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Need better standards for plugins and loaders. Documentation needs drastic improvement

I don't know if this post belongs here but I would appreciate if you don't close this issue right away to see if others share in my frustration. I am a true newbie and there is a lack of good documentation or standards for the webpack ecosystem. To make matters worse, the proliferation of plugins and loaders without standards is causing confusion.
Please consider recommending certain style guidelines before sponsoring or supporting plugins or loaders.
Few examples:

Unnecessary plugins creates saturation in webpack development. If a new plugin is created, it should be peer reviewed and determined if it belongs in the webpack ecosystem before recommending it to users: e.g. The need for clean-webpack-plugin vs. rimraf which already exists.

Poorly named plugins. I can't think of a good reason why extract-text-webpack-plugin should be named as such since it boils down as the defacto CSS bundler and should be named as such.

Precedence of operations in the webpack build process is not clear. Its not even mentioned in the docs. For example, it was surprising to learn that style-loader must load after css-loader.

https://medium.com/a-beginners-guide-for-webpack-2/webpack-loaders-css-and-sass-2cc0079b5b3a
Thanks for listening and I hope this helps someone else.

First of all, please do not delete the issue template. I'm okay having this conversation here but this is not the place to discuss about the documentation or the ecosystem. It would have been better suited on webpack/webpack.js.org repository.

That's something we don't have control on. If someone creates a new plugin or a new loader, we can't stop them from doing it. This person probably has a good reason doing so. clean-webpack-plugin has a legitimate use for example. If you run a build in watch mode (not talking about the dev server) you may need to remove the assets between each rebuild. That's not possible using rimraf.

Regarding Poorly named plugins, webpack can't do anything about it. If you want to publish a plugin named pizza-cat-css-webpack-plugin, I cannot prevent you from publishing it on NPM or telling you that someone already created a plugin called cat-pizza-css-webpack-plugin. The ecosystem is too vast to be monitored. Each plugin/loader author should do some legwork before creating something new.
extract-text-webpack-plugin is advertised as a way to extract CSS from your bundle. However if look closing at the source code, you'll find there is no reference to CSS in the src/ folder. The reason is simple: this plugin is not dedicated to CSS processing! CSS is only the most obvious use-case. One could use it to extract all JSON files from a bundle. Hence the naming.

The order is the one enforced by composition in FP. [style, css, less] should be interpreted as style(css(less(source))). That's something mentioned in the documentation in the Rule.use section.

I admit that our discussion is far from perfect but we do our best to improve it. We have a dedicated repository for it and I encourage you to expose your concerns there and to submit pull requests to add what you think is missing!

That is how the ecosystem works, this is not a close webpack ecosystem, it is completely open, anybody can and will create plugins for their needs. Users should test and judge thoughtfully which libraries or plugins install in their applications.

extract-text-webpack-plugin readme clearly states:

Extract text from a bundle, or bundles, into a separate file.

CSS extraction is just an example of all endless possibilities. We could add different examples, like extracting JSON files.

Those loaders readme says:
css-loader

The css-loader interprets @import and url() like import/require() and will resolve them.

It is also necessary to make webpack understand CSS files, it doesn't by default, yet (https://github.com/webpack/webpack/pull/6448).
style-loader

Adds CSS to the DOM by injecting a

Thanks, I can leave same feedback for webpack/webpack.js.org repository. We can close this here.


⚠ Jenkins Plugins Artifactory has degraded performance

In 623539f, Jenkins Plugins Artifactory (https://get.jenkins.io/plugins/artifactory/) experienced degraded performance:

HTTP code: 200
Response time: 1220 ms

Resolved: Jenkins Plugins Artifactory performance has improved in 89dcc24 after 25 minutes.


[RFC] Added MessageBox

Describe the changes you have made to improve this project
Added a MessageBox.
Additional context
This is not base on MetroWindow but original Window.
Closed Issues
Issue #3476.

I think the question was not about how to have a MessageBox without a MetroWindow. He wants to use a MessageBox without a MetroWindow as Dialog host, which is currently not possible and needs a complex change to get this working.
It's possible to get an external message box without the need of a MetroWindow host.

Sorry for my poor English. I don't understand what you said.
What I added is exactly an external message box.


How can I use near or not_geocoded condition?

I want use OR condition to optional geocodification.

Hi @dtelaroli I'm not sure I understand what you're asking. Could you clarify?

I have some not geocoded items in my database.
I want find items using coordinates or items not geocoded.
Something like this:
Venue.near_or_not_geocoded([40.71, -100.23], 20)

For now, i'm using two queries to find, because the API does not have that option.
Venue.near([40.71, -100.23], 20) + Venue.not_geocoded

Sorry for my bad english.

As of Rails 5 you can do this:
Venue.near([40.71, -100.23], 20).or(Venue.not_geocoded)

Thanks
Em 28 de jun de 2017 19:03, "Alex Reisner"<EMAIL_ADDRESS>escreveu:

As of Rails 5 you can do this:
Venue.near([40.71, -100.23], 20).or(Venue.not_geocoded)
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
https://github.com/alexreisner/geocoder/issues/1137#issuecomment-311805395,
or mute the thread
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Ignore non-chinese characters

Describe the bug
Maobi does not work when the source field contains characters that are not within its database. For instance, various punctuation characters.
To Reproduce
Create a card with "." in it.
Expected behavior
Ignore the unsupported characters.

Thanks for this. I can practice writing a sentence, at least on the front side, after copying that function less its name change from that branch.

Glad to hear that! I think I’ve had a couple of changes that we did not immediately merge back to master as testing was missing @jcklie ? I think it is stable.

I merged it (I forgot about it because there was no PR) and will release it soonish

Solved with 0.5.2


added redirects

Pre-Flight checklist

[x] Testing

[x] Code is tested
[x] Changes have been manually tested

What are the relevant tickets?
Closes https://github.com/mitodl/ol-infrastructure/issues/922
What's this PR do?
Adds redirect
How should this be manually tested?

Click the latest netlify preview
Navigate to /fairuse
Verify it redirects

Working as intended. Thank you and approved!

fixed via https://github.com/mitodl/ol-infrastructure/pull/926


Image field should be in a loading state while upload is in-progress

https://github.com/tinacms/tinacms/pull/1221 created a loading state for the sidebar image field that displays while the previewSrc is loading.
We should also show this loading state while an upload is in progress.
Or, perhaps, an in-progress upload should trigger the form loading state (https://github.com/tinacms/tinacms/pull/1222)
Even better, we should just build the media manager and not have to deal with these problems

we built the media manager


NCCL + XLA fails for multi-GPU training.

Issue type
Bug
Have you reproduced the bug with TensorFlow Nightly?
Yes
Source
binary
TensorFlow version
tf 2.15
Custom code
Yes
OS platform and distribution
Linux Ubuntu 22.04
Mobile device
No response
Python version
3.11
Bazel version
No response
GCC/compiler version
No response
CUDA/cuDNN version
12.2/8.9.4
GPU model and memory
A100 40GB (20GB MiG)
Current behavior?
I am trying to run multi-GPU training with an XLA compiled model (simple CNN with a classification head). Without XLA, everything runs fine. With XLA enabled, I get one of two errors in the log, depending on whether I am using 4 GPUs or 2 GPUs. The GPUs are split into 2 MiGs.
I also tried on previous TF/CUDA versions and I get the same result.
Standalone code to reproduce the issue
import argparse
import json
import os
from typing import Any

import numpy as np
import tensorflow as tf

def get_replica_hostnames():
    ...

def get_replica_id():
    ...

def set_multiworker_env_config():
    hostnames = get_replica_hostnames()
    replica_index = get_replica_id()

    os.environ["TF_CONFIG"] = json.dumps(
        {
            "cluster": {
                "worker": hostnames,
            },
            "task": {"type": "worker", "index": replica_index},
        }
    )

class Model(tf.keras.models.Model):
    def __init__(self, *args: Any, **kwargs: Any) -> None:
        super().__init__(*args, **kwargs)

        self._embedder = tf.keras.Sequential(
            [
                tf.keras.layers.Conv2D(
                    filters=8,
                    kernel_size=3,
                    padding="same",
                    activation=tf.keras.activations.relu,
                    use_bias=False,
                ),
                tf.keras.layers.BatchNormalization(),
                tf.keras.layers.Conv2D(
                    filters=8,
                    kernel_size=3,
                    padding="same",
                    activation=tf.keras.activations.relu,
                    use_bias=False,
                ),
                tf.keras.layers.BatchNormalization(),
                tf.keras.layers.MaxPool2D(),
                tf.keras.layers.GlobalAveragePooling2D(),
            ]
        )

        self._classifier = tf.keras.layers.Dense(550)

    def call(self, x: tf.Tensor) -> tf.Tensor:
        x = self._embedder(x)
        x = self._classifier(x)
        x = tf.keras.layers.Activation("linear", dtype="float32")(x)
        return x

def create_dummy_dataset(batch_size: int) -> tf.data.Dataset:
    X = np.random.rand(batch_size, 384, 640, 1)
    y = np.random.randint(550, size=batch_size)
    return tf.data.Dataset.from_tensor_slices((X, y)).batch(batch_size, True).repeat()

def train():
    set_multiworker_env_config()
    strategy = tf.distribute.MultiWorkerMirroredStrategy()
    num_replicas = strategy.num_replicas_in_sync

    batch_size = 16 * num_replicas
    dataset = create_dummy_dataset(batch_size)
    dataset = strategy.experimental_distribute_dataset(dataset)

    with strategy.scope():
        model = Model()
        model.compile(
            loss=tf.keras.losses.SparseCategoricalCrossentropy(
                from_logits=True,
            ),
            optimizer=tf.keras.optimizers.Adam(
                learning_rate=1e-3,
                weight_decay=1e-5,
            ),
            metrics=[
                "accuracy",
            ],
            jit_compile=True,
        )

    model.fit(
        dataset,
        epochs=10,
        steps_per_epoch=100,
    )

if __name__ == "__main__":
    train()

Relevant log output
Log output for 4 GPUs:

2024-01-08 12:48:24.103746: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
2024-01-08 12:48:24.103807: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
2024-01-08 12:48:24.104896: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
2024-01-08 12:48:24.111875: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
2024-01-08 12:48:24.978525: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
2024-01-08 12:48:27.492019: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1929] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 18370 MB memory:  -> device: 0, name: NVIDIA A100-SXM4-40GB MIG 3g.20gb, pci bus id: 0000:01:00.0, compute capability: 8.0
2024-01-08 12:48:27.503592: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1929] Created device /job:worker/replica:0/task:0/device:GPU:0 with 18370 MB memory:  -> device: 0, name: NVIDIA A100-SXM4-40GB MIG 3g.20gb, pci bus id: 0000:01:00.0, compute capability: 8.0
2024-01-08 12:48:27.528772: I tensorflow/core/distributed_runtime/rpc/grpc_server_lib.cc:457] Started server with target: grpc://gen-svc-4e03d749-0565-47d7-b7ff-63437f0ab5b3:80
2024-01-08 12:48:27.535501: I external/local_tsl/tsl/distributed_runtime/coordination/coordination_service.cc:553] /job:worker/replica:0/task:0 has connected to coordination service. Incarnation:<PHONE_NUMBER>207696637
2024-01-08 12:48:27.535846: I external/local_tsl/tsl/distributed_runtime/coordination/coordination_service_agent.cc:304] Coordination agent has successfully connected.
2024-01-08 12:48:28.425710: I external/local_tsl/tsl/distributed_runtime/coordination/coordination_service.cc:553] /job:worker/replica:0/task:1 has connected to coordination service. Incarnation:<PHONE_NUMBER>4892823189
2024-01-08 12:48:29.509519: I external/local_tsl/tsl/distributed_runtime/coordination/coordination_service.cc:553] /job:worker/replica:0/task:2 has connected to coordination service. Incarnation:<PHONE_NUMBER>7490357420
2024-01-08 12:48:29.766944: I external/local_tsl/tsl/distributed_runtime/coordination/coordination_service.cc:553] /job:worker/replica:0/task:3 has connected to coordination service. Incarnation:<PHONE_NUMBER>178506894
WARNING:absl:You use TensorFlow DType <dtype: 'string'> in tfds.features This will soon be deprecated in favor of NumPy DTypes. In the meantime it was converted to object.
WARNING:absl:You use TensorFlow DType <dtype: 'int64'> in tfds.features This will soon be deprecated in favor of NumPy DTypes. In the meantime it was converted to int64.
ml-wf-receipt-ext-logo-classifier-pipelinenxxxs-train-template:37:563 [0] NCCL INFO Bootstrap : Using eth0:<IP_ADDRESS><0>
ml-wf-receipt-ext-logo-classifier-pipelinenxxxs-train-template:37:563 [0] NCCL INFO NET/Plugin : No plugin found (libnccl-net.so), using internal implementation
2024-01-08 12:48:32.756935: I external/local_tsl/tsl/profiler/lib/profiler_session.cc:104] Profiler session initializing.
2024-01-08 12:48:32.756993: I external/local_tsl/tsl/profiler/lib/profiler_session.cc:119] Profiler session started.
2024-01-08 12:48:32.757173: I external/local_xla/xla/backends/profiler/gpu/cupti_tracer.cc:1883] Profiler found 1 GPUs
2024-01-08 12:48:32.790801: I external/local_tsl/tsl/profiler/lib/profiler_session.cc:131] Profiler session tear down.
2024-01-08 12:48:32.790934: I external/local_xla/xla/backends/profiler/gpu/cupti_tracer.cc:2017] CUPTI activity buffer flushed
Epoch 1/10
2024-01-08 12:48:37.520453: I external/local_xla/xla/service/service.cc:168] XLA service 0x7fe284006a40 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:
2024-01-08 12:48:37.520583: I external/local_xla/xla/service/service.cc:176]   StreamExecutor device (0): NVIDIA A100-SXM4-40GB MIG 3g.20gb, Compute Capability 8.0
2024-01-08 12:48:37.680983: I tensorflow/compiler/mlir/tensorflow/utils/dump_mlir_util.cc:269] disabling MLIR crash reproducer, set env var `MLIR_CRASH_REPRODUCER_DIRECTORY` to enable.
2024-01-08 12:48:38.693930: I external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:454] Loaded cuDNN version 8904
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
I0000 00:00:1704718137.764316     430 device_compiler.h:186] Compiled cluster using XLA!  This line is logged at most once for the lifetime of the process.
ml-wf-receipt-ext-logo-classifier-pipelinenxxxs-train-template:37:1288 [0] NCCL INFO cudaDriverVersion 12020
NCCL version 2.16.5+cudaCUDA_MAJOR.CUDA_MINOR
ml-wf-receipt-ext-logo-classifier-pipelinenxxxs-train-template:37:1288 [0] NCCL INFO Failed to open libibverbs.so[.1]
ml-wf-receipt-ext-logo-classifier-pipelinenxxxs-train-template:37:1288 [0] NCCL INFO NET/Socket : Using [0]eth0:<IP_ADDRESS><0>
ml-wf-receipt-ext-logo-classifier-pipelinenxxxs-train-template:37:1288 [0] NCCL INFO Using network Socket

ml-wf-receipt-ext-logo-classifier-pipelinenxxxs-train-template:37:1288 [0] external/nccl_archive/src/init.cc:642 NCCL WARN Duplicate GPU detected : rank 0 and rank 2 both on CUDA device 1000
ml-wf-receipt-ext-logo-classifier-pipelinenxxxs-train-template:37:1288 [0] NCCL INFO external/nccl_archive/src/init.cc:1100 -> 5
ml-wf-receipt-ext-logo-classifier-pipelinenxxxs-train-template:37:1288 [0] NCCL INFO external/nccl_archive/src/init.cc:1173 -> 5
ml-wf-receipt-ext-logo-classifier-pipelinenxxxs-train-template:37:1288 [0] NCCL INFO external/nccl_archive/src/init.cc:1209 -> 5
2024-01-08 12:48:58.577448: W external/local_xla/xla/service/gpu/runtime/support.cc:58] Intercepted XLA runtime error:
INTERNAL: external/local_xla/xla/service/gpu/nccl_utils.cc:297: NCCL operation ncclCommInitRank(&comm, nranks, id, rank) failed: invalid usage
2024-01-08 12:48:58.577775: I tensorflow/core/framework/local_rendezvous.cc:421] Local rendezvous recv item cancelled. Key hash:<PHONE_NUMBER>5935290807
2024-01-08 12:48:58.577798: I tensorflow/core/framework/local_rendezvous.cc:421] Local rendezvous recv item cancelled. Key hash:<PHONE_NUMBER>502530449
2024-01-08 12:48:58.577844: I tensorflow/core/framework/local_rendezvous.cc:421] Local rendezvous recv item cancelled. Key hash:<PHONE_NUMBER>3729140565
Traceback (most recent call last):
  File "/kirax_source/train.py", line 346, in <module>
    train_tf(args=args, jit_compile=XLA)
  File "/kirax_source/train.py", line 246, in train_tf
    model.fit(
  File "/usr/local/lib/python3.11/dist-packages/keras/src/utils/traceback_utils.py", line 70, in error_handler
    raise e.with_traceback(filtered_tb) from None
  File "/usr/local/lib/python3.11/dist-packages/tensorflow/python/eager/execute.py", line 53, in quick_execute
    tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
tensorflow.python.framework.errors_impl.InternalError: Graph execution error:

Detected at node StatefulPartitionedCall defined at (most recent call last):
  File "/usr/lib/python3.11/threading.py", line 1002, in _bootstrap

  File "/usr/lib/python3.11/threading.py", line 1045, in _bootstrap_inner

Detected at node StatefulPartitionedCall defined at (most recent call last):
  File "/usr/lib/python3.11/threading.py", line 1002, in _bootstrap

  File "/usr/lib/python3.11/threading.py", line 1045, in _bootstrap_inner

2 root error(s) found.
  (0) INTERNAL:  Failed to execute XLA Runtime executable: run time error: custom call 'xla.gpu.all_reduce' failed: external/local_xla/xla/service/gpu/nccl_utils.cc:297: NCCL operation ncclCommInitRank(&comm, nranks, id, rank) failed: invalid usage; current tracing scope: all-reduce-start.4; current profiling annotation: XlaModule:#hlo_module=a_inference_run_step_7562__.4006,program_id=447#.
         [[{{node StatefulPartitionedCall}}]]
         [[Reshape_3/_22]]
  (1) INTERNAL:  Failed to execute XLA Runtime executable: run time error: custom call 'xla.gpu.all_reduce' failed: external/local_xla/xla/service/gpu/nccl_utils.cc:297: NCCL operation ncclCommInitRank(&comm, nranks, id, rank) failed: invalid usage; current tracing scope: all-reduce-start.4; current profiling annotation: XlaModule:#hlo_module=a_inference_run_step_7562__.4006,program_id=447#.
         [[{{node StatefulPartitionedCall}}]]
0 successful operations.
0 derived errors ignored. [Op:__inference_train_function_7900]

Log output for 2 GPUs:

2024-01-08 13:32:56.555585: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
2024-01-08 13:32:56.555666: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
2024-01-08 13:32:56.557055: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
2024-01-08 13:32:56.563733: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
2024-01-08 13:32:57.475551: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
2024-01-08 13:32:59.868467: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1929] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 18370 MB memory:  -> device: 0, name: NVIDIA A100-SXM4-40GB MIG 3g.20gb, pci bus id: 0000:41:00.0, compute capability: 8.0
2024-01-08 13:32:59.880625: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1929] Created device /job:worker/replica:0/task:0/device:GPU:0 with 18370 MB memory:  -> device: 0, name: NVIDIA A100-SXM4-40GB MIG 3g.20gb, pci bus id: 0000:41:00.0, compute capability: 8.0
2024-01-08 13:32:59.903354: I tensorflow/core/distributed_runtime/rpc/grpc_server_lib.cc:457] Started server with target: grpc://gen-svc-d871b43e-6f9e-4d8f-9faf-d98a734319f3:80
2024-01-08 13:32:59.912608: I external/local_tsl/tsl/distributed_runtime/coordination/coordination_service.cc:553] /job:worker/replica:0/task:0 has connected to coordination service. Incarnation:<PHONE_NUMBER>4147221766
2024-01-08 13:32:59.913045: I external/local_tsl/tsl/distributed_runtime/coordination/coordination_service_agent.cc:304] Coordination agent has successfully connected.
2024-01-08 13:33:00.820050: I external/local_tsl/tsl/distributed_runtime/coordination/coordination_service.cc:553] /job:worker/replica:0/task:1 has connected to coordination service. Incarnation:<PHONE_NUMBER>757352804
WARNING:absl:You use TensorFlow DType <dtype: 'string'> in tfds.features This will soon be deprecated in favor of NumPy DTypes. In the meantime it was converted to object.
WARNING:absl:You use TensorFlow DType <dtype: 'int64'> in tfds.features This will soon be deprecated in favor of NumPy DTypes. In the meantime it was converted to int64.
ml-wf-receipt-ext-logo-classifier-pipelinegl897-train-template:31:784 [0] NCCL INFO Bootstrap : Using eth0:<IP_ADDRESS><0>
ml-wf-receipt-ext-logo-classifier-pipelinegl897-train-template:31:784 [0] NCCL INFO NET/Plugin : No plugin found (libnccl-net.so), using internal implementation
2024-01-08 13:33:03.552619: I external/local_tsl/tsl/profiler/lib/profiler_session.cc:104] Profiler session initializing.
2024-01-08 13:33:03.552667: I external/local_tsl/tsl/profiler/lib/profiler_session.cc:119] Profiler session started.
2024-01-08 13:33:03.552814: I external/local_xla/xla/backends/profiler/gpu/cupti_tracer.cc:1883] Profiler found 1 GPUs
2024-01-08 13:33:03.587433: I external/local_tsl/tsl/profiler/lib/profiler_session.cc:131] Profiler session tear down.
2024-01-08 13:33:03.587611: I external/local_xla/xla/backends/profiler/gpu/cupti_tracer.cc:2017] CUPTI activity buffer flushed
Epoch 1/10
2024-01-08 13:33:08.149597: I external/local_xla/xla/service/service.cc:168] XLA service 0x7ff338008540 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:
2024-01-08 13:33:08.149730: I external/local_xla/xla/service/service.cc:176]   StreamExecutor device (0): NVIDIA A100-SXM4-40GB MIG 3g.20gb, Compute Capability 8.0
2024-01-08 13:33:08.732338: I tensorflow/compiler/mlir/tensorflow/utils/dump_mlir_util.cc:269] disabling MLIR crash reproducer, set env var `MLIR_CRASH_REPRODUCER_DIRECTORY` to enable.
2024-01-08 13:33:09.871101: I external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:454] Loaded cuDNN version 8904
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
I0000 00:00:1704720809.106117     425 device_compiler.h:186] Compiled cluster using XLA!  This line is logged at most once for the lifetime of the process.
ml-wf-receipt-ext-logo-classifier-pipelinegl897-train-template:31:1280 [0] NCCL INFO cudaDriverVersion 12020
NCCL version 2.16.5+cudaCUDA_MAJOR.CUDA_MINOR
ml-wf-receipt-ext-logo-classifier-pipelinegl897-train-template:31:1280 [0] NCCL INFO Failed to open libibverbs.so[.1]
ml-wf-receipt-ext-logo-classifier-pipelinegl897-train-template:31:1280 [0] NCCL INFO NET/Socket : Using [0]eth0:<IP_ADDRESS><0>
ml-wf-receipt-ext-logo-classifier-pipelinegl897-train-template:31:1280 [0] NCCL INFO Using network Socket

ml-wf-receipt-ext-logo-classifier-pipelinegl897-train-template:31:1280 [0] external/nccl_archive/src/misc/nvmlwrap.cc:183 NCCL WARN nvmlDeviceGetHandleByPciBusId() failed: Not Found
ml-wf-receipt-ext-logo-classifier-pipelinegl897-train-template:31:1280 [0] NCCL INFO Setting affinity for GPU 0 to ffffffff,00000000,ffffffff
ml-wf-receipt-ext-logo-classifier-pipelinegl897-train-template:31:1280 [0] NCCL INFO Channel 00/02 :    0   1
ml-wf-receipt-ext-logo-classifier-pipelinegl897-train-template:31:1280 [0] NCCL INFO Channel 01/02 :    0   1
ml-wf-receipt-ext-logo-classifier-pipelinegl897-train-template:31:1280 [0] NCCL INFO Trees [0] 1/-1/-1->0->-1 [1] -1/-1/-1->0->1
ml-wf-receipt-ext-logo-classifier-pipelinegl897-train-template:31:1280 [0] NCCL INFO P2P Chunksize set to 131072
ml-wf-receipt-ext-logo-classifier-pipelinegl897-train-template:31:1284 [0] NCCL INFO NCCL_SOCKET_NTHREADS set by environment to 8.
ml-wf-receipt-ext-logo-classifier-pipelinegl897-train-template:31:1284 [0] NCCL INFO NET/Socket: Using 8 threads and 1 sockets per thread
ml-wf-receipt-ext-logo-classifier-pipelinegl897-train-template:31:1280 [0] NCCL INFO Channel 00/0 : 1[1000] -> 0[41000] [receive] via NET/Socket/0
ml-wf-receipt-ext-logo-classifier-pipelinegl897-train-template:31:1284 [0] NCCL INFO NET/Socket: Using 8 threads and 1 sockets per thread
ml-wf-receipt-ext-logo-classifier-pipelinegl897-train-template:31:1280 [0] NCCL INFO Channel 01/0 : 1[1000] -> 0[41000] [receive] via NET/Socket/0
ml-wf-receipt-ext-logo-classifier-pipelinegl897-train-template:31:1280 [0] NCCL INFO Channel 00/0 : 0[41000] -> 1[1000] [send] via NET/Socket/0
ml-wf-receipt-ext-logo-classifier-pipelinegl897-train-template:31:1280 [0] NCCL INFO Channel 01/0 : 0[41000] -> 1[1000] [send] via NET/Socket/0
ml-wf-receipt-ext-logo-classifier-pipelinegl897-train-template:31:1280 [0] NCCL INFO Connected all rings
ml-wf-receipt-ext-logo-classifier-pipelinegl897-train-template:31:1280 [0] NCCL INFO Connected all trees
ml-wf-receipt-ext-logo-classifier-pipelinegl897-train-template:31:1280 [0] NCCL INFO threadThresholds 8/8/64 | 16/8/64 | 512 | 512
ml-wf-receipt-ext-logo-classifier-pipelinegl897-train-template:31:1280 [0] NCCL INFO 2 coll channels, 2 p2p channels, 2 p2p channels per peer
ml-wf-receipt-ext-logo-classifier-pipelinegl897-train-template:31:1280 [0] NCCL INFO comm 0x7fe61cffcb20 rank 0 nranks 2 cudaDev 0 busId 41000 commId 0xe105507e5746b5a2 - Init COMPLETE
2024-01-08 13:33:29.780117: W external/local_xla/xla/service/gpu/runtime/support.cc:58] Intercepted XLA runtime error:
INTERNAL: There was an error before calling cuModuleGetFunction (101): cudaErrorInvalidDevice : invalid device ordinal
2024-01-08 13:33:29.780331: I tensorflow/core/framework/local_rendezvous.cc:421] Local rendezvous recv item cancelled. Key hash:<PHONE_NUMBER>3376429067
2024-01-08 13:33:29.780349: I tensorflow/core/framework/local_rendezvous.cc:421] Local rendezvous recv item cancelled. Key hash:<PHONE_NUMBER>7180422187
2024-01-08 13:33:29.780389: I tensorflow/core/framework/local_rendezvous.cc:421] Local rendezvous recv item cancelled. Key hash:<PHONE_NUMBER>829094043
Traceback (most recent call last):
  File "/kirax_source/train.py", line 346, in <module>
    train_tf(args=args, jit_compile=XLA)
  File "/kirax_source/train.py", line 246, in train_tf
    model.fit(
  File "/usr/local/lib/python3.11/dist-packages/keras/src/utils/traceback_utils.py", line 70, in error_handler
    raise e.with_traceback(filtered_tb) from None
  File "/usr/local/lib/python3.11/dist-packages/tensorflow/python/eager/execute.py", line 53, in quick_execute
    tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
tensorflow.python.framework.errors_impl.InternalError: Graph execution error:

Detected at node StatefulPartitionedCall defined at (most recent call last):
  File "/usr/lib/python3.11/threading.py", line 1002, in _bootstrap

  File "/usr/lib/python3.11/threading.py", line 1045, in _bootstrap_inner

Detected at node StatefulPartitionedCall defined at (most recent call last):
  File "/usr/lib/python3.11/threading.py", line 1002, in _bootstrap

  File "/usr/lib/python3.11/threading.py", line 1045, in _bootstrap_inner

2 root error(s) found.
  (0) INTERNAL:  Failed to execute XLA Runtime executable: run time error: custom call 'xla.gpu.func.launch' failed: There was an error before calling cuModuleGetFunction (101): cudaErrorInvalidDevice : invalid device ordinal; current tracing scope: fusion.274; current profiling annotation: XlaModule:#hlo_module=a_inference_run_step_7562__.4006,program_id=447#.
         [[{{node StatefulPartitionedCall}}]]
         [[CollectiveReduceV2_1/_17]]
  (1) INTERNAL:  Failed to execute XLA Runtime executable: run time error: custom call 'xla.gpu.func.launch' failed: There was an error before calling cuModuleGetFunction (101): cudaErrorInvalidDevice : invalid device ordinal; current tracing scope: fusion.274; current profiling annotation: XlaModule:#hlo_module=a_inference_run_step_7562__.4006,program_id=447#.
         [[{{node StatefulPartitionedCall}}]]
0 successful operations.
0 derived errors ignored. [Op:__inference_train_function_7900]

Hi @cyanic-selkie ,
Could you please provide complete code snippet required for replication of this problem. Thanks!

Sorry for the delay, @SuryanarayanaY, I updated my issue with the full code snippet.

Hi @cyanic-selkie ,
As you are using TF2.15 version with tf.keras,first you need to import tf-keras package using pip install tf-keras
and then set environment variable os.environ["TF_USE_LEGACY_KERAS"]="1".
Then you can import keras from tensorflow or simply use tf.keras.
Can you try this and comeback with outcome. Thanks!

@SuryanarayanaY I did as you said, there is no difference.

Hi @cyanic-selkie ,
Could you please provide minimal code snippet for testing? Thanks!

@SuryanarayanaY I already provided the minimum reproducible example in the initial post. Is there something else you need?

same bug 'xla.gpu.all_reduce' failed, i found that "tensorflow.keras.applications.inception_resnet_v2.InceptionResNetV2" was called before all_reduce, the problem occur, but if i use dense layer as replacement, it work well.... sb. help me plz

i guess the former batchnormalize layer called cause the later all_reduce crash as the code above


How to avoid this kind of isolation in controller?

After increasing the

Control objective: 1rad/s for 1s and -1 rad/s for 1s.

Only control with Kd: cannot deal with object torque

Control with PI (KP=4e2,KI=2e4): performant normal in the beginning but isolated later.

Smaller KI
Choose a smaller KI -> does not help :question:

KI*=0.3
KI*=0.1

Larger KP
Choose a larger KP (*=3.0)

Make both KI KP smaller
Choose a smaller KP(x=0.3) and a smaller KI (x=0.3):

Larger KD
Choosing a larger KD =0.3 :arrow_forward: does not help to reduce isolation.

:grey_question:

Why would isolation happen in the second step command?
Is this the fundamental limitation of the PID controller?

Final solution
This problem is caused by the high-frequency isolation caused by the spring-based rope. By changing the spring coefficient to a smaller value to make sure the control frequency is higher than the rope isolation frequency, the problem is resolved.
This comes at the cost of a softer rope.


sudo: semaphore : command not found

Hello how are you,
Today I try to install semaphore but I have a problem at the starting of installation.
Once I have installed semaphore by snap on my ubuntu, I must create a user, so I use the command:
sudo semaphore user add --admin
--login john
--name=John
<EMAIL_ADDRESS>--password=12345
return error: sudo: semaphore: command not found
if I use
semaphore user add --admin
--login john
--name=John
<EMAIL_ADDRESS>--password=12345
return error: Use sudo to execute semaphore commands.
I tried with multiple accounts, user, root it doesn't work. After doing multiple searches on the internet without success, I just asked the source directly. Has anyone encountered this problem before? Do you have a solution?
Thank you for reading and your future responses.
Pompelup

@ItN0wPompelup what Linux distrib do you use?

Ubuntu 22.04.4
Thank you for your answer

@ItN0wPompelup
It is on my Ubuntu server: https://asciinema.org/a/s6etRkZCN3MwiHmyTZnVc1ywD
Try to reinstall Semaphore.

OK thanks for the info @fiftin but I already tried to reinstall via snap. I will try to install it via a wget/apt otherwise I will try on another OS version.

You do not need sudo if you are running as root.  Having said that,  I tried the snap installation and was confused with Ansible's created environment. I decided to go back to my docker installation, which works fine now after creating my own version of dockerfile.

This does not help resolve the problem but by going through a manual installation I successfully installed it without any problem.

Hi all
I've tried today the installation of Semaphore on my RedHat Enterprise 9.3
I installed snap as in the officall instructions and then sudo snap install semaphore works like butter.
Semaphore is reachable on the machine with localhost:3000 but as soon as I like to create a new user I get the error:
sudo: semaphore: command not found
and without sudo:
Use sudo to execute semaphore commands.
Do someone have a clue what could be the problem?
I already tired to reinstall the whole thing with snap. Maybe someone have a solution otherwise I install semaphore manual...
Thanks

IMHO we should deprecate snap and just provide repos for the existing debs and rpms.

In the end I installed Semaphore also completely manual.
It works fine like this and I can decide by myself which Python Version is used.


How to use the calculator.py on the ToaruOS?

It's a very beginner question, but how do I call the calculator.py on the ToaruOS?
Thanks.

Issue reports are not for asking questions like this. Please ask questions on IRC.
sudo msk update; sudo msk install python-demos; source ~/.eshrc; calculator.py


Seems fine to switch to spago now

Spago made it easier to test the 0.14 changes. If this looks good I'll convert the others as well.

I personally am still not sold on Spago for libraries: https://github.com/purescript/purescript/issues/3942#issuecomment-741414900
If we are going to switch then I think we should ensure that the bower.json we have checked in matches the one Spago would generate for us, and that it is exercised in CI (i.e. you can install dependencies with it and run tests with it). If we don't do this, then we might struggle to publish the package to Pursuit.

Hmm, I see what you mean. I've been using the spago-generated bower.json in react-basic-hooks for a while and kind of assumed that was the "correct" approach (i.e. keep it working with the latest package set and emit a compatible bower.json for those users).

The generated bower.json seems like the easiest way to keep supporting bower while also frequently testing with the latest package set.

There isn't really a "correct" approach that everyone agrees on right now, unfortunately. Hopefully this will become clearer once the registry work is a bit further along. As I say though, I think checking in a generated bower.json is fine, but I think it would be better to either exercise it directly in CI (i.e. via bower install and then checking the library can be compiled with pulp), or at least to verify in CI that running the spago command to regenerate bower.json doesn't result in changes. Preferably both?

Makes sense, I'll add those


Split rpm in different packages

According to the architecture, there are several packages that should be created for the edge node, I think:

edge-node-monitoring (prometheus + node-exporter + cadvisor when available)
edge-node-logging (promtail or any alternative)
edge-node-db (postgresql + postgres_exporter)
edge-node-app (quarkus app) depending on edge-node-db

@drhelius, WDYT?

Looks good to me. But they should have their own git repo too.

Why? Is it not allowed to use several specs in the same repo?

With a single repo a change in any of them will trigger a build for all packages. Also all packages are tied to the same version.
With multiple repos they can evolve independently.


ci(github): version lerna nightlies

Coverage remained the same at 79.448% when pulling 53b83c9f385db3c1c9a6c7f3553193a98f415eba on nightlyversion into a81b37e185e1a255886143bac2a129d22f91befb on dev.


Dynamically update : latest magisk & busybox

Right now magisk.zip is pre-downloaded. For having latest version would be great to implement a way to dynamically update it by downloading it from official sources. Same applies for busybox.

Using a pre-downloaded or customized build of magisk.zip prevents the breakage support of x86 in Magisk Canary version. But I think it is good to have an option for people to sync upstream automatically. :)

Now we can execute ' patch.sh canary ' to use latest canary build :)
https://github.com/shakalaca/MagiskOnEmulator/commit/9fe167a6d8bc8483b032ecf802737d7c197bad9d

Awesome ! I will test as soon as I can.

It worked!
However:
FIRST thought:
It would be good to have the documentation updated so that it is clear for somebody new on how to update magisk after ramdisk was previously already patched:

It is mandatory for future magisk updates, to have a backup of the original ramdisk.img that will be used for patching with latest canary ( because only the original ramdisk can be patched . an already patched one fails to be patched again). ---- we could actually backup the ramdisk initially and reuse it in future patching (see below)
magisk manager apk can be updated from within the manager itself.

SECOND thought:
A mention about the git commit. I think the patch.sh doesn't need to be modified at all (no need for the "if [[ "$1" != "canary" ]]"), as magisk.zip is removed anyways in process.sh before downloading it from github. Also, patch.bat needs the canary parameter passed: adb -e shell "sh /data/local/tmp/process.sh /data/local/tmp $1"
How the patching scripts could look like:
patch.sh:
#!/bin/sh
adb wait-for-device
if [[ -s ramdisk.img.BACKUP ]]; then
#restore original ramdisk.img for patching
cp -f ramdisk.img.BACKUP ramdisk.img
else
#backup original ramdisk for future patching
cp ramdisk.img ramdisk.img.BACKUP
fi
adb -e push ramdisk.img /data/local/tmp/ramdisk.img.gz
adb -e push magisk_emu.zip /data/local/tmp/magisk.zip
adb -e push update-binary /data/local/tmp/
adb -e push process.sh /data/local/tmp/
adb -e shell "dos2unix /data/local/tmp/process.sh"
adb -e shell "sh /data/local/tmp/process.sh /data/local/tmp $1"
adb -e pull /data/local/tmp/ramdisk.img

patch.bat:
@echo off
adb wait-for-device
if exist ramdisk.img.BACKUP (
rem restore original ramdisk.img for patching
copy /b/v/y ramdisk.img.BACKUP ramdisk.img
) else (
rem backup original ramdisk for future patching
copy /b/v/y ramdisk.img ramdisk.img.BACKUP
)
adb -e push ramdisk.img /data/local/tmp/ramdisk.img.gz
adb -e push magisk_emu.zip /data/local/tmp/magisk.zip
adb -e push update-binary /data/local/tmp
adb -e push process.sh /data/local/tmp
adb -e shell "dos2unix /data/local/tmp/process.sh"
adb -e shell "sh /data/local/tmp/process.sh /data/local/tmp $1"
adb -e pull /data/local/tmp/ramdisk.img

It worked!
FIRST thought:
It would be good to have the documentation updated so that it is clear for somebody new on how to update magisk after ramdisk was previously already patched:

It is mandatory for future magisk updates, to have a backup of the original ramdisk.img that will be used for patching with latest canary ( because only the original ramdisk can be patched . an already patched one fails to be patched again).
magisk manager apk can be updated from within the manager itself.

SECOND thought:
A mention about the git commit. I think the patch.sh doesn't need to be modified at all (no need for the "if [[ "$1" != "canary" ]]"), as magisk.zip is removed anyways in process.sh before downloading it from github. Also, patch.bat needs the canary parameter passed: adb -e shell "sh /data/local/tmp/process.sh /data/local/tmp $1"

Really appreciate your feedback ! I'll see what I can do, in the mean time it would be great if you can issue a PR ;-)

#6 Here's the PR


GEODE-2578: Remove 64 KiB limit on query strings.

Remove artificial cap of 65535 for query string
length by using 32 bits for the length of query
strings in DataOutput::writeFullUTF().
Rename parameter to TcrMessage::writeStringPart()
whose name is misleading due to copy-and-paste.
Add three unit tests for query-related messages:

testConstructorEXECUTECQ_MSG_TYPE
testConstructorWithGinormousQueryEXECUTECQ_MSG_TYPE
testConstructorEXECUTECQ_WITH_IR_MSG_TYPE

@PivotalSarge looks like some unit tests are failing.

The unit tests failed on Linux but not other platforms. It turns out that DataOutput has some not-very-obvious (and apparently platform-specific) behavior around buffer management that results in the return values from getBufferLength() and getRemainingBufferLength() depending on the behavior of other unit tests that may precede them. Hence, the test of ginormous query strings was causing the return values of those methods to differ from what would be returned if that test was not run. So I reworked how the DataOutput cursor advancement unit tests work and created GEODE-2598 to understand and test how DataOutput's buffer management works.

@PivotalSarge can you rebase your branch off of develop. We backed out all those C++11 changes and now they are showing up in your pull.

Roger that. Expect a new PR forthwith...
Sarge

On 7 Mar, 2017, at 08:10, Jacob Barrett<EMAIL_ADDRESS>wrote:
@PivotalSarge https://github.com/PivotalSarge can you rebase your branch off of develop. We backed out all those C++11 changes and now they are showing up in your pull.
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub https://github.com/apache/geode-native/pull/44#issuecomment-284767886, or mute the thread https://github.com/notifications/unsubscribe-auth/ATlz4jShpxAMJQ6goU2ocGZqUWWhijVQks5rjYGPgaJpZM4MRo4O.


Missing questions in Google article!

Aforementioned article lacks the technical interview round questions. It needs to be comprehensive covering questions across all rounds. Anyone taking this issue must follow the contributing guidelines.

I would like to work on this, please assign me this part

I can do this kindly assign it to me sir.

I would like to add Google  technical interview round questions. Please assign me to this.

Hey @rishabh115  Can i work on this?

@khushibalyan220101 @aakashg34 @priyanka001tech @sakshi006 I have assigned the issues to you. Please try to add as much questions as possible across section following contributing guidelines. Happy Coding ✌

I would like to work on this.


typedoc/dartdoc/etc support

This has been mentioned a few times, and would be a nice feature.
It could be done in various ways:

using typedoc-markdown-plugin to generate .md files, and formatting them from here (would have to do this for each language, and probably quite prone to errors imo)

writing our own plugin for typedoc etc (this is what docusaurus do, but potentially a lot of effort)

write some kind of parser of various generated json files into a common format for docs.page (potentially also a lot of effort)

Began work on this here https://github.com/invertase/docs.page/tree/typedoc-cli
Remaining tasks for typedoc support:

error catching (missing config options etc) on dart_cli
make sure references works with preview mode
make sure references works with locales
generate a nicer references/index.mdx and also make sure it doesn’t overwrite existing file
add docs for everything


[meson] Remove duplicated bits from test/meson

Changes proposed in this PR:

Add conv2d_unittest.tar.gz to be unzipped for ninja testing
Add foreach loop to handle duplicated control flow

Self evaluation:

Build test: [X]Passed [ ]Failed [ ]Skipped
Run test: [X]Passed [ ]Failed [ ]Skipped

Signed-off-by: Jihoon Lee<EMAIL_ADDRESS>

:memo: TAOS-CI Version: 1.4.20191203. Thank you for submitting PR #159. Please a submit 1commit/1PR (one commit per one PR) policy to get comments quickly from reviewers. Your PR must pass all verificiation processes of cibot before starting a review process from reviewers. If you are new member to join this project, please read manuals in documentation folder and wiki page. In order to monitor a progress status of your PR in more detail, visit http://nnsuite.mooo.com/.


rm Dashboards /v1 doc

Purpose of this pull request
rm Dashboards /v1 doc
Select the type of change

[ ] Minor Changes - Typos, formatting, slight revisions
[x] Update Content - Revisions, updating sections
[ ] New Content - New features, sections, pages, tutorials
[ ] Site and Tools - .clabot, version updates, maintenance, dependencies, new packages for the site (Docusaurus, Gatsby, React, etc.)

Ticket (if applicable)
https://sumologic.atlassian.net/browse/DOCS-75

Looks good, @kimsauce. I made a small update to the CID file so that the PR would pass the build-and-deploy check (see commit "Fix to CID file").

Great catch! I completely missed that.


Register Firebase for ios

As a developer
I want the ios version of the app to be able to connect to Firebase
Requirements:

Ios support is added

Rejecting Firebase solution


ILVerify command line options to include/exclude certain methods

I've added two command line options to the ILVerify program to include/exclude certain methods for verification. The include/exclude patterns can be specified as regular expressions and multiple occurrences are possible.
Example:
ILVerify.exe --include=Console\..* --exclude=Console\.WriteLine --include=System\..*

@mmayr-at,
Thanks for having already signed the Contribution License Agreement. Your agreement has not been validated yet. We will now review your pull request.
Thanks,
.NET Foundation Pull Request Bot


Add api-mock image to test and develop against

Signed-off-by: Nico Schieder<EMAIL_ADDRESS>

/lgtm


not showing more than 19 profiles

Windows Terminal version
1.12.10983.0
Windows build number
10.0.22000.652
Other Software
no other software required
Steps to reproduce

create more than 19 (on my machine) profiles
open the dropdown menu for creating a new session with a new profile

Expected Behavior
The profile list should be scrollable. There is no way to create sessions from profiles later in the list except by assigning key combinations in the settings.
Actual Behavior
Only the first 19 profiles are shown and it is not possible to scroll down.

Huh, I'm not seeing this on a current dev build:

I really doubt it was fixed since 1.12.
Have you hit "Save" since adding all those other profiles/? That menu probably isn't going to update itself until the settings are actually saved.

Yeah, my fault. I really thought I hit save, especially since it showed some of the copied profiles.


Select Grant admin consent for..., then select Yes to provide admin consent for the selected permission. is wrong

The readme in app-auth is wrong. The option admin consent for ... does not exist. When running the example I got an error:
[root@mg-wopitest-tux graphapponlytutorial]# sh ./gradlew --console plain run
> Task :app:compileJava UP-TO-DATE
> Task :app:processResources UP-TO-DATE
> Task :app:classes UP-TO-DATE

> Task :app:run
Java App-Only Graph Tutorial

SLF4J: Failed to load class "org.slf4j.impl.StaticLoggerBinder".
SLF4J: Defaulting to no-operation (NOP) logger implementation
SLF4J: See http://www.slf4j.org/codes.html#StaticLoggerBinder for further details.
Please choose one of the following options:
0. Exit
1. Display access token
2. List users
3. Make a Graph call
2
Feb 16, 2023 10:43:04 AM com.microsoft.graph.logger.DefaultLogger logError
Error getting users
SEVERE: CoreHttpProvider[sendRequestInternal] - 408Graph service exception
Feb 16, 2023 10:43:04 AM com.microsoft.graph.logger.DefaultLogger logError
Error code: Authorization_RequestDenied
SEVERE: Throwable detail: com.microsoft.graph.http.GraphServiceException: Error code: Authorization_RequestDenied
Error message: Insufficient privileges to complete the operation.
Error message: Insufficient privileges to complete the operation.

GET https://graph.microsoft.com/v1.0/users?%24select=displayName%2Cid%2Cmail&%24top=25&%24orderby=displayName

SdkVersion : graph-java/v5.45.0

GET https://graph.microsoft.com/v1.0/users?%24select=displayName%2Cid%2Cmail&%24top=25&%24orderby=displayName

SdkVersion : graph-java/v5.45.0
403 : Forbidden

[...]

403 : Forbidden

[...]
[Some information was truncated for brevity, enable debug logging for more details]

Please choose one of the following options:
[Some information was truncated for brevity, enable debug logging for more details]
0. Exit
1. Display access token
2. List users
3. Make a Graph call
0
Goodbye...

BUILD SUCCESSFUL in 19s
3 actionable tasks: 1 executed, 2 up-to-date
[root@mg-wopitest-tux graphapponlytutorial]#

Either update your documentation  or fix the problem.

403 is expected if an admin has not granted consent. The README isn't wrong - there will be a button with to grant admin consent, provided you are logged in as a Global admin. If you are not a Global admin, the button should still be there, but disabled.

Thanks. I oversaw in the Readme, that I need a Global Administrator Role in my Azure Acount.

Thanks. I'm sorry about that. It is working, now.

BTW: My old Account has Global Administration. It must be another reason. With my new Microsoft 365 account it is working. So I don't care.


Fix Markdown formatting of code blocks & snippets

The code samples in the readme weren't rendering correctly in GitHub's readme viewer.

Thanks! Merging now


📄 fix docker-compose in readme

Thank you for contributing to Homarr! So that your Pull Request can be handled effectively, please populate the following fields (delete sections that are not applicable)
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Documentation
Overview

Remove invalid characters from the quick start docker-compose yml in Readme

@ajnart is there any special reason why those characters are there? Were they made by mistake?

@ajnart is there any special reason why those characters are there? Were they made by mistake?

No idea, i didn't push the docker compose 😅

That is a standard yaml start of document header
https://yaml.org/spec/1.1/#id897596

That is a standard yaml start of document header https://yaml.org/spec/1.1/#id897596

Interesting, I didn't know that. How does this correlate with docker-compose? Some users reported that they are unable to use compose with this document header.

It needs to be the first item in the file. In all honest Id just remove it from the example as it isnt needed and is just causing confusion.

It needs to be the first item in the file. In all honest Id just remove it from the example as it isnt needed and is just causing confusion.

So as long as the header would be on the first line, docker-compose would be able to parse it?


Bird Buddy stops running.

It looks like Bird Buddy integration has stopped running. Since October 20, it's entities are not updated anymore. If I restart HA the BB entities are updated once and I get the following message.
My first impression is that it is since I updated to HA 2023.10. But I am not really sure about that. My BB has been low on battery. But I did several restarts of HA since I recharged the BB battery.
Logger: birdbuddy
Source: custom_components/birdbuddy/sensor.py:201
Integration: Bird Buddy (documentation, issues)
First occurred: 13:00:09 (1 occurrences)
Last logged: 13:00:09
Unexpected Feed type: FeedItemCollectedPostcard

Thanks for the report.
It looks like they've updated the schema by adding a new feed item type, and the library is being strict about what it can interpret. That obviously isn't safe, so we should be able to allow unknown feed item types and just ignore them (or try to interpret them generically)

Could the ne feed item type have to do soemthing with the new subscription they offered? Part of that is a higher resolution video.

No, the new feed item is not subscription related.
It looks like the new feed item has an expiration time, and includes some metadata like whether it includes mystery visitors, new/unlocked species, and a list of species in the postcard.
The actual problem is that even though the new feed item's schema shows that it should contain a createdAt timestamp field, the feed items do not contain data for that field. So trying to convert it to a Python timestamp is failing.

So, the feed item does include the createdAt timestamp - but we weren't selecting it, because we didn't know that it should exist (the downsides of GraphQL).
Testing a fix now, which should not only resolve this issue, but also allow future added feed items to be handled gracefully instead of breaking.
The warning log you mentioned will still continue to be logged in these cases. But that was not what broke the coordinator. What actually broke it was this:
ERROR (MainThread) [custom_components.birdbuddy] Error fetching birdbuddy data: object of type 'NoneType' has no len()

and that's what I'm fixing now.

The change appears to be working for me. I'll merge it and get it released: jhansche/pybirdbuddy#20

Great! Thank you.

Oops. Maybe we should reopen this issue? The problem with the logbook message disappeared indeed. But the problem that the attributes are updated only once (at restart of HA) still persists.
I also found that a photo of 1 week ago now has been presented as a new one, with the time stamp of the moment I restart HA. The value of the wifi strength and the battery level have the same problem. Reason that I did not see that my BB’s battery level was too low.
I really think this has to do with the change toward the PRO subscription. I think that they did something with resolutions. A video I downloaded before they offered the PRO subscription had a 1080 video resolution. If I download a video now it has the 720 resolution. So they must have reduced the standard resolution and offered the previous standard resolution as a PRO option. As you may expect I have a meaning about that…
My impression is that they have been fooling around with the interface, which may explain the other problems I have now. Maybe they try to block your API?

No, it has nothing to do with subscription, or videos, at all.
After the v0.0.18 update, my integration is now receiving updates as expected, including battery and signal levels; and the automation to collect postcards is working properly now, on its own. I can confirm that the auto-collected postcard is also appearing in my BB app as a visitor, and a separate automation that I have that triggers on new_postcard and increments a helper counter was triggered and completed successfully.
If your battery level is too low now, maybe that is the problem? Try charging it first and see if the integration updates to show that it is charging.

I did already charge the battery. So that should not be the problem. Switching the Power Profile works fine in both directions. I will check the entities and the visitors next morning, as the BB is now in sleeping mode.
I'll let you know the outcome!

However I still have this problem. The last update of this entity was 42 minutes ago, which is exactly the moment I restarted HA. I still do not understand that.

So if the Power Profile test works, then that should show that the coordinator is updating on its own. If it's in sleeping mode, then it probably won't update, at least not as frequently. Looking back at historical graphs on my end, I see 2 things:

While the feeder is "Sleeping", the updates are happening less frequently. When it's "Ready", the updates happen more often.
The issue began Oct 19 at 8am (US EDT).

I had the problem of my entities not updating also at day time.

But my testing now after your update started when the device got into sleeping mode. I'll check how things are tomorrow morning. 😊

Yeah, let's leave it running for at least 70 minutes, and see if it updates wifi signal strength on its own. And check again tomorrow when it's no longer sleeping.
From what I can see right now on my own feeder (currently not sleeping as it is daytime), it is updating successfully now (but it was broken since Oct 19, before the fix).
If you're still seeing issues tomorrow during the day, search your logs for birdbuddy to see if any errors or warnings are appearing.

It is working correctly! Thanx a lot for your support!


Issue with tutorials/modis-ndvi-time-series-animation/index.md

There is an issue when printing the GIF URL to the console. I used the same code and example as the one provided on the website.
"Setting the CRS, geodesic, or evenOdd flag on a computed Geometry is not supported.  Use Geometry.transform()."

I can't reproduce the issue when running the unmodified demo.
Are you changing the region variable?
Could you could share the Code Editor script that produces the error?

Closing for now. Reopen if this is still an issue for you and please include a reproducible script.


fix: Add Installation struct to CheckSuitePayload and CheckRunPayload

This pull request fixes issue #129.

@juliojimenez hi! Do you want to merge it in v5? Or you want to merge it to the "latest" branch? It's master (and I hope it will be default branch soon).

@juliojimenez I'll merge it to the master and will release new 6-beta. I would prefer to don't release new v5 version if it's not bug fix.


[AWS] Update AWS Notebook Image to v1.2.0

Update AWS Notebook Image from tag from 1.1.0 to 1.2.0

👋 @Jeffwan (the 2nd approver in OWNERS) please /lgtm @PatrickXYS 's PR if it looks good 👍

/cc @jngo2
Can you take a look as well? Btw, @jngo2 will be part of kubeflow on AWS project in the future.

@8bitmp3 Hi since @Jeffwan is not working in AWS currently, can we move forward given I'm the only OWNER of AWS content?

@PatrickXYS Let me try
/lgtm
@Jeffwan can also LGTM, I think

/test all

Maybe we should update the OWNERS file @PatrickXYS and add 1-2 more approvers/reviewers cc @RFMVasconcelos

@8bitmp3  Yeah it sounds good, though I'm not sure how will be added as approvers/reviewers
In short term, AWS will have me as the only engineer on the whole Kubeflow project, other folks are working on Sagemaker part.


use same fix for upload as install metadata.json

metadata.json is a datafile, created by metadata.rb.
for whatever reason, the inclusion of one or the other is now a free choice.
This means that sometimes cookbooks may come with one and not the other.
Including the resulting DATA and not the CODE is now supported by prior changes when using the "knife cookbook site install"
However, that change was not incorporated globally and so we find that  "knife cookbook upload" continues to fail.
example failure:
+ echo 'Uploading consul to chef servers'
Uploading consul to chef servers
+ cd ..
+ which knife
/usr/bin/knife
+ knife -v
Chef: 12.1.2
+ knife cookbook upload consul -o .
Uploading consul         [0.6.0]
ERROR: Cookbook consul depends on cookbooks which are not currently
ERROR: being uploaded and cannot be found on the server.
ERROR: The missing cookbook(s) are: 'golang' version '~> 1.3.0'

The failure here is that the consul cookbook from supermarket does not come with metadata.rb, the code required to generate said metadata.json, and which is looked for by the "knife cookbook upload" command. A fix was put in place for "knife cookbook site install"
now, i can use knife cookbook metadata to generate a metadata.json, however there is no option for reverse engineering the metadata.rb from the data.
I've added the same logic to make upload work.
this supporting routine most likely belongs else where, however, for its true global reach.
I still question that it can be correct to exclude the CODE (metadata.rb) and include the DATA (metadata.json).
this feels broken to me with this PR being a hack on top of a bug to dress-up the bug.

problem is in dependencies themselves and not upload. it only appeared that way.
i'm still of the mind that DATA, the metadata.json, is not appropriate for supermarket to serve out and that the metadata.rb really needs to be there. - this would be a bug for another place.


Refactor WaterIF97_base and WaterIF97_fixedregion

Reported by fcasella on 12 Mar 2013 15:11 UTC
Modelica.Media.Water.WaterIF97_base and Modelica.Media.Water.WaterIF97_fixedregion have lots of code in common, so it's hard to spot the differences and maintain the code. They should probably be refactored, so that WaterIF97_fixedregion extends WaterIF97_base and just redeclares what is needed.

Migrated-From: https://trac.modelica.org/Modelica/ticket/1018

Comment by fcasella on 25 Mar 2013 10:06 UTC
While doing this, WaterIF97_fixedregion should probably be fixed, in order to make sure that a single region, specified by the package constant Region, is always assumed for all computations. In particular:

the setState_XXX() functions should not have an extra region input (which is not part of the PartialTwoPhaseMedium interface, BTW), but rather use the Region package constant
the setState_XXX() functions should determine the phase based on the known region, rather than by calling functions such as phase_ps(), which would cause a waste of time

Comment by beutlich on 29 Oct 2015 20:26 UTC
@fcasella and @hubertus: This is one of the two open high-priority tickets on MSL 3.2.2 milestone. Do you think you can manage the refactoring in due time for MSL 3.2.2 release which is expected by end of 2015? Thanks for your contributions.

Comment by hubertus on 29 Oct 2015 21:15 UTC
The honest answer for myself is no, I don't have the time. But I will check if someone else within Modelon can take a look at this. I'll get back, ....
Francesco?

Comment by fcasella on 29 Oct 2015 22:35 UTC
I can manage to find some time to do this, it's not a difficult task. Some help from Modelon would be appreciated, e.g. for testing and double-checking. Is that possible?

Comment by hubertus on 2 Nov 2015 12:02 UTC
That is possible for sure.

Comment by hubertus on 7 Dec 2015 14:05 UTC
Reminder, ...

Comment by fcasella on 19 Dec 2015 01:35 UTC
I have done a first analysis of the task. The package Modelica.Media.Water.WaterIF97_fixedregion as it is now also supports setting Region = 0, which means that the region is unknown and needs to be computed. Supporting this option makes the code quite involved.
In fact, Modelica.Media.Water.WaterIF97_fixedregion(Region = 0) is completely equivalent to Modelica.Media.Water.WaterIF97_base, so there I don't see the point of handling this case twice with duplicate code. The rationale for Modelica.Media.Water.WaterIF97_fixedregion is that it should be used as a plug-in replacement for Modelica.Media.Water.WaterIF97_base when the region is known, in order to save time spent in useless checks to determine the region. Therefore, the region has to be known a-priori, and the interface of all the functions of Modelica.Media.Water.WaterIF97_fixedregion should be the same as inModelica.Media.Water.WaterIF97_base
I would then propose to exclude the Region = 0 case. Although strictly speaking this is a non-backwards compatible change, it does not affect any of the derived packages in the MSL, which of course set a well-defined region, corresponding to a positive value of the package constant Region. I think it is highly unlikely that anyone has actually used the Modelica.Media.Water.WaterIF97_fixedregion base class directly and set Region = 0, as there is really no reason to do so, since one can just use Modelica.Media.Water.WaterIF97_base instead in that case. Of course we should mention this in the release notes, just in case someone did.
Hubertus, if you give me the green light, I can commit the code to a branch for a quick inspection by you or someone from Modelon, and have it ready on trunk before the feature freeze on Dec 23.
A further issue I raised in comment:1 is that I don't see the point of having an extra input Region for the setState_XX and density_ph, density_pT etc. functions, which is not defined in the PartialTwoPhaseMedium interface. The region considered should just be the one set by the Region package constant, and the interface of those functions should be the same as in the base case. I can keep the code as it is, and just add a default binding region = Region for those inputs to the package constants, but this seems to me a useless complication. BTW, as these functions are defined now, with region = 0 by default, the package is completely useless, because all the checks will be always performed in all those functions if one just plugs in a fixedregion medium in place of the base one, even if the package constant Region is set to a positive value.
If you agree, I would also remove this feature from the Modelica.Media.Water.WaterIF97_fixedregion, and set the region input of the low level function straight to the Region package constant.
I stand by for your feedback in order to proceed.

Comment by hubertus on 19 Dec 2015 03:59 UTC
Francesco, please go ahead. I agree with all your suggestions. I'll look through this after you have committed this.

Comment by fcasella on 23 Dec 2015 18:42 UTC
It is actually going to be a bit more complicated than I thought. My original plan was to extend the _fixedregion package from the _base one and redeclare only what was necessary. Unfortunately, in _fixedregion I cannot undeclare stuff (e.g., BaseProperties equations) which was declared in _base, and if I extend from the base classes in Media I end up in type hell.
So, the refactoring requires to first define a _common base class with all the shared stuff, and then have _base and _fixedregion both extend from that, adding specific code. Maybe I can rewrite _base to also act as _common with the default Region = 0 choice, I have to check that.
I'll attend to this asap. As this is considered as a bugfix and not a new feature, there is time until Jan 12 to review it.

Comment by fcasella on 4 Jan 2016 01:56 UTC
It turns out the solution is quite easy. The original _base package functions did not use the region input of all low-level functions, which then defaults to zero. If the package constant Region = 0 is added to the _base package, then the _fixedregion low level function implementations can be used also for the _base package, with the same semantics. As a consequence, the _fixedregion implementation can be substituted by the simple extend statement
partial package WaterIF97_fixedregion
  "Water: Steam properties as defined by IAPWS/IF97 standard, fixed region"
  extends WaterIF97_base(Region(min=1)=1);
end WaterIF97_fixedregion;

which simply bars using Region = 0.
This is immediately apparent by looking at the diff between 084176239fc9dc7728d50f105a1abd021daad020 and the previous revision, whereby a large chunk of code of the _base function is removed and replaced by the original implementations inside _fixedregion. It was also necessary to add one more case to the BaseProperties equations to handle the  phase variable in case of fixed region selection, i.e., Region > 0.
Two important fixes were also introduced.
The first is that the original _fixedregion package did not work as expected when used as a plug-in replacement for the WaterIF97_ph package, because the package constant Region was ignored, and it was expected that the extra input Region be set explicitly by the calling model. Of course this didn't work because the calling model is not changed at all if only the package is redeclared. This has now been fixed by having all the package functions use the package constant Region as a default region input.
The second fix concerns the phase field in the setState_dTX, phX, and psX functions. The _base functions contained the statment phase = 0;, while the _fixedregion functions had something like phase = if region == 0 then IF97_Utilities.phase_ph(p, h). Since these functions are meant to be inlined, the latter implementation eventually brings to an Integer equation with conditions based on Real variables outside a when clause, which cannot be handled. I have thus kept the phase = 0 implementation in the new _base package functions.
Some tests with ThermoPower in Dymola reveal that the new implementation of the _fixedregion for a liquid water heat exchanger brings to a speed-up of almost a factor 2, when WaterIF97_R1ph is used instead of WaterIF97_ph, while the previous implementation actually failed for the above-mentioned reason.
The examples in Modelica.Fluid using the water medium seem to work fine. It would be good to do some more testing with other libraries, botht with the standard water package and with the fixed region ones.

Comment by fcasella on 4 Jan 2016 01:57 UTC
Fixed in 084176239fc9dc7728d50f105a1abd021daad020

Modified by beutlich on 4 Jan 2016 13:24 UTC

Changelog modified by beutlich on 4 Jan 2016 13:24 UTC
Refactored WaterIF97_base and WaterIF97_fixedregion


Revert "Migrate GHA deployment workflows to ArgoCD triggering"

Reverts bcgov/traction#1225

Changes reverted as they turned out to not work fully as expected


Support non-rectangular boxes in Amber

https://github.com/openforcefield/openff-interchange/pull/707#pullrequestreview-1482373038

It looks like a couple are supported in some capacity
http://ambermd.org/FileFormats.php#parm.dat

IFBOX    : set to 1 if standard periodic box, 2 when truncated octahedral

There might also be a secret other type https://github.com/ParmEd/ParmEd/pull/844

Looks like box dimensions in the prmtop are ignored now:

%FLAG BOX_DIMENSIONS
%FORMAT(5E16.8)  OLDBETA, BOX(1), BOX(2), BOX(3)
  OLDBETA   : periodic box, angle between the XY and YZ planes in
              degrees. This is now redundant, as it is present in the
              inpcrd files. It is ignored here.
  BOX       : the periodic box lengths in the X, Y, and Z directions.
              This is now redundant, as it is present in the inpcrd files.
              It is ignored here.

Which makes sense, coz octahedral boxes are bigger/less efficient than dodecahedrons, and are also a kind of triclinic box iirc.


Add macro call in snippet

This change is

@orizi
Hi, I've added some macro call methods to the snippet in vscode-cairo to see if you can merge them. Thank you

@orizi
Thank you for your suggestion. In PR, some changes need to be made, and now, it has been adjusted according to the suggestions


Backports v0.18: PR's #14242, 15351, 14519 and 14982

Backports v0.18: PR's #14242, 15351, 14519 and 14982

should drop 14242 (it's empty) + see below (feels like quite a few earlier PRs are missing)

Okay, I will take-up earlier PR's that are mandatory to port this(will fix this later)

should drop 14242 (it's empty) + see below (feels like quite a few earlier PRs are missing)

added commit that was missing for 14242

Pls rebase on top of develop and add missing changes to test/sanitizer_suppressions/ubsan (14242), this file should exist now that we merged 14764 via #4341.

Pls rebase on top of develop and add missing changes to test/sanitizer_suppressions/ubsan (14242), this file should exist now that we merged 14764 via #4341.

above mentioned changes has been done


Allow message filter on lang

Also fix /messages/is/messages to /messages/id/content

Travis happy - Landing for https://github.com/praekelt/mama-ng-control/issues/6 @gsvr double-check later please

:+1:


Kube Provider

Description: move kube provider to the new directory, providers and add new service provider functions
Related PR: #3609, #3620
Associated Issue: #3456

Affected area:

Functional Area
x

New Functionality
[ ]

Documentation
[ ]

Install
[ ]

CLI Tool
[ ]

Certificate Management
[ ]

Control Plane
[ ]

Ingress
[ ]

Egress
[ ]

Networking
[ ]

Observability
[ ]

SMI Policy
[ ]

Sidecar Injection
[ ]

Security
[ ]

Upgrade
[ ]

Tests
[ ]

CI System
[ ]

Demo
[ ]

Performance
[ ]

Other
[x ]

Please answer the following questions with yes/no.

Does this change contain code from or inspired by another project?

Did you notify the maintainers and provide attribution?

No

Is this a breaking change?

No

Codecov Report

Merging #3614 (36748d9) into main (548facb) will decrease coverage by 0.29%.
The diff coverage is 0.00%.

@@            Coverage Diff             @@
##             main    #3614      +/-   ##
==========================================
- Coverage   67.31%   67.01%   -0.30%
==========================================
  Files         178      178
  Lines        8658     8696      +38
==========================================
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- Misses       2799     2837      +38
  Partials       31       31

Flag
Coverage Δ

unittests
67.01% <0.00%> (-0.30%)
:arrow_down:

Flags with carried forward coverage won't be shown. Click here to find out more.

Impacted Files
Coverage Δ

cmd/osm-controller/osm-controller.go
14.38% <0.00%> (ø)

pkg/catalog/fake.go
37.39% <ø> (ø)

pkg/providers/kube/client.go
56.52% <0.00%> (ø)

pkg/providers/kube/fake.go
0.00% <ø> (ø)

Continue to review full report at Codecov.

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Miguel Update rbac.md

PR created based on https://github.com/semaphoreci/semaphore/discussions/250

Thank you so much @mrosatii 🙏

Thanks @TomFern :)


fix: rewrite hero initialization logic for + 6.5x echo duplicate ult charge rate

:tada: This PR is included in version 1.2.0 :tada:
The release is available on GitHub release
Your semantic-release bot :package::rocket:


Fixed regex for different root

After https://github.com/RedMadRobot/gradle-infrastructure/pull/72 we can define gradle infrastructure anywhere, but detekt checks with type resolution have a regex that doesn't support this. This PR fixes this.

Can you add this change to Changelog, please?


Concurrency support for multiple processes (1 exclusive initializer / n readers)

Can the designers of leveldb explain the rational behind the design decision of
not supporting multiple processes in leveldb implementation?

The documentation clearly says, under Concurrency section that: "A database may
only be opened by one process at a time. The leveldb implementation acquires a
lock from the operating system to prevent misuse."

Currently I can see that when one process opens level db, it uses fcntl with RW
lock (exclusive lock). However this is a severely limiting, as no other process
can ever open the same database even if it wants to just inspect the database
contents for RDONLY purposes.

The use case for example is - one process exclusively opens leveldb database
and fills up the database, then closes it. Then n different processes start
reading that database.

Original issue reported on code.google.com by<EMAIL_ADDRESS>on 10 Jun 2013 at 8:03

Since starting to work on a project using LevelDB, I have already encountered
two cases where the lack of support for multiple concurrent readers has been a
problem:

(1) Building an MPI program that reads input from a LevelDB

(2) I had an existing program which it was undesirable to modify, reading a
LevelDB. I then wanted another utility to check intermediate results of the
first program while it was still running, but the analysis I wanted to perform
depended on the same LevelDB.

Original comment by<EMAIL_ADDRESS>on 3 Oct 2014 at 12:36

On most platforms, fcntl locks are advisory. Mandatory locks require specific
additional steps are taken (on Linux, you have to have enabled it for both the
file system *and* the file). So, if you want to read the file directly, you can
totally do that.

In the case of multiple read-only readers without altering the code base, you
*could* simply copy the file for each reader. Yes, it will be inefficient
(though not on file systems that dedupe data), but then again, so would having
multiple leveldb processes running as they wouldn't be able to share their
memory/buffer/etc.

So, this doesn't seem like a good feature for LevelDB to implement. If you
really feel you need it, you can always subclass the PosixEnv and provide your
own LockFile and UnlockFile methods whose logic suits your unique use case.

Out of curiosity... why not just use multiple threads instead of multiple
processes?

Original comment by<EMAIL_ADDRESS>on 4 Oct 2013 at 10:36

Best reason not do do multiple threads is that the communications protocol to
the primary program may not be as robust as the file-access protocol that
leveldb uses.   in cases where a primary program isn't responding quickly, it's
often more efficient to access the file directly, than to attempt to build in
some sort of back-channel.

Original comment by<EMAIL_ADDRESS>on 3 Sep 2014 at 1:21

Like in our case, where the key-value object is constructed once and remains
static, having something like a constant access object which opens the file
RDONLY and that does not alter the backend files, can be used concurrently in
threads without locking and concurrently across processes does indeed seem
appealing to me.

Original comment by<EMAIL_ADDRESS>on 19 Dec 2013 at 3:48


[BUG] add COLNUM=3 into config_GitFeGie_symlink.ini

missing keyword in config file, line 101;

Solved.


WIP: Add SPM support.

Update libraries and resolve errors from module/name changes introduced in their SPM versions, which are not always broken down the same way as their Cocoapods counterparts.  May not be able to keep the same version working with SPM and Cocoapods sub-dependencies.
Fix ambiguous references between returns with protocol and concrete generic result type responses in EosioRpcProvider.  May want to tune how this is done.  We could consider changing the naming of the functions as exposed by EosioRpcProviderProtocol but not sure what to change them to.

Nice work!

Thanks!  I'm assuming we'll probably not want to merge this type of thing to the develop branch yet, so probably leave it in its own branch for now?


[WIP] Bump ansible-lint to v4

This initial PR bumps ansible-lint to version 4. This change alone will break the build, but I will leave this open and add fixes for the new default rules piecemeal.

@JamieMagee Are you still working on fixing these?

Fixes #782

@sxa555 - I think I'd prefer to see the ansible scripts get fixed as part of this PR - thoughts?

@karianna Either this one, or another one that goes in first.
@Willsparker can you take a look at ansible-lint v4 and see how much work it would be to make our playbooks compliant with it?

I think given we have #1190 close to being ready to be merged and running a slightly more updated version of ansible-lint, this can be closed.


fix(rpc): rpc add cors setting

Codecov Report

Merging #55 (09a0c0e) into main (0889e0b) will increase coverage by 9.79%.
The diff coverage is n/a.

@@            Coverage Diff             @@
##             main      #55      +/-   ##
==========================================
+ Coverage   43.07%   52.87%   +9.79%
==========================================
  Files          43       20      -23
  Lines        2340      418    -1922
  Branches       67       21      -46
==========================================
- Hits         1008      221     -787
+ Misses       1332      197    -1135

Impacted Files
Coverage Δ

...cts/types/src/generated/force_bridge_lockscript.rs

...th-contracts/contracts/libraries/MultisigUtils.sol

offchain-modules/ckb-contracts/tests/src/lib.rs

...-modules/ckb-contracts/types/src/recipient_cell.rs

...es/eth-contracts/contracts/libraries/SafeERC20.sol

...in-modules/eth-contracts/contracts/ForceBridge.sol

...dules/ckb-contracts/tests/src/utils/case_runner.rs

...les/eth-contracts/contracts/libraries/SafeMath.sol

...tracts/types/src/generated/recipient_typescript.rs

...ckb-contracts/lib/bridge-lockscript-lib/src/lib.rs

... and 13 more

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git tfs clone pauses and I have to press return/enter to make it continue

I am running git tfs clone on a tfs2010 server with a large codebase and very long history (10s of thousands of changesets?).  git tfs clone runs for a while and then appears to pause.  I then press enter and it continues.  This is not ideal.
I installed git tfs through chocolatey on Windows 7 powershell installed via windows management framework (4? 5?).
edit: I looked like it needed prodding but the task finished over the weekend anyway, without my attention, so perhaps this is a red herring.

Perhaps a little late...
I don't know of such problem with git-tfs.
Did you use cmd.exe or powershell to do your clone?
Because there is a feature called Qiuck edit mode that is know to pause the running process when clicking in the console (the console enter in a selection mode) and waiting for the user to press enter to put the selection in the clipboard. Since the day I discover this behavior, I'm very careful anout that....because that's very easy to enter in this mode :(

Enter wq after :


🚀 Feature Request: Multiple workers support + shared resources

Describe the solution
I'm trying to set up locally few workers that access shared resources like D1, KV in prod env.
Let's take an example to make things easier.
WorkerA with access to D1_A, KV_A, KV_B
WorkerB with access to D1_A, KV_B.
I'm struggling to set up proper development experience which is to start multiple workers with wrangler, make the bindings to each of them work and most important, share the database resources between each other ( WorkerA and WorkerB point to same instance of KV_B and D1_A and not set one resource instance/ worker ).
Without the possibility of sharing resources and make the bindings work, it is impossible to properly develop locally an application in such scenario?

potentially relevant issues:

https://github.com/cloudflare/workers-sdk/issues/1182
https://github.com/cloudflare/workers-sdk/issues/1040
https://github.com/cloudflare/workers-sdk/pull/1503

2024 now, any new official advice how to let multiple workers access the same d1 database? Monorepo?

@BerndWessels here's how I did it in a monorepo based on what @mrbbot mentioned, it seems to be working fine though I haven't had a lot of time for testing yet.
I have two apps in my monorepo, one is a Pages app (in web-app directory) and one is a Worker. My Pages app just uses the normal wrangler pages dev command but for the Worker app I have this in my package.json:
"dev": "wrangler dev --persist-to=../web-app/.wrangler/state",
The Worker app now seems to open and read/write from the same DB as the Pages app.


Exception while editing IronPython code

VS2013 Desktop Express, IronPython 2.7.5, PTVS 2.2.30718.00
Occasionally while editing IronPython code I get a modal MessageBox telling me that
"An exception has been encountered. This may be caused by an extension."
The relevant entry in the VS activity log starts
System.InvalidCastException: Unable to cast object of type 'IronPython.Runtime.Types.BuiltinFunction' to type 'IronPython.Runtime.Types.PythonType'. at
Microsoft.IronPythonTools.Interpreter.RemoteInterpreter.<>c__DisplayClass64_0.b__0() at Microsoft.IronPythonTools.Interpreter.RemoteInterpreter.CallAndHandle[T](Func`1 action, T defaultValue) at
Microsoft.IronPythonTools.Interpreter.RemoteInterpreter.GetPythonTypeMemberType(ObjectIdentityHandle pythonType) at
Microsoft.IronPythonTools.Interpreter.RemoteInterpreterProxy.GetPythonTypeMemberType(ObjectIdentityHandle value) at
Microsoft.IronPythonTools.Interpreter.RemoteInterpreterProxy.GetPythonTypeMemberType(ObjectIdentityHandle value) at
Microsoft.IronPythonTools.Interpreter.IronPythonType.get_MemberType() at
Microsoft.PythonTools.Analysis.Values.BuiltinClassInfo.get_MemberType() at
Microsoft.PythonTools.Analysis.Values.SpecializedNamespace.get_MemberType() at
Microsoft.PythonTools.Analysis.MemberResult.GetMemberType() at
Microsoft.PythonTools.Analysis.MemberResult.get_MemberType() at
Microsoft.PythonTools.Intellisense.CompletionAnalysis.PythonCompletion(IGlyphService service, MemberResult memberResult) at
...
Unfortunately I can't see any way of attaching the activity log here.

Also, while rebuilding a combined C# and IronPython solution, I occasionally get a total freeze of VS with a dialog message "Microsoft Visual Studio Express 2013 for Windows Desktop has stopped working" with the following problem signature that is also a cast exception. Nothing has been added to the activity log.
Problem signature:
Problem Event Name:	CLR20r3
Problem Signature 01:	WDExpress.exe
Problem Signature 02:	12.0.40629.0
Problem Signature 03:	5590c29f
Problem Signature 04:	Microsoft.PythonTools.IronPython.Interpreter
Problem Signature 05:	2.2.30718.0
Problem Signature 06:	55aadecd
Problem Signature 07:	205
Problem Signature 08:	0
Problem Signature 09:	System.InvalidCastException
OS Version:	6.1.76<IP_ADDRESS>.768.3
Locale ID:	2057
Additional Information 1:	0a9e
Additional Information 2:	0a9e372d3b4ad19135b953a78882e789
Additional Information 3:	0a9e
Additional Information 4:	0a9e372d3b4ad19135b953a78882e789

That's totally okay, the stack trace is more than enough information for us here.
(The best way to provide a big text file on GitHub is to create a https://gist.github.com/ and link to it.)

We should also backport this fix to 2.1.1.

So I started fixing this but have to get onto something else right now. Here are the changes I've made so far, and there are a lot more unconditional casts that now need to be checked properly (I assume IronPython 2.7.5 changed the base types of some types).
diff --git a/Python/Product/IronPython/Interpreter/RemoteInterpreter.cs b/Python/Product/IronPython/Interpreter/RemoteInterpreter.cs
--- a/Python/Product/IronPython/Interpreter/RemoteInterpreter.cs
+++ b/Python/Product/IronPython/Interpreter/RemoteInterpreter.cs
@@ -702,7 +702,18 @@

         internal PythonMemberType GetPythonTypeMemberType(ObjectIdentityHandle pythonType) {
             return CallAndHandle(() => {
-                var value = (PythonType)Unwrap(pythonType);
+                var pt = Unwrap(pythonType);
+                var value = pt as PythonType;
+                if (value == null) {
+                    if (pt is BuiltinFunction) {
+                        return PythonMemberType.Function;
+                    }
+                    if (pt is BuiltinMethodDescriptor) {
+                        return PythonMemberType.Method;
+                    }
+                    Debug.Fail("Unhandled IronPython type: " + pt.GetType().FullName);
+                    return PythonMemberType.Unknown;
+                }
                 var type = value.__clrtype__();
                 if (type.IsEnum) {
                     return PythonMemberType.Enum;
@@ -716,8 +727,8 @@

         internal bool PythonTypeHasNewOrInitMethods(ObjectIdentityHandle pythonType) {
             return CallAndHandle(() => {
-                var value = (PythonType)Unwrap(pythonType);
-                return PythonTypeHasNewOrInitMethods(value);
+                var value = Unwrap(pythonType) as PythonType;
+                return value != null && PythonTypeHasNewOrInitMethods(value);
             }, false);
         }

I do hope this is fixed soon. As my project is growing the constant freezing of VS during compilation is getting tedious to the point of being almost unusable.

Having looked deeper into this, I don't think handling all the types is actually the correct approach. It looks more like we're creating an IronPythonType object around something (probably from a managed DLL) that isn't actually represented by a PythonType within IronPython. I suspect the function below from IronPythonInterpreter.cs is to blame:
        internal IPythonType GetTypeFromType(ObjectIdentityHandle type) {
            if (type.IsNull) {
                return null;
            }

            lock (this) {
                IMember res;
                if (!_members.TryGetValue(type, out res)) {
                    _members[type] = res = new IronPythonType(this, type);
                }
                return res as IPythonType;
            }
        }

But it's called from a lot of places. @DinoV might be able to track down the incorrect one faster than I can.


Update bindings.json for sql templates

PR https://github.com/Azure/azure-functions-templates/pull/1345 fixes this.


this.setValues is not a function

When using google map with API key, it showing the following error:

this.setValues is not a function

How can I work around it?

Not sure of the issue here, try:
http://stackoverflow.com/questions/19274953/google-maps-api-v3-object-object-has-no-method-setvalues-error


"Select Python Interpreter" shown when changing environment via changing "python.pythonPath" in "settings.json" file

Visual Studio Code - Insiders: 1.33.0-insider
python-insider: 2019.4.6266-alpha
Repro step:

Open a folder
Press "Ctrl+Shift+P" to select "Python:Select Interpreter->3.7.3 64-bit"
Click ".vscode" to open "settings.json" file
Copy "C:\Python27\python.exe" to change the value of "python.pythonPath"
Change "C:\Python27\python.exe" to "C:\Python27\python.exe"
Save the "settings.json" file

Actual Result:
It shows "Select Python Interpreter" in status bar

Expect Result:
It should display "Python 2.7.16 64bit"
Note:
If type the path "C:\Python27\python.exe" manually. The environment changed correctly.
Repro gif: \bvtsrv2\team\v-xiaofz\PVSC\ChangeEnvironment.gif

Change "C:\Python27\python.exe" to "C:\Python27\python.exe"

What do you mean here?

Repro gif: \bvtsrv2\team\v-xiaofz\PVSC\ChangeEnvironment.gif

Please upload the gif

It should display "Python 2.7.16 64bit"

Please could you provide the following info (logs):

Logs
Output for Python in the Output panel (View→Output, change the drop-down the upper-right of the Output panel to Python)

XXX

Output from Console under the Developer Tools panel (toggle Developer Tools on under Help; turn on source maps to make any tracebacks be useful by running Enable source map support for extension debugging)

XXX

This issue is not reproduced on latest environment(Visual Studio Code - Insiders: 1.34.0-insider +
python-insider: 2019.4.6458-alpha).

@DonJayamanne I found this issue occurs again on Visual Studio Code - Insiders: 1.34.0-insider +
python-insider: 2019.46828-alpha. Please help to trace it.
Below screenshot is the Output for Python in the Output panel.

Below attachment is the Output from Console under the Developer Tools panel
-1555483616881.log
Below gif is the repro video.

Unfortunately there's nothing in the logs that indicates the problem.
Please could you try installing the latest dev version of the extension and letting me know.

I tried with the latest dev version of the extension(2019.5.11931-dev), it is still repro. If you needed, you can get the live environment from below link. https://microsoft.sharepoint.com/teams/CloudPlatformToolsDevOpsCTI/_layouts/OneNote.aspx?id=%2Fteams%2FCloudPlatformToolsDevOpsCTI%2FShared%20Documents%2FTeam%20Notes%2FDevOps%20CTI%20Wuxi&wd=target%2804%20PTVS%2FVSC%2FTestResults.one%7C348D6694-EBC5-49EE-A222-89D835E9C194%2FTest%20machine%20info%7C26E995B8-C181-407C-B692-38BCAE9331F2%2F%29onenote:https://microsoft.sharepoint.com/teams/CloudPlatformToolsDevOpsCTI/Shared%20Documents/Team%20Notes/DevOps%20CTI%20Wuxi/04%20PTVS/VSC/TestResults.one#Test%20machine%20info&section-id={348D6694-EBC5-49EE-A222-89D835E9C194}&page-id={26E995B8-C181-407C-B692-38BCAE9331F2}&object-id={76073FFD-F05A-06F3-3B9A-DE9A89E7F002}&10

@xiaofeng0123 Apologies for the delay, will look into this today

@xiaofeng0123 Not sure what was wrong, but if I copied the text from a separate text file then it works. Looks like there was some invalid character in the text file (possibly an encoding issue).
Possible you copied the path/text from word or other application that resulted in the text getting copied with weird characters.


array field undefined value length check

#179

@chrisvxd , sorry but there was one check which got missed in the previous fix. This should resolve the issue completely.

@chrisvxd  what is the canary version for this change.

0.10.1-canary.68afd09
They're automatically published on each merge with the commit, in this case 68afd09. You should always be able to see it pop up a few minutes after merge on NPM: https://www.npmjs.com/package/@measured/puck?activeTab=versions