 'crawlab.scrapy.pipelines.CrawlabPipeline': 888
运行项目，之前OK的项目，报如下错误：
'scrapy.spidermiddlewares.depth.DepthMiddleware']
2022-06-19 19:29:29 [twisted] CRITICAL: Unhandled error in Deferred:
2022-06-19 19:29:29 [twisted] CRITICAL:
Traceback (most recent call last):
File "/usr/local/lib/python3.7/site-packages/twisted/internet/defer.py", line 1660, in _inlineCallbacks
result = current_context.run(gen.send, result)
File "/usr/local/lib/python3.7/site-packages/scrapy/crawler.py", line 87, in crawl
self.engine = self._create_engine()
File "/usr/local/lib/python3.7/site-packages/scrapy/crawler.py", line 101, in _create_engine
return ExecutionEngine(self, lambda _: self.stop())
File "/usr/local/lib/python3.7/site-packages/scrapy/core/engine.py", line 70, in init
self.scraper = Scraper(crawler)
File "/usr/local/lib/python3.7/site-packages/scrapy/core/scraper.py", line 71, in init
self.itemproc = itemproc_cls.from_crawler(crawler)
File "/usr/local/lib/python3.7/site-packages/scrapy/middleware.py", line 53, in from_crawler
return cls.from_settings(crawler.settings, crawler)
File "/usr/local/lib/python3.7/site-packages/scrapy/middleware.py", line 34, in from_settings
mwcls = load_object(clspath)
File "/usr/local/lib/python3.7/site-packages/scrapy/utils/misc.py", line 61, in load_object
mod = import_module(module)
File "/usr/lib64/python3.7/importlib/init.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "", line 1006, in _gcd_import
File "", line 983, in _find_and_load
File "", line 953, in _find_and_load_unlocked
File "", line 219, in _call_with_frames_removed
File "", line 1006, in _gcd_import
File "", line 983, in _find_and_load
File "", line 965, in _find_and_load_unlocked
ModuleNotFoundError: No module named 'crawlab.scrapy'

之前是报 crawlab 找不到，单独用 pip install crawlab 后，就报上述错误了，想用pip安装不了。
[root@cecloud-ecs-78456 62adaf0b2fc909326db774e7]# pip install crawlab.scrapy
ERROR: Could not find a version that satisfies the requirement crawlab.scrapy (from versions: none)
ERROR: No matching distribution found for crawlab.scrapy
期望结果
能正常存入mongodb，不报错能工作。
截屏
CPU是ARM64的，对应的软件环境，Scrapy的版本不是默认v0.6的版本，因为高版本之前运行会报一个Reactor的错误，就降低到2.5.1了。

crawlab-sdk 版本多少？
pip freeze | grep crawlab-sdk


glusterfs  tier demote file fail?why

[2018-04-20 12:49:55.980303] E [MSGID: 109037] [tier.c:2532:tier_run] 0-vol-panda-tier-dht: Demotion failed
[2018-04-20 12:49:59.300175] E [MSGID: 109037] [tier.c:720:tier_lookup_file] 0-vol-panda-tier-dht: Failed to lookup file help_wev8.gif.ocTransferId1356036382.part
this is the error information,why to lookup the end of ".part" file?
who can tell me how tosresolve it ? thanks very much

hi hexulin-miaomiao
I don't understand at all what to do and what is failing.
We need to explain the issue in detail.
thanks.


Low watermark should not be changed by import

Low watermark should be not be changed by import. This should be a user initiated process to change the low watermark mostly like via a subcommand.

This really depends on WHERE the imported blocks/attestations go WRT existing entries.
I.e. if ANY entry in the import is above our highest entry - the low water mark should be incremented.
This implies we must have an explicit low watermark per validator for both block_slot, attestation_source_epoch and attestation_target_epoch


Apply pyupgrade --py39-plus.

Notable changes:

use PEP 585 type names
use PEP 604 type union syntax where from __future__ import annotations is present.
use f-strings in more places.
remove redundant arguments to open().

Fixes #16537

h/t to @lgeiger for pointing out that pyupgrade is a thing.

If you do the jupytext fixes via pre-commit run jupytext --all-files then you won't get the version mismatches.
Alternatively, make sure your local jupytext matches the version specified in pre-commit-config.yaml.

If you do the jupytext fixes via pre-commit run jupytext --all-files then you won't get the version mismatches.
Alternatively, make sure your local jupytext matches the version specified in pre-commit-config.yaml.

Done

Does this mean we can't/shouldn't use Optional[type] anymore?
Like Jake, I also prefer Optional[type] over type | None.

I personally prefer x | None over Optional, so I agree with pyupgrade personally. If nothing else, it requires one fewer import and it's shorter. Shorter code is our primary goal in life!

Does this mean we can't/shouldn't use Optional[type] anymore?
Like Jake, I also prefer Optional[type] over type | None.

Well, we don't have a rule here. Do as you like. But I suspect if I run pyupgrade Python 3.10 it may rewrite to this form.


Featured vs Approved tag

On WP website, I found this information regarding the Quality Tags:
"
Inclusion of pathways into specific pathway collections
WikiPathways uses quality tags to identify subsets of pathways as specific collections. For example, the quality tags "Featured version" and "Approved version" identify subsets of pathways in this way. Using tags to identify pathways as belonging to a specific collection is informative when viewing pathways, and also facilitates downloading of pathway archives. For inclusion to the archives mentioned above the criteria are as follows:
Featured: The "Featured version" collection contains pathways that represent the highest quality in terms of annotation. A pathway tagged as "featured" has a description and is annotated with ontology tags. The pathway also has to have a proper graph representation, meaning all relevant interactions must be connected to pathway entities and all data nodes must be annotated, at least for gene products.
Approved: The "Approved version" contains pathways that are considered to be close to complete in terms of the graph representation. This means that all relevant interactions must be connected to pathway entities, and data nodes must be annotated when possible. While "Approved version" pathways may not be complete in terms of bibliography and description, they are still useful for data analysis in other programs, like PathVisio and Cytoscape.
NOTE: Pathways that don't depict a biological process, for example list-based pathways, should NOT be included in the Featured and Approved sets.
"
Therefore, we shoudl run the Curation criteria for both Tags (and probably with slightly different criteria).

Agreed! Let's focus on Approved version first.
So references and description are not needed but I would keep them in the table so we know. I find the note about the list-based pathways interesting (I think that one is new), but that's also something easy to check (pathways with data nodes but no interactions).


Sort externalTargets queried from DNS

In case CoreDNS runs with loadbalancer round_robin plugin enabled, k8gb
controller gets shuffled results while computing externalTarget list.
This leads to DNSEndpoint object update despite the fact list is the
same. Lets make list sorted and reproducible to avoid unnescessary
reconcilation loops.
Signed-off-by: Dinar Valeev<EMAIL_ADDRESS>

@kuritka done


Mapping stack frame data to function variables

I have a crash report generated by breakpad:
 9  server.so + 0x00fea69f
    rbp = 0x00007ffd3dc42c90   rsp = 0x00007ffd3dc42c60   rip = 0x00007f4dc53cd69f

	Found by: previous frame's frame pointer
	Stack contents:
	 000000003dc42c60	00 08 02 61 0c 7f 00 00 12 00 00 00 00 50 c3 47	...a.........P.G
	 000000003dc42c70	61 04 00 00 00 00 00 00 00 26 3f 20 0c 7f 00 00	a........&? ....
	 000000003dc42c80	ff ff ff ff 00 00 00 00 00 26 3f 20 0c 7f 00 00	.........&? ....
	 000000003dc42c90	c0 2c c4 3d fd 7f 00 00 3a d8 3c c5 4d 7f 00 00	.,.=....:.<.M...

10  server.so + 0x00fea83a
    rbp = 0x00007ffd3dc42cc0   rsp = 0x00007ffd3dc42ca0   rip = 0x00007f4dc53cd83a

	Found by: previous frame's frame pointer
	Stack contents:
	 000000003dc42ca0	00 26 3f 20 0c 7f 00 00 61 04 00 00 00 00 00 00	.&? ....a.......
	 000000003dc42cb0	00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00	................
	 000000003dc42cc0	10 2d c4 3d fd 7f 00 00 58 41 be c4 4d 7f 00 00	.-.=....XA..M...

11  server.so + 0x00801158
    rbp = 0x00007ffd3dc42d10   rsp = 0x00007ffd3dc42cd0   rip = 0x00007f4dc4be4158

	Found by: previous frame's frame pointer
	Stack contents:
	 000000003dc42cd0	61 04 00 00 00 00 00 00 00 00 00 00 00 00 00 00	a...............
	 000000003dc42ce0	01 c7 03 00 00 00 00 00 00 26 3f 20 0c 7f 00 00	.........&? ....
	 000000003dc42cf0	61 04 00 00 00 00 00 00 00 00 00 00 00 00 00 00	a...............
	 000000003dc42d00	01 c7 03 00 00 00 00 00 ff ff ff ff 00 00 00 00	................
	 000000003dc42d10	a0 2e c4 3d fd 7f 00 00 fd 38 30 c5 4d 7f 00 00	...=.....80.M...

And the function from headless ghidra:
// Call address: 0x00fea83a
// Call line: ~7
// Parameter count: 1
// Parameter: [long * param_1@RDI:8]
// Stack frame size: 36
// Stack frame contents:
// >                  -28	local_1c (4 bytes)
// >                  -16	local_10 (8 bytes)
// > return offset    0
// > param offset     8

void FUN_010ea820(long *param_1)
{
  int iVar1;
  float fVar2;
  float fVar3;

  iVar1 = FUN_010ea5b0(0.5,param_1);
  if (0 < iVar1) {
    fVar3 = 0.0;
    if (*(char *)(param_1 + 0x177) == '\0') {
      fVar3 = 0.5;
    }
    fVar2 = (float)FUN_00c1c550(*(undefined4 *)(param_1[2] + 0x38));
    FUN_00900b50(fVar2 + fVar3,param_1,0);
    return;
  }
  FUN_009008a0(0,param_1,0,0,0,0);
  return;
}

Is it possible to identify the values in param_1, iVar1, fVar2 and fVar3 ?
How are the local_1c and local_10 related to the function variables? Why are they different in size and count?

The listing establishes local variables when it detects stack references, however these may not be true variables as determined by the decompiler (e.g., a single variable can jump between varnodes - comes in on register and moves to stack).


Add linting to project

I found a tool with which I could lint my code. This is very interesting and as far as I saw it can be integrated into the FAKE building process.
https://fsprojects.github.io/FSharpLint/index.html

I move that to another milestone. I tried to integrate it, but I'm not used to FAKE yet and I couldn't make it work.

As far as I understand it this depends on #1

I guess this is already included in Ionide so I don't see why I should add it to the project.


Update usage of endian builtin

It looks like there has been a change in how the endian flag is exposed in the standard library.
Compiled with zig 0.8.0-dev.2591+4b69bd61e
2 wikimedia tests in main.zig fail with OOM:
test "HTTPS request on wikipedia main page"... FAIL (CertificateVerificationFailed)
/opt/software/zig-0.8-dev/lib/std/heap/general_purpose_allocator.zig:606:13: 0x21d149 in std.heap.general_purpose_allocator.GeneralPurposeAllocator((struct std.heap.general_purpose_allocator.Config constant)).resize (test)
            return error.OutOfMemory;

test "HTTPS request on wikipedia alternate name"... FAIL (CertificateVerificationFailed)
/opt/software/zig-0.8-dev/lib/std/heap/general_purpose_allocator.zig:606:13: 0x21d149 in std.heap.general_purpose_allocator.GeneralPurposeAllocator((struct std.heap.general_purpose_allocator.Config constant)).resize (test)
            return error.OutOfMemory;

I was unable to verify the prior state as it doesn't seem the project builds with zig 0.7.1. The rest of the tests pass.

This looks like a duplicate of #15

:+1: Oh, sorry, I didn't see that!

Thanks anyway, I somehow missed thsi change :) (merged the other PR)


[Feature] Create GIF output as video thumbnail

Is there any possibility to create gif output for video thumbnail?

I don't have an idea to resolve the time range of cropping.

I think that gif should start from mediaInfo.duration / 3 up top next 2 or 3 seconds and method should be getVideoThumbnailAsGifFile(String videoPath)
Is it possible?

@lecicdjuro Thanks for your feedback.
I think it will solve this bill with problems
Future<File> saveToGif(String path, {
  int startTime,
  int endTime,
  int cutSec,  // When you do not know the end time
})

gif should start from mediaInfo.duration / 3 up top next 2 or 3 seconds

The default parameters will be adopted in your way
Usage
File = await saveToGif(path)

If you agree with the idea, it will be updated in the next release.

Perfect. Thanks a lot!
When do you plan to release the next version?

This weekend 🤔

Hey @TenkaiRuri sorry to drop in like this, but I am @lecicdjuro's colleague and I had some spare time so I actually implemented the feature. However, I cannot open a pull request on your git, nor can I push a code change to a branch. Can you please add me so I can get the change up on for review if that is ok with you?

Thanks! Can you please take a look when you get a chance?
Please note that I'm an Android developer and don't have any experience in Flutter nor in iOS and Swift so when review please take a special look at that part of the code.
Also, I have taken the liberty to refactor Kotlin code since the single class where everything was located was  getting too big so I have just broken it into several smaller classes instead to improve readability.

@vlada3003
Tbh, I am also a beginner. Neither swift nor kotlin have been formally written.
All code is written in google search. I am originally a front end developer.
Maybe this is why my code is bad :)
Thank you for the pull request. I am very happy now, the language can't express my happiness. .
Rumi Amami

thanks. when will you upload the next version to the repo?

@vlada3003 Already, I modified some document comments so that dart can better support.


Clarify instructions in readme

It just says make run, but which script should we run? snippets of the commands to actually run from start to finish would be nice as well as this software attracts filthy casuals like me.

Hi,
thanks for your comment. On which OS are you trying to run the script ?
can you please describe the issue you are seeing and what is really blocking you.
make run is a command to type in your shell to start Makefile invocation.
the commands to run the script are below:
$ make pipenv-install this command install all environment needed by this python script
$ make run execute the script. (You can also run manually pipenv run add_indexer.py)
Makefile execute all commands needed

https://github.com/Guilhem23/Jackett_Indexerr/blob/master/Makefile

Did you get it sorted? I'm having the same problem.
Cloned the repo using Github Desktop
Ran config.py once to generate config.ini
Replaced jackett_apikey & apikey with my jackett API.
Ran add_indexer.py but nothing happened.
Sorry I'm a noob! Any help appreciated thanks.

@Spykerwolf can you please paste your config file here without apikey and command used to run?
thx

Hey man. Sure thing - here you go.
I'm on Windows 10 x64 - tried double clicking on add_indexer.py to run it.
[default]
jackett_apikey = MYAPI_FROM_JACKETTKEY
jackett_url = http://<IP_ADDRESS>:9117
indexer_prefix = AUTO:
[sonarr]
apikey = MYAPI_FROM_JACKETTKEY
url = https://localhost/sonarr/api/
categoryprefixes = ['TV']
animecategoryprefixes = ['Anime', 'TV']
[radarr]
apikey = MYAPI_FROM_JACKETTKEY
url = https://localhost/radarr/api/
categoryprefixes = ['Movies']
animecategoryprefixes = ['Anime', 'Movies']
[lidarr]
apikey = MYAPI_FROM_JACKETTKEY
url = https://localhost/lidarr/api/v1/
categoryprefixes = ['Audio']

humm ok Windows 10... never tried on windows.
Have you tried to use make run from a powershell command instead of double clicking on the python script?

I tried running make file with PS but got the following error - please see attached.
How are you running it? Maybe I can setup a VM in order to run it.

Just checking to see if you had a chance to read my last comment?


fix: ensure environment variables are passed correctly in integrations

Updated logic to properly handle and pass environment variables from integrations to tasks

This fix is connected to the discussion I opened up in General

t.Environment.JSON isn't environment variables. This JSON used in --extra-vars parameter of ansible-playbook.

Well then you must absolutely modify your docs where it states differently
https://github.com/semaphoreui/semaphore-docs/blob/fe6c8b493b5d7d47c9a0eceb8f738986372be6d1/user-guide/integrations.md?plain=1#L21


Shortcut not working

I can use the extension when right-clicking files and pick "batch rename". It even shows the shortcut (control + command + R) in my case but when I press the shortcut, nothing happens. When the action is clicked via mouse menu, it works. No other action is assigned to this shortcut. I've tried different shortcuts, same result.
Using VSCode 1.74.3

Same issue here

Can confirm this issue still happens, I tried to bind it to Shift-F2 (as a counterpart to F2 to rename) but it silently fails.

Can you check View/Output/Extension Host?
I was getting the error [error] Error: EACCES: permission denied, open '/Users/User/.vscode/extensions/jannisx11.batch-rename-extension-0.0.6/out/src/.Batch Rename.txt'
Fixing the rights, fixed the issue.


fix: restore instruction count functionality

Brings back instruction counts that show that bytecode has changed rather than VM performance. They were previously disabled because vm2 didn't support tracers.

heap_read_write is still N/A, which seems wrong.


Increase odom queue size so messages dont drop

Would it make sense to do this for the other point drawing plugins as well?  (GPS, Route, Tf, I forget if there are others)

It probably would. I'll go ahead and do that

I pushed that now. I went and changed all the single point types ones. I hesitate doing it for routes as those really shouldnt run into the same cases.


[Bug Android] Scrolling vertically on ListView, make a swipe out of range.

Hello There,
I got an issue with Carousel View with two listViews Content, it's just happening on Android
It's literally swipe out of range, when I'm doing a vertical scroll on ListView.
then I just do a click and the List is coming back.
I didn't get this issue on iOS
There a demo:

If you got any idea where could be the problem, let me know.
regards,

Hi
Try to play with

VerticalSwipeThresholdDistance = 1000
SwipeThresholdDistance = 100
etc.

I need a sample for debugging it, what is causing animation

Yeah I tried
I have not enough time to give you a sample right now.
It's seems to come when I change manually the CarouselView.SelectedIndex then I swipe

@Phenek try it now please
if you want, you can debug, why CurrentView == CurrentBackViews[0].
It seems, that SetupBackViews isn't called sometimes

try 1.6.4

Hey first Thanks,
unfortunately 1.6.4 didn't worked, I still get the issue like in the Gif.
I will investigate why CurrentView == CurrentBackViews[0]
when I got time.

Hey first Thanks,
unfortunately 1.6.4 didn't worked, I still get the issue like in the Gif.
I will investigate why CurrentView == CurrentBackViews[0]
when I got time.

I think, this issue is related to embedding view only and doesn't affect ItemTemplate approach


Issue: IncludeVocabAndRules not including rules

Hi,
I am deploying a project and everything except policies is being deployed. In my .btdfproj file i have:
True
True
And later when adding policies:

path_to_policy_folder

path_to_policy_folder

The project builds without error, but no policies are deployed. In the output, there is nothing related to DeployBTRules, so it seems like it isn't even trying to deploy the rules.
Any help would be appreciated.
Thanks,
Dale
This work item was migrated from CodePlex
CodePlex work item ID: '10668'
Vote count: '1'

[tfabraham@7/2/2014]
The most likely cause of nothing happening is that it can't locate the XML files.  Are you running this deployment within Visual Studio?  Are you using a relative path in LocationPath?

[dalemac89@7/3/2014]
Hi, thanks for the response.
Yes, I am building in Visual Studio via Tools -> Deployment Framework for BizTalk -> Deploy BizTalk Solution.
Yes, the LocationPath is relative, like so:
<RulePolicies Include="Property.Policy.xml">
      <LocationPath>..\$(ProjectName).Deployment\Policies\Localhost</LocationPath>
    </RulePolicies>

It is the exact same format that is used to load schemas, itineraries, etc, and they all work fine.
Thanks,
Dale

[dalemac89@7/3/2014]
Sorry, I have another question, too.
If i wanted to preprocess the policy xml files before they are deployed, what would I need to do?
The policies contain some transport locations that will be different depending on the environment, so i'm wondering what the best way to handle that would be.
Thanks,
Dale

[tfabraham@7/7/2014]
The preprocessing question has been discussed here.
Are the policies at least being published, if not deployed?  You should see the DeployVocabAndRules target executing after ImportBindings.

[dalemac89@7/8/2014]
Hi Tom,
No, the policies are not being published to the database. There is no DeployVocabAndRules at any point of the process during output. It is as if it isn't being invoked for whatever reason.
Thanks,
Dale

[tfabraham@7/8/2014]
I'm making the assumption that you are using a stock, unmodified BTDF v5.5, and that you're on at least BizTalk 2010.
Please add this to your .btdfproj near the end and capture the results.
<Target Name="PreDeployVocabAndRules" AfterTargets="ImportBindings">
  <Message Text="IncludeVocabAndRules = '$(IncludeVocabAndRules)'" />
  <Message Text="RulePolicies = '@(RulePolicies)'" />
  <Message Text="RuleVocabularies = '@(RuleVocabularies)'" />
  <Message Text="RulePoliciesQualified = '@(RulePoliciesQualified)'" />
  <Message Text="RuleVocabulariesQualified = '@(RuleVocabulariesQualified)'" />
</Target>

[dalemac89@7/9/2014]
Hi Tom,
I re-exported the policies from the BizTalk Admin Console and then it magically started working. I can only assume the XML markup was malformed for some reason. I would have though incorrect markup would have thrown an error though.
Anyhow, it is solved now. Thanks for the suggestions and support.
Dale

[dalemac89@7/9/2014]
From one BRI issue to another.
Now that the policies are being built into an MSI, I tried to deploy to the server and it failed. Tried it on the local and it fails, too.
The policies are being exported into one policy file using the biztalk admin console. I haven't started pre-processing them yet. This is the error I get:
 Information: Adding resource (-Type="System.BizTalk:Rules" -Luid="RULE/ESB.EndPointInfo/1.0") to application "UoL.ESB"...
  Information: Validating resources (count=1)...
  * Validating resource (-Type="System.BizTalk:Rules" -Luid="RULE/ESB.EndPointInfo/1.0")...
  Information: Found the rules store SERVER="DALE-BIZTALK-PC" and DATABASE="BizTalkRuleEngineDb".
  Information: Finding the rule set name="ESB.EndPointInfo" and version="1.0"...
EXEC : error : Failed to add resource(s). [C:\Users\dale-biztalk\Documents\Visual Studio 2012\Projects\UoL.ESB\Main\UoL.ESB\Deployment\Deployment.btdfproj]
  Validation failed for 1 resource(s).
  The rules policy "ESB.EndPointInfo" with version 1.0 is not found in the rule store. Please select existing policy.

Upon checking the re_vocabulary table on BizTalkRuleEngineDb the vocabilaries are there as they should be.
I have checked the permissions on the database and they are all fine. I have tried exporting the policies individually and adding them to the deployment config individually. Google doesn't give any real insight into this error.
Any ideas?
Thanks,
Dale

[dalemac89@7/9/2014]
Here is the PreDeployVocabAndRules target:
PreDeployVocabAndRules:
  IncludeVocabAndRules = 'True'
  RulePolicies = 'UoL.ESB.Policies.ALL_POLICIES.xml'
  RuleVocabularies = 'UoL.ESB.Vocabularies.xml'
  RulePoliciesQualified = '..\UoL.ESB.Deployment\Deployment\Policies\Original\UoL.ESB.Policies.ALL_POLICIES.xml'
  RuleVocabulariesQualified = '..\UoL.ESB.BRE\UoL.ESB.Vocabularies.xml'
UndeployVocabAndRules:
  Populating metadata in ItemGroup from policy/vocabulary files content...
    Working on '..\UoL.ESB.Deployment\Deployment\Policies\Original\UoL.ESB.Policies.ALL_POLICIES.xml'...
      Added item [PolicyName:'ESB.EndPointInfo'; PolicyVersion:'1.0']
      Added item [PolicyName:'ESB.ContextInfo'; PolicyVersion:'1.0']
      Added item [PolicyName:'ESB.Itinerary'; PolicyVersion:'1.1']
      Added item [PolicyName:'ESB.TransformInfo'; PolicyVersion:'1.0']
      Added item [PolicyName:'UoL.ESB.Policies.SMS.Student'; PolicyVersion:'1.0']
      Added item [PolicyName:'UoL.ESB.Policies.SMS.StudentAddress'; PolicyVersion:'1.0']
      Added item [PolicyName:'UoL.ESB.Policies.EMS.Floor'; PolicyVersion:'1.0']
      Added item [PolicyName:'UoL.ESB.Policies.SMS.CompositeStudent'; PolicyVersion:'1.0']
      Added item [PolicyName:'UoL.ESB.Policies.EMS.Location'; PolicyVersion:'1.0']
      Added item [PolicyName:'UoL.ESB.Policies.ItinerarySelect'; PolicyVersion:'1.0']
      Added item [PolicyName:'UoL.ESB.Policies.EMS.Space'; PolicyVersion:'1.0']
      Added item [PolicyName:'UoL.ESB.Policies.EMS.Property'; PolicyVersion:'1.0']
  Finished populating metadata in ItemGroup from policy/vocabulary files content.
  "C:\Program Files (x86)\Deployment Framework for BizTalk 5.5\Framework\DeployTools\DeployBTRules.exe" /ruleSetName "ESB.EndPointInfo" /ruleSetVersion "1.0" /unpublish /undeploy
  BizTalk Rules Engine Policy/Vocabulary Deployment Tool v<IP_ADDRESS>
  Copyright (C) 2005-2014 Scott Colestock, Thomas F. Abraham

  No published ruleset with name 'ESB.EndPointInfo' and version '1.0'.
  Operation complete.

  "C:\Program Files (x86)\Deployment Framework for BizTalk 5.5\Framework\DeployTools\DeployBTRules.exe" /ruleSetName "ESB.ContextInfo" /ruleSetVersion "1.0" /unpublish /undeploy
  BizTalk Rules Engine Policy/Vocabulary Deployment Tool v<IP_ADDRESS>
  Copyright (C) 2005-2014 Scott Colestock, Thomas F. Abraham

  No published ruleset with name 'ESB.ContextInfo' and version '1.0'.
  Operation complete.

  "C:\Program Files (x86)\Deployment Framework for BizTalk 5.5\Framework\DeployTools\DeployBTRules.exe" /ruleSetName "ESB.Itinerary" /ruleSetVersion "1.1" /unpublish /undeploy
  BizTalk Rules Engine Policy/Vocabulary Deployment Tool v<IP_ADDRESS>
  Copyright (C) 2005-2014 Scott Colestock, Thomas F. Abraham

  No published ruleset with name 'ESB.Itinerary' and version '1.1'.
  Operation complete.

  "C:\Program Files (x86)\Deployment Framework for BizTalk 5.5\Framework\DeployTools\DeployBTRules.exe" /ruleSetName "ESB.TransformInfo" /ruleSetVersion "1.0" /unpublish /undeploy
  BizTalk Rules Engine Policy/Vocabulary Deployment Tool v<IP_ADDRESS>
  Copyright (C) 2005-2014 Scott Colestock, Thomas F. Abraham

  No published ruleset with name 'ESB.TransformInfo' and version '1.0'.
  Operation complete.

  "C:\Program Files (x86)\Deployment Framework for BizTalk 5.5\Framework\DeployTools\DeployBTRules.exe" /ruleSetName "UoL.ESB.Policies.SMS.Student" /ruleSetVersion "1.0" /unpublish /undeploy
  BizTalk Rules Engine Policy/Vocabulary Deployment Tool v<IP_ADDRESS>
  Copyright (C) 2005-2014 Scott Colestock, Thomas F. Abraham

  No published ruleset with name 'UoL.ESB.Policies.SMS.Student' and version '1.0'.
  Operation complete.

  "C:\Program Files (x86)\Deployment Framework for BizTalk 5.5\Framework\DeployTools\DeployBTRules.exe" /ruleSetName "UoL.ESB.Policies.SMS.StudentAddress" /ruleSetVersion "1.0" /unpublish /undeploy
  BizTalk Rules Engine Policy/Vocabulary Deployment Tool v<IP_ADDRESS>
  Copyright (C) 2005-2014 Scott Colestock, Thomas F. Abraham

  No published ruleset with name 'UoL.ESB.Policies.SMS.StudentAddress' and version '1.0'.
  Operation complete.

  "C:\Program Files (x86)\Deployment Framework for BizTalk 5.5\Framework\DeployTools\DeployBTRules.exe" /ruleSetName "UoL.ESB.Policies.EMS.Floor" /ruleSetVersion "1.0" /unpublish /undeploy
  BizTalk Rules Engine Policy/Vocabulary Deployment Tool v<IP_ADDRESS>
  Copyright (C) 2005-2014 Scott Colestock, Thomas F. Abraham

  No published ruleset with name 'UoL.ESB.Policies.EMS.Floor' and version '1.0'.
  Operation complete.

  "C:\Program Files (x86)\Deployment Framework for BizTalk 5.5\Framework\DeployTools\DeployBTRules.exe" /ruleSetName "UoL.ESB.Policies.SMS.CompositeStudent" /ruleSetVersion "1.0" /unpublish /undeploy
  BizTalk Rules Engine Policy/Vocabulary Deployment Tool v<IP_ADDRESS>
  Copyright (C) 2005-2014 Scott Colestock, Thomas F. Abraham

  No published ruleset with name 'UoL.ESB.Policies.SMS.CompositeStudent' and version '1.0'.
  Operation complete.

  "C:\Program Files (x86)\Deployment Framework for BizTalk 5.5\Framework\DeployTools\DeployBTRules.exe" /ruleSetName "UoL.ESB.Policies.EMS.Location" /ruleSetVersion "1.0" /unpublish /undeploy
  BizTalk Rules Engine Policy/Vocabulary Deployment Tool v<IP_ADDRESS>
  Copyright (C) 2005-2014 Scott Colestock, Thomas F. Abraham

  No published ruleset with name 'UoL.ESB.Policies.EMS.Location' and version '1.0'.
  Operation complete.

  "C:\Program Files (x86)\Deployment Framework for BizTalk 5.5\Framework\DeployTools\DeployBTRules.exe" /ruleSetName "UoL.ESB.Policies.ItinerarySelect" /ruleSetVersion "1.0" /unpublish /undeploy
  BizTalk Rules Engine Policy/Vocabulary Deployment Tool v<IP_ADDRESS>
  Copyright (C) 2005-2014 Scott Colestock, Thomas F. Abraham

  No published ruleset with name 'UoL.ESB.Policies.ItinerarySelect' and version '1.0'.
  Operation complete.

  "C:\Program Files (x86)\Deployment Framework for BizTalk 5.5\Framework\DeployTools\DeployBTRules.exe" /ruleSetName "UoL.ESB.Policies.EMS.Space" /ruleSetVersion "1.0" /unpublish /undeploy
  BizTalk Rules Engine Policy/Vocabulary Deployment Tool v<IP_ADDRESS>
  Copyright (C) 2005-2014 Scott Colestock, Thomas F. Abraham

  No published ruleset with name 'UoL.ESB.Policies.EMS.Space' and version '1.0'.
  Operation complete.

  "C:\Program Files (x86)\Deployment Framework for BizTalk 5.5\Framework\DeployTools\DeployBTRules.exe" /ruleSetName "UoL.ESB.Policies.EMS.Property" /ruleSetVersion "1.0" /unpublish /undeploy
  BizTalk Rules Engine Policy/Vocabulary Deployment Tool v<IP_ADDRESS>
  Copyright (C) 2005-2014 Scott Colestock, Thomas F. Abraham

  No published ruleset with name 'UoL.ESB.Policies.EMS.Property' and version '1.0'.
  Operation complete.

Why does it think that ESB.EndPointInfo, ESB.ContextInfo etc are policies? Surely they should be vocabularies?
Thanks
Dale

[tfabraham@7/9/2014]
Yes, those are vocabularies and not ones that you should be deploying anyway.  They're part of the ESB Toolkit Microsoft.Practices.ESB app deployment.
This might all be a result of how you're exporting the policies/vocabs.  The Deployment Framework expects policies and vocabularies to be in separate XML files, never mixed.  The feature was designed to work with the output of the Business Rules Engine Deployment Wizard, not the export feature in BizTalk Admin.  Can you try again using the BRE Deployment Wizard to export, and update your .btdfproj accordingly?

[dalemac89@7/11/2014]
Hi Tom,
Got it all working as expected now so thanks again. I've just made a small donation to show my gratitude.
Still have to figure out pre-processing the policy files, but i don't think that will be to much as an issue.
Thanks,
Dale

[tfabraham@7/11/2014]
Thanks very much Dale!  Did you end up re-exporting using the BRE Deployment Wizard?
I think everything necessary to set up the policy preprocessing is covered here, but if not just post a message on that thread.

[dalemac89@7/11/2014]
Hi Tom,
It's the least I could do.
Yes, I exported the policies using the BRE Depolyment Wizard. There were some additional issues as some of the additional vocabularies were not installed on the server for some reason, but that was an easy fix.
I won't be looking at the policy preprocessing for the next week as i am off work, but it i run into trouble i will post on that thread as you suggested.
Thanks again,
Dale

[UnknownUser@7/11/2014]

Issue closed by tfabraham with comment
Policy and vocab files must be exported by BRE Deployment Wizard instead of BizTalk Admin
Reason closed
Not BTDF


Fit for swift2.0

Please...I really like it..........I cant remove it from my project at all

extension String
{
func stringByAppendingPathComponent(path: String) -> String
{
let nsSt = self as NSString
return nsSt.stringByAppendingPathComponent(path)
}
}

You also need to delete the sqlite2 library from your project tree and add libsqlite3.tbd in the "build phase" tab, section "Link Binary With Libraries"

thank u,thank u,thank u,thank u,thank u,thank u,thank u,I just change it into "aaa"+"\bbb"

i have deleted the sqlite 2 library from my project and added the libsqlite3.tbd in the build phase. but i don't know where to add the extension.. can you help me with this?

Add a new swift file in your project (I called mine StringExtention.swift) and put the class extension code in it.

I am able to create the string extension. However, SwiftData.swift has more than 100 errors when I try to add it to a Swift 2 project. Some of them are pretty simple to fix, but I am not sure about the rest.

did you do this step?
" You also need to delete the sqlite2 library from your project tree and add libsqlite3.tbd in the "build phase" tab, in section "Link Binary With Libraries" "
Also, are the first errors related to stringByAppendingPathComponent?
If yes then the compiler is not seeing your extention. The best it to put it in a separate file.
Don't forget to import Foundation in the extention file.

RegisStGelais, thanks... it save me.

Nice fix , thanks!


[SPARK-26990][SQL][BACKPORT-2.4] FileIndex: use user specified field names if possible

What changes were proposed in this pull request?
Back-port of #23894 to branch-2.4.
WIth the following file structure:
/tmp/data
└── a=5

In the previous release:
scala> spark.read.schema("A int, ID long").parquet("/tmp/data/").printSchema
root
 |-- ID: long (nullable = true)
 |-- A: integer (nullable = true)

While in current code:
scala> spark.read.schema("A int, ID long").parquet("/tmp/data/").printSchema
root
 |-- ID: long (nullable = true)
 |-- a: integer (nullable = true)

We can see that the partition column name a is different from A as user specifed. This PR is to fix the case and make it more user-friendly.
Closes #23894 from gengliangwang/fileIndexSchema.
Authored-by: Gengliang Wang<EMAIL_ADDRESS>Signed-off-by: Wenchen Fan<EMAIL_ADDRESS>How was this patch tested?
Unit test

Can one of the admins verify this patch?

Can one of the admins verify this patch?

Test build #102830 has started for PR 23909 at commit 06606d6.

Test build #102830 has finished for PR 23909 at commit 06606d6.

This patch passes all tests.
This patch merges cleanly.
This patch adds no public classes.

Merged build finished. Test PASSed.

Test PASSed.
Refer to this link for build results (access rights to CI server needed):
https://amplab.cs.berkeley.edu/jenkins//job/SparkPullRequestBuilder/102830/
Test PASSed.

ah sorry I thought it's a bug only in master, thanks for doing it!

merging to 2.4!


Gradients calculation doesn't match with probability

Gradients
https://github.com/Microsoft/LightGBM/blob/master/src/objective/binary_objective.hpp#L63-L78
63        const score_t response = -2.0f * label * sigmoid_ / (1.0f + std::exp(2.0f * label * sigmoid_ * score[i]));
66        hessians[i] = abs_response * (2.0f * sigmoid_ - abs_response) * label_weight;
and line 75, 78
This is derived from logloss func L = -log(1+exp(-2 * label * score)) and prob = 1 / (1+exp(-2*score)).
But the following prob calcs don't contain 2 *  within exp().
Probability
https://github.com/Microsoft/LightGBM/blob/master/src/boosting/gbdt.cpp#L368
368    ret = 1.0 / (1.0 + std::exp(-sigmoid_ * ret));
https://github.com/Microsoft/LightGBM/blob/master/src/metric/binary_metric.hpp#L60-L68
60, 68         score_t prob = 1.0f / (1.0f + std::exp(-sigmoid_ * score[i]));
So you have two options. you can remove all 2.0f * in Gradients calculation, or you can add 2.0f* within exp() in probability calc.

Thanks, you are right, have fixed.


Investigate numeric ids (wip)

ref GRO-33
Got some code for us? Awesome 🎊!
Please include a description of your change & check your PR against this list, thanks!

[ ] There's a clear use-case for this code change, explained below
[ ] Commit message has a short title & references relevant issues
[ ] The build will pass (run yarn test:all and yarn lint)

We appreciate your contribution!

🤖[deprecated] Generated by Copilot at bb3ca2c
This pull request adds a feature and tests for using numeric object IDs in the email service. It modifies the base model file events.js to switch between MongoDB's ObjectID and numeric IDs, and the test file batch-sending.test.js to use both types of IDs in the email service tests.

This PR is genius 😍


Make re-exports from other crates show up as such

… in types and sub-modules.

Orthogonally, I think we need to be consistent here. Some times we import the crate ( e.g., uuid ), sometimes the type ( eg., BigDecimal ), and sometimes we define a new module for only some of the types ( chrono, time ).
cc @abonander


High-level api for computing eigenvalues and eigenvectors from square matrices?

Hi @sarah-ek,
Is there any plans on adding any high-level APIs for computing eigenvectors and eigenvalues of square, but not necessarily symmetric, matrices?
I really like the ergonomics of your library but it would be nice to just have a functional, simple API for providing matrices and getting out eigenvalues and their associated eigenvectors without having to hand roll some form of iterative/inverse iteration method in each new crate.

Hi @sarah-ek,
Thanks for the pointer - I must of missed this. The crate has really evolved since I last looked around, it's very impressive! The eigendecomposition and the partial LU pivot are working great for my use case after testing, I'll be switching out the nalgebra components for faer now.
I'll close this issue.


⚠ GitHub has degraded performance

In 4c017c4, GitHub (https://www.githubstatus.com/api/v2/status.json) experienced degraded performance:

HTTP code: 200
Response time: 357 ms

Resolved: GitHub performance has improved in 7f60c7c.


Error: Multiple matching artifacts found upon testing w/ latest nightly version

Component
Forge
Have you ensured that all of these are up to date?

[ ] Foundry
[ ] Foundryup

What version of Foundry are you on?
forge 0.2.0 (440ec52 2024-04-11T00:22:09.585245000Z)
What command(s) is the bug in?
forge test
Operating System
macOS (Apple Silicon)
Describe the bug
With foundry nightly-440ec525deb00b4dca138794865c27d1e8ea4d01 and above, whenever I run my tests, I get an Multiple matching artifacts found error. Upon reverting my foundry to nightly-f625d0fa7c51e65b4bf1e8f7931cd1c6e2e285e9 and before, the tests pass.
Specifically, the setup breaks when I call deployCode() on an contract that has multiple artifacts (that are not matching).
The line in it's full context can be seen here.
Error code:

Artifacts:

after running foundryup -v nightly-f625d0fa7c51e65b4bf1e8f7931cd1c6e2e285e9 && forge test, the tests pass.

We've recently added validation and more checks for getCode cheatcodes so it is now more sensitive to ambiguous inputs. It seems that your GaugePointFacet.sol file contains 2 contracts (interface and actual contract), thus this error occurs.
You can change this line to deployCode("GaugePointFacet") or deployCode("GaugePointFacet.sol:GaugePointFacet") and it should fix the issue