Annotate nn.initializers

This was done to address concerns in this review: https://github.com/google/flax/pull/1803#discussion_r807895042, namely to expose an Initializers type annotation that can be used in other libraries.

@jakevdp Would you mind taking a look at this old pull request when you get a chance?  Thank you :)

Thank you!

It looks like this introduced some dtype errors in the test suite – please take a look!

Last thing - could you please squash your changes into a single commit? See https://jax.readthedocs.io/en/latest/contributing.html#single-change-commits-and-pull-requests for more. Thanks!

@jakevdp Yes, I'll squash them now!
I was told by some people not to squash during a code review to make it easy for you to verify that I'm making the requested changes.  When I'm submitting to Jax, would you prefer that I keep doing this going forward (not squashing until we're ready to push), or squash every time I make a change?

FYI, this needed to be rolled back (#11735) because some of the annotations were incorrect (in particular, downstream callers were passing tuples of ints to some shapes annotated as NamedShape)

@jakevdp Sorry about that! The only things annotated NamedShape are private functions, so I guess I wrongly assumed that those wouldn't be called externally?

In theory, that's true. In practice, folks use whatever they want 😁

@jakevdp Fair enough :smile: I'll try to be more careful of this in the future.  Do you think #11748 fixes that problem?


Update the comments

After upgrading XGBoost to the master version, I found that when I set the param num_col to 0 as usual in XGDMatrixCreateFromFile, it could not get the correct columns.
Signed-off-by: Hao Ziyu<EMAIL_ADDRESS>

Codecov Report

Merging #6457 (a75d025) into master (c2ba4fb) will increase coverage by 0.21%.
The diff coverage is n/a.

@@            Coverage Diff             @@
##           master    #6457      +/-   ##
==========================================
+ Coverage   79.94%   80.15%   +0.21%
==========================================
  Files          12       13       +1
  Lines        3475     3512      +37
==========================================
+ Hits         2778     2815      +37
  Misses        697      697

Impacted Files
Coverage Δ

python-package/xgboost/config.py
100.00% <0.00%> (ø)

python-package/xgboost/dask.py
81.14% <0.00%> (+0.14%)
:arrow_up:

python-package/xgboost/__init__.py
89.47% <0.00%> (+0.58%)
:arrow_up:

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
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Thanks for submitting the PR.  I will try to follow up.


Improve isAlphaNum

Using recent version of LDC, here are the codegen I get:
        lea     eax, [rdi - 48]
        cmp     eax, 74
        ja      .LBB2_1
        lea     ecx, [rdi - 97]
        mov     al, 1
        cmp     ecx, -39
        jb      .LBB2_4
        add     edi, -65
        cmp     edi, 26
        setb    al
.LBB2_4:
        ret
.LBB2_1:
        xor     eax, eax
        ret

And now:
        lea     eax, [rdi - 48]
        cmp     eax, 9
        setb    cl
        or      edi, 32
        add     edi, -97
        cmp     edi, 26
        setb    al
        or      al, cl
        ret

Which is much better all around: less instructions, no branches, etc...
I will note that doing isDigit(c) || isAlpha(c) also gives me good codegen using LDC, but I chose against it as DMD fails to inline properly and the end result is pretty bad.

What is required to unblock this?

What is required to unblock this?

Try rebasing.

@thewilsonator this is on top of master already.

then just force-push to restart the CIs


PYTHON not found in PATH - build 3.8

Here is my docker file:
FROM jfloff/alpine-python:3.8-onbuild

# Build stage
FROM node:lts-alpine as build

RUN apk update; \
  apk add git;
WORKDIR /tmp
COPY package*.json ./
RUN npm ci
COPY . .
RUN npm run build

# Release stage
FROM node:lts-alpine as release

RUN apk update; \
  apk add git;

VOLUME /parse-server/cloud /parse-server/config

WORKDIR /parse-server

COPY package*.json ./

RUN npm ci --production --ignore-scripts

COPY bin bin
COPY public_html public_html
COPY views views
COPY --from=build /tmp/lib lib
RUN mkdir -p logs && chown -R node: logs

ENV PORT=80
USER node
EXPOSE $PORT

ENTRYPOINT ["node", "./bin/parse-server"]

docker build throws a path error.
PYTHON, PYTHON2, PYTHON3 not found in path
I have copied the entrypoint.sh in the same dir and my requirements.txt is empty as I dont have any package dependencies.

Your problem is here: FROM node:lts-alpine as release this won't have the alpine-python overlays in the final package.
I notice you're using the "onbuild" image at the top, but don't have any ONBUILD calls in your multi-stage Dockerfile.
I think if you remove that top line and replace this FROM node:lts-alpine as release with FROM jfloff/alpine-python:3.8 you might get the desired effect?


Paralell read_sql

Hello,
do you plan to implement parallel execution for pandas.read_sql ?
Dask has parallel access to databases but API is cumbersome and limited to queries written with sqlalchemy expressions.
I think pointing partitions would be an extra as a read_sql parameter (also number of threads/sessions to DB).
Regards,
RD

HI @igorborgest
Looks like a good trail to follow Spark.
Do you think of a query as really  arbitrary, including the where statement? pyspark.sql.DataFrameReader.jdbc has predicates to filter data.
I would consider number of maximum threads as a parameter. DBMS`s instances often have limitations on users which may make trouble while loading data, or you just want it to leave to modin number of processors parameter?

Hey @rd5802, we have an experimental API that was merged as a part of #436.
After you pip install git+https://github.com/modin-project/modin (current master branch) you can try it with this:
import modin.experimental.pandas as pd
import pandas
import sqlite3
import numpy as np
filename = "test_from_sql.db"
conn = sqlite3.connect(filename)
table = "test_from_sql"
frame_data = np.random.randint(0, 100, size=(100, 100))
pandas.DataFrame(frame_data).add_prefix("col").to_sql(table, conn)
db_uri = "sqlite:///" + filename
df = pd.read_sql("select * from {}".format(table), db_uri, partition_column="[index]", lower_bound=0, upper_bound=100)

For this case, query can be an arbitrary query, so something like predicates shouldn't be necessary. You raise a very good point about process number, that is something we will have to look into. Right now it is defaulting to the number of cores on the machine, but that could be problematic on larger machines. Each process creates its own connection, so we may have to force limit the parallelism on the Modin side.
We could add a parameter for number of connections/processes in the experimental API. Would you prefer a parameter?

Hey @devin-petersohn,
Yes, I want a parameter !!!  E.g.  max_connections, connections or parallelism .

Hi @devin-petersohn,
I run the cone after pip install, it says ModuleNotFoundError: No module named 'modin.experimantal'

Hey @rd5802, we have an experimental API that was merged as a part of #436.
After you pip install git+https://github.com/modin-project/modin (current master branch) you can try it with this:
import modin.experimental.pandas as pd
import pandas
import sqlite3
import numpy as np
filename = "test_from_sql.db"
conn = sqlite3.connect(filename)
table = "test_from_sql"
frame_data = np.random.randint(0, 100, size=(100, 100))
pandas.DataFrame(frame_data).add_prefix("col").to_sql(table, conn)
db_uri = "sqlite:///" + filename
df = pd.read_sql("select * from {}".format(table), db_uri, partition_column="[index]", lower_bound=0, upper_bound=100)

For this case, query can be an arbitrary query, so something like predicates shouldn't be necessary. You raise a very good point about process number, that is something we will have to look into. Right now it is defaulting to the number of cores on the machine, but that could be problematic on larger machines. Each process creates its own connection, so we may have to force limit the parallelism on the Modin side.
We could add a parameter for number of connections/processes in the experimental API. Would you prefer a parameter?

Hi @devin-petersohn,
I run the cone after pip install, it says ModuleNotFoundError: No module named 'modin.experimantal'
Regards,
RD

Hey @rd5802, we have an experimental API that was merged as a part of #436.
After you pip install git+https://github.com/modin-project/modin (current master branch) you can try it with this:
import modin.experimental.pandas as pd
import pandas
import sqlite3
import numpy as np
filename = "test_from_sql.db"
conn = sqlite3.connect(filename)
table = "test_from_sql"
frame_data = np.random.randint(0, 100, size=(100, 100))
pandas.DataFrame(frame_data).add_prefix("col").to_sql(table, conn)
db_uri = "sqlite:///" + filename
df = pd.read_sql("select * from {}".format(table), db_uri, partition_column="[index]", lower_bound=0, upper_bound=100)

For this case, query can be an arbitrary query, so something like predicates shouldn't be necessary. You raise a very good point about process number, that is something we will have to look into. Right now it is defaulting to the number of cores on the machine, but that could be problematic on larger machines. Each process creates its own connection, so we may have to force limit the parallelism on the Modin side.
We could add a parameter for number of connections/processes in the experimental API. Would you prefer a parameter?

Works like a charm.

Were you able to install from master? We haven't released a version with this to pypi so you have to pip install with the specific command for git.

Docs:
https://modin.readthedocs.io/en/latest/installation.html#installing-from-the-github-master-branch

Not sure if this is relevant, but for anyone interested in reading about how parallel read queries are currently accomplished with SQLalchemy and Dask, their discussion on the issue is located at https://github.com/dask/dask/issues/2604.

Thanks @Shellcat-Zero, We do have a way to do this already, merged in #499. Feel free to try it out!
There is also an experimental API that uses hints similar to the Spark SQL API #436.

Thanks @devin-petersohn.  Most generally I think a common use case with Dask at least is to apply dataframe or machine learning operations across a cluster, and their implementation (discussed in the link provided) I believe will distribute partitions of the query across the cluster nodes, whereas my understanding of this implementation with Modin is that it is doing a parallel read into the partitions of a dataframe on a single machine.
As a new user to Modin, I haven't found much documentation yet on clustering as one might do with Dask, or if that is a desired feature for Modin. If that is a currently supported, I was wondering if you could point me to the relevant documentation.

Sorry for the noise, I believe I found what I was looking for: https://modin.readthedocs.io/en/latest/using_modin.html#using-modin-on-a-cluster

I am going to close this issue as it has been implemented.
@Shellcat-Zero if you have a question on cluster usage, I am happy to discuss in a new issue.


Removed duplicate foxit-pdf-reader app manifest

Deleted the duplicate app manifest for foxit-pdf-reader. Both the files foxit-pdf-reader and foxit-reader had the same file hash and contents hence I removed foxit-reader and kept foxit-pdf-reader as it helps in easily searching for pdf readers in scoop.sh
Hash (SHA256) : F3974726390277A5454EBA2F7993B3482C622B0A7A2AA0AD59E7D38E4FB9C440:1327
FullName
E:\Extras\bucket\foxit-pdf-reader.json
E:\Extras\bucket\foxit-reader.json

[X] I have read the Contributing Guide.

/verify

https://github.com/ScoopInstaller/Extras/pull/9633#issue-1433411847


add test cases for merge

Fixes #ISSUSE_ID.
Changes proposed in this pull request:

Codecov Report

Merging #687 into dev will increase coverage by 1.11%.
The diff coverage is n/a.

@@            Coverage Diff             @@
##              dev     #687      +/-   ##
==========================================
+ Coverage   67.44%   68.56%   +1.11%
==========================================
  Files         441      441
  Lines        8413     8413
  Branches     1347     1347
==========================================
+ Hits         5674     5768      +94
+ Misses       2426     2333      -93
+ Partials      313      312       -1

Impacted Files
Coverage Δ

...ingjdbc/core/parsing/parser/context/OrderItem.java
92.3% <0%> (+2.56%)
:arrow_up:

...dbc/core/merger/dql/common/StreamMergedResult.java
100% <0%> (+4.54%)
:arrow_up:

...o/shardingjdbc/core/merger/dql/DQLMergeEngine.java
89.28% <0%> (+7.14%)
:arrow_up:

...e/merger/dal/show/ShowCreateTableMergedResult.java
36.36% <0%> (+36.36%)
:arrow_up:

...dql/pagination/RowNumberDecoratorMergedResult.java
84.21% <0%> (+47.36%)
:arrow_up:

...gination/TopAndRowNumberDecoratorMergedResult.java
94.11% <0%> (+94.11%)
:arrow_up:

...c/core/merger/dal/show/ShowTablesMergedResult.java
96.42% <0%> (+96.42%)
:arrow_up:

...bc/core/merger/dal/show/ShowOtherMergedResult.java
100% <0%> (+100%)
:arrow_up:

...o/shardingjdbc/core/merger/dal/DALMergeEngine.java
100% <0%> (+100%)
:arrow_up:

...ore/merger/dal/show/ShowDatabasesMergedResult.java
100% <0%> (+100%)
:arrow_up:

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 699b06b...a084e43. Read the comment docs.


404 Page Creation Required

I need a good 404 page for my website - https://github.com/Superari15/funari/issues/1,

Here are few best 404 pages from the Codepen.

https://codepen.io/saransh/pen/aezht
https://codepen.io/marcobiedermann/pen/WbGazL?q=+404+page.&limit=all&type=type-pens
https://codepen.io/kborling/pen/QwbKEe?q=+404+page.&limit=all&type=type-pens
https://codepen.io/mycnlz/pen/LNbwwj?limit=all&page=2&q=+404+page.
https://codepen.io/benstanley/pen/JYepog?limit=all&page=2&q=+404+page.

You can find more from the codepen itself

The issue is closed in the original repo. Shouldn't we close this as well?

Yes.
On 01-Dec-2017, at 7:41 AM, Paulo Fernandes <notifications<EMAIL_ADDRESS>wrote:
The issue is closed in the original repo.https://github.com/Superari15/funari/issues/1 Shouldn't we close this as well?
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHubhttps://github.com/yourfirstpr/yourfirstpr.github.io/issues/95#issuecomment-348381265, or mute the threadhttps://github.com/notifications/unsubscribe-auth/AV6_JhL_RpG-TdgTc5qU9Ls9DT-dWjHmks5s72AygaJpZM4QaxkX.

I'll be very glad to contribute here.


FE-73: Fix breadcrumb's position

Overview
JIRA: https://r3-cev.atlassian.net/browse/FE-73
Breadcrumb is now fixed at the top of pages so that it’s always visible, regardless of user scrolling.

However, the original position/layout is kept for smaller screen (e.g. on mobile deviceS), meaning it will get hidden once user scroll further down the page. Since we got very limited display on small device, it's best practice and common to not to fix non-essential ui element on the screen.

Thanks, @zhengmar3. There's a preview site here: https://docs.preview.docs.r3.com/en/platform/corda/5.0-beta.html
There's an issue when you click one of the top drop-down menus from a page with a breadcrumb:

Also, do you think some kind of border or something under the breadcrumb to differentiate it from the main content would be nice?

Really
On Thu, Apr 6, 2023, 3:30 AM Yariv Bachar @.***> wrote:

@.**** commented on this pull request.
thx @zhengmar3 https://github.com/zhengmar3
—
Reply to this email directly, view it on GitHub
https://github.com/corda/corda-docs-portal/pull/1261#pullrequestreview-1374439341,
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Clap detection

CODAL has added a "clap" event, similar to "loud" and "quiet".

https://github.com/lancaster-university/codal-core/commit/99b9399857fd5e6110c2f0b9f2b3d134cd59e92d
https://github.com/bbcmicrobit/micropython/pull/793

For the set_threshold() method we'll need to throw an exception if the "clap" event is provided, as that threshold cannot be configured.

SoundEvent.CLAP is added in 8b8c1d3802164abe40659edde9cf3a717aabfde4

For the set_threshold() method we'll need to throw an exception if the "clap" event is provided,

This is also done (didn't need any changes, was already raising an exception for invalid sound events).

@microbit-carlos this is already done (see above).  I tested it and it seems to work, microphone.get_events() does emit a SoundEvent.CLAP on occasion.


Feature request: Transform Processor support in ADOT Collector

tl;dr: it would be great if the ADOT collector distribution supported the transform processor so users can easily replace illegal characters in span attributes.
We route OTel data to X-Ray, which limits the legal characters in segment names; in particular, ! characters are not allowed. Unfortunately, our telemetry includes the peer.service span attribute with values that look like protocol!service, and if peer.service is present, it's used as the segment name.
If the collector supported the transform processor, we could apply the following transformation:
processors:
  transform/replace-exclamation-with-colon:
    trace_statements:
    - context: span
      statements:
      - replace_pattern(attributes["peer.service"], "!", ":")

Without transform, we have a workaround:
processors:
  attributes:
    actions:
      - key: peer.service
        action: extract
        pattern: ^(.+)!(?P<peerservice>.*)$    # AFAICT using "peer.service" would be an illegal capture group name
      - key: peer.service
        action: update
        from_attribute: peerservice
      - key: peerservice
        action: delete

but this is three steps instead of one, and I'm not confident it will hold up as we scale up the number of spans we're processing.

ADOT PM here. Thanks for raising this issue (though would be more appropriate against https://github.com/aws-observability/aws-otel-collector). This makes certainly sense and we will look into that. Once I have a timeline, will update the issue with it.

Oops, sorry about that. I'm happy to move it over there if it would help!


Support different improper torsion multiplicity

This PR fixes #156 and #150.

Codecov Report

Merging #157 (f89982e) into master (c623ca1) will not change coverage.
The diff coverage is 0.00%.


SAM type change causes undercompilation

This is yet another example of Zinc lagging Scala language spec change.
https://www.scala-lang.org/news/2.12.0/#lambda-syntax-for-sam-types
steps
Haven't minimized it but I noticed while coding. First you have a Java interface in one subproject.
import java.nio.file.Path;
import java.util.Optional;

public interface SingleOutput {
    public Path getOutputDirectory();

    public default Optional<Path> getSingleOutput() {
        return Optional.of(getOutputDirectory());
    }
}

In another subproject, use it as  SAM-type lambda:
val output: SingleOutput = () => RootFilePath.resolve("out")

Then change the Java interface..
import java.io.File;
import java.util.Optional;

public interface SingleOutput {
    public File getOutputDirectory();

    public default Optional< File > getSingleOutput() {
        return Optional.of(getOutputDirectory());
    }
}

problem
The Scala code is not invalidated. So locally compile keeps succeeding. On CI the build fails if it's compiled from scratch.
expectation
Invalidate correctly.

Fixed in Scala 3 with https://github.com/lampepfl/dotty/pull/16996.

Interesting, this got closed from a commit in another repo, but should be kept open since it's still an issue in scala 2.


visual studio 2022 crashes when loading my solution

This issue has been moved from a ticket on Developer Community.

visual studio 2022 crashes when loading my solution
when i load visual studio without my solution, (or another solution) it does not crash.
I had this problem before, but it went away when upgrading visual studio 2022.
I have been working in this solution - VS version just yesterday and everything was fine.
Now it crashes on open.
Using the latest vs version 17.1.3
the solution loads without crashing in VS 2019

Original Comments
Feedback Bot on 4/11/2022, 03:21 AM:
(private comment, text removed)
Kaylee Xu [MSFT] on 4/11/2022, 11:18 PM:
(private comment, text removed)
sjors miltenburg on 4/20/2022, 06:44 AM:
(private comment, text removed)
sjors miltenburg on 4/11/2022, 11:34 PM:
(private comment, text removed)
Kaylee Xu [MSFT] on 4/13/2022, 01:35 AM:
(private comment, text removed)
sjors miltenburg on 4/13/2022, 03:26 AM:
(private comment, text removed)
Kaylee Xu [MSFT] on 4/13/2022, 08:42 PM:
(private comment, text removed)
Feedback Bot on 4/20/2022, 08:38 PM:
(private comment, text removed)

Original Solutions
(no solutions)

I believe it was this issue: https://github.com/Redth/ResizetizerNT/commit/9e0defbd4bb5366d3f3b5d2526765a1d5c3dccd4


please change allocation.cc line 102 copied_buffer_ = std::move(buffer);

System information

Have I written custom code (as opposed to using a stock example script provided in TensorFlow):
OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
CentOS 6.9
TensorFlow installed from (source or binary):
source
TensorFlow version (use command below):
1.9.0-rc2
Python version:
3.6.2
Bazel version (if compiling from source):
0.14.1
GCC/Compiler version (if compiling from source):
gcc 6.2.0
CUDA/cuDNN version:
cuda 9.0 and cudnn 7.1.1
GPU model and memory:
NVIDIA K80 (12GB/GPU) and P100(16GB/GPU)
Exact command to reproduce:

exec env -
CUDA_TOOLKIT_PATH=/apps/cuda/9.0
CUDNN_INSTALL_PATH=/apps/cudnn/7.1.1-cuda9.0
GCC_HOST_COMPILER_PATH=/apps/gcc/6.2.0/wrapper/gcc
LD_LIBRARY_PATH=/apps/gcc/6.2.0/lib/gcc/x86_64-pc-linux-gnu/6.2.0:/apps/gcc/6.2.0/lib64:/apps/nccl/2.2.13-cuda9.0/lib:/apps/openmpi/3.1.0/lib:/apps/openmpi/3.1.0/lib/profilers:/apps/intel-ct/<IP_ADDRESS>/mkl/lib/intel64:/apps/python3/3.6.2/lib:/apps/binutils/2.25/lib:/apps/java/jdk1.8.0_60/lib:/apps/cudnn/7.1.1-cuda9.0/lib64:/apps/cuda/9.0/extras/CUPTI/lib64:/apps/cuda/9.0/lib64
NCCL_INSTALL_PATH=/apps/nccl/2.2.13-cuda9.0
PATH=/apps/gcc/6.2.0/wrapper:/apps/gcc/6.2.0/bin:/apps/openmpi/wrapper/fortran:/apps/openmpi/3.1.0/bin:/apps/python3/3.6.2/bin:/apps/binutils/2.25/bin:/apps/bazel/0.14.1/bin:/apps/java/jdk1.8.0_60/bin:/apps/cuda/9.0/bin:/home/900/yxs900/.local/bin:/opt/bin:/bin:/usr/bin
PWD=/proc/self/cwd
PYTHON_BIN_PATH=/apps/python3/3.6.2/bin/python3
PYTHON_LIB_PATH=/apps/python3/3.6.2/lib/python3.6/site-packages
TF_CUDA_CLANG=0
TF_CUDA_COMPUTE_CAPABILITIES=3.7,6.0
TF_CUDA_VERSION=9.0
TF_CUDNN_VERSION=7
TF_NCCL_VERSION=2
TF_NEED_CUDA=1
TF_NEED_OPENCL_SYCL=0
external/local_config_cuda/crosstool/clang/bin/crosstool_wrapper_driver_is_not_gcc -MD -MF bazel-out/k8-opt/bin/tensorflow/contrib/lite/objs/framework/tensorflow/contrib/lite/allocation.pic.d '-frandom-seed=bazel-out/k8-opt/bin/tensorflow/contrib/lite/objs/framework/tensorflow/contrib/lite/allocation.pic.o' -DEIGEN_MPL2_ONLY '-DEIGEN_MAX_ALIGN_BYTES=64' -iquote . -iquote bazel-out/k8-opt/genfiles -iquote external/bazel_tools -iquote bazel-out/k8-opt/genfiles/external/bazel_tools -iquote external/eigen_archive -iquote bazel-out/k8-opt/genfiles/external/eigen_archive -iquote external/local_config_sycl -iquote bazel-out/k8-opt/genfiles/external/local_config_sycl -iquote external/gemmlowp -iquote bazel-out/k8-opt/genfiles/external/gemmlowp -iquote external/flatbuffers -iquote bazel-out/k8-opt/genfiles/external/flatbuffers -isystem third_party/eigen3/mkl_include -isystem bazel-out/k8-opt/genfiles/third_party/eigen3/mkl_include -isystem bazel-out/k8-opt/bin/third_party/eigen3/mkl_include -isystem external/eigen_archive -isystem bazel-out/k8-opt/genfiles/external/eigen_archive -isystem bazel-out/k8-opt/bin/external/eigen_archive -isystem tensorflow/contrib/lite/schema -isystem bazel-out/k8-opt/genfiles/tensorflow/contrib/lite/schema -isystem bazel-out/k8-opt/bin/tensorflow/contrib/lite/schema -isystem external/flatbuffers/include -isystem bazel-out/k8-opt/genfiles/external/flatbuffers/include -isystem bazel-out/k8-opt/bin/external/flatbuffers/include '-std=c++11' -Wno-builtin-macro-redefined '-D__DATE="redacted"' '-D__TIMESTAMP__="redacted"' '-D__TIME__="redacted"' -fPIC -U_FORTIFY_SOURCE '-D_FORTIFY_SOURCE=1' -fstack-protector -Wall -fno-omit-frame-pointer -no-canonical-prefixes -DNDEBUG -g0 -O2 -ffunction-sections -fdata-sections '-D_GLIBCXX_USE_CXX11_ABI=0' '-march=native' -DFARMHASH_NO_CXX_STRING -c tensorflow/contrib/lite/allocation.cc -o bazel-out/k8-opt/bin/tensorflow/contrib/lite/_objs/framework/tensorflow/contrib/lite/allocation.pic.o

Describe the problem
Describe the problem clearly here. Be sure to convey here why it's a bug in TensorFlow or a feature request.
The build stops because the variables buffer and copied_buffer have different types,  char*& and const char*&, respectively, and std::swap expects identical types of their inputs and code found no candidate for std::swap, see details in the error message below. Simply change line 102 in tensorflow/contrib/lite/allocation.cc {{ copied_buffer_ = std::move(buffer); }} to {{copied_buffer_.reset(const_cast<char const *>(buffer.release()));}} fix the bug.
Source code / logs
tensorflow/contrib/lite/allocation.cc:102:36:   required from here
/apps/gcc/6.2.0/include/c++/6.2.0/bits/unique_ptr.h:614:6: error: no matching function for call to 'swap(const char*&, char*&)'
swap(std::get<0>(_M_t), __p);
In file included from /apps/gcc/6.2.0/include/c++/6.2.0/bits/stl_pair.h:59:0,
               from /apps/gcc/6.2.0/include/c++/6.2.0/utility:70,
               from tensorflow/contrib/lite/allocation.cc:27:
/apps/gcc/6.2.0/include/c++/6.2.0/bits/move.h:179:5: note: candidate: template<class _Tp> typename std::enable_if<std::__and_<std::is_move_constructible<_Tp>, std::is_move_assignable<_Tp> >::value>::type std::swap(_Tp&, _Tp&)
   swap(_Tp& __a, _Tp& __b)
   ^~~~
/apps/gcc/6.2.0/include/c++/6.2.0/bits/move.h:179:5: note:   template argument deduction/substitution failed:
In file included from /apps/gcc/6.2.0/include/c++/6.2.0/memory:81:0,
               from ./tensorflow/contrib/lite/simple_memory_arena.h:19,
               from ./tensorflow/contrib/lite/allocation.h:25,
               from tensorflow/contrib/lite/allocation.cc:29:
/apps/gcc/6.2.0/include/c++/6.2.0/bits/unique_ptr.h:614:6: note:   deduced conflicting types for parameter '_Tp' ('const char*' and 'char*')
swap(std::get<0>(_M_t), __p);
~~~~^~~~~~~~~~~~~~~~~~~~~~~~
In file included from /apps/gcc/6.2.0/include/c++/6.2.0/bits/stl_pair.h:59:0,
               from /apps/gcc/6.2.0/include/c++/6.2.0/utility:70,
               from tensorflow/contrib/lite/allocation.cc:27:
/apps/gcc/6.2.0/include/c++/6.2.0/bits/move.h:202:5: note: candidate: template<class _Tp, long unsigned int _Nm> typename std::enable_if<std::__is_swappable<_Tp>::value>::type std::swap(_Tp (&)[_Nm], _Tp (&)[_Nm])
   swap(_Tp (&__a)[_Nm], _Tp (&__b)[_Nm])
   ^~~~
/apps/gcc/6.2.0/include/c++/6.2.0/bits/move.h:202:5: note:   template argument deduction/substitution failed:
In file included from /apps/gcc/6.2.0/include/c++/6.2.0/memory:81:0,
               from ./tensorflow/contrib/lite/simple_memory_arena.h:19,
               from ./tensorflow/contrib/lite/allocation.h:25,
               from tensorflow/contrib/lite/allocation.cc:29:
/apps/gcc/6.2.0/include/c++/6.2.0/bits/unique_ptr.h:614:6: note:   mismatched types '_Tp [_Nm]' and 'std::__tuple_element_t<0ul, std::tuple<const char*, std::default_delete<const char []> > > {aka const char*}'
swap(std::get<0>(_M_t), __p);
~~~~^~~~~~~~~~~~~~~~~~~~~~~~
In file included from /apps/gcc/6.2.0/include/c++/6.2.0/utility:70:0,
               from tensorflow/contrib/lite/allocation.cc:27:
/apps/gcc/6.2.0/include/c++/6.2.0/bits/stl_pair.h:403:5: note: candidate: template<class _T1, class _T2> void std::swap(std::pair<_T1, _T2>&, std::pair<_T1, _T2>&)
   swap(pair<_T1, _T2>& __x, pair<_T1, _T2>& __y)
   ^~~~
/apps/gcc/6.2.0/include/c++/6.2.0/bits/stl_pair.h:403:5: note:   template argument deduction/substitution failed:
In file included from /apps/gcc/6.2.0/include/c++/6.2.0/memory:81:0,
               from ./tensorflow/contrib/lite/simple_memory_arena.h:19,
               from ./tensorflow/contrib/lite/allocation.h:25,
               from tensorflow/contrib/lite/allocation.cc:29:
/apps/gcc/6.2.0/include/c++/6.2.0/bits/unique_ptr.h:614:6: note:   mismatched types 'std::pair<_T1, _T2>' and 'std::__tuple_element_t<0ul, std::tuple<const char*, std::default_delete<const char []> > > {aka const char*}'
swap(std::get<0>(_M_t), __p);
~~~~^~~~~~~~~~~~~~~~~~~~~~~~
In file included from /apps/gcc/6.2.0/include/c++/6.2.0/vector:64:0,
               from ./tensorflow/contrib/lite/allocation.h:22,
               from tensorflow/contrib/lite/allocation.cc:29:
/apps/gcc/6.2.0/include/c++/6.2.0/bits/stl_vector.h:1557:5: note: candidate: template<class _Tp, class _Alloc> void std::swap(std::vector<_Tp, _Alloc>&, std::vector<_Tp, _Alloc>&)
   swap(vector<_Tp, _Alloc>& __x, vector<_Tp, _Alloc>& __y)
   ^~~~
/apps/gcc/6.2.0/include/c++/6.2.0/bits/stl_vector.h:1557:5: note:   template argument deduction/substitution failed:
In file included from /apps/gcc/6.2.0/include/c++/6.2.0/memory:81:0,
               from ./tensorflow/contrib/lite/simple_memory_arena.h:19,
               from ./tensorflow/contrib/lite/allocation.h:25,
               from tensorflow/contrib/lite/allocation.cc:29:
/apps/gcc/6.2.0/include/c++/6.2.0/bits/unique_ptr.h:614:6: note:   mismatched types 'std::vector<_Tp, _Alloc>' and 'std::__tuple_element_t<0ul, std::tuple<const char*, std::default_delete<const char []> > > {aka const char*}'
swap(std::get<0>(_M_t), __p);
~~~~^~~~~~~~~~~~~~~~~~~~~~~~
In file included from /apps/gcc/6.2.0/include/c++/6.2.0/vector:65:0,
               from ./tensorflow/contrib/lite/allocation.h:22,
               from tensorflow/contrib/lite/allocation.cc:29:
/apps/gcc/6.2.0/include/c++/6.2.0/bits/stl_bvector.h:112:3: note: candidate: void std::swap(std::_Bit_reference, std::_Bit_reference)
 swap(_Bit_reference __x, _Bit_reference __y) noexcept
 ^~~~
/apps/gcc/6.2.0/include/c++/6.2.0/bits/stl_bvector.h:112:3: note:   no known conversion for argument 1 from 'std::__tuple_element_t<0ul, std::tuple<const char*, std::default_delete<const char []> > > {aka const char*}' to 'std::_Bit_reference'
/apps/gcc/6.2.0/include/c++/6.2.0/bits/stl_bvector.h:120:3: note: candidate: void std::swap(std::_Bit_reference, bool&)
 swap(_Bit_reference __x, bool& __y) noexcept
 ^~~~
/apps/gcc/6.2.0/include/c++/6.2.0/bits/stl_bvector.h:120:3: note:   no known conversion for argument 1 from 'std::__tuple_element_t<0ul, std::tuple<const char*, std::default_delete<const char []> > > {aka const char*}' to 'std::_Bit_reference'
/apps/gcc/6.2.0/include/c++/6.2.0/bits/stl_bvector.h:128:3: note: candidate: void std::swap(bool&, std::_Bit_reference)
 swap(bool& __x, _Bit_reference __y) noexcept
 ^~~~
/apps/gcc/6.2.0/include/c++/6.2.0/bits/stl_bvector.h:128:3: note:   no known conversion for argument 2 from 'char*' to 'std::_Bit_reference'
In file included from /apps/gcc/6.2.0/include/c++/6.2.0/list:63:0,
               from ./tensorflow/contrib/lite/simple_memory_arena.h:18,
               from ./tensorflow/contrib/lite/allocation.h:25,
               from tensorflow/contrib/lite/allocation.cc:29:
/apps/gcc/6.2.0/include/c++/6.2.0/bits/stl_list.h:1918:5: note: candidate: template<class _Tp, class _Alloc> void std::swap(std::list<_Tp, _Alloc>&, std::list<_Tp, _Alloc>&)
   swap(list<_Tp, _Alloc>& __x, list<_Tp, _Alloc>& __y)
   ^~~~
/apps/gcc/6.2.0/include/c++/6.2.0/bits/stl_list.h:1918:5: note:   template argument deduction/substitution failed:
In file included from /apps/gcc/6.2.0/include/c++/6.2.0/memory:81:0,
               from ./tensorflow/contrib/lite/simple_memory_arena.h:19,
               from ./tensorflow/contrib/lite/allocation.h:25,
               from tensorflow/contrib/lite/allocation.cc:29:
/apps/gcc/6.2.0/include/c++/6.2.0/bits/unique_ptr.h:614:6: note:   mismatched types 'std::list<_Tp, _Alloc>' and 'std::__tuple_element_t<0ul, std::tuple<const char*, std::default_delete<const char []> > > {aka const char*}'
swap(std::get<0>(_M_t), __p);
~~~~^~~~~~~~~~~~~~~~~~~~~~~~
In file included from /apps/gcc/6.2.0/include/c++/6.2.0/string:52:0,
               from /apps/gcc/6.2.0/include/c++/6.2.0/stdexcept:39,
               from /apps/gcc/6.2.0/include/c++/6.2.0/array:39,
               from /apps/gcc/6.2.0/include/c++/6.2.0/tuple:39,
               from /apps/gcc/6.2.0/include/c++/6.2.0/functional:55,
               from /apps/gcc/6.2.0/include/c++/6.2.0/memory:79,
               from ./tensorflow/contrib/lite/simple_memory_arena.h:19,
               from ./tensorflow/contrib/lite/allocation.h:25,
               from tensorflow/contrib/lite/allocation.cc:29:
/apps/gcc/6.2.0/include/c++/6.2.0/bits/basic_string.h:5287:5: note: candidate: template<class _CharT, class _Traits, class _Alloc> void std::swap(std::basic_string<_CharT, _Traits, _Alloc>&, std::basic_string<_CharT, _Traits, _Alloc>&)
   swap(basic_string<_CharT, _Traits, _Alloc>& __lhs,
   ^~~~
/apps/gcc/6.2.0/include/c++/6.2.0/bits/basic_string.h:5287:5: note:   template argument deduction/substitution failed:
In file included from /apps/gcc/6.2.0/include/c++/6.2.0/memory:81:0,
               from ./tensorflow/contrib/lite/simple_memory_arena.h:19,
               from ./tensorflow/contrib/lite/allocation.h:25,
               from tensorflow/contrib/lite/allocation.cc:29:
/apps/gcc/6.2.0/include/c++/6.2.0/bits/unique_ptr.h:614:6: note:   mismatched types 'std::basic_string<_CharT, _Traits, _Alloc>' and 'std::__tuple_element_t<0ul, std::tuple<const char*, std::default_delete<const char []> > > {aka const char*}'
swap(std::get<0>(_M_t), __p);
~~~~^~~~~~~~~~~~~~~~~~~~~~~~
In file included from /apps/gcc/6.2.0/include/c++/6.2.0/tuple:39:0,
               from /apps/gcc/6.2.0/include/c++/6.2.0/functional:55,
               from /apps/gcc/6.2.0/include/c++/6.2.0/memory:79,
               from ./tensorflow/contrib/lite/simple_memory_arena.h:19,
               from ./tensorflow/contrib/lite/allocation.h:25,
               from tensorflow/contrib/lite/allocation.cc:29:
/apps/gcc/6.2.0/include/c++/6.2.0/array:275:5: note: candidate: template<class _Tp, long unsigned int _Nm> void std::swap(std::array<_Tp, _Nm>&, std::array<_Tp, _Nm>&)
   swap(array<_Tp, _Nm>& __one, array<_Tp, _Nm>& __two)
   ^~~~
/apps/gcc/6.2.0/include/c++/6.2.0/array:275:5: note:   template argument deduction/substitution failed:
In file included from /apps/gcc/6.2.0/include/c++/6.2.0/memory:81:0,
               from ./tensorflow/contrib/lite/simple_memory_arena.h:19,
               from ./tensorflow/contrib/lite/allocation.h:25,
               from tensorflow/contrib/lite/allocation.cc:29:
/apps/gcc/6.2.0/include/c++/6.2.0/bits/unique_ptr.h:614:6: note:   mismatched types 'std::array<_Tp, _Nm>' and 'std::__tuple_element_t<0ul, std::tuple<const char*, std::default_delete<const char []> > > {aka const char*}'
swap(std::get<0>(_M_t), __p);
~~~~^~~~~~~~~~~~~~~~~~~~~~~~
In file included from /apps/gcc/6.2.0/include/c++/6.2.0/functional:55:0,
               from /apps/gcc/6.2.0/include/c++/6.2.0/memory:79,
               from ./tensorflow/contrib/lite/simple_memory_arena.h:19,
               from ./tensorflow/contrib/lite/allocation.h:25,
               from tensorflow/contrib/lite/allocation.cc:29:
/apps/gcc/6.2.0/include/c++/6.2.0/tuple:1546:5: note: candidate: template<class ... _Elements> void std::swap(std::tuple<_Elements ...>&, std::tuple<_Elements ...>&)
   swap(tuple<_Elements...>& __x, tuple<_Elements...>& __y)
   ^~~~
/apps/gcc/6.2.0/include/c++/6.2.0/tuple:1546:5: note:   template argument deduction/substitution failed:
In file included from /apps/gcc/6.2.0/include/c++/6.2.0/memory:81:0,
               from ./tensorflow/contrib/lite/simple_memory_arena.h:19,
               from ./tensorflow/contrib/lite/allocation.h:25,
               from tensorflow/contrib/lite/allocation.cc:29:
/apps/gcc/6.2.0/include/c++/6.2.0/bits/unique_ptr.h:614:6: note:   mismatched types 'std::tuple<_Elements ...>' and 'std::__tuple_element_t<0ul, std::tuple<const char*, std::default_delete<const char []> > > {aka const char*}'
swap(std::get<0>(_M_t), __p);
~~~~^~~~~~~~~~~~~~~~~~~~~~~~
In file included from /apps/gcc/6.2.0/include/c++/6.2.0/memory:79:0,
               from ./tensorflow/contrib/lite/simple_memory_arena.h:19,
               from ./tensorflow/contrib/lite/allocation.h:25,
               from tensorflow/contrib/lite/allocation.cc:29:
/apps/gcc/6.2.0/include/c++/6.2.0/functional:2238:5: note: candidate: template<class _Res, class ... _Args> void std::swap(std::function<_Res(_ArgTypes ...)>&, std::function<_Res(_ArgTypes ...)>&)
   swap(function<_Res(_Args...)>& __x, function<_Res(_Args...)>& __y)
   ^~~~
/apps/gcc/6.2.0/include/c++/6.2.0/functional:2238:5: note:   template argument deduction/substitution failed:
In file included from /apps/gcc/6.2.0/include/c++/6.2.0/memory:81:0,
               from ./tensorflow/contrib/lite/simple_memory_arena.h:19,
               from ./tensorflow/contrib/lite/allocation.h:25,
               from tensorflow/contrib/lite/allocation.cc:29:
/apps/gcc/6.2.0/include/c++/6.2.0/bits/unique_ptr.h:614:6: note:   mismatched types 'std::function<_Res(_ArgTypes ...)>' and 'std::__tuple_element_t<0ul, std::tuple<const char*, std::default_delete<const char []> > > {aka const char*}'
swap(std::get<0>(_M_t), __p);
~~~~^~~~~~~~~~~~~~~~~~~~~~~~

Not sure why the compilers we test with don't catch this. But in any case, feel free to send a pull request!

I have approved the pull request #20711. Thank you @SneakyFish5 for your contribution.


requestCache.maxTtl unit

The comments in readme suggest that maxTtl and maxTtlIfError are in milliseconds
      requestCache: {
        maxTtl: 1000 * 60 * 10, // 10min, will respond for 10min with the cached result (updated every 10min)
        maxTtlIfError: 1000 * 60 * 30, // 30min, will respond with the cached response in case of an error (for further 20min)
      },

while the comments in the code say it's in seconds. I think the latter is correct, especially since apollo-server-caching mentions seconds, too.

Hi @shkaper seconds is correct.


Faster DeltaBitPackDecoder

Is your feature request related to a problem or challenge? Please describe what you are trying to do.
The current DeltaBitPackDecoder implementation decodes each value separately with a call to BitReader::get_unaligned. This prevents it from benefiting from the vectorized unpack32 that is used by RLEDecoder, and makes for a complex inner body of the loop. It also seems to do a fair amount of memory allocation on the hot path, which is also unfortunate.
Describe the solution you'd like
The DeltaBitPackDecoder should be faster than RLEDecoder and theoretically should be even faster than PlainDecoder - the algorithm is specifically designed to vectorize well. Most of the logic to achieve this already exists, it is just a matter of hooking it up.
One small detail is unpack32 can only handle a bit width less than 32. This should be rare in non-degenerate data, but the logic will need to fallback in such a case

I have a PR of this mostly done, just hunting down remaining bugs


feat: add trait_added_supertrait

Lint for "non-sealed trait added new supertraits"
See https://github.com/obi1kenobi/cargo-semver-checks/issues/870
Closes #441
I blessed the tests, but it makes duplicate reports for trait_newly_sealed (as sealing a trait requires adding a supertrait) which may be annoying.

Added tests with std supertraits, but the current query doesn't catch them. Do you have any idea why?

Another test case to add, maybe:
given:
pub mod one {
    /// Trait #1
    pub trait MyTrait {}
}

pub mod two {
    /// trait #2
    pub trait MyTrait {}
}

old:
use one::MyTrait;

pub trait Subtrait: MyTrait {}

new:
use two::MyTrait;

pub trait Subtrait: MyTrait {}

where one::MyTrait and two::MyTrait are different traits, even though they have the same name.

Added tests with std supertraits, but the current query doesn't catch them. Do you have any idea why?

To me, it looks like a bug in the trustfall rustdoc adapter: it doesn't seem to show supertraits from other crates.
Querying the itertools crate for traits with supertraits, it only returns HomogenousTuple: itertools::tuple_impl::TupleCollect.  However, this is certainly not all of them, take the Itertools trait which is : core::iter::Iterator, but it doesn't come up in the query.

Yes, in general we can't see traits from other crates. Recall that rustdoc JSON only contains data for the crate being analyzed, so other crates' items (including traits) are not present in the JSON. This unfortunately includes Rust's built-in crates std and core.
To work around this limitation until we have the ability to connect multiple rustdoc JSONs, we have a hardcoded list of traits from Rust's builtins that we pretend are part of the JSON and should be able to lint.
The code to pretend those traits exist when they are implemented by a type is here. Unfortunately, it appears that the implementation of traits' supertrait edge has neglected to add an equivalent block. This is a bug.
Thanks for catching it! It should be an easy fix, if you'd like to try your hand at writing some Trustfall adapter code @mrnossiom! We'd want to update this test and its corresponding test crate to contain some std bounds, and add a small block of code to look them up like in the other place.

@mrnossiom no pressure, just checking in to see if you're interested in putting together the fix for trustfall-rustdoc-adapter to unblock this PR, or if I or someone else should take over either just that component or this PR as a whole. It's no trouble either way, and it's totally fine if you're busy and would like to step away completely. I just wanted to get your preferences on how you'd like this PR to proceed, since you did a lot of work on it already.

Hi Predrag, I'm afraid I don't currently have the time to make the fix myself. But I'll be happy to finish the work of this PR's scope once the fix is merged.

No worries at all, I can take care of it and unblock this PR.

The fix is in and I've updated the adapter library versions here, so if you pull the issue should go away.
While working on the fix, I thought of another interesting edge case we want to ensure isn't going to cause a false-positive:
pub trait Example: std::fmt::Debug {}
// becomes
pub trait Example: core::fmt::Debug {}

This shouldn't get flagged since the name change is essentially only cosmetic — we don't currently track std requirements, especially not within any given lint. But in principle, some possible implementations of the supertrait name property might have considered this a name change, and we want to protect against a bad implementation there causing us a false-positive here.

The fix is in and I've updated the adapter library versions here, so if you pull the issue should go away.
While working on the fix, I thought of another interesting edge case we want to ensure isn't going to cause a false-positive:
pub trait Example: std::fmt::Debug {}
// becomes
pub trait Example: core::fmt::Debug {}

This shouldn't get flagged since the name change is essentially only cosmetic — we don't currently track std requirements, especially not within any given lint. But in principle, some possible implementations of the supertrait name property might have considered this a name change, and we want to protect against a bad implementation there causing us a false-positive here.

The current lint doesn't flag the edge case you mentioned, but I feel like it should. If you have any idea why tell me else I'll look further into it this weekend.

The current lint doesn't flag the edge case you mentioned, but I feel like it should.

This message was referencing this edge case, right?
pub trait Example: std::fmt::Debug {}
// becomes
pub trait Example: core::fmt::Debug {}

If so, the correct behavior is to not flag this — we want the test case as a guard against false-positives here. The reason is that std::fmt::Debug is just a pub re-export of core:fmt::Debug, so those two bounds are equivalent from a supertraits perspective. The only difference is that one of them is usable in a no_std context and the other is not, but that's not the subject of this lint.
So I believe everything is in order with this lint and I think it's safe to merge. Do you agree? Happy to merge it if so, just wanted to confirm with you in case I've missed something :+1:

It's just that there is no special handling for std to core changes. This means that if std::fmt::Debug to core::fmt::Debug doesn't trigger, it also means that switching lib_foo::Trait to lib_bar::Trait would not trigger either.
I don't know if that's acceptable, else I have no other concern for this PR.

You're right, there's definitely an issue there, though not with std::fmt::Debug and core::fmt::Debug specifically (the std one is a re-export of the core one) but with lib_foo::Trait to lib_bar::Trait. This is recorded in issue #922.
However, because of #638, bounds like lib_foo::Trait currently won't show up at all, which massively diminishes the surface area of the problem. Technically #638 prevents us from resolving even common built-in Rust traits like Debug and Clone, but we've special-cased a number of them in particular to work around this temporarily.
There's another (quite remote) false-positive issue here, around blanket impls: adding a supertrait bound can be "non-binding" (essentially, irrelevant and non-breaking) if there's already a blanket impl for that supertrait over all types that could impl the trait. This is #923.
We will resolve all three of these eventually, and the name-matching (#922) is a much bigger concern than blanket impls (#923). But given that #638 prevents the vast majority of the cases where the name-matching would be a problem, I think we'll help vastly more people by shipping this lint as-is and improving it later.


Installation & configuration issue with playbook

I'm Installing Microsoft SQL on RHEL machine using ansible. Following is the playbook, I'm using it.
---

- hosts: dev
  become: yes

  vars:

    mssql_accept_microsoft_odbc_driver_17_for_sql_server_eula: true
    mssql_accept_microsoft_cli_utilities_for_sql_server_eula: true
    mssql_accept_microsoft_sql_server_standard_eula: true
    mssql_password: "123@Nagesh"
    mssql_edition: Evaluation
    mssql_enable_sql_agent: true
    mssql_install_fts: true
    mssql_install_powershell: true
    mssql_tune_for_fua_storage: true

  roles:
    - microsoft.sql.server

So while executing this playbook getting error in  [MSSQL Setup] section.
TASK [microsoft.sql.server : Set up MSSQL] ****************************************************
FAILED! => {"changed": true, "cmd": ["/opt/mssql/bin/mssql-conf", "-n", "setup"], "delta": "0:00:00.782593", "end": "2022-12-15 12:03:37.830729", "msg": "non-zero return code", "rc": 1, "start": "2022-12-15 12:03:37.048136", "stderr": "/opt/mssql/bin/sqlservr: Unable to start the process, with error 101.", "stderr_lines": ["/opt/mssql/bin/sqlservr: Unable to start the process, with error 101."], "stdout": "\nThe license terms for this product can be found in\n/usr/share/doc/mssql-server or downloaded from:\nhttps://go.microsoft.com/fwlink/?LinkId=2104294&clcid=0x409\n\nThe privacy statement can be viewed at:\nhttps://go.microsoft.com/fwlink/?LinkId=853010&clcid=0x409\n\nConfiguring SQL Server...\nInitial setup of Microsoft SQL Server failed. Please consult the ERRORLOG\nin /var/opt/mssql/log for more information.", "stdout_lines": ["", "The license terms for this product can be found in", "/usr/share/doc/mssql-server or downloaded from:", "https://go.microsoft.com/fwlink/?LinkId=2104294&clcid=0x409", "", "The privacy statement can be viewed at:", "https://go.microsoft.com/fwlink/?LinkId=853010&clcid=0x409", "", "Configuring SQL Server...", "Initial setup of Microsoft SQL Server failed. Please consult the ERRORLOG", "in /var/opt/mssql/log for more information."]}

And MicrosoftSQL server is also not able to start by itself
 mssql-server.service - Microsoft SQL Server Database Engine
     Loaded: loaded (/usr/lib/systemd/system/mssql-server.service; disabled; vendor preset: disabled)
     Active: failed (Result: exit-code) since Thu 2022-12-15 07:32:58 UTC; 4h 37min ago
   Duration: 769ms
       Docs: https://docs.microsoft.com/en-us/sql/linux
   Main PID: 38755 (code=exited,

/var/opt/mssql/log/mssql-conf/logs :
2022-12-15 12:03:37,156:INFO:mssql-conf: Running script: [/opt/mssql/lib/mssql-conf/checkrunninginstance.sh]
2022-12-15 12:03:37,170:INFO:mssql-conf: Script gave output: []
2022-12-15 12:03:37,172:INFO:mssql-conf: Running script: [/opt/mssql/lib/mssql-conf/checkrunninginstance.sh]
2022-12-15 12:03:37,185:INFO:mssql-conf: Script gave output: []
2022-12-15 12:03:37,815:INFO:mssql-conf: Trying to make owner and group of the log files at /var/opt/mssql/log/mssql-conf mssql.
2022-12-15 12:03:37,816:INFO:mssql-conf: Found user ID (989) and group ID (989) for user mssql.
2022-12-15 12:03:37,816:INFO:mssql-conf: Trying chown the directory.
2022-12-15 12:03:37,816:INFO:mssql-conf: Succesfully chown'd the directory.
2022-12-15 12:03:37,816:INFO:mssql-conf: Trying to set ownership for file /var/opt/mssql/log/mssql-conf/mssql-conf.log.
2022-12-15 12:03:37,816:INFO:mssql-conf: Successfully set ownership for file.
2022-12-15 12:03:37,816:INFO:mssql-conf: Changing the permissions of the file to 660.
2022-12-15 12:03:37,816:INFO:mssql-conf: Changed the permissions of the file.
2022-12-15 12:03:37,816:INFO:mssql-conf: Successfully changed ownership for the directory /var/opt/mssql/log/mssql-conf and all files in that directory.

Please help me with this. !!!!

Hello @nageshredhat, thank you for your feedback. Please let me know what RHEL version do you run this against playbook against. And also paste content of /var/opt/mssql/log file fater mssql-serve failed here.

Using RHEL 9.1 & following are the logs:
core.sqlservr.12_17_2022_18_27_8.69201.log
12/17/2022 18:27:08.365146631 Info [paldumper] <0000069200/0x00000000> Executing PalDumper against PID: 69201
12/17/2022 18:27:08.365178401 Info [paldumper] <0000069200/0x00000000>                       Dump type: miniplus
12/17/2022 18:27:08.365184145 Info [paldumper] <0000069200/0x00000000> Stopping target
12/17/2022 18:27:08.365192903 Info [paldumper] <0000069200/0x00000000> Target stopped
12/17/2022 18:27:08.365197481 Info [paldumper] <0000069200/0x00000000> Attaching to target threads
12/17/2022 18:27:08.365246384 Warning [paldumper] <0000069200/0x00000000> Yama PTRACE mode: 0-Classic
12/17/2022 18:27:08.365356847 Info [paldumper] <0000069200/0x00000000> Parsing /proc/69201/maps for region coverage
12/17/2022 18:27:08.365651530 Info [paldumper] <0000069200/0x00000000> Virtual memory region count: 277
12/17/2022 18:27:08.365668948 Info [paldumper] <0000069200/0x00000000>     Using ThreadInfo::m_Head at: 0x00005614CD8E0DB8
12/17/2022 18:27:08.365675004 Info [paldumper] <0000069200/0x00000000>     Using ProcessList at: 0x00003FFF8C868D40
12/17/2022 18:27:08.365748086 Info [paldumper] <0000069200/0x00000000>      Using m_ProtocolVersion at: 0x00005614CD834B50
12/17/2022 18:27:08.365802860 Info [paldumper] <0000069200/0x00000000>      Using sm_SOSNodeManager at: 0x00003FFF8C809B20
12/17/2022 18:27:08.365809387 Info [paldumper] <0000069200/0x00000000>   Using sm_MemoryNodeManager at: 0x00003FFF8C809E40
12/17/2022 18:27:08.365813990 Info [paldumper] <0000069200/0x00000000> Using sm_GlobalSchedulerList at: 0x00003FFF8C809E20
12/17/2022 18:27:08.365818637 Info [paldumper] <0000069200/0x00000000>        Using ELF module list at: 0x00007FD3AE0E2220
BEGIN IMAGE LIST
linux-vdso.so.1
/lib64/libpthread.so.0
/lib64/librt.so.1
/lib64/libdl.so.2
/lib64/libnuma.so.1
/lib64/libgssapi_krb5.so.2
/lib64/libkrb5.so.3
/lib64/libk5crypto.so.3
/lib64/libcom_err.so.2
/lib64/libsss_nss_idmap.so.0
/lib64/libuuid.so.1
/lib64/libpam.so.0
/lib64/libm.so.6
/lib64/liblber-2.4.so.2
/lib64/libldap-2.4.so.2
/lib64/libudev.so.1
/opt/mssql/bin/../lib/libc++.so.1
/opt/mssql/bin/../lib/libc++abi.so.1
/lib64/libgcc_s.so.1
/lib64/libc.so.6
/lib64/ld-linux-x86-64.so.2
/lib64/libkrb5support.so.0
/lib64/libkeyutils.so.1
/lib64/libcrypto.so.3
/lib64/libresolv.so.2
/lib64/libaudit.so.1
/lib64/libeconf.so.0
/lib64/liblber.so.2
/lib64/libldap.so.2
/lib64/libselinux.so.1
/lib64/libz.so.1
/lib64/libcap-ng.so.0
/lib64/libevent-2.1.so.7
/lib64/libsasl2.so.3
/lib64/libssl.so.3
/lib64/libpcre2-8.so.0
/lib64/libcrypt.so.2
/opt/mssql/bin/../lib/libunwind.so.8
/lib64/liblzma.so.5
/lib64/libnss_myhostname.so.2
/usr/lib64/sasl2/libanonymous.so
/usr/lib64/sasl2/libsasldb.so
/lib64/libgdbm.so.6
/usr/lib64/sasl2/libgssapiv2.so
END IMAGE LIST
12/17/2022 18:27:08.366077002 Info [paldumper] <0000069200/0x00000000> Attempting to capture scheduler nodes
12/17/2022 18:27:08.366091613 Info [paldumper] <0000069200/0x00000000> Attempting to capture memory nodes
12/17/2022 18:27:08.366101965 Info [paldumper] <0000069200/0x00000000> Attempting to capture schedulers
12/17/2022 18:27:08.366153676 Info [paldumper] <0000069200/0x00000000> Adding VMM and VAD tree memory
12/17/2022 18:27:08.376219421 Info [paldumper] <0000069200/0x00000000> Adding Debugger::ThreadInfo list
12/17/2022 18:27:08.376271845 Info [paldumper] <0000069200/0x00000000> ------------------------------------------------
12/17/2022 18:27:08.376280133 Info [paldumper] <0000069200/0x00000000> ThreadInfo @: 0x00007FD3AA12E000
12/17/2022 18:27:08.376285120 Info [paldumper] <0000069200/0x00000000>               m_Teb: 0x00003FFF8C840000
12/17/2022 18:27:08.376289729 Info [paldumper] <0000069200/0x00000000>     m_PalStackLimit: 0x00007FD3AA518000
12/17/2022 18:27:08.376294170 Info [paldumper] <0000069200/0x00000000>      m_PalStackBase: 0x00007FD3AA538000
12/17/2022 18:27:08.376298714 Info [paldumper] <0000069200/0x00000000>  m_SignalStackLimit: 0x00007FD3AA11DD40
12/17/2022 18:27:08.376303321 Info [paldumper] <0000069200/0x00000000>   m_SignalStackBase: 0x00007FD3AA12DD40
12/17/2022 18:27:08.376307749 Info [paldumper] <0000069200/0x00000000>     m_ErrnoLocation: 0x00007FD3AA535C68
12/17/2022 18:27:08.376320805 Info [paldumper] <0000069200/0x00000000>          m_DkThread: 0x00007FD3AD019800
12/17/2022 18:27:08.376380884 Info [paldumper] <0000069200/0x00000000>     TID @: 0x00003FFF8C840000
12/17/2022 18:27:08.376387833 Info [paldumper] <0000069200/0x00000000>     ExceptionList: 0x0000000000000000
12/17/2022 18:27:08.376392423 Info [paldumper] <0000069200/0x00000000>         StackBase: 0x0000300008660000
12/17/2022 18:27:08.376396754 Info [paldumper] <0000069200/0x00000000>        StackLimit: 0x0000300008650000
12/17/2022 18:27:08.376401152 Info [paldumper] <0000069200/0x00000000>              Self: 0x00003FFF8C840000
12/17/2022 18:27:08.376405604 Info [paldumper] <0000069200/0x00000000>         ProcessId: 0x0000000000000004
12/17/2022 18:27:08.376410034 Info [paldumper] <0000069200/0x00000000>          ThreadId: 0x0000000000000008
12/17/2022 18:27:08.376508997 Info [paldumper] <0000069200/0x00000000>      PEB @: 0x00003FFF8C844000
12/17/2022 18:27:08.376517850 Error [paldumper] <0000069200/0x00000000> Found less than 2 threads
12/17/2022 18:27:08.376524011 Error [paldumper] <0000069200/0x00000000> Unable to determine region information
12/17/2022 18:27:08.376529312 Info [paldumper] <0000069200/0x00000000> Detaching from target threads

core.sqlservr.12_17_2022_18_27_08.69201.txt
This program has encountered a fatal error and cannot continue running at Sat Dec 17 18:27:08 2022
The following diagnostic information is available:

         Reason: 0x00000004
        Message: RETAIL ASSERT: Expression=(NT_SUCCESS(status)) File=drtl.cpp Line=1550
        Process: 69201 - sqlservr
         Thread: 69206 (application thread 0x8)
    Instance Id: 70b3c3f9-f3db-41bf-87f8-0c3264cf0398
       Crash Id: b0be1d70-47f4-4886-9bec-02d0d293950a
    Build stamp: 3adfb630dbeb72d1b00cf287fe8e78928263639de8a3ea620c5b04528b8685f1
   Distribution: Red Hat Enterprise Linux 9.1 Beta (Plow)
     Processors: 2
   Total Memory:<PHONE_NUMBER> bytes
      Timestamp: Sat Dec 17 18:27:08 2022
     Last errno: 13
Last errno text: Permission denied

SQL Server does not support RHEL 9 yet, therefore, the role does not support it too. This is mentioned in the README. You must run your playbooks against RHEL 8 or 7.

oh, ok
Thank you.
Any plan for RHEL 9 rollout

All I know is that Microsoft is working on this, and shortly after Microsoft ships support for RHEL 9, support will be added to the role too.

ok, thank


RocketChip: Project Formation

Project Documentation & Links
Project Name: RocketChip
Project Repository: https://github.com/chipsalliance/rocket-chip
Project Data File/PR: https://github.com/chipsalliance/tac/blob/main/projects/project-data-files/rocket-chip.yml
Project Checklist

[x] TAC Vote Grandfathered
[ ] New Project Created In LFX - Exists as Rocket WG - should fix
[ ] Legal Submission

[ ] Project formation form submitted by project
[ ] Technical Charter Draft Approved
[ ] Contribution Agreement Approved
[ ] Trademark Docs Approved

[ ] Board Vote  Date
[ ] Project made active in PCC by notifying the formation team
[ ] Merge PR & Confirm Website Is Accurate
[ ] Add ‘thelinuxfoundation’ as an owner of the GitHub org
[ ] Transfer any domains
[ ] Onboard to LFX/Community Metrics/Insights
[ ] Enforce CLA on repo(s)
[ ] Accept/adopt LF code of conduct
[ ] Enable security vulnerability reporting process

Emailed project contact.

Contact confirmed, requested intake form be filled out.

Form filled out, blocked waiting on project formation steps being completed. Have not heard back from stakeholder.

Reached out to Jiuyang L again to check on next steps.

Target completion next week.

Checked in via email Aug 15

Jiuyang approval of legal docs Aug 20.

Scott requested "Thank you both. Ben, can you have the details completed for the contribution agreement and work with Todd to have that docusign sent out? Thanks,"
I will complete post PTO

https://github.com/chipsalliance/rocket-chip/pull/3683


Android APK build obsolete warning

3 warnings
warning: [options] source value 7 is obsolete and will be removed in a future release

warning: [options] target value 7 is obsolete and will be removed in a future release

warning: [options] To suppress warnings about obsolete options, use -Xlint:-options.

Before: https://github.com/openfoodfacts/smooth-app/runs/2125741190#step:8:286
After: https://github.com/openfoodfacts/smooth-app/pull/268/checks?check_run_id=2125859540#step:8:286


Auto SSL certs

typicode#309 and typicode#346. This would be really great.

I have been using this little snippet for ages now. Never had any issues. I use .box as my tld. If yours is different just adjust accordingly in 2 places. It uses mkcert which is installed via Homebrew.
ls ~/.chalet/servers | sed -E 's/\.json/.box/g' | tr '\n' ' ' | xargs mkcert -key-file ~/.chalet/key.pem -cert-file ~/.chalet/cert.pem 'localhost' '<IP_ADDRESS>' '<IP_ADDRESS>' 'chalet.box'

I actually have it setup as an alias in my system:
alias make_local_ssl="ls ~/.chalet/servers | sed -E 's/\.json/.box/g' | tr '\n' ' ' | xargs mkcert -key-file ~/.chalet/key.pem -cert-file ~/.chalet/cert.pem 'localhost' '<IP_ADDRESS>' '<IP_ADDRESS>' 'chalet.box'"

Thanks @leeovery
I tried to install mkcert and your snippet (I ran mkcert -install after).
alias make_local_ssl="ls ~/.chalet/servers | sed -E 's/\.json/.test/g' | tr '\n' ' ' | xargs mkcert -key-file ~/.chalet/key.pem -cert-file ~/.chalet/cert.pem 'localhost' '<IP_ADDRESS>' '<IP_ADDRESS>' 'chalet.test'"

But I still have issues with the SSL on Brave:

@jeansaad I'm wondering if you ever found a working SSL solution for Safari. Where I'm at:
On my old work computer:

I have a working chalet setup using minica for SSL and am able to view chalet hosts on Chrome, Firefox, and Safari.
Some time last year I replaced my chalet minica certs with mkcert certs and everything is still working fine.
I'm switching jobs so I have to surrender this working computer at the end of the month. I'm trying to replicate this setup on my new work computer.

On my new work computer:

I've got chalet setup with mkcert, and am able to view chalet hosts in Chrome and Firefox (partly thanks to this guide https://web.dev/articles/how-to-use-local-https)
But Safari refuses to load my chalet hosts. It just shows a partial progress bar indefinitely, with no error page or any sort of diagnostic info:

There's also nothing in my app server logs, and no new logs in chalet's daemon.log after its initial start up logs (tested this by moving the old log aside and restarting chalet with a fresh log). So looks like Safari isn't even reaching chalet, and I'm kinda stumped how to figure out what the blocker is. So if you have any pointers on debugging this, I'd love to hear em. (Obviously not your problem so feel free to just say 'good luck with that buddy', haha.)


INFINITY-2601, INFINITY-2496 CLI: faster, better error message, support service_name setting

Fix the inaccurate messaging when a 404 is encountered.
Attempt to read the toml file directly to save time, but fall back to running 'dcos' directly as before if that fails for some reason
Fix the undocumented '.service_name' setting, and document it in relevant error messages

Demo!:

Speed:

BEFORE:
$ time dcos kafka pod list
[
  "kafka-0",
  "kafka-1",
  "kafka-2"
]

real	0m2.297s
user	0m2.020s
sys	0m0.240s

AFTER:
$ time dcos beta-kafka pod list
[
  "kafka-0",
  "kafka-1",
  "kafka-2"
]

real	0m0.522s
user	0m0.360s
sys	0m0.072s

(or faster depending on your network)

404 fixed using <pkg>.service_name:

$ dcos beta-kafka pod list
Got 404 Not Found response from http://nick-plsx-elasticl-a9tyx0cj04fx-1638172899.us-west-2.elb.amazonaws.com/service/beta-kafka/v1/pod:
- The service scheduler may have been unable to find an item that was specified in your request.
- The DC/OS cluster may have been unable to find a service named "beta-kafka". Specify a service name with '--name=<name>', or with 'dcos config set beta-kafka.service_name <name>'.

$ dcos config set beta-kafka.service_name kafka
[beta-kafka.service_name]: set to 'kafka'

$ dcos beta-kafka pod list
[
  "kafka-0",
  "kafka-1",
  "kafka-2"
]

TODO: Config dir lookup doesn't work when manually tested on windows. This isn't the end of the world as it's just falling back to the prior behavior. I'll see if I can find the correct path on windows, and update the config retrieval to try there as well.
>dcos beta-cassandra -v pod list
Unable to resolve CLI config directory (DCOS_DIR or HOME/.dcos), falling back to running CLI command.
Running DC/OS CLI command: dcos config show core.dcos_url
Unable to resolve CLI config directory (DCOS_DIR or HOME/.dcos), falling back to running CLI command.
Running DC/OS CLI command: dcos config show core.dcos_acs_token
HTTP Query: GET http://nick-ym2i-elasticl-13syk38h0atvx-16587567.us-west-2.elb.amazonaws.com/service/beta-cassandra/v1/pod