get_started.py error: src/codegen/codegen.cc:27: Check failed: bf != nullptr Target llvm is not enabled

Is llvm necessary?  I saw these lines in config.mk:
# whether build with LLVM support
# Requires LLVM version >= 4.0
# Set LLVM_CONFIG to your version, uncomment to build with llvm support
#
# LLVM_CONFIG = llvm-config

It seems llvm is not necessary and it's commented out defaultly. However, I'm confused because of this error: nullptr Target llvm is not enabled
Env.
I installed tvm on my laptop.
Ubuntu 16.04 64bit
clinfo

yuens@Spark:~$ clinfo                                                                                [16/16]
Number of platforms                               1
  Platform Name                                   Intel Gen OCL Driver
  Platform Vendor                                 Intel
  Platform Version                                OpenCL 1.2 beignet 1.1.1
  Platform Profile                                FULL_PROFILE
  Platform Extensions                             cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics cl_khr_byte_addressable_store cl_khr_spir cl_khr_icd
  Platform Extensions function suffix             Intel

  Platform Name                                   Intel Gen OCL Driver
Number of devices                                 1
  Device Name                                     Intel(R) HD Graphics IvyBridge M GT2
  Device Vendor                                   Intel
  Device Vendor ID                                0x8086
  Device Version                                  OpenCL 1.2 beignet 1.1.1
  Driver Version                                  1.1.1
  Device OpenCL C Version                         OpenCL C 1.2 beignet 1.1.1
  Device Type                                     GPU
  Device Profile                                  FULL_PROFILE
  Max compute units                               16
  Max clock frequency                             1000MHz
  Device Partition                                (core)
    Max number of sub-devices                     1
    Supported partition types                     None, None, None
  Max work item dimensions                        3
  Max work item sizes                             512x512x512
  Max work group size                             512
  Preferred work group size multiple              16
  Preferred / native vector sizes
    char                                                16 / 8
    short                                                8 / 8
    int                                                  4 / 4
    long                                                 2 / 2
    half                                                 0 / 8        (n/a)
    float                                                4 / 4
    double                                               0 / 2        (n/a)
  Half-precision Floating-point support           (n/a)
  Single-precision Floating-point support         (core)
    Denormals                                     No
    Infinity and NANs                             Yes
    Round to nearest                              Yes
    Round to zero                                 No
    Round to infinity                             No
    IEEE754-2008 fused multiply-add               No
    Support is emulated in software               No
    Correctly-rounded divide and sqrt operations  No
  Double-precision Floating-point support         (n/a)
  Address bits                                    32, Little-Endian
  Global memory size<PHONE_NUMBER> (2GiB)
  Error Correction support                        No
  Max memory allocation<PHONE_NUMBER> (1024MiB)
  Unified memory for Host and Device              Yes
  Minimum alignment for any data type             128 bytes
  Alignment of base address                       1024 bits (128 bytes)
  Global Memory cache type                        Read/Write
  Global Memory cache size                        8192
  Global Memory cache line                        64 bytes
  Image support                                   Yes
    Max number of samplers per kernel             16
    Max size for 1D images from buffer            65536 pixels
    Max 1D or 2D image array size                 2048 images
    Max 2D image size                             8192x8192 pixels
    Max 3D image size                             8192x8192x2048 pixels
    Max number of read image args                 128
    Max number of write image args                8
  Local memory type                               Global
  Local memory size                               65536 (64KiB)
  Max constant buffer size                        134217728 (128MiB)
  Max number of constant args                     8
  Max size of kernel argument                     1024
  Queue properties
    Out-of-order execution                        No
    Profiling                                     Yes
  Prefer user sync for interop                    Yes
  Profiling timer resolution                      80ns
  Execution capabilities
    Run OpenCL kernels                            Yes
    Run native kernels                            Yes
    SPIR versions                                 <printDeviceInfo:138: get   SPIR versions size : error -30>
  printf() buffer size                            1048576 (1024KiB)
  Built-in kernels                                __cl_copy_region_align4;__cl_copy_region_align16;__cl_cpy_region_unalign_same_offset;__cl_copy_region_unalign_dst_offset;__cl_copy_region_unalign_src_offset;__cl_copy_buffer_rect;__cl_copy_image_1d_to_1d;__cl_copy_image_2d_to_2d;__cl_copy_image_3d_to_2d;__cl_copy_image
_2d_to_3d;__cl_copy_image_3d_to_3d;__cl_copy_image_2d_to_buffer;__cl_copy_image_3d_to_buffer;__cl_copy_buffer_to_image_2d;__cl_copy_buffer_to_image_3d;__cl_fill_region_unalign;__cl_fill_region_align2;__cl_fill_region_align4;__cl_fill_region_align8_2;__cl_fill_region_align8_4;__cl_fill_region_align8_8;__cl_fill_region_
align8_16;__cl_fill_region_align128;__cl_fill_image_1d;__cl_fill_image_1d_array;__cl_fill_image_2d;__cl_fill_image_2d_array;__cl_fill_image_3d;
  Device Available                                Yes
  Compiler Available                              Yes
  Linker Available                                Yes
  Device Extensions                               cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics cl_khr_byte_addressable_store cl_khr_spir cl_khr_icd

NULL platform behavior
  clGetPlatformInfo(NULL, CL_PLATFORM_NAME, ...)  Intel Gen OCL Driver
  clGetDeviceIDs(NULL, CL_DEVICE_TYPE_ALL, ...)   Success [Intel]
  clCreateContext(NULL, ...) [default]            Success [Intel]
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_CPU)  No devices found in platform
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_GPU)  Success (1)
    Platform Name                                 Intel Gen OCL Driver
    Device Name                                   Intel(R) HD Graphics IvyBridge M GT2
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_ACCELERATOR)  No devices found in platform
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_CUSTOM)  No devices found in platform
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_ALL)  Success (1)
    Platform Name                                 Intel Gen OCL Driver
    Device Name                                   Intel(R) HD Graphics IvyBridge M GT2

ICD loader properties
  ICD loader Name                                 OpenCL ICD Loader
  ICD loader Vendor                               OCL Icd free software
  ICD loader Version                              2.2.8
  ICD loader Profile                              OpenCL 1.2
        NOTE:   your OpenCL library declares to support OpenCL 1.2,
                but it seems to support up to OpenCL 2.1 too.

config.mk
I copy ./make/config.mk to root directory and modified lines below:
DEBUG = 1
USE_OPENCL = 1 # I installed opencl previously
USE_BLAS = openblas

After successful build, I set the environment variable and executed cd python; python setup.py install --user according to tvm/install.md.
Error Log
yuens@Spark:~/Software/tvm/tutorials/python$ python get_started.py
<class 'tvm.tensor.Tensor'>
[15:44:03] /home/yuens/Software/tvm/dmlc-core/include/dmlc/logging.h:308: [15:44:03] src/codegen/codegen.cc:27: Check failed: bf != nullptr Target llvm is not enabled

Stack trace returned 10 entries:
[bt] (0) /home/yuens/Software/tvm/lib/libtvm.so(_ZN3tvm7codegen5BuildERKNS_5ArrayINS_11LoweredFuncEvEERKNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEE+0x10b1) [0x7feac33eea41]
[bt] (1) /home/yuens/Software/tvm/lib/libtvm.so(+0x302eb9) [0x7feac339aeb9]
[bt] (2) /home/yuens/Software/tvm/lib/libtvm.so(TVMFuncCall+0x5e) [0x7feac35977ce]
[bt] (3) /usr/local/lib/anaconda2/lib/python2.7/lib-dynload/_ctypes.so(ffi_call_unix64+0x4c) [0x7feacbef357c]
[bt] (4) /usr/local/lib/anaconda2/lib/python2.7/lib-dynload/_ctypes.so(ffi_call+0x1f5) [0x7feacbef2cd5]
[bt] (5) /usr/local/lib/anaconda2/lib/python2.7/lib-dynload/_ctypes.so(_ctypes_callproc+0x3e6) [0x7feacbeea376]
[bt] (6) /usr/local/lib/anaconda2/lib/python2.7/lib-dynload/_ctypes.so(+0x9db3) [0x7feacbee1db3]
[bt] (7) /usr/local/lib/anaconda2/bin/../lib/libpython2.7.so.1.0(PyObject_Call+0x53) [0x7feacd4cde93]
[bt] (8) /usr/local/lib/anaconda2/bin/../lib/libpython2.7.so.1.0(PyEval_EvalFrameEx+0x715d) [0x7feacd58080d]
[bt] (9) /usr/local/lib/anaconda2/bin/../lib/libpython2.7.so.1.0(PyEval_EvalCodeEx+0x89e) [0x7feacd582c3e]

Traceback (most recent call last):
  File "get_started.py", line 111, in <module>
    fadd_cuda = tvm.build(s, [A, B, C], "cuda", target_host="llvm", name="myadd")
  File "/home/yuens/Software/tvm/python/tvm/build_module.py", line 349, in build
    mhost = codegen.build_module(fhost, target_host)
  File "/home/yuens/Software/tvm/python/tvm/codegen.py", line 20, in build_module
    return _Build(lowered_func, target)
  File "/home/yuens/Software/tvm/python/tvm/_ffi/function.py", line 255, in my_api_func
    return flocal(*args)
  File "/home/yuens/Software/tvm/python/tvm/_ffi/_ctypes/function.py", line 183, in __call__
    ctypes.byref(ret_val), ctypes.byref(ret_tcode)))
  File "/home/yuens/Software/tvm/python/tvm/_ffi/base.py", line 62, in check_call
    raise TVMError(py_str(_LIB.TVMGetLastError()))
tvm._ffi.base.TVMError: [15:44:03] src/codegen/codegen.cc:27: Check failed: bf != nullptr Target llvm is not enabled

Stack trace returned 10 entries:
[bt] (0) /home/yuens/Software/tvm/lib/libtvm.so(_ZN3tvm7codegen5BuildERKNS_5ArrayINS_11LoweredFuncEvEERKNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEE+0x10b1) [0x7feac33eea41]
[bt] (1) /home/yuens/Software/tvm/lib/libtvm.so(+0x302eb9) [0x7feac339aeb9]
[bt] (2) /home/yuens/Software/tvm/lib/libtvm.so(TVMFuncCall+0x5e) [0x7feac35977ce]
[bt] (3) /usr/local/lib/anaconda2/lib/python2.7/lib-dynload/_ctypes.so(ffi_call_unix64+0x4c) [0x7feacbef357c]
[bt] (4) /usr/local/lib/anaconda2/lib/python2.7/lib-dynload/_ctypes.so(ffi_call+0x1f5) [0x7feacbef2cd5]
[bt] (5) /usr/local/lib/anaconda2/lib/python2.7/lib-dynload/_ctypes.so(_ctypes_callproc+0x3e6) [0x7feacbeea376]
[bt] (6) /usr/local/lib/anaconda2/lib/python2.7/lib-dynload/_ctypes.so(+0x9db3) [0x7feacbee1db3]
[bt] (7) /usr/local/lib/anaconda2/bin/../lib/libpython2.7.so.1.0(PyObject_Call+0x53) [0x7feacd4cde93]
[bt] (8) /usr/local/lib/anaconda2/bin/../lib/libpython2.7.so.1.0(PyEval_EvalFrameEx+0x715d) [0x7feacd58080d]
[bt] (9) /usr/local/lib/anaconda2/bin/../lib/libpython2.7.so.1.0(PyEval_EvalCodeEx+0x89e) [0x7feacd582c3e]

Did you compile with LLVM_CONFIG? otherwise target_host="llvm" doesn't work.

@Huyuwei
I compiled without LLVM_CONFIG.
Is llvm necessary?  I saw these lines in config.mk:
# whether build with LLVM support
# Requires LLVM version >= 4.0
# Set LLVM_CONFIG to your version, uncomment to build with llvm support
#
# LLVM_CONFIG = llvm-config

It seems llvm is not necessary and it's commented out defaultly. However, I'm confused because of this error: nullptr Target llvm is not enabled

@Huyuwei
I rebuild with LLVM_CONFIG. However, build failed as below:
src/codegen/llvm/././llvm_common.h:10:40: fatal error: llvm/ExecutionEngine/MCJIT.h: No such file or directory
compilation terminated.
Makefile:160: recipe for target 'build/codegen/llvm/codegen_arm.o' failed
make: *** [build/codegen/llvm/codegen_arm.o] Error 1
make: *** Waiting for unfinished jobs....

run llvm-config in shell to make sure llvm is installed correctly.
if you are generating llvm target, then llvm is necessary.

@javelinjs Thanks!


Added link for the starter repo

Coverage remained the same at 100.0% when pulling 4d49eeb6813fc62e7fe8b59d2207e03a832f6cde on hwclass:preact-unistore-parcel-starter into 834a869c0d80b6f77199a6d25354076a0ad31733 on developit:master.


Remove the node engine check from version 1

According to the #339, please, add this PR to version 1 too. Thanks

+1


Remove jasmine as a dependency

I cannot build our angular project due to a clash of types between jasmine and jest. Jasmine is added as a dependency and therefore installed when the package is installed. Jasmine should be installed as a devdep rather than a dep.

Thanks for reporting. Fixed in #17.


Estimating quantification coverage

Hi, I am using FlashFLQ to quantify crosslinked samples (crosslinker is EDC, manually added to MetaMorpheus).
I calibrated and searched the raw files using common modifications, and after adding custom EDC modifications I expect to see (present on unimod.org, but not in the built-in modifications lists).
I would like to compare the overall identification coverage between the two different sets of modifications. Is there a straightforward way to judge? For example, does MetaMorpeus directly report on unidentified peaks?
The allresults.txt files are helpful, but somewhat too ambiguous for me to paint an accurate picture. It could be that what I am looking for is there.
(thank you for the gift that is this software)

MetaMorpheus doesn't report unidentified peaks, but you could try summing all of the quantified+identified peptide intensities and compare these numbers between your two searches. I assume the search with EDC modifications would have a higher identified TIC.
Since EDC is a crosslinker and not a simple modification, have you tried the XL search to identified crosslinked peptides?

MetaMorpheus doesn't report unidentified peaks, but you could try summing all of the quantified+identified peptide intensities and compare these numbers between your two searches. I assume the search with EDC modifications would have a higher identified TIC.
Since EDC is a crosslinker and not a simple modification, have you tried the XL search to identified crosslinked peptides?


Add a new state class for odometer

Defining a state class for odometer allows for long-term statistics. Fixes the issue #213
Total: "The state represents a total amount that can both increase and decrease, e.g. a net energy meter."
Examples:
The sensor's value never resets, e.g. a lifetime total energy consumption or production: state_class total, last_reset not set or set to None
https://developers.home-assistant.io/docs/core/entity/sensor/#available-state-classes

LGTM. Thanks for your contribution!

I think it doesn't matter all that much in this case, as it should never decrease anyhow.


Fix broken link in README.md

Why

The link is broken.
What

It now links to the License file.

Good catch 👍


Npgsql V4 breaks Marten

What previously worked for DocumentStore.For(_ => ...  and Npsql v3.x now breaks with Npgsql v4
ex
[NullReferenceException: Object reference not set to an instance of an object.]
   Marten.Util.TypeMappings.ToDbType(Type type) +93
   Marten.Schema.DuplicatedField..ctor(EnumStorage enumStorage, MemberInfo[] memberPath) +141
   Marten.Schema.DocumentMapping.DuplicateField(MemberInfo[] members, String pgType, String columnName) +195
   Marten.Events.EventQueryMapping.duplicateField(Expression1 property, String columnName) +94
   Marten.Events.EventQueryMapping..ctor(StoreOptions storeOptions) +485
   Marten.Storage.StorageFeatures.PostProcessConfiguration() +364
   Marten.DocumentStore..ctor(StoreOptions options) +259
   Marten.DocumentStore.For(Action1 configure) +60

I see deep down in the weeds Marten uses reflection to get to access a sealed Npgsql.TypeHandlerRegistry.  I'm sure this is a known issue, I just couldn't find a way to track the progress, so making an issue.

@mhov If you'll do a quick search through the GitHub repo you'll see other issues and preliminary PR's on this very thing.

@jeremydmiller I did search through the issues and only saw #1027, to which the v4 incompatibility is kind of tangent to the ticket.  I forget to look through PRs though.  Anyways, I thought this ticket would make it easier to find for others in the same boat.  If you think its redundant though, feel free to close it.
I've been reading ShadeTreeDeveloper since the fubumvc days, thanks for all your contributions.

Just in case it's not obvious to future readers, this was resolved in the 3.0 Alpha 1 release (line right before this comment that's easy to gloss over when reading GitHub threads), so just update to the latest and it should work.

This should be way more prevalent a warning on the README until the fix lands in stable. You have to jump through quite some hoops to find this issue here.

This is fixed in the 3.0 branch and alpha. I'm closing this for now.


AF-143: Update bslDeployToS3 to upload under prefixes within s3, and …

…append .copy to anyfiles that would overwrite another on upload

No longer appends .copy to files, but rather has 3 config options.

skip : does not copy the file up - print a warning. (default).
overwrite : overwrites existing file with new one (people can choose this if they have turned s3 versioning on).
error : raise error and cancel.


Better tools for accessing multiple entities in Query iterables

What problem does this solve or what need does it fill?
Within a mutable query iteration, we can't access more than one entity at a time, because of the borrow checker. This is frustrating when trying to do things like write your own collision detection or handling other entity-entity interactions.
What solution would you like?
Provide a Bevy-native tool (with a simple game example) to allow careful mutable access to more than one entity within a loop.
Here's some initial discussion of what that might look like.
What alternative(s) have you considered?
Fully solving #1631 would allow us to use iter_tools directly for this sort of thing, but Clone on mutable queries is probably a hard no.
As a workaround, you can record which entities you need to access, then use query.get() to pull out their components separately. This is not super obvious and very cumbersome.
Additional context
First raised on Discord.

related to #1763

Duplicate of #2042.


Deploy PyTorch model with TorchServe InferenceService Example does not work

/kind bug
What steps did you take and what happened:
I followed the Deploy PyTorch model with TorchServe InferenceService Example here: (https://kserve.github.io/website/modelserving/v1beta1/torchserve/)
The inference service was created and showed up as READY:TRUE.
However, when looking at the logs of the pod (container kserve-container), it showed that the worker died.
LOGS:
WARNING: sun.reflect.Reflection.getCallerClass is not supported. This will impact performance.
2023-01-04T17:19:27,271 [INFO ] main org.pytorch.serve.servingsdk.impl.PluginsManager - Initializing plugins manager...
2023-01-04T17:19:27,654 [INFO ] main org.pytorch.serve.ModelServer -
Torchserve version: 0.6.0
TS Home: /usr/local/lib/python3.8/dist-packages
Current directory: /home/model-server
Temp directory: /home/model-server/tmp
Number of GPUs: 0
Number of CPUs: 8
Max heap size: 8026 M
Python executable: /usr/bin/python
Config file: /mnt/models/config/config.properties
Inference address: http://<IP_ADDRESS>:8085
Management address: http://<IP_ADDRESS>:8081
Metrics address: http://<IP_ADDRESS>:8082
Model Store: /mnt/models/model-store
Initial Models: N/A
Log dir: /home/model-server/logs
Metrics dir: /home/model-server/logs
Netty threads: 4
Netty client threads: 0
Default workers per model: 8
Blacklist Regex: N/A
Maximum Response Size: 6553500
Maximum Request Size: 6553500
Limit Maximum Image Pixels: true
Prefer direct buffer: false
Allowed Urls: [file://.|http(s)?://.]
Custom python dependency for model allowed: false
Metrics report format: prometheus
Enable metrics API: true
Workflow Store: /mnt/models/model-store
Model config: N/A
2023-01-04T17:19:27,663 [INFO ] main org.pytorch.serve.servingsdk.impl.PluginsManager -  Loading snapshot serializer plugin...
2023-01-04T17:19:27,688 [INFO ] main org.pytorch.serve.snapshot.SnapshotManager - Started restoring models from snapshot {"name":"startup.cfg","modelCount":1,"models":{"mnist":{"1.0":{"defaultVersion":true,"marName":"mnist.mar","minWorkers":1,"maxWorkers":5,"batchSize":1,"maxBatchDelay":5000,"responseTimeout":120}}}}
2023-01-04T17:19:27,760 [INFO ] main org.pytorch.serve.snapshot.SnapshotManager - Validating snapshot startup.cfg
2023-01-04T17:19:27,761 [INFO ] main org.pytorch.serve.snapshot.SnapshotManager - Snapshot startup.cfg validated successfully
2023-01-04T17:19:28,269 [DEBUG] main org.pytorch.serve.wlm.ModelVersionedRefs - Adding new version 1.0 for model mnist
2023-01-04T17:19:28,269 [DEBUG] main org.pytorch.serve.wlm.ModelVersionedRefs - Setting default version to 1.0 for model mnist
2023-01-04T17:19:28,270 [DEBUG] main org.pytorch.serve.wlm.ModelVersionedRefs - Setting default version to 1.0 for model mnist
2023-01-04T17:19:28,270 [INFO ] main org.pytorch.serve.wlm.ModelManager - Model mnist loaded.
2023-01-04T17:19:28,270 [DEBUG] main org.pytorch.serve.wlm.ModelManager - updateModel: mnist, count: 1
2023-01-04T17:19:28,366 [INFO ] main org.pytorch.serve.ModelServer - Initialize Inference server with: EpollServerSocketChannel.
2023-01-04T17:19:28,365 [DEBUG] W-9000-mnist_1.0 org.pytorch.serve.wlm.WorkerLifeCycle - Worker cmdline: [/usr/bin/python, /usr/local/lib/python3.8/dist-packages/ts/model_service_worker.py, --sock-type, unix, --sock-name, /home/model-server/tmp/.ts.sock.9000]
2023-01-04T17:19:28,853 [INFO ] main org.pytorch.serve.ModelServer - Inference API bind to: http://<IP_ADDRESS>:8085
2023-01-04T17:19:28,854 [INFO ] main org.pytorch.serve.ModelServer - Initialize Management server with: EpollServerSocketChannel.
2023-01-04T17:19:28,855 [INFO ] main org.pytorch.serve.ModelServer - Management API bind to: http://<IP_ADDRESS>:8081
2023-01-04T17:19:28,855 [INFO ] main org.pytorch.serve.ModelServer - Initialize Metrics server with: EpollServerSocketChannel.
2023-01-04T17:19:28,856 [INFO ] main org.pytorch.serve.ModelServer - Metrics API bind to: http://<IP_ADDRESS>:8082
[I 230104 17:19:29 main:75] Wrapper : Model names ['mnist'], inference address http//<IP_ADDRESS>:8085, management address http://<IP_ADDRESS>:8081, model store /mnt/models/model-store
[I 230104 17:19:29 TorchserveModel:54] kfmodel Predict URL set to <IP_ADDRESS>:8085
[I 230104 17:19:29 TorchserveModel:56] kfmodel Explain URL set to <IP_ADDRESS>:8085
[I 230104 17:19:29 TSModelRepository:30] TSModelRepo is initialized
[I 230104 17:19:29 model_server:150] Registering model: mnist
[I 230104 17:19:29 model_server:123] Listening on port 8080
[I 230104 17:19:29 model_server:125] Will fork 1 workers
[I 230104 17:19:29 model_server:128] Setting max asyncio worker threads as 12
Model server started.
2023-01-04T17:19:29,672 [WARN ] pool-3-thread-1 org.pytorch.serve.metrics.MetricCollector - worker pid is not available yet.
2023-01-04T17:19:29,959 [INFO ] pool-3-thread-1 TS_METRICS - CPUUtilization.Percent:0.0|#Level:Host|#hostname:torchserve-predictor-default-00001-deployment-76d76564c7-smz2h,timestamp:1672852769
2023-01-04T17:19:29,960 [INFO ] pool-3-thread-1 TS_METRICS - DiskAvailable.Gigabytes:13.193183898925781|#Level:Host|#hostname:torchserve-predictor-default-00001-deployment-76d76564c7-smz2h,timestamp:1672852769
2023-01-04T17:19:29,961 [INFO ] pool-3-thread-1 TS_METRICS - DiskUsage.Gigabytes:25.375598907470703|#Level:Host|#hostname:torchserve-predictor-default-00001-deployment-76d76564c7-smz2h,timestamp:1672852769
2023-01-04T17:19:29,961 [INFO ] pool-3-thread-1 TS_METRICS - DiskUtilization.Percent:65.8|#Level:Host|#hostname:torchserve-predictor-default-00001-deployment-76d76564c7-smz2h,timestamp:1672852769
2023-01-04T17:19:29,961 [INFO ] pool-3-thread-1 TS_METRICS - MemoryAvailable.Megabytes:29446.06640625|#Level:Host|#hostname:torchserve-predictor-default-00001-deployment-76d76564c7-smz2h,timestamp:1672852769
2023-01-04T17:19:29,961 [INFO ] pool-3-thread-1 TS_METRICS - MemoryUsed.Megabytes:2227.64453125|#Level:Host|#hostname:torchserve-predictor-default-00001-deployment-76d76564c7-smz2h,timestamp:1672852769
2023-01-04T17:19:29,962 [INFO ] pool-3-thread-1 TS_METRICS - MemoryUtilization.Percent:8.3|#Level:Host|#hostname:torchserve-predictor-default-00001-deployment-76d76564c7-smz2h,timestamp:1672852769
2023-01-04T17:19:30,226 [INFO ] W-9000-mnist_1.0-stdout MODEL_LOG - Listening on port: /home/model-server/tmp/.ts.sock.9000
2023-01-04T17:19:30,226 [INFO ] W-9000-mnist_1.0-stdout MODEL_LOG - [PID]48
2023-01-04T17:19:30,227 [INFO ] W-9000-mnist_1.0-stdout MODEL_LOG - Torch worker started.
2023-01-04T17:19:30,227 [INFO ] W-9000-mnist_1.0-stdout MODEL_LOG - Python runtime: 3.8.0
2023-01-04T17:19:30,227 [DEBUG] W-9000-mnist_1.0 org.pytorch.serve.wlm.WorkerThread - W-9000-mnist_1.0 State change null -> WORKER_STARTED
2023-01-04T17:19:30,234 [INFO ] W-9000-mnist_1.0 org.pytorch.serve.wlm.WorkerThread - Connecting to: /home/model-server/tmp/.ts.sock.9000
2023-01-04T17:19:30,243 [INFO ] W-9000-mnist_1.0-stdout MODEL_LOG - Connection accepted: /home/model-server/tmp/.ts.sock.9000.
2023-01-04T17:19:30,246 [INFO ] W-9000-mnist_1.0 org.pytorch.serve.wlm.WorkerThread - Flushing req. to backend at:<PHONE_NUMBER>246
2023-01-04T17:19:30,297 [INFO ] W-9000-mnist_1.0-stdout MODEL_LOG - model_name: mnist, batchSize: 1
2023-01-04T17:19:30,893 [INFO ] W-9000-mnist_1.0-stdout MODEL_LOG - generated new fontManager
2023-01-04T17:19:31,509 [INFO ] W-9000-mnist_1.0-stdout MODEL_LOG - Backend worker process died.
2023-01-04T17:19:31,509 [INFO ] W-9000-mnist_1.0-stdout MODEL_LOG - Traceback (most recent call last):
2023-01-04T17:19:31,510 [INFO ] W-9000-mnist_1.0-stdout MODEL_LOG -   File "/usr/local/lib/python3.8/dist-packages/ts/model_service_worker.py", line 210, in
2023-01-04T17:19:31,510 [INFO ] W-9000-mnist_1.0-stdout MODEL_LOG -     worker.run_server()
2023-01-04T17:19:31,510 [INFO ] W-9000-mnist_1.0-stdout MODEL_LOG -   File "/usr/local/lib/python3.8/dist-packages/ts/model_service_worker.py", line 181, in run_server
2023-01-04T17:19:31,510 [INFO ] W-9000-mnist_1.0-stdout MODEL_LOG -     self.handle_connection(cl_socket)
2023-01-04T17:19:31,511 [INFO ] W-9000-mnist_1.0-stdout MODEL_LOG -   File "/usr/local/lib/python3.8/dist-packages/ts/model_service_worker.py", line 139, in handle_connection
2023-01-04T17:19:31,511 [INFO ] epollEventLoopGroup-5-1 org.pytorch.serve.wlm.WorkerThread - 9000 Worker disconnected. WORKER_STARTED
2023-01-04T17:19:31,511 [INFO ] W-9000-mnist_1.0-stdout MODEL_LOG -     service, result, code = self.load_model(msg)
2023-01-04T17:19:31,511 [INFO ] W-9000-mnist_1.0-stdout MODEL_LOG -   File "/usr/local/lib/python3.8/dist-packages/ts/model_service_worker.py", line 104, in load_model
2023-01-04T17:19:31,511 [INFO ] W-9000-mnist_1.0-stdout MODEL_LOG -     service = model_loader.load(
2023-01-04T17:19:31,512 [INFO ] W-9000-mnist_1.0-stdout MODEL_LOG -   File "/usr/local/lib/python3.8/dist-packages/ts/model_loader.py", line 127, in load
2023-01-04T17:19:31,512 [DEBUG] W-9000-mnist_1.0 org.pytorch.serve.wlm.WorkerThread - System state is : WORKER_STARTED
2023-01-04T17:19:31,512 [INFO ] W-9000-mnist_1.0-stdout MODEL_LOG -     envelope_class = self._load_default_envelope(envelope)
2023-01-04T17:19:31,512 [INFO ] W-9000-mnist_1.0-stdout MODEL_LOG -   File "/usr/local/lib/python3.8/dist-packages/ts/model_loader.py", line 172, in _load_default_envelope
2023-01-04T17:19:31,513 [INFO ] W-9000-mnist_1.0-stdout MODEL_LOG -     module = importlib.import_module(
2023-01-04T17:19:31,513 [INFO ] W-9000-mnist_1.0-stdout MODEL_LOG -   File "/usr/lib/python3.8/importlib/init.py", line 127, in import_module
2023-01-04T17:19:31,513 [INFO ] W-9000-mnist_1.0-stdout MODEL_LOG -     return _bootstrap._gcd_import(name[level:], package, level)
2023-01-04T17:19:31,513 [INFO ] W-9000-mnist_1.0-stdout MODEL_LOG -   File "", line 1014, in _gcd_import
2023-01-04T17:19:31,514 [INFO ] W-9000-mnist_1.0-stdout MODEL_LOG -   File "", line 991, in _find_and_load
2023-01-04T17:19:31,514 [INFO ] W-9000-mnist_1.0-stdout MODEL_LOG -   File "", line 973, in _find_and_load_unlocked
2023-01-04T17:19:31,514 [INFO ] W-9000-mnist_1.0-stdout MODEL_LOG - ModuleNotFoundError: No module named 'ts.torch_handler.request_envelope.kfserving'
2023-01-04T17:19:31,512 [DEBUG] W-9000-mnist_1.0 org.pytorch.serve.wlm.WorkerThread - Backend worker monitoring thread interrupted or backend worker process died.
java.lang.InterruptedException: null
at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.reportInterruptAfterWait(AbstractQueuedSynchronizer.java:2056) ~[?:?]
at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.awaitNanos(AbstractQueuedSynchronizer.java:2133) ~[?:?]
at java.util.concurrent.ArrayBlockingQueue.poll(ArrayBlockingQueue.java:432) ~[?:?]
at org.pytorch.serve.wlm.WorkerThread.run(WorkerThread.java:189) [model-server.jar:?]
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:515) [?:?]
at java.util.concurrent.FutureTask.run(FutureTask.java:264) [?:?]
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128) [?:?]
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628) [?:?]
at java.lang.Thread.run(Thread.java:829) [?:?]
2023-01-04T17:19:31,554 [WARN ] W-9000-mnist_1.0 org.pytorch.serve.wlm.BatchAggregator - Load model failed: mnist, error: Worker died.
2023-01-04T17:19:31,555 [DEBUG] W-9000-mnist_1.0 org.pytorch.serve.wlm.WorkerThread - W-9000-mnist_1.0 State change WORKER_STARTED -> WORKER_STOPPED
2023-01-04T17:19:31,555 [WARN ] W-9000-mnist_1.0 org.pytorch.serve.wlm.WorkerLifeCycle - terminateIOStreams() threadName=W-9000-mnist_1.0-stderr
2023-01-04T17:19:31,555 [WARN ] W-9000-mnist_1.0 org.pytorch.serve.wlm.WorkerLifeCycle - terminateIOStreams() threadName=W-9000-mnist_1.0-stdout
2023-01-04T17:19:31,556 [INFO ] W-9000-mnist_1.0 org.pytorch.serve.wlm.WorkerThread - Retry worker: 9000 in 1 seconds.
2023-01-04T17:19:31,564 [INFO ] W-9000-mnist_1.0-stdout org.pytorch.serve.wlm.WorkerLifeCycle - Stopped Scanner - W-9000-mnist_1.0-stdout
2023-01-04T17:19:31,564 [INFO ] W-9000-mnist_1.0-stderr org.pytorch.serve.wlm.WorkerLifeCycle - Stopped Scanner - W-9000-mnist_1.0-stderr
What did you expect to happen:
I expected the worker to load the model and accept connections for inference.
What's the InferenceService yaml:
apiVersion: serving.kserve.io/v1beta1
kind: InferenceService
metadata:
annotations:
kubectl.kubernetes.io/last-applied-configuration: |
{"apiVersion":"serving.kserve.io/v1beta1","kind":"InferenceService","metadata":{"annotations":{},"name":"torchserve","namespace":"default"},"spec":{"predictor":{"pytorch":{"storageUri":"gs://kfserving-examples/models/torchserve/image_classifier"}}}}
creationTimestamp: "2023-01-04T17:19:19Z"
finalizers:

inferenceservice.finalizers
generation: 1
name: torchserve
namespace: default
resourceVersion: "19132"
uid: cb162ca6-382c-4936-a04f-b6baadfec913
spec:
predictor:
model:
modelFormat:
name: pytorch
name: ""
resources: {}
storageUri: gs://kfserving-examples/models/torchserve/image_classifier
status:
address:
url: http://torchserve.default.svc.cluster.local/v1/models/torchserve:predict
components:
predictor:
address:
url: http://torchserve-predictor-default.default.svc.cluster.local
latestCreatedRevision: torchserve-predictor-default-00001
latestReadyRevision: torchserve-predictor-default-00001
latestRolledoutRevision: torchserve-predictor-default-00001
traffic:

latestRevision: true
percent: 100
revisionName: torchserve-predictor-default-00001
url: http://torchserve-predictor-default.default.example.com
conditions:

lastTransitionTime: "2023-01-04T17:19:31Z"
status: "True"
type: IngressReady
lastTransitionTime: "2023-01-04T17:19:31Z"
severity: Info
status: "True"
type: PredictorConfigurationReady
lastTransitionTime: "2023-01-04T17:19:31Z"
status: "True"
type: PredictorReady
lastTransitionTime: "2023-01-04T17:19:31Z"
severity: Info
status: "True"
type: PredictorRouteReady
lastTransitionTime: "2023-01-04T17:19:31Z"
status: "True"
type: Ready
modelStatus:
copies:
failedCopies: 0
totalCopies: 1
states:
activeModelState: Loaded
targetModelState: Loaded
transitionStatus: UpToDate
url: http://torchserve.default.example.com

Anything else you would like to add:
I am using the KServe "Quickstart" environment as described here: https://kserve.github.io/website/0.9/get_started/
I have tried different images for the inference service and it seems that the image pytorch/torchserve-kfs:0.4.1 is the last one to load the model. Anything newer and the model will not load.
Environment:

Istio Version: 1.14.0
Knative Version: 1.4.0
KServe Version: 0.9.0-rc0
Kubeflow version: N/A
Cloud Environment:[k8s_istio/istio_dex/gcp_basic_auth/gcp_iap/aws/aws_cognito/ibm]: on-prem K8s v1.22.17
Minikube/Kind version: N/A
Kubernetes version: (use kubectl version): v1.22.17
OS (e.g. from /etc/os-release): 22.04.1 LTS

@hugcyrill i think you need to follow the 0.9 doc https://kserve.github.io/website/0.9/modelserving/v1beta1/torchserve/#creating-model-storage-with-model-archive-and-config-file, the doc you linked was for 0.7

@yuzisun Thank you! That is exactly what happened. I think the problem is that the referenced example GCS bucket (gs://kfserving-examples/models/torchserve/image_classifier) has the config.properties with the service_envelope property. So if you simply follow the guide and do not create the model.mar and config.properties file yourself, you will run into this issue.
I therefore suggest to change this section from the documentation here:
For remote storage you can choose to start the example using the prebuilt mnist MAR file stored on KServe example GCS bucket gs://kfserving-examples/models/torchserve/image_classifier, or generate the MAR file with torch-model-archiver and create the model store on remote storage according to the above layout.

/cc @jagadeeshi2i

@hugcyrill . Pls use gs://kfserving-examples/models/torchserve/image_classifier/v1 for v1 and gs://kfserving-examples/models/torchserve/image_classifier/v2 for v2
I have updated the docs and will be fixed in  #2635

Perfect thank you @jagadeeshi2i and @yuzisun!


Missing NUnit package references

NUnit appears to be missing from NWN.Anvil.TestRunner/NWN.Anvil.TestRunner.csproj
/home/jkn/dev/Anvil/NWN.Anvil.TestRunner/src/main/TestRunnerService.cs(12,7): error CS0246: The type or namespace name 'NUnit' could not be found (are you missing a using directive or an assembly reference?) [/home/jkn/dev/Anvil/NWN.Anvil.TestRunner/NWN.Anvil.TestRunner.csproj]
/home/jkn/dev/Anvil/NWN.Anvil.TestRunner/src/main/TestRunnerService.cs(13,7): error CS0246: The type or namespace name 'NUnitLite' could not be found (are you missing a using directive or an assembly reference?) [/home/jkn/dev/Anvil/NWN.Anvil.TestRunner/NWN.Anvil.TestRunner.csproj]

Are these the correct versions?
dotnet add NWN.Anvil.TestRunner/ package NUnit --version 3.13.2
dotnet add NWN.Anvil.TestRunner/ package NUnitLite --version 3.13.2

After installing I get another error from https://github.com/nwn-dotnet/Anvil/blob/adaf95247ea27c96c53c7d92899bc4e97d480f8b/NWN.Anvil.TestRunner/src/main/TestRunnerService.cs#L48
'TestCommand' does not contain a definition for 'DefaultSynchronizationContext' [NWN.Anvil.TestRunner]csharp(CS0117)

The test runner uses a customised version of the package: https://github.com/nwn-dotnet/nunit
Did you pull all submodules? You should use the nunit attributes included in the test runner package rather than the ones from the nuget package: https://github.com/nwn-dotnet/Anvil/tree/development/NWN.Anvil.TestRunner/src/lib

Oh I didn't realize there are submodules now. Closing.


Make elasticsearch port less 15 chars

4b13faa34643a95c24e833e6bc14c2f09a00d392 changed the limit on port name
from 64 to 15. So we need to make our port names smaller.

@sdminonne

Satnam has #10453 which seems to overlap

This is already done in an existing PR which is waiting to be merged. #10453

but only partially - @satnam6502
One of you please absorb the other and ping - let's get this in today

I will adjust PR.

closing mine.


New Script sample: Export teams information to CSV

Created a new sample to get all teams from MS Teams with some related information (using PnP powershell) and export results into CSV.

Hey @chandaniprajapati , thank you 👏 for the double contribution - super awesome. This should be live shortly 😊


immich: 1.118.2 -> 1.119.0

Changelog: https://github.com/immich-app/immich/releases/tag/v1.119.0
fixes https://github.com/NixOS/nixpkgs/issues/351943

Things done

Built on platform(s)

[x] x86_64-linux
[ ] aarch64-linux
[ ] x86_64-darwin
[ ] aarch64-darwin

For non-Linux: Is sandboxing enabled in nix.conf? (See Nix manual)

[ ] sandbox = relaxed
[ ] sandbox = true

[ ] Tested, as applicable:

NixOS test(s) (look inside nixos/tests)
and/or package tests
or, for functions and "core" functionality, tests in lib/tests or pkgs/test
made sure NixOS tests are linked to the relevant packages

[ ] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[ ] Tested basic functionality of all binary files (usually in ./result/bin/)
24.11 Release Notes (or backporting 23.11 and 24.05 Release notes)

[ ] (Package updates) Added a release notes entry if the change is major or breaking
[ ] (Module updates) Added a release notes entry if the change is significant
[ ] (Module addition) Added a release notes entry if adding a new NixOS module

[x] Fits CONTRIBUTING.md.

Add a :+1: reaction to pull requests you find important.

nixpkgs-review result
Generated using nixpkgs-review.
Command: nixpkgs-review pr 351975

x86_64-linux

:fast_forward: 1 package blacklisted:

nixos-install-tools

:white_check_mark: 4 packages built:

immich
immich-cli
immich-machine-learning
immich-machine-learning.dist

aarch64-linux

:fast_forward: 2 packages marked as broken and skipped:

immich-machine-learning
immich-machine-learning.dist

:fast_forward: 1 package blacklisted:

nixos-install-tools

:white_check_mark: 2 packages built:

immich
immich-cli

x86_64-darwin

:white_check_mark: 1 package built:

immich-cli

aarch64-darwin

:white_check_mark: 1 package built:

immich-cli


pyfluent cname

listed here with warnings for dev.fluent.docs and dev.fluentdocs

Fixed by Roberto


Improve peer uptime metrics calculation by checking reliable public domains

We can periodically check public domains such as google.com and a few others and report results to Bazaar.
Based on this Bazaar can calculate peer uptime better

by @niclash :

Point is basically to report availability over a much longer period than the reporting interval to Bazaar.
For instance, in the metrics, provide availability for last 24 hours, 7 days and 1 month.
And Bazaar can choose how to present that, but otherwise doesn't need to rely on heartbeats
Because it is more likely that Bazaar is down

https://crunchify.com/how-to-get-ping-status-of-any-http-end-point-in-java/

This approach has potential problems. Malicious user can edit /etc/hosts file and setup local counterparts of such public servers to respond. Instead of this, would not it be better to have Bazaar send ping commands to a random public server known only to Bazaar or rely on heartbeats to determine peer availability?


Fix TestExecInfo failures in daint-ci

This PR changes the build mechanism of TestExecInfo so that it builds the stencil in separate folders per worker.

bors try

bors try-
bors try

bors try-
bors try

bors try-
bors try


No such file or directory when importing to Virt-Manager.

I'm getting the following error when attempting to import into Virt Manager. I'm running Fedora 35 GNOME desktop.
./make.sh --add
template.xml has been generated in /home/aia832003/Documents/notAperson535-OneClick-macOS-Simple-KVM-61657ee
[sudo] password for aia832003:
error: Failed to define domain from template.xml
error: Cannot check QEMU binary /run/current-system/sw/bin/qemu-system-x86_64: No such file or directory

@aia832003 before we try anything else, run git pull --rebase in the root directory, and try it again.

@notAperson535 git pull --rebase
fatal: not a git repository (or any parent up to mount point /)
Stopping at filesystem boundary (GIT_DISCOVERY_ACROSS_FILESYSTEM not set).

@aia832003 install git, then do a git clone https://github.com/notAperson535/OneClick-macOS-Simple-KVM.git, and try again

I've tried that too.
Andrew Allen
On May 1 2022, at 5:50 pm, notAperson535 @.***> wrote:

@aia832003 @./0?redirect=https%3A%2F%2Fgithub.com%2Faia832003&recipient=cmVwbHkrQUNUN09VNTRZUk9BWEY1UE9GVE82WVdBUFJBU1RFVkJOSEhFUldMNkFBQHJlcGx5LmdpdGh1Yi5jb20%3D) install git, then do a git clone https://github.com/notAperson535/OneClick-macOS-Simple-KVM.git, and try again
—
Reply to this email directly, view it on GitHub @./1?redirect=https%3A%2F%2Fgithub.com%2FnotAperson535%2FOneClick-macOS-Simple-KVM%2Fissues%2F14%23issuecomment-1114355985&recipient=cmVwbHkrQUNUN09VNTRZUk9BWEY1UE9GVE82WVdBUFJBU1RFVkJOSEhFUldMNkFBQHJlcGx5LmdpdGh1Yi5jb20%3D), or unsubscribe @.***/2?redirect=https%3A%2F%2Fgithub.com%2Fnotifications%2Funsubscribe-auth%2FACT7OU5HZOHEI66XNIGJPLLVH4DCTANCNFSM5U2DVBLQ&recipient=cmVwbHkrQUNUN09VNTRZUk9BWEY1UE9GVE82WVdBUFJBU1RFVkJOSEhFUldMNkFBQHJlcGx5LmdpdGh1Yi5jb20%3D).
You are receiving this because you were mentioned.

@aia832003 are you using a custom qemu binary?

@aia832003 actually try creating a symlink to /usr/libexec/qemu-kvm

@aia832003 sorry, I said the wrong directory create a symlink to /run/current-system/sw/bin/

@aia832003 install the regular version of QEMU, it should work fine.

Thanks for your patience. I've used the installation directly from QEMU's site with the same results of missing file or directory when using the ./make.sh --add command.
Andrew Allen
On May 2 2022, at 11:45 am, notAperson535 @.***> wrote:

@aia832003 @./0?redirect=https%3A%2F%2Fgithub.com%2Faia832003&recipient=cmVwbHkrQUNUN09VWUlRS0lOWkVXTzZLQkxNTU9BUFU2VEZFVkJOSEhFUldMNkFBQHJlcGx5LmdpdGh1Yi5jb20%3D) install the regular version of QEMU, it should work fine.
—
Reply to this email directly, view it on GitHub @./1?redirect=https%3A%2F%2Fgithub.com%2FnotAperson535%2FOneClick-macOS-Simple-KVM%2Fissues%2F14%23issuecomment-1115111033&recipient=cmVwbHkrQUNUN09VWUlRS0lOWkVXTzZLQkxNTU9BUFU2VEZFVkJOSEhFUldMNkFBQHJlcGx5LmdpdGh1Yi5jb20%3D), or unsubscribe @.***/2?redirect=https%3A%2F%2Fgithub.com%2Fnotifications%2Funsubscribe-auth%2FACT7OU3QEVHNAWV4XCMPZELVIABDFANCNFSM5U2DVBLQ&recipient=cmVwbHkrQUNUN09VWUlRS0lOWkVXTzZLQkxNTU9BUFU2VEZFVkJOSEhFUldMNkFBQHJlcGx5LmdpdGh1Yi5jb20%3D).
You are receiving this because you were mentioned.

@aia832003 remove the old qemu repository version and remove the symlink I told you to use. Then try again.

I got this error as well. I fixed it by manually editing the template.xml file. I changed the line that referred to run/current-system/sw/bin/qemu-system-x86_64 with /usr/bin/qemu-system-x86_64 which is where the binary is actually stored on my system (Arch Linux).

I got this error as well. I fixed it by manually editing the template.xml file. I changed the line that referred to run/current-system/sw/bin/qemu-system-x86_64 with /usr/bin/qemu-system-x86_64 which is where the binary is actually stored on my system (Arch Linux).

that sounds like it should work

I got this error as well. I fixed it by manually editing the template.xml file. I changed the line that referred to run/current-system/sw/bin/qemu-system-x86_64 with /usr/bin/qemu-system-x86_64 which is where the binary is actually stored on my system (Arch Linux).

that sounds like it should work

@aia832003

I'm assuming this is closed


Test bug fixes

Fixed bugs in tests. Some were caused by my own recent code refactoring, and others by fixes in the UI.

:tada: This PR is included in version 0.374.1 :tada:
The release is available on:

npm package (@next dist-tag)
GitHub release

Your semantic-release bot :package::rocket:


nixos/sdImage: add postBuildCommands

This allows to perform dd if= of=$img after the image is built
which is handy to add e.g. uBoot SPL to the built image.
Instructions for some ARM boards sometimes contain this step
that needs to be performed manually, with this patch it can be
part of the nix file used to built the image.

Motivation for this change
Things done

[x] Tested using sandboxing (nix.useSandbox on NixOS, or option sandbox in nix.conf on non-NixOS linux)
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 nixpkgs-review --run "nixpkgs-review wip"
[ ] Tested execution of all binary files (usually in ./result/bin/)
[ ] Determined the impact on package closure size (by running nix path-info -S before and after)
[ ] Ensured that relevant documentation is up to date
[x] Fits CONTRIBUTING.md.

This breaks eval for me:
The option `sdImage.postBuildCommands' is used but not defined.

Was missing a default value. Thanks!

Looks good to me. Could create a default sdImage


Is html font-size should be hardcoded ?

On https://github.com/paceaux/typography-baseline.scss/blob/master/sass/baseline/_baseline-mixin.scss#L93, wouldn't it be better to use something like this :
font-size: calc(0.5vw + var(--baseTextSize));

And why not add a variable for the 0.5vw ?

Thanks for your answer ! :-)
That would be great !
I've got some other questions I write in here instead of opening new issues. You tell me if you'd prefer new issues :)

why do you add some horizontal margin on some elements (https://github.com/paceaux/typography-baseline.scss/blob/master/sass/baseline/_baseline-mixin.scss#L114) ? Some elements aren't in this list, like address, form... Would it be possible to make this optional ?
in the lists section (https://github.com/paceaux/typography-baseline.scss/blob/master/sass/baseline/_baseline-mixin.scss#L160) maybe add a rule like this one:

ol,
ul {
  list-style: sassOrCssVar(listStyle);
}

in https://github.com/paceaux/typography-baseline.scss/blob/master/sass/baseline/textSizes.variables.scss#L16, it seems the scale is not coherent : why the "small" sizes starts at 0.8 instead of 0.9 ?

I think I'm done for now !
Thanks a lot for this very nice baseline and in advance.

Thanks a lot for these detailed explanations !
This project of yours is exactly what I was looking for, and the starting point it generates is really neat :-) Thanks a lot !


Automatically visualize point clouds from depth maps

Following a discussion with @Wumpf, we would like to experiment with a Renderer that is capable of raytracing through discrete volumes (i.e. an Amanatides & Woo kinda thing).
This renderer should ideally be capable of using either a 3D texture + bounding box or a 2D texture (interpreted as depth) + bounding box as input and render that in a spatial view as needed.
Our first real use-case would be to try and render depth maps in spatial views.
Today, the only way we have at our disposal to do that is to project the depth map back into 3D on the client-side, build a point cloud out of that, and upload the result to Rerun (see nyud example).
Of course this is pretty costly and doesn't scale nicely with the resolution: a 4K depth map would result in a 8M+ point cloud each frame :cold_sweat:

Also relates to https://github.com/rerun-io/rerun/issues/1164 since, in practice, one would need to specify that the depth map should be rendered as a volume and not an image in 3D space.
Also relates to https://github.com/rerun-io/rerun/issues/910 since you would ideally like to apply some color-mapping/transfer-function to these kind of renders.

Implemented in #1421


Octoprint: Access Request issues

Hi there!
I recently got your octoprint edge driver setup and I noticed I keep getting access requests from it, about once every ~24hrs. Is this a limitation of smartthings, or is there something wrong? I'd gladly input the api key into the driver settings if that would help fix the issue.
Another issue I wanted to bring to your attention (though it's really a smartthings issue): usernames in octopi are Case-Sensitive. In the smartthings app, the username field automatically capitalizes the first character upon saving, which broke my setup since my octopi username is all lower case. Might be a good gotcha to note in the setup instructions.

Hey!
Thanks for the bug report. I will take a look at what might be going on with the api key setup. I might be able to support both API Key and the octopi recommended authorization flow.

the username field automatically capitalizes the first character upon saving

So long as you deselect the 'Shift' button when entering it, it should be saved as all lowercase, though it may be displaying with an upper first character if you try and edit it again it should still be all lowercase.

So long as you deselect the 'Shift' button when entering it, it should be saved as all lowercase, though it may be displaying with an upper first character if you try and edit it again it should still be all lowercase.
strange, I could have sworn that it was still capitalizing it, but rechecking just now shows that's not the case. Guess I just mis-typed it the first few times.

Another thing I just noticed about the auth issue, it appears that it's requesting authentication even if it doesn't need it. I'm still able to see all the info from my printer, and the lgocat shows everything is coming through just fine. Maybe a check to see if it needs authentication is all that's needed?

ok, awesome! thanks for the update!

I've updated the driver to explicitly call driver.datastore:save after the API key is captured and this seemed to fix it on the hub I tested. I also reduced the state poll duration from 1 second to 5 seconds to allow a little more space for the datastore update to occur. I ended up publishing the changes last week so it should already be deployed, please let me know if this solves the problem for you as well.

I am request my credentials be reset for 1Password

I am request my credentials be reset for 1Password

Hi, are you having a problem with the octopi driver? It doesn't have any connection to 1Password could you elaborate on what you are looking for?

Sorry I am looking for help with 1password
On Wed, Sep 21, 2022 at 4:30 PM Robert Masen @.***>
wrote:

I am request my credentials be reset for 1Password
Hi, are you having a problem with the octopi driver? It doesn't have any
connection to 1Password could you elaborate on what you are looking for?
—
Reply to this email directly, view it on GitHub
https://github.com/FreeMasen/SmartThingsEdgeDrivers/issues/6#issuecomment-1254334668,
or unsubscribe
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.
You are receiving this because you commented.Message ID:
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--
Donald Rich
Senior Performance Strategist
https://www.kitmanlabs.com?utm_source=sl&utm_medium=email&utm_campaign=signature
P:<PHONE_NUMBER>
E: @.***


Create An Image for Social Media Post

We need an image for our next post on Twitter.
The copy for the design is " What does CHAOSS stands for? "
For any questions kindly let me know. Thanks!

Hey @iamkingsleey, kindly assign me to this task.

Have this issues been worked on ?

Have this issues been worked on ?

Hello @Delight362, I would love if you could help? Connect with me on slack, please?

@Delight362 From earlier conversation, it has been assigned. I'll get back to you on this if it has not been completed.
Thank you.

Have this issues been worked on ?

No. Can you take this on?

Okay what's the content,?
On Sat, Oct 21, 2023, 10:38 AM Nyiabari Joseph @.***>
wrote:

Have this issues been worked on ?
No. Can you take this on?
—
Reply to this email directly, view it on GitHub
https://github.com/chaoss/chaoss-africa/issues/18#issuecomment-1773733971,
or unsubscribe
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You are receiving this because you were mentioned.Message ID:
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@iamkingsleey Can this be closed?


Optimize app icon size

Optimize the app icon size so that it doesn't get cut off on different devices.
https://developer.android.com/distribute/google-play/resources/icon-design-specifications

Fixed in v1.0.3.


Match naked domains at urlSelector

Solves #40

I find INCLUDES is too lenient. It should be 'ends with' (not sure if graphl has it, I can't reach my playground atm.). Something like this regex ^(https?://)?(www\.)?url$ is even better, but escaping in the remaining url would be a pain.

I would agree if stash-checker does more than indicate missing or existing scenes. Matching URL with includes is way more precise than matching by name/title. The larger your own collection becomes, the more likely it is that duplicate or worse false positives will occur.
https://github.com/stashapp/stash-box/blob/e7605da7fa1edc6f13be833d57fc104fdc9a419a/graphql/schema/types/filter.graphql#L46

True.


Two questions regarding the code

Hi @xingyi-li,
Thanks for the impressive work and the released code.
I have two questions regarding the codes:

Is it possible to release the training code of the proposed method?

For the baseline method[19: Animating pictures with eulerian motion fields]. It seems the author didn't release the code as well, how to get the corresponding results of [19]?

Best regards and thanks in advance,

Hi @Amazingren,
Thanks for your interest!
i) We currently don't plan to release the training code. We are sorry for any inconvenience caused.
ii) Indeed, the authors of [19] did not release the code for their paper. We refer to SLR-SFS and reimplement the baseline method. It is interesting to note that, we cannot fully reproduce the results demonstrated in [19]. This made us believe that the task of predicting optical flow from a single image is highly uncertain and challenging. To achieve better motion estimation results, we were inspired by recent papers on controllable motion estimation and incorporated hints and masks to assist the motion estimation module, which we believe, can reduce the difficulty of optical flow prediction. In this way, we can obtain relatively satisfactory results and controllable animation. As a result, when implementing our framework, for in-the-wild photos, we used the controllable motion estimation module as our motion estimation network. Maybe predicting accurate optical flow from just a single RGB image can be done when we train with more data.
Regards,
Xingyi

Hi @Amazingren,
Thanks for your interest!
i) We currently don't plan to release the training code. We are sorry for any inconvenience caused. ii) Indeed, the authors of [19] did not release the code for their paper. We refer to SLR-SFS and reimplement the baseline method. It is interesting to note that, we cannot fully reproduce the results demonstrated in [19]. This made us believe that the task of predicting optical flow from a single image is highly uncertain and challenging. To achieve better motion estimation results, we were inspired by recent papers on controllable motion estimation and incorporated hints and masks to assist the motion estimation module, which we believe, can reduce the difficulty of optical flow prediction. In this way, we can obtain relatively satisfactory results and controllable animation. As a result, when implementing our framework, for in-the-wild photos, we used the controllable motion estimation module as our motion estimation network. Maybe predicting accurate optical flow from just a single RGB image can be done when we train with more data.
Regards, Xingyi

thanks a lot for the reply. And it helps a lot for me about the [19].
Bests regards and many thanks!


Using different loss

Hi, I'm doing experiments with your code and I need to use different loss than CrossEntropy. Since you added -1 to the targets (during padding), you use ignore_index=-1 flag, how can I prevent to compute gradient on those -1 using different losses? (Of course they can't offer the ignore_index flag)

You could find the index of each token which denotes  ignore_index!=-1 and then keep the corresponding loss in your sentence. In other words, it is not necessary to sum the losses of all tokens in a sentence, you just sum the losses of some tokens whose ignore_index!=-1.


Reverted to before dodgy merge

I couldn't work out how to get rid of the old commit so I've made a new branch

I promise it builds this time


Define story arcs and chapters

We want to create a basic story arc, and define chapters, then look through the advice and check whether we can write vignettes and choices that capture the most common advice.

[x] Define broad "time periods" aka chapters
[ ] Produce a story arc
[ ] Assign advice to chapters
[ ] Write vignettes / choices to illustrate each piece of advice

More ideas to turn into vignettes
1 year ahead

Defining the event topic/audience (will raise different issues depending on audience) CHOICE
Funding
-- CHOICE: Travel support? Yes - more funding needed, no - you limit the diversity of your participants
Putting together a committee - ensuring representation, balance
-- CHOICE: members
Creating a timeline
Format of conference (can people participate remotely? Will you have standard panels? How long will they be (e.g. bearing in mind regular breaks needed for various health issues)?
CHOICE: remote participation? Yes - need infrastructure set-up + format that includes well* remote participants, no - you lose input from remote participants, people who find it hard to get visas
Investigate accommodation options
Naming the event
Not sure how you might do choices here but there’s a study that shows the difference between naming something a hackathon, a coding challenge and a code and chat event on the type of attendees.


Adding go get golint before running go lint

Fixing https://github.com/kubernetes/test-infra/pull/7563#issuecomment-379324371 to ensure that we fetch golint before running it.
cc @G-Harmon @BenTheElder @krzyzacy

/LGTM.
Will wait for test to pass.

okay, all checks passed, great!


Small tweak to cleanse the Query of /* ... */ style comments which …

Small tweak to cleanse the Query of /* ... */ style comments which break the query explain parser
(a bit of an edge case, I know, but our query building tool adds non-standard /* ... */ style comments for query information, which seemed to collapse to nothing, breaking the queries.

Hi @kwiksand, thanks for the pull request. Before we can merge it, we need you to sign our Contributor License Agreement. You can do so electronically here: http://opensource.box.com/cla
Once you have signed, just add a comment to this pull request saying, "CLA signed". Thanks!

CLA signed

Verified that @kwiksand has just signed the CLA. Thanks, and we look forward to your contribution.

Hi @kwiksand ,
Thank you for sending the PR. The fix look pretty useful. Do you want to write a unit test for it?

ported in https://github.com/box/Anemometer/commit/1a4cca940046a465065e7388d4789cfc0d424485


Form controls

CYF NORTH WEST | HABEN SOLOMON KIDANE | Module User Focused Data| Form Controls | WEEK2
Learners, PR Template
Self checklist

[x] I have committed my files one by one, on purpose, and for a reason
[x] I have titled my PR with COHORT_NAME | FIRST_NAME LAST_NAME | REPO_NAME | WEEK
[x] I have tested my changes
[x] My changes follow the style guide
[x] My changes meet the requirements of this task

Changelist
Briefly explain your PR.
Questions
Needs Review

I am looking for your constructive feedbacks

The current branch is created from wireframe branch and not from the main branch. Please try to seek help from volunteers in Saturday workshop to rebase this branch so that it branch out from main.


Doc request: how to configure the examples in the README

I'm tryin' but failing. I'd love to see the config settings for the examples in the README. Thank you!

There are a couple other tickets where I explained some of them #94 #133
You can take a look if there.
I will also update the readme with all configurations for each screenshot when I have some time.

Here is how I config:
function config.indent_blankline()
    vim.cmd [[highlight IndentOne guifg=#BF616A guibg=NONE gui=nocombine]]
    vim.cmd [[highlight IndentTwo guifg=#D08770 guibg=NONE gui=nocombine]]
    vim.cmd [[highlight IndentThree guifg=#EBCB8B guibg=NONE gui=nocombine]]
    vim.cmd [[highlight IndentFour guifg=#A3BE8C guibg=NONE gui=nocombine]]
    vim.cmd [[highlight IndentFive guifg=#5E81AC guibg=NONE gui=nocombine]]
    vim.cmd [[highlight IndentSix guifg=#88C0D0 guibg=NONE gui=nocombine]]
    vim.cmd [[highlight IndentSeven guifg=#B48EAD guibg=NONE gui=nocombine]]
    vim.g.indent_blankline_char = "│"
    vim.g.indent_blankline_char_highlight_list = {
        "IndentOne", "IndentTwo", "IndentThree", "IndentFour", "IndentFive",
        "IndentSix", "IndentSeven"
    }
    vim.g.indent_blankline_show_first_indent_level = true
    vim.g.indent_blankline_filetype_exclude = {
        "startify", "dashboard", "dotooagenda", "log", "fugitive", "gitcommit",
        "packer", "vimwiki", "markdown", "json", "txt", "vista", "help",
        "todoist", "NvimTree", "peekaboo", "git", "TelescopePrompt", "undotree",
        "flutterToolsOutline", "" -- for all buffers without a file type
    }
    vim.g.indent_blankline_buftype_exclude = {"terminal", "nofile"}
    vim.g.indent_blankline_show_trailing_blankline_indent = false
    vim.g.indent_blankline_show_current_context = true
    vim.g.indent_blankline_context_patterns = {
        "class", "function", "method", "block", "list_literal", "selector",
        "^if", "^table", "if_statement", "while", "for"
    }
    -- because lazy load indent-blankline so need readd this autocmd
    vim.cmd('autocmd CursorMoved * IndentBlanklineRefresh')
end

Effect:

Thank you

Yeah, it would be helpful to know how to configure the treesitter highlighting example shown in the readme.

@cinerea0

Yeah, it would be helpful to know how to configure the treesitter highlighting example shown in the readme.

You need to install TreeSitter with your plugin manager, then use :TSInstall YOUR_LANGUAGE to install the language parser for example :TSInstall javascript. You can use the 2nd config @ayamir supplied and it should start working for you.

Nice screenshots, poor documentation. The examples are not clear and where the heck this "function" needs to be? Don't think for users, nothing is obvious...


Noty size to match text

Is there an option that can set the size of a noty to match the text. ie. Shrink it to fit the text.
Also a new feature request. I'd like to see a centered, below top option like GMail notifications work.
Neville, http://www.surfulater.com

For now, there is no option for that. But you can set a new layout in options. After that, you can write a css for new layout. Thats it. I will create a new layout when I found the appropriate time

@nevf I added a new GMail like layout with this commit. https://github.com/needim/noty/commit/d910dc29c7e952e23a73072a232bbf14c9c145be

@needim Thank you for doing this and so quickly.


Remove URL from Mirador single-item view

Look for solutions in tamu-mirador configuration or in the structure of the generated IIIF Manifest.
Text from customer:

The URL, and perhaps the 1 of 1, should be removed from the Mirador image viewer. This is taking up too much landscape and the link is ugly. The project tamu-mirador should be investigated to determine if a configuration may be found within.

Could test Mirador here: https://demos.library.tamu.edu/mirador/
Could feed it manifests such as: https://api.library.tamu.edu/iiif-service/fedora/presentation/3b/6f/c3/25/3b6fc325-f6ca-41d8-b91e-8c5db3be8c13/time_of_resolve_objects/93

Here is an example where the footer has something more than 1 of 1 and also has a much shorter file name.

https://library.tamu.edu/discovery/discovery-context/geologic-atlas-united-states/Mi1lZWI3ZjNjNC1hOTQyLTQ3YmMtOTkzZi02ZDVhNjViMTYxOWQ=

Created issue #509 to provide a solution derived from this investigation.


Clean up certificate timestamp comparisons

Description

There are three places we compare certificates against SET or TSA timestamps:

We aggregate all timestamps from SETs and TSAs and verify the certificate's validity with those timestamps here. The timestamp needs to fall in the range of "Not Before" <= timestamp <= "Not After" (go source code)
The code signing certificate is compared against the TSA timestamp here,  which does the same comparison against "not before" and "not after"
We verify the certificate against the SET timestamp here, which will do the same not before/after comparison.

As noted in a comment, the latter two are unnecessary, and so should be removed.

I could be misunderstanding but I think each of these instances are different from each other and necessary:
Verify() -> VerifyLeafCertificate() (link) - aggregates SETs and TSAs and verifies them against the fulcio CA
Verify() -> VerifyObserverTimestamps() -> VerifyTimestampAuthority() -> verifySignedTimestamp() (link) - verifies each timestamp, if any, against the bundle certificates. The signed entity doesn't always have a timestamps issued by a TSA. I think the comment here is mistaken.
Verify() -> VerifyTransparencyLogInclusion() -> VerifyArtifactTransparencyLog() (link) - verifies the tlog entry time against the bundle certificates
@haydentherapper do you still think these are superfluous?

For the first, the SET and TSA timestamps are used to verify the code-signing/leaf certificate. That timestamp, CurrentTime, will be used when comparing NotBefore and NotAfter (go source link). The CA certificate validity window is also compared (link).
That is the same check that we do in the second, comparing the certificate's NotBefore and NotAfter (link). That will be the same as the third check as well, just using the tlog entry timestamp instead.
I think the latter two are still superfluous. With that said, I think there are two things to discuss:

As an API, should we do timestamp comparisons as part of VerifyTimestampAuthority and VerifyArtifactTransparencyLog, even if it's repeated in signed_entity.Verify()? I'd lean towards no, that the responsibility of each of these functions is to verify either a signed timestamp and return the timestamp or verify log inclusion and return a timestamp if available, and what to do with the timestamps are for another API (which is VerifyLeafCertificate).
We've mostly been thinking about certificate verification, but not verification with keys. Keys provided as part of the verification material will only be a hint, not the key itself, so there is not validity window (link). However when constructing a trust root, you can provide an expiring key (example), and when comparing a bundle's verification material that contains a key, it will look up that expiring key by the hint (link). If we do remove these additional timestamp checks from the latter two APIs, then we would need to add back support for comparing the key's expiration somewhere,  since we only do timestamp comparisons if the verification content contains a certificate.

Thoughts? Either we need to a) update the comments on the APIs and leave everything as is, or b) remove the timestamp comparisons and also add timestamp comparisons back for key verification.

@haydentherapper would you mind updating the links in the original issue with permalinks so I can be sure I'm looking at the same code you're talking about? The first seems to link to a call to VerifyObserverTimestamps and the second seems to link to another function that's called from within VerifyObserverTimestamps so it's not clicking for me where the duplication is.

@cmurphy Updated the links, lemme know if that helps.


Null type is adding to the variants

Hey
Please refer this below image

When i am removing the "null" from here

Every thing is working fine as expected

Closing as this doesn't correspond to the issue template, null will be removed in<EMAIL_ADDRESS>and this is likely a Storybook issue not a cva issue


Slow Adam sparse updates in distributed TF

I am trying to train a model with the tf.nn.embedding_lookup_sparse operation. Small example: https://gist.github.com/Bobrosoft98/2d639d3924dfbc4ec7bc620fd5a4d480
When I run this code with NUM_WORKERS = 1, the output is as follows
0 calc in 0.0176000595093
0 apply in 0.184364080429
0 calc in 0.0167639255524
0 apply in 0.189659118652
...

However, when I increase the number of workers to 30, every single process works more than 30 times slower:
6 calc in 0.432843923569
11 calc in 0.787642002106
3 calc in 0.440953016281
14 calc in 0.377243995667
20 calc in 0.569782018661
...
6 apply in 5.63959908485

The CPU load is only ~50%, so there is a lot of resources available for the computation. This makes me think that sparse updates use locking, even though the use_locking flag is set to False by default. There is no such problem with other optimizers (I tried GradientDescentOptimizer and AdadeltaOptimizer). Also if I exclude sparse operations from the graph (commented lines), the problem disappears.
What related GitHub issues or StackOverflow threads have you found by searching the web for your problem?
https://github.com/tensorflow/tensorflow/issues/464 - there was mentioned that Adam was slower on sparse updates in general
Environment info
Operating System: Ubuntu 16.04
Installed version of CUDA and cuDNN: I used the CPU version
If installed from binary pip package, provide:

A link to the pip package you installed: https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.12.0-cp27-none-linux_x86_64.whl
The output from python -c "import tensorflow; print(tensorflow.__version__)".

$ python -c "import tensorflow; print(tensorflow.__version__)"
0.12.0-rc1

@theweiho can you comment?

This seems to be more a sparse tensor/Adam interaction issue than an embedding issue. @concretevitamin - any idea about the sparse updates part?
Or @vrv for general performance issues - or any idea who might know more about the Adam optimizer?

+cc @mrry in case this could be solved by your recent optimizations on distributed runtime performance!

I tried profiling the code as described here and got interesting results.
This is what I get with GradientDescentOptimizer and 30 workers:

This is AdamOptimizer with 30 workers

And this is Adam with 1 worker

So all the expensive operations are running on the PS.

@concretevitamin Thanks for the hopefulness, but alas I don't think any of my recent optimizations will make this better.
@Bobrosoft98 What is your CPU utilization like on the PS machine when running Adam with one worker? From a quick glance it looks like the ops duration might be dilating because of contention for the threadpools (in particular the intra-op parallelism) that do parallel work in a TF server. If 30 workers all attempts to send their gradients at approximately the same time, there will be 30x the amount of work to do at the PS.
One possible mitigation would be to use tf.train.SyncReplicasOptimizer to wrap the Adam optimizer. This would have the benefit that all of the gradients from the different workers would be aggregated (relatively cheaply) before the Adam update rule is evaluated. This should cut down on the amount of work, compared to an asynchronous setup that processes the incoming batches separately. (It's not a free lunch... the synchronous replication is more vulnerable to stragglers, and a little more tricky to set up... but it might be worth it for your case.)

@mrry I run everything on a single machine, the CPU load with one worker is the same as with 30 workers (about 50% on all cores).
Still, it's not clear for me why Adam has this problem, and other optimizers don't. What do mean these huge "Mul" and "Assign" blocks on the timeline? Why assigning something takes so much time?

It seems to me that a problem is adam not working properly with sparse updates. Although it is said that

Note that in dense implement of this algorithm, m_t, v_t and variable will
update even if g is zero, but in sparse implement, m_t, v_t and variable
will not update in iterations g is zero

the code of _apply_sparse looks like it is updating the whole matrix.

I also met the same problem when using Adam optimizer solving a model involving big embedding matrix. Compared to Adagrad or Adadelta, Adam works much slower. When I doubled the vocabulary size, the time consumption for Adam also doubled...

There is a post in Tensorflow mail list that solves my problem: https://groups.google.com/a/tensorflow.org/forum/#!searchin/discuss/adam$20sparse/discuss/6GvpMz8kb-U/FaBAJkbvEQAJ

LazyAdamOptimizer is supposed to make it faster -- github.com/tensorflow/tensorflow/commit/819a690d

SparseAdam in pytorch is same as Tensorflow LazyAdam. The convergence of LazyAdam is lower than Adam.  The main problem is if the gradient is 0, we don't update m, and v.
Actually, m and v should be updated when other weights are updated.  This is why LazyAdam convergence is low.
I have proposed a method to fix this issue. The performance is about the same as LazyAdam, and the convergence is the same as Adam.
Could you please review my method:
https://github.com/tensorflow/tensorflow/issues/23668


the source code of align function with python

Required Info

Camera Model
D455

Firmware Version
Open RealSense Viewer

Operating System & Version
Linux

Kernel Version (Linux Only)

Platform
PC

SDK Version
{ legacy / 2.. }

Language
python }

Segment
Robot }

Issue Description
I would like to know where is the corresponding source code for implementing the align function in the pyrealsense2 library? Thank you very much!!

Hi @puyiwen  The RealSense SDK has a pyrealsense2 example program for depth to color alignment called align_depth2color.py at the link below.
https://github.com/IntelRealSense/librealsense/blob/master/wrappers/python/examples/align-depth2color.py

你好@puyiwen RealSense SDK 有一个用于深度到颜色对齐的pyrealsense2 示例程序，名为**align_depth2color.py，**位于下面的链接。
https://github.com/IntelRealSense/librealsense/blob/master/wrappers/python/examples/align-depth2color.py

Thank you for your reply, the code you provided has used the align API, and I would like to know what is the implementation of the align API interface of this module?

Hi @puyiwen  Do you require further assistance with this case, please?  Thanks!

Case closed due to no further comments received.


Translations update from Mattermost Weblate

Translations update from Mattermost Weblate for mattermost-languages-shipped/mattermost-mobile-v2.
Current translation status:

Hello @weblate,
Thanks for your pull request! A Core Committer will review your pull request soon. For code contributions, you can learn more about the review process here.

/release-note-none

@cwarnermm can you aprove this PR as well? We can merge then

@lieut-data @cwarnermm
Can you help approving this PR so it can be merged?

/release-note-none


Improper treatment of booleans in QueryBuilder::toRawSql for Postgres

Laravel Version
10.17
PHP Version
8.2.8
Database Driver & Version
Postgresql 14
Description
When using Postgresql, booleans are transformed into integers in Builder::toRawSql().
I tried to fix it but I'm a bit worried to make a mess to fix that.
PostgresConnectiondoes has a valid escapeBoolmethod but the proble is higher in the call stack.
When running User::query()->where('is_admin', true)->toRawSql();, toRawSql() looks like
    public function toRawSql()
    {
        return $this->grammar->substituteBindingsIntoRawSql(
            $this->toSql(), $this->connection->prepareBindings([true])
        );
    }

which resolves in
    public function toRawSql()
    {
        return $this->grammar->substituteBindingsIntoRawSql(
            $this->toSql(), [1]
        );
    }

because of  https://github.com/laravel/framework/blob/19b42097f542a837d3c0e6aad2abaf2b05a6cbee/src/Illuminate/Database/Connection.php#L713-L729
(note that the boolean cast into integer)
@tpetry Any smart idea to fix that ?
I guess overriding prepareBindingsand bindValues in PostgresConnection should do the trick but is not a valid move for Laravel :
Related explanations on why booleans are casted to integers in Laravel by Taylor : https://github.com/php/php-src/pull/6801#issuecomment-828783810
Steps To Reproduce
User::query()->where('is_admin', true)->toRawSql();

returns 'select * from "users" where "is_admin" = 1'
while it should return 'select * from "users" where "is_admin" = true'

Changing this in Laravel may break some applications. So it is not a good approach to change it.
Casting those values to int is not perfect, but it is also not a problem. PostgreSQL is intelligent enough to recognize that you are comparing a boolean column to a 0 or 1 value and will automatically cast them. So for almost any application, this is not a problem. I had some code parts in the past where this automatic casting did not work correctly and PG will then fail with an error about incompatible types. If you haven't seen this yet, the bool -> int cast is not a problem.
If you've had this problem or insist on having is_admin = TRUE in your query, you can use the whereBool method from tpetry/laravel-postgresql-enhanced

@tpetry unfortunately, postgres does not seed to be able to cast int -> bool.
When I try to replay manually an SQL query fetched from ddRawSql(), Postgresql complains about the type :
select * from "users" where "is_admin" = 1;
ERROR:  operator does not exist: boolean = integer
LINE 1: select * from "users" where "is_admin" = 1;
                                               ^
HINT:  No operator matches the given name and argument types. You might need to add explicit type casts.

Is it a configuration problem in postgres ? I quite don't understant why the int instead of bool will pass in PDO but not in the pgsql console.

I think maybe that was the edge case for me too, not quite sure. As said, you can use my whereBool method.


Don't add no op mutations when diffing lists

When diffing lists, the Virtual Dom will sometimes insert mutations that do nothing like appending no children or inserting no nodes before or after a node. This checks for those cases and only inserts mutations when needed

Looks like the behavior of some tests changed.


Handle Configuration Directories vs Files

Split configs to config-dirs and config-files

We removed this and simply mounted $HOME to /root


Built in webview incompatible with zoom

VSCode Version: 1.8.1
OS Version: Windows 10 Version 1607

Steps to Reproduce:

May require a Hi-DPI screen with 125% scale?
Press Ctrl + "+" zoom Code
Open release note or markdown preview

dupe #5745


Implementation of interface requires members redeclaration

interface A {
	foo: Function;
}

class B implements A {
	constructor() {
		this.foo = () => {};
	}
}

Here TypeScript says that B incorrectly implements A and requires B to also have foo property with the same signature. So question is: why I need duplicate definition of properties when implement interface if I cannot override that definition anyway:
interface A {
	foo: Function;
}

class B implements A {
	foo: boolean;
	constructor() {
		this.foo = true;
	}
}

Here B again incorrectly implements A. Only way to fix it is to add foo:Function to B which absolutely has no point since A already has that.

Stating class B implements interface A is like promising to implement each member present in A inside B.
Remember that interfaces only describe members. They don't implement anything.
Implementation is reserved for classes. Classes can extend other classes and promise to implement interfaces.

This looks like a duplicate of #340. @RyanCavanaugh explained some of the rationale here: https://github.com/Microsoft/TypeScript/issues/340#issuecomment-51098654.

@GoToLoop Thanks, I know what is interfaces and what is classes.

Stating class B implements interface A is like promising to implement each member present in A inside B.

Exactly. This is why duplicate declaration of members shouldn't be needed.
@DanielRosenwasser I am talking here about implementation of one interface, while @RyanCavanaugh shows examples of multiple classes. These cases are not relevant, you can handle multiple implementation in other way than since implementation. Still, I want to comment some moments:

it becomes very unclear/confusing what it means if you explicitly write those members:

In case of single implementation it's "incorrectly implements" if signatures are mismatched. This is why there is no rationale to duplicate them. Even more, with multiple implementations you still get that error:
interface A {
	foo:Function;
}

interface B {
	foo:boolean;
}

class C implements A, B {
	foo:boolean;
	constructor() {
		this.foo = true;
	}
}

Here "C incorrectly implements A", which is expected.
Even more, @RyanCavanaugh 's examples are relevant only to methods of class which absolutely should have their own rule since overloading is different topic.
One more interesting about multiple implementations and different methods signature is that there is only one way and all other ways report "incorrect implementation", this way:
interface A {
	foo(a:string):void
}

interface B {
	foo(a:number):void
}

class C implements A, B {
	foo: (a:string | number) => void;
	constructor() {
		this.foo = (a:string | number) => {}
	}
}

So again, if this is only way to handle multiple implementations and all other ways throw, then signature of foo() should be implicitly created. If you care about errors, it anyway will be reported on property assignment in constructor.

And please, open this back. I do not want create new issue for it
On Nov 23, 2015 6:40 AM, "Daniel Rosenwasser"<EMAIL_ADDRESS>wrote:

Closed #5749 https://github.com/Microsoft/TypeScript/issues/5749.
—
Reply to this email directly or view it on GitHub
https://github.com/Microsoft/TypeScript/issues/5749#event-471717047.

The issues is a duplicate of #340.  While the example given demonstrates why it becomes complex when implementing multiple interfaces, it is the root cause of why the team of chosen to not implement this feature as #340 states, it is too complex and they consider it out of scope.  Opening another issue will just get it closed and marked as a duplicate again.
Your example is that you have an interface that provides no implementation of method foo.  It isn't just "redeclaring" as you asserted, it is about providing an implementation.  The same goes for properties, because the class which implements an interface need to specify the implementation (e.g. a default value, or no default value or potentially property accessors).
The way you want to deal with the code seems more in line with the abstract keyword and classes, where you only have to implement the methods you have have marked as abstract in the final non-abstract class.

This seems to work any maybe covers some use cases:
export interface A {
    foobar: number;
}

export interface B extends A {
    new(): B;

    quux: number;

    // More members go here.
}

export var C: B;

C is now assumed to be a class correctly implementing interfaces A and B. Only the interface defining the actual type of C should have a new() method returning the interface itself.


CucumberOptions annotation causes exception in 0.6.2

I have a set of tests that works fine with Karate 0.6.1. In the top-level test runner class, we have the following annotation to support Cucumber reporting: @CucumberOptions(plugin = {"pretty", "json:target/cucumber/cucumber-data"}).  When I try to upgrade to 0.6.2, this results in all tests failing, reporting that all scenarios have 0 scenarios and 0 steps.  To recreate, generate a project with the archetype, After running to make sure it works, add the annotation mentioned above (along with an import import cucumber.api.CucumberOptions; to ExamplesTest.java.  Run mvn test to see the failure.  The first exception:
-------------------------------------------------------------------------------
Test set: examples.ExamplesTest
-------------------------------------------------------------------------------
Tests run: 1, Failures: 0, Errors: 1, Skipped: 0, Time elapsed: 1.358 sec <<< FAILURE!
Feature: sample karate test script  Time elapsed: 0.765 sec  <<< ERROR!
java.lang.NullPointerException
        at gherkin.formatter.JSONFormatter.match(JSONFormatter.java:123)
        at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
        at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
        at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
        at java.lang.reflect.Method.invoke(Method.java:498)
        at cucumber.runtime.Utils$1.call(Utils.java:40)
        at cucumber.runtime.Timeout.timeout(Timeout.java:16)
        at cucumber.runtime.Utils.invoke(Utils.java:34)
        at cucumber.runtime.RuntimeOptions$1.invoke(RuntimeOptions.java:294)
        at com.sun.proxy.$Proxy6.match(Unknown Source)
        at com.intuit.karate.cucumber.KarateHtmlReporter.match(KarateHtmlReporter.java:307)
        at cucumber.runtime.junit.JUnitReporter.match(JUnitReporter.java:68)
        at com.intuit.karate.junit4.Karate$1.match(Karate.java:90)
        at com.intuit.karate.cucumber.CucumberUtils.afterStep(CucumberUtils.java:160)
        at com.intuit.karate.cucumber.CucumberUtils.runStep(CucumberUtils.java:146)
        at com.intuit.karate.cucumber.KarateRuntime.runStep(KarateRuntime.java:80)
        at cucumber.runtime.model.StepContainer.runStep(StepContainer.java:44)
        at cucumber.runtime.model.StepContainer.runSteps(StepContainer.java:39)
        at cucumber.runtime.model.CucumberScenario.runBackground(CucumberScenario.java:59)
        at cucumber.runtime.model.CucumberScenario.run(CucumberScenario.java:42)
        at cucumber.runtime.junit.ExecutionUnitRunner.run(ExecutionUnitRunner.java:102)
        at cucumber.runtime.junit.FeatureRunner.runChild(FeatureRunner.java:63)
        at cucumber.runtime.junit.FeatureRunner.runChild(FeatureRunner.java:18)
        ...

Changing the Karate version back to 0.6.1 and the example will work again.

@msennett9 I'll look at this in a moment. meanwhile, I'd like to explore if you would be okay to NOT use the pretty and json 'native' reports.
especially the json, in Karate you are supposed to use what is generated by the parallel runner, refer: https://github.com/intuit/karate#parallel-execution
and pretty was useful only in dev mode and now you have the HTML report: https://github.com/intuit/karate#junit-html-report
I may have missed making this clear in the doc, and instead of a null-pointer I'm considering a helpful error message instead. would that work ?

I did see the doc about the parallel runner.  We are generating the json because we wanted to use the net.masterthought maven plugin for generating the nice-looking Cucumber reports.  I'll take a look to see if we can use another approach.

@msennett9 the karate json is standard (most importantly the in-line HTTP logs, plus some nice tweaks for api testing, for e.g. you see the feature file name not the 'friendly' name) will work with the masterthought plugin.

@msennett9 were you able to try the karate parallel runner + json + the masterthought reports ?
also, I released an un-official <IP_ADDRESS> version, would be great if you try and let me know if fixed.


Using core NATS rather than jetstream from safe inputs

Need to switch this over to jetstream for message persistence

Added Jetstream to safe-inputs - now using consumer with js sub in service 1


404 page: button and icon GTM script.

add GTM scripts to the navigation icons and buttons on the 404 page.

These are now configured.


fix(zopaicon): fix ZopaLogo naming and fix default color

Update naming from ZopaLogo to ZopaIcon for documentation purposes.
Fix ZopaIcon default color (from blue to teal).

:tada: This PR is included in version 4.0.0 :tada:
The release is available on:

npm package (@latest dist-tag)
GitHub release

Your semantic-release bot :package::rocket:


Platform v1.27

Wait, why do we have a 1.29 build? https://github.com/sublime-security/go-mantis/releases/tag/v1.29.13-rc.0

@hugh-sublime confirmed that the release branch is correct, but the tag is wrong. So I think this will be fine? I assume we'll have to fix the tags though. cc @cameron-dunn-sublime


Support creating InstanceMetadata from env

Which issue this PR addresses:
Inability to access instance metadata endpoint inside ACI.
What this PR does / why we need it:
In Ev2 deployments the deployer is running in Azure Container Instance
(ACI) and does not have access to the instance metadata we have used
to date.  But we have the info to populate env vars.  So we will do that
and attempt to use env vars first.  If we get everything we need, log
what happened and do not use metadata endpoint.  Else fallback to
existing behavior.
Test plan for issue:
Deploying in INT for all supported clouds.
Is there any documentation that needs to be updated for this PR?
No?

Please do not merge it. Gonna check it in the morning. Logging should not be instantiated again. Will check tomorrow :)

@mjudeikis yes, this never calls GetEntry() on its own, always requires it be called elsewhere.  So we only ever have a single (if only called once) instance.  And if not set things fail.

Did this whule reviewing: https://github.com/mjudeikis/ARO-RP/commit/a24741ef99a4557b6958c1eecbb901ea76cb9a53 you can use if you want.
In addition if p.populateInstanceMetadataFromEnvironment() { needs to be gated by EV2 env variable. Otherwise it will introduce flakes into TestPopulateInstanceMetadata test. And it would be good to add test cases for this function as we modified its behavior.

@mjudeikis changes merged except unit tests.  Will see how I can get that going with use of mock, challenge from what I read last night being mocking getenv is not a thing but.. we'll see.  If you're OK with current state without tests I ask we consider merging now.  I will work on tests today regardless.

@mjudeikis @m1kola ready for review with unit tests.

/azp run E2E


fix: port schema example changes

Fixes #3153

Pull Request Test Coverage Report for Build 436300592

0 of 0   changed or added relevant lines in 0 files are covered.
1 unchanged line in 1 file lost coverage.
Overall coverage remained the same at 84.471%

Files with Coverage Reduction
New Missed Lines
%

libraries/botbuilder-lg/src/templateExtensions.ts
1
85.0%

Totals

Change from base Build 421844958:
0.0%

Covered Lines:
17657

Relevant Lines:
19975

💛  - Coveralls


As a multi-environment system owner I want support to work with unidirectional security barriers in trestle.

Issue description / feature objectives
Suppose we have two systems A and B, where one system (A) is more generally accessible (within and without a service provide) and system B is highly restricted.
System (A) and system (B) are based on the same architecture, however, may have significant differences
e.g. Deployment topology, Services available, and some process and procedures.
E.g. we need to do a 'merge' update across repositories.  Where B pulls in content from A but not reverse. This may be possible using git based workflows only (and could be documented that way).

This can be defined by git workflows and appropriate access. Similar to separate repositories for catalog, profile, ssp and updates from one repo being pushed to other.


Support Linux Mint

Linux Mint is based on Ubuntu which is based on Debian
fixes #143

Not sure if you like the approach I took with this, but I noticed the Debian/Ubuntu duplication and decided to let the code mirror the relationship between the distros while still allowing for individial customization should the need arise.
I could also go back to my initial fix or make the simplest possible thing:
      when "Debian", "Ubuntu", "LinuxMint"
        require "invoker/power/setup/distro/debian"
        Debian.new

and then individual code can be added when needed.
Your call :)
Tobi

I think current fix is acceptable. We can refactor things later. I will merge.


Dropbox new OAuth2 (with supporting refresh token).

Hi! Dropbox plans do not support long-live access token (after September 2021) and will support refresh token. Will you change this lib according to new rules?
More info is here: https://dropbox.tech/developers/migrating-app-permissions-and-access-tokens

The lib already works as is with refresh tokens, all you need to do is not to set a redirectUri when setting up the provider.

The lib already works as is with refresh tokens, all you need to do is not to set a redirectUri when setting up the provider.

Thank you!

Thank you!


Unfeature flag the cloud debugger

Relates to #1032.

Are you planning on submitting individual PRs to unfeature each component?

yes to both comments.
On Mon, Oct 17, 2016 at 3:33 PM, Etan Shaul<EMAIL_ADDRESS>wrote:

@etanshaul commented on this pull request.
In google-cloud-tools-plugin/src/com/google/cloud/tools/intellij/startup/
CloudToolsPluginInitializationComponent.java
https://github.com/GoogleCloudPlatform/google-cloud-intellij/pull/1033#pullrequestreview-4542181
:

@@ -62,10 +62,6 @@ public void initComponent() {
CloudToolsPluginInfoService pluginInfoService = ServiceManager
.getService(CloudToolsPluginInfoService.class);

if (pluginInfoService.shouldEnable(GctFeature.DEBUGGER)) {

Should we also remove GctFeature.Debugger?
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
https://github.com/GoogleCloudPlatform/google-cloud-intellij/pull/1033#pullrequestreview-4542181,
or mute the thread
https://github.com/notifications/unsubscribe-auth/AHf5HatF3mxbUjIwkEdmRVrl127wLhyoks5q081xgaJpZM4KY-IK
.

ok. lgtm then after the unit test fix


tile manipulation for cupy.ndarray

For #599

I have done.

Updated.

Please add test of changing the conditions of resp.

zero: e.g. resp=0
one: e.g. resp=1
negative: e.g. resp=-1
long: e.g. resp=(2, 3, 4, 5)

enough? https://github.com/pfnet/chainer/pull/605/files#diff-075b672822ebbfe27365fdc6e53d5b36R44

Perfect!
LGTM.

Thanks!


⚠ Bofrost.at has degraded performance

In f4a312e, Bofrost.at (https://www.bofrost.at) experienced degraded performance:

HTTP code: 200
Response time: 2076 ms

Resolved: Bofrost.at performance has improved in 68f989b.


switching a template to standalone makes it disappear in swarm mode

Bug description
I created a custom type=Swarm template, then flipped the type to Standalone in an edit. It wasn't obvious to me what the two options meant, so I wanted to find out.
The custom template disappeared, but is not gone and apparently can't be accessed anywhere in the UI. This means that, for example, it's no longer possible to delete the template, create a new one with the same name, or flip it back to type=Swarm.
(I have had the suggestion that it might be possible to delete it through the API, but I have not confirmed this.)
Expected behavior
The invisibility of type=Standalone templates is said to be:

This is working as designed. The underlying principle of Portainer is to enforce best practice across all functions, including Swarm. When using swarm, you should always use Swarm services and not containers.

If that is the case, then to prevent (apparent) data loss either:

An option which will permanently hide a template should not be presented, or
Some kind of warning and confirmation sequence should be enforced.

Steps to reproduce the issue:

Run Portainer on a Docker swarm
Create a swarm-mode custom template
Edit the template and flip it to "Standalone"
Observe that the template has disappeared and no longer appears anywhere in the UI
(Attempt to) Create a new template with the same name and observe that this is not permitted.

Technical details:

Portainer version: 2.0.1
Docker version (managed by Portainer): mix of 18.06.3 and 20.10.2
Kubernetes version (managed by Portainer): n/a
Platform (windows/linux): Linux
Command used to start Portainer (docker run -p 9000:9000 portainer/portainer): docker stack deploy --compose-file portainer-agent-stack.yml portainer
Browser: Safari

Required changes
Custom template list view
Instead of filtering the templates based on the current managed endpoint type (standalone/Swarm), we should display all the templates but prevent the deployment of the template.

If the template is a standalone template and the managed endpoint is a Swarm endpoint, disable the Deploy the stack button and add a warning message underneath stating "This template type cannot be deployed on this endpoint.".

Required changes
Custom template list view
Instead of filtering the templates based on the current managed endpoint type (standalone/Swarm), we should display all the templates but prevent the deployment of the template.

If the template is a standalone template and the managed endpoint is a Swarm endpoint, disable the Deploy the stack button and add a warning message underneath stating "This template type cannot be deployed on this endpoint.".

Ticket update by Amet Doohan<EMAIL_ADDRESS>bug confirmed by @deviantony

Ticket update by Amet Doohan<EMAIL_ADDRESS>bug confirmed by @deviantony

@deviantony what about just moving the templates out of the endpoint scope?

@deviantony what about just moving the templates out of the endpoint scope?