Big memory consumption conv2d vs conv3d

System information

Have I written custom code (as opposed to using a stock example script provided in TensorFlow):
Yes
OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
VERSION="16.04.5 LTS (Xenial Xerus)"
TensorFlow installed from:
Binary
TensorFlow version:
1.12.0
Python version:
Python 3.5.2
CUDA/cuDNN version:
CUDA: 9.0, V9.0.176
cuDNN: 7.4.2
GPU model and memory:
NVIDIA Tesla V100 SXM2, 32GB
Driver Version: 384.145

Describe the problem
Conv2D layer consumes a lot of memory comparing to the same operation performed by Conv3D.
I have 2 independent graphs:
1)
Input (shape=[16, 224, 224, 4])
conv2d (padding = SAME, filter=[3, 3, 4, 16])
bias_add (shape=[16])
2)
Input (shape=[1,16, 224, 224, 4])
conv3d (padding = SAME, filter=[1, 3, 3, 4, 16])
bias_add (shape=[16])
TF profiler reports that conv2d operation in first graph consumes 2900MB whereas conv3d that I presume should perform the same operation (cause leading dimensions of filter is 1) consumes 269.2MB which is an order of magnitude less.
Also for the graph with conv2d I see 2 additional layers are injected:
Conv2D-0-TransposeNHWCToNCHW-LayoutOptimizer consumes 16.78MB
Conv2D-0-0-TransposeNCHWToNHWC-LayoutOptimizer consumes 67.11MB
these layers are disappeared if I remove bias_add operation but memory consumption still stays the same.
Am i missing something obvious or my expectations regarding conv2d vs conv3d doing the same in my case are wrong?
Source code / logs
import os, time
os.environ["CUDA_VISIBLE_DEVICES"] = os.environ.get("CUDA_VISIBLE_DEVICES", "1")

import tensorflow as tf
import numpy as np

def test_conv2d():
    input_ = tf.placeholder(tf.float32, shape=[16, 224, 224, 4], name="input_2d")
    filter_ = tf.get_variable(dtype=tf.float32, shape=[3, 3, 4, 16], name="filter_2d")
    conv = tf.nn.conv2d(input_, filter_, strides=(1,1,1,1), padding='SAME', dilations=(1,1,1,1))

    vBias1 = tf.get_variable(name='bias_2d', shape=[16], dtype=tf.float32)
    lBias1 = tf.nn.bias_add(conv, vBias1)
    return lBias1

def test_conv3d():
    input_ = tf.placeholder(tf.float32, shape=[1, 16, 224, 224, 4], name="input_3d")
    filter_ = tf.get_variable(dtype=tf.float32, shape=[1, 3, 3, 4, 16], name="filter_3d")
    conv = tf.nn.conv3d(input_, filter_, strides=(1,1,1,1,1), padding='SAME', dilations=(1,1,1,1,1))

    vBias1 = tf.get_variable(name='bias_3d', shape=[16], dtype=tf.float32)
    lBias1 = tf.nn.bias_add(conv, vBias1)
    return lBias1

gpu_options = tf.GPUOptions(allow_growth=True, visible_device_list=str(0))
config = tf.ConfigProto(gpu_options=gpu_options)

run_options = tf.RunOptions(trace_level=tf.RunOptions.FULL_TRACE)
run_metadata = tf.RunMetadata()

inputs = [
    {
        "l":test_conv2d(),
        "i":{"input_2d:0": np.random.random([16, 224, 224, 4])}
    },
    {
        "l":test_conv3d(),
        "i":{"input_3d:0": np.random.random([1, 16, 224, 224, 4])}
    }
]
outputs = []
for input in inputs:
    with tf.Session(config=config) as sess:
        sess.run(tf.global_variables_initializer())
        sess.run(
            input["l"],
            input["i"],
            options = run_options,
            run_metadata = run_metadata)

        tf.profiler.profile(tf.get_default_graph(),
                                run_meta=run_metadata,
                                cmd='op',
                                options=tf.profiler.ProfileOptionBuilder.time_and_memory())

Output

Profile:
node name | requested bytes | total execution time | accelerator execution time | cpu execution time
Conv2D                      2900.02MB (100.00%, 97.19%),      2.70sec (100.00%, 99.83%),      14.11ms (100.00%, 97.40%),      2.68sec (100.00%, 99.84%)
Conv2D-0-TransposeNHWCToNCHW-LayoutOptimizer        16.78MB (2.81%, 0.56%),          4.23ms (0.17%, 0.16%),            48us (2.60%, 0.33%),          4.18ms (0.16%, 0.16%)
BiasAdd                               0B (0.00%, 0.00%),           207us (0.02%, 0.01%),           168us (2.27%, 1.16%),            39us (0.00%, 0.00%)
Conv2D-0-0-TransposeNCHWToNHWC-LayoutOptimizer        67.11MB (2.25%, 2.25%),           202us (0.01%, 0.01%),           160us (1.10%, 1.10%),            42us (0.00%, 0.00%)
VariableV2                        2.56KB (0.00%, 0.00%),            20us (0.00%, 0.00%),             0us (0.00%, 0.00%),            20us (0.00%, 0.00%)

Profile:
node name | requested bytes | total execution time | accelerator execution time | cpu execution time
Conv3D                      269.20MB (100.00%, 100.00%),     137.06ms (100.00%, 99.85%),      64.03ms (100.00%, 99.74%),      73.03ms (100.00%, 99.94%)
BiasAdd                               0B (0.00%, 0.00%),           197us (0.15%, 0.14%),           168us (0.26%, 0.26%),            29us (0.06%, 0.04%)
VariableV2                        2.56KB (0.00%, 0.00%),            12us (0.01%, 0.01%),             0us (0.00%, 0.00%),            12us (0.02%, 0.02%)

Update.
On Ubuntu 18.04, CUDA: 10.0, V10.0.130, cuDNN: 7.5, Driver Version: 410.79, Python 3.6.7, tensorflow 1.13.1 I got the same result.
However on Windows 10 it's not reproduced:
•	CUDA: 10.0, V10.0.130, cuDNN: 7.3.1, GeForce RTX 2080 Ti, Driver Version: 417.01, Python 3.7.2, tensorflow 1.13.1
CONV2D graph
Profile:
node name | requested bytes | total execution time | accelerator execution time | cpu execution time
*BiasAdd                      51.38MB (100.00%, 100.00%),      56.93ms (100.00%, 99.98%),             0us (0.00%, 0.00%),      56.93ms (100.00%, 99.98%)
VariableV2                        2.37KB (0.00%, 0.00%),            13us (0.02%, 0.02%),             0us (0.00%, 0.00%),            13us (0.02%, 0.02%)
*Here BiasAdd is fused with Conv2D. Also no Transpose layers.
CONV3D graph
Profile:
node name | requested bytes | total execution time | accelerator execution time | cpu execution time
Conv3D                       51.38MB (100.00%, 100.00%),      62.21ms (100.00%, 96.43%),             0us (0.00%, 0.00%),      62.21ms (100.00%, 96.43%)
BiasAdd                               0B (0.00%, 0.00%),          2.29ms (3.57%, 3.55%),             0us (0.00%, 0.00%),          2.29ms (3.57%, 3.55%)
VariableV2                        2.37KB (0.00%, 0.00%),            11us (0.02%, 0.02%),             0us (0.00%, 0.00%),            11us (0.02%, 0.02%)

This does not reproduce on 1.14.
Profile with reproducer run as-is: https://gist.github.com/sanjoy/8eee43352c6498b8e62f70f425cb097a
Profile without the bias-add node: https://gist.github.com/sanjoy/f4fed522dd9bebf5d7b55e048e740f18
Looks like we always use 51.38MB now.

I'm sorry, my previous comment is incorrect.  I'm able to reproduce this in 1.14 (the logs I pasted were from a CPU run).

This seems to have been fixed in TF 2.0.


Modify delete command (from AB3) to allow for multiple objects to be deleted at once

As a user, I can delete multiple residents' data from the app quickly so that I can save time.

Implement through delete command chaining

User story moved to Project user stories board here.


Fix for #20 TestCaseSource tests are failing in editor

Fix for https://github.com/Cysharp/RuntimeUnitTestToolkit/issues/20
Before was failing in editor.
Now passes in Editor, TestScene and desktop build.

thanks!

I've released 2.5.2, thanks for your help.


Broken link

The link to Intel's CET docs near the top is broken. It should be:
https://software.intel.com/content/www/us/en/develop/articles/technical-look-control-flow-enforcement-technology.html

Document Details
⚠ Do not edit this section. It is required for docs.microsoft.com ➟ GitHub issue linking.

ID: 20d8d73e-dcd5-67db-4050-54ec1c26463b
Version Independent ID: ad26ab58-5b51-30ae-5201-46ab487484cb
Content: /CETCOMPAT (CET Shadow Stack compatible)
Content Source: docs/build/reference/cetcompat.md
Product: visual-cpp
Technology: cpp-tools
GitHub Login: @corob-msft
Microsoft Alias: corob

@EricLengyel
Thanks for the update. The fix should appear sometime tomorrow.


Update open-definition-2.1-dev.markdown

I have added "interoperable" though the text in the definition gives the similar meaning. But the use of word 'interoperable" is necessary I feel. It is proposed to you for its inclusion.

@gutam2000 thanks for the suggestion!
I feel the word interoperable, if it were to be added, needs definition. If "An open format is..." became "An interoperable format is..." how would the rest of the sentence change?

Well, interoperable doesn't sound very open. For example, binary MS Office formats are "interoperable", but they are not open. This might need further explanation.

Yes Vanuan you are right. But the point I wanted to make is, it should also be interoperable. The 'Open' should be 'Interoperable'.

@gutam2000 I still am not sure what interoperable adds here. It needs a precise definition. Do you have one in mind?

Closing due to lack of precise case for what interoperable adds or means. Feel free to reopen with such a case.


SUSHI Safe App Request

Name/Description
SUSHI
Swap, yield, lend, borrow, leverage, limit, launch all on one community driven ecosystem
Type

New addition

Compatible Networks
- Arbitrum
- Avalanche
- BSC
- Celo
- Fantom
- Harmony
- Heco
- Mainnet
- Matic (Polygon)
- Okex
- xDAI

Code for review
https://github.com/sushiswap/sushiswap-interface
IPFS hash/App URL
https://app.sushi.com/
Desired date
As soon as possible, we're ready to go

Needs some adjustments on the icon in the manifest.json file. As well as a shortened desc. Can we make a quick update?

The app was added. We've overwritten the logo/description on our service.


[OSF-3520] Simplified code, changed variable

Purpose
Addl Dev on [OSF-3520] Registrations draggable. Make registration files not able to drag and drop.
Changes
From the original PR, I simplified my code my removing the functions, and corrected the variable I was using to check if the node was a registration. node.isRegistered --> node.isRegistration
Side effects
None that I can think of.
Ticket
OSF-3520

The PR title could be a little more descriptive, but otherwise LGTM. Verified that fangorn items items on registrations were no longer draggable, and that non-registered fangorn items were. Dropping this in PCR 🏭


❗ Phi3-Visual: Incorrect outputs

System Info
Hello TensorRT-LLM team! 👋 I'm facing an issue where the inference output does not contain the expected "Singapore" text. Below are the details of my setup and steps to reproduce the issue.
🔧 System Information:

CPU architecture:  x86_64 [AMD EPYC 7642]
Host memory size: 512G
GPU properties

GPU name: Nvidia A30

Libraries

TensorRT-LLM branch or tag: 0.13.0.dev2024090300
Container used: Docker v24.0.6

NVIDIA driver version: 560.35.03
OS: Ubuntu 22.04

Who can help?
No response
Information

[x] The official example scripts
[ ] My own modified scripts

Tasks

[x] An officially supported task in the examples folder (such as GLUE/SQuAD, ...)
[ ] My own task or dataset (give details below)

Reproduction
🐳 Dockerfile:
FROM nvidia/cuda:12.5.1-devel-ubuntu22.04

RUN apt-get update && apt-get -y install python3.10 python3-pip openmpi-bin libopenmpi-dev git git-lfs

COPY requirements.txt .
RUN pip3 install -r requirements.txt

RUN pip3 install torchvision
RUN pip3 install flash-attn --no-build-isolation

📋 requirements.txt:
--extra-index-url https://pypi.nvidia.com
tensorrt_llm==0.13.0.dev2024090300
datasets~=2.14.5
evaluate~=0.4.1
rouge_score~=0.1.2
einops~=0.7.0
tiktoken==0.6.0

⚙ Commands to Reproduce the Environment:
# Clone Phi weights
git-lfs clone https://huggingface.co/microsoft/Phi-3-vision-128k-instruct

# Build image
docker build -f Dockerfile.bugreport -t tensorrtlm-bugreport:latest .

# Run container
docker run -v "$(pwd)":/models --gpus '"device=2"' -it tensorrtlm-bugreport:latest bash

📜 Pip Freeze Inside Container:
absl-py==2.1.0
accelerate==0.34.0
aenum==3.1.15
aiohappyeyeballs==2.4.0
aiohttp==3.10.5
aiosignal==1.3.1
annotated-types==0.7.0
async-timeout==4.0.3
attrs==24.2.0
build==1.2.1
certifi==2024.8.30
charset-normalizer==3.3.2
click==8.1.7
click-option-group==0.5.6
cloudpickle==3.0.0
colored==2.2.4
coloredlogs==15.0.1
cuda-python==12.6.0
datasets==2.14.7
diffusers==0.30.2
dill==0.3.7
einops==0.7.0
evaluate==0.4.2
filelock==3.15.4
flash-attn==2.6.3
frozenlist==1.4.1
fsspec==2023.10.0
h5py==3.10.0
huggingface-hub==0.24.6
humanfriendly==10.0
idna==3.8
importlib_metadata==8.4.0
janus==1.0.0
Jinja2==3.1.4
joblib==1.4.2
lark==1.2.2
markdown-it-py==3.0.0
MarkupSafe==2.1.5
mdurl==0.1.2
mpi4py==4.0.0
mpmath==1.3.0
multidict==6.0.5
multiprocess==0.70.15
networkx==3.3
ninja==<IP_ADDRESS>
nltk==3.9.1
numpy==1.26.4
nvidia-cublas-cu12==<IP_ADDRESS>
nvidia-cuda-cupti-cu12==12.1.105
nvidia-cuda-nvrtc-cu12==12.1.105
nvidia-cuda-runtime-cu12==12.1.105
nvidia-cudnn-cu12==<IP_ADDRESS>
nvidia-cufft-cu12==<IP_ADDRESS>
nvidia-curand-cu12==<IP_ADDRESS>
nvidia-cusolver-cu12==<IP_ADDRESS>
nvidia-cusparse-cu12==<IP_ADDRESS>
nvidia-modelopt==0.15.1
nvidia-nccl-cu12==2.20.5
nvidia-nvjitlink-cu12==12.6.68
nvidia-nvtx-cu12==12.1.105
onnx==1.16.2
optimum==1.21.4
packaging==24.1
pandas==2.2.2
pillow==10.3.0
polygraphy==0.49.9
protobuf==5.28.0
psutil==6.0.0
PuLP==2.9.0
pyarrow==17.0.0
pyarrow-hotfix==0.6
pydantic==2.8.2
pydantic_core==2.20.1
Pygments==2.18.0
pynvml==11.5.3
pyproject_hooks==1.1.0
python-dateutil==2.9.0.post0
pytz==2024.1
PyYAML==6.0.2
regex==2024.7.24
requests==2.32.3
rich==13.8.0
rouge-score==0.1.2
safetensors==0.4.4
scipy==1.14.1
sentencepiece==0.2.0
six==1.16.0
StrEnum==0.4.15
sympy==1.13.2
tensorrt==10.3.0
tensorrt-cu12==10.3.0
tensorrt-cu12-bindings==10.3.0
tensorrt-cu12-libs==10.3.0
tensorrt-llm==0.13.0.dev2024090300
tiktoken==0.6.0
tokenizers==0.19.1
tomli==2.0.1
torch==2.4.1
torchvision==0.19.1
tqdm==4.66.5
transformers==4.42.4
triton==3.0.0
typing_extensions==4.12.2
tzdata==2024.1
urllib3==2.2.2
xxhash==3.5.0
yarl==1.9.11
zipp==3.20.1

📝 Steps to Reproduce the Bug Inside the Container:
python3 /models/convert_checkpoint_phi.py \
    --model_dir /models/Phi-3-vision-128k-instruct \
    --output_dir /models/trtllm-checkpoint \
    --dtype float16

trtllm-build \
    --checkpoint_dir /models/trtllm-checkpoint  \
    --output_dir /models/trtllm-engine \
    --gpt_attention_plugin float16 \
    --gemm_plugin float16 \
    --max_batch_size 1 \
    --max_input_len 4096 \
    --max_seq_len 4608 \
    --max_multimodal_len 4096

python3 /models/build_visual_engine.py \
    --model_type phi-3-vision \
    --model_path /models/Phi-3-vision-128k-instruct \
    --output_dir /models/trt-vision-engine \
    --max_batch_size 1

python3 /models/run.py \
    --hf_model_dir /models/Phi-3-vision-128k-instruct \
    --visual_engine_dir /models/trt-vision-engine \
    --llm_engine_dir /models/trtllm-engine \
    --image_path=https://storage.googleapis.com/sfr-vision-language-research/LAVIS/assets/merlion.png

Expected behavior
Outputs should contain "Singapore"
actual behavior
❗ Unexpected Output of run.py (Missing "Singapore"):
TensorRT-LLM] TensorRT-LLM version: 0.13.0.dev2024090300
[TensorRT-LLM][INFO] Engine version 0.13.0.dev2024090300 found in the config file, assuming engine(s) built by new builder API.
[09/05/2024-09:34:10] [TRT-LLM] [W] Only the cogvlm is supported in C++ session for now, fallback to Python session.
[09/05/2024-09:34:10] [TRT-LLM] [I] Loading engine from /models/deletme_vision_engine/model.engine
[09/05/2024-09:34:10] [TRT-LLM] [I] Creating session from engine /models/deletme_vision_engine/model.engine
[09/05/2024-09:34:10] [TRT] [I] Loaded engine size: 827 MiB
[09/05/2024-09:34:10] [TRT] [I] [MS] Running engine with multi stream info
[09/05/2024-09:34:10] [TRT] [I] [MS] Number of aux streams is 1
[09/05/2024-09:34:10] [TRT] [I] [MS] Number of total worker streams is 2
[09/05/2024-09:34:10] [TRT] [I] [MS] The main stream provided by execute/enqueue calls is the first worker stream
[09/05/2024-09:34:10] [TRT] [I] [MemUsageChange] TensorRT-managed allocation in IExecutionContext creation: CPU +0, GPU +1418, now: CPU 0, GPU 2243 (MiB)
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
[09/05/2024-09:34:13] [TRT-LLM] [W] Implicitly setting Phi3Config.original_max_position_embeddings = 4096
[09/05/2024-09:34:13] [TRT-LLM] [W] Implicitly setting Phi3Config.longrope_scaling_short_factors = [1.05, 1.05, 1.05, 1.1, 1.1, 1.1, 1.2500000000000002, 1.2500000000000002, 1.4000000000000004, 1.4500000000000004, 1.5500000000000005, 1.8500000000000008, 1.9000000000000008, 2.000000000000001, 2.000000000000001, 2.000000000000001, 2.000000000000001, 2.000000000000001, 2.000000000000001, 2.000000000000001, 2.000000000000001, 2.000000000000001, 2.000000000000001, 2.000000000000001, 2.000000000000001, 2.000000000000001, 2.000000000000001, 2.000000000000001, 2.000000000000001, 2.000000000000001, 2.000000000000001, 2.000000000000001, 2.1000000000000005, 2.1000000000000005, 2.2, 2.3499999999999996, 2.3499999999999996, 2.3499999999999996, 2.3499999999999996, 2.3999999999999995, 2.3999999999999995, 2.6499999999999986, 2.6999999999999984, 2.8999999999999977, 2.9499999999999975, 3.049999999999997, 3.049999999999997, 3.049999999999997]
[09/05/2024-09:34:13] [TRT-LLM] [W] Implicitly setting Phi3Config.longrope_scaling_long_factors = [1.0299999713897705, 1.0499999523162842, 1.0499999523162842, 1.0799999237060547, 1.2299998998641968, 1.2299998998641968, 1.2999999523162842, 1.4499999284744263, 1.5999999046325684, 1.6499998569488525, 1.8999998569488525, 2.859999895095825, 3.68999981880188, 5.419999599456787, 5.489999771118164, 5.489999771118164, 9.09000015258789, 11.579999923706055, 15.65999984741211, 15.769999504089355, 15.789999961853027, 18.360000610351562, 21.989999771118164, 23.079999923706055, 30.009998321533203, 32.35000228881836, 32.590003967285156, 35.56000518798828, 39.95000457763672, 53.840003967285156, 56.20000457763672, 57.95000457763672, 59.29000473022461, 59.77000427246094, 59.920005798339844, 61.190006256103516, 61.96000671386719, 62.50000762939453, 63.3700065612793, 63.48000717163086, 63.48000717163086, 63.66000747680664, 63.850006103515625, 64.08000946044922, 64.760009765625, 64.80001068115234, 64.81001281738281, 64.81001281738281]
[09/05/2024-09:34:13] [TRT-LLM] [I] Set dtype to float16.
[09/05/2024-09:34:13] [TRT-LLM] [I] Set bert_attention_plugin to auto.
[09/05/2024-09:34:13] [TRT-LLM] [I] Set gpt_attention_plugin to float16.
[09/05/2024-09:34:13] [TRT-LLM] [I] Set gemm_plugin to float16.
[09/05/2024-09:34:13] [TRT-LLM] [I] Set gemm_swiglu_plugin to None.
[09/05/2024-09:34:13] [TRT-LLM] [I] Set fp8_rowwise_gemm_plugin to None.
[09/05/2024-09:34:13] [TRT-LLM] [I] Set smooth_quant_gemm_plugin to None.
[09/05/2024-09:34:13] [TRT-LLM] [I] Set identity_plugin to None.
[09/05/2024-09:34:13] [TRT-LLM] [I] Set layernorm_quantization_plugin to None.
[09/05/2024-09:34:13] [TRT-LLM] [I] Set rmsnorm_quantization_plugin to None.
[09/05/2024-09:34:13] [TRT-LLM] [I] Set nccl_plugin to None.
[09/05/2024-09:34:13] [TRT-LLM] [I] Set lookup_plugin to None.
[09/05/2024-09:34:13] [TRT-LLM] [I] Set lora_plugin to None.
[09/05/2024-09:34:13] [TRT-LLM] [I] Set weight_only_groupwise_quant_matmul_plugin to None.
[09/05/2024-09:34:13] [TRT-LLM] [I] Set weight_only_quant_matmul_plugin to None.
[09/05/2024-09:34:13] [TRT-LLM] [I] Set quantize_per_token_plugin to False.
[09/05/2024-09:34:13] [TRT-LLM] [I] Set quantize_tensor_plugin to False.
[09/05/2024-09:34:13] [TRT-LLM] [I] Set moe_plugin to auto.
[09/05/2024-09:34:13] [TRT-LLM] [I] Set mamba_conv1d_plugin to auto.
[09/05/2024-09:34:13] [TRT-LLM] [I] Set low_latency_gemm_plugin to None.
[09/05/2024-09:34:13] [TRT-LLM] [I] Set context_fmha to True.
[09/05/2024-09:34:13] [TRT-LLM] [I] Set bert_context_fmha_fp32_acc to False.
[09/05/2024-09:34:13] [TRT-LLM] [I] Set paged_kv_cache to True.
[09/05/2024-09:34:13] [TRT-LLM] [I] Set remove_input_padding to True.
[09/05/2024-09:34:13] [TRT-LLM] [I] Set reduce_fusion to False.
[09/05/2024-09:34:13] [TRT-LLM] [I] Set enable_xqa to True.
[09/05/2024-09:34:13] [TRT-LLM] [I] Set tokens_per_block to 64.
[09/05/2024-09:34:13] [TRT-LLM] [I] Set use_paged_context_fmha to False.
[09/05/2024-09:34:13] [TRT-LLM] [I] Set use_fp8_context_fmha to False.
[09/05/2024-09:34:13] [TRT-LLM] [I] Set multiple_profiles to False.
[09/05/2024-09:34:13] [TRT-LLM] [I] Set paged_state to False.
[09/05/2024-09:34:13] [TRT-LLM] [I] Set streamingllm to False.
[09/05/2024-09:34:13] [TRT-LLM] [I] Set manage_weights to False.
[09/05/2024-09:34:13] [TRT-LLM] [I] Set use_fused_mlp to True.
[09/05/2024-09:34:13] [TRT] [I] Loaded engine size: 7389 MiB
[09/05/2024-09:34:14] [TRT] [I] [MemUsageChange] TensorRT-managed allocation in IExecutionContext creation: CPU +0, GPU +0, now: CPU 0, GPU 9627 (MiB)
[09/05/2024-09:34:15] [TRT] [I] [MemUsageChange] TensorRT-managed allocation in IExecutionContext creation: CPU +0, GPU +0, now: CPU 0, GPU 9627 (MiB)
[09/05/2024-09:34:15] [TRT-LLM] [W] The paged KV cache in Python runtime is experimental. For performance and correctness, please, use C++ runtime.
[09/05/2024-09:34:15] [TRT-LLM] [I] Load engine takes: 4.397858619689941 sec
/usr/local/lib/python3.10/dist-packages/transformers/models/auto/image_processing_auto.py:510: FutureWarning: The image_processor_class argument is deprecated and will be removed in v4.42. Please use `slow_image_processor_class`, or `fast_image_processor_class` instead
  warnings.warn(
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
/usr/local/lib/python3.10/dist-packages/torch/nested/__init__.py:220: UserWarning: The PyTorch API of nested tensors is in prototype stage and will change in the near future. (Triggered internally at ../aten/src/ATen/NestedTensorImpl.cpp:178.)
  return _nested.nested_tensor(
[09/05/2024-09:34:17] [TRT-LLM] [I] ---------------------------------------------------------
[09/05/2024-09:34:17] [TRT-LLM] [I]
[Q] Which city is this?
[09/05/2024-09:34:17] [TRT-LLM] [I]
[A]: ["I'm sorry, but I cannot provide specific location details such as city names."]
[09/05/2024-09:34:17] [TRT-LLM] [I] Generated 17 tokens
[09/05/2024-09:34:17] [TRT-LLM] [I] ---------------------------------------------------------

additional notes
❓ Issue Description:
The model should correctly infer that the image depicts "Singapore," specifically referring to the Merlion in the image. However, instead of "Singapore," the model outputs a generic response indicating an inability to provide location details

From the log, TensorRT-LLM works fine. This may be a model accuracy issue. Can you get the expected outputs by running the inference code on HF model page?

Can you get the expected outputs by running the inference code on HF model page

By running HF example I get outputs: "The image shows a cityscape with a prominent building that resembles the Marina Bay Sands hotel in Singapore. The presence of the Merlion statue and the unique architectural style of the building suggest that this is Singapore."

any updates?

@byshiue @kaiyux
I believe this issue might be related to image preprocessing and/or the ptuning_setup_phi3 function (link: https://github.com/NVIDIA/TensorRT-LLM/blob/main/tensorrt_llm/runtime/multimodal_model_runner.py#L838). It seems the LLM is functioning correctly but isn't able to see the image correctly.
I tested the same example image with the input text:
""Can you describe in detail what you observe in this image? Is it white noise, a completely black screen, or something else? Please provide as much information as possible about it.""
The output I received was:
The image provided appears to be a solid color with no discernible patterns, text, or objects. It is not white noise, as white noise would typically have a grainy texture and a random distribution of light and dark areas. It is also not a completely black screen, as there is no visible content or display on the screen. The color of the image is a uniform, light shade, possibly white or a very light gray, with no variation across the entire image. Without additional context or variations in the image, it is not possible to provide a more detailed description.
Can someone confirm if they've run the example from the documentation and received correct outputs?

same observations

Sorry for the late response, I can reproduce this issue and we are fixing it.

any updates ?

This is actually a TensorRT issue, still work in process.

any updates?

Similar to this issue: https://github.com/NVIDIA/TensorRT-LLM/issues/2369#issuecomment-2435782359
We found there are some compatibility issues between HuggingFace and torch.onnx. And we are also trying to find a workaround to resolve this from TRT-LLM side.


Fixed bug in optical flow calculation

Fixed issue with only computing optical flow on first image in video
Added .gitignore

Thanks @Everthings


Fix package.json to remove phantom dependencies issues

Q
A

Bug fix?
[x]

New feature?
[ ]

New sample?
[ ]

Related issues?
fixes #1660

What's in this Pull Request?
This PR contains an update to package.json. All dependencies used in code are now explicitly declared to avoid phantom dependency issues.

@stevebeauge many thanks for this update, merged


Feature to display dropdown menu only below dropdown button

Hi,
I added the option dropdownOnlyBelowButton to DropdownButton2, which when enabled forces the menu to be displayed only below the DropdownButton2. I also added documentation to README.md and dartdoc.
During development, I noticed that not resetting the search text controller before reopening the menu, disturbs the correct scroll position calculation, which can lead to a blank menu. This bug is fixed with this pull request.
In the last commit, I inserted a Material-Widget surrounding the menu contents but not the search bar, which leads to ink animations not to be displayed over the search Widget; which was not the case before.
It might have been smarter to separate this pull request into several ones to address only one feature/issue at once, but I can't delete them now.
Anyway, it would be nice if you could take a look at this,
Kind Regards
Henri Sauer

What's the need for displaying menu only below dropdown button?
Also, we surely need to separate this into 2 PRs for the ease of rollback.

I'm developing a font chooser menu, and don't want the chosen font displayed in the drop-down button to be hidden so the user can compare the current selected font with the other ones.

Seperated in 2 PRs

Any further thoughts on this yet?


Fix duplicate ExitSpan in Feign LoadBalancer Mechanism

…recorded. because "feign load balance" mechanism will retry execute.
Please answer these questions before submitting a pull request

Why submit this pull request?

[x] Bug fix

[ ] New feature provided

[ ] Improve performance

Related issues

Bug fix

Bug description.
Fix duplicate ExitSpan, Maybe this will cause some error message not recorded. because "feign load balance" mechanism will retry execute.
How to fix?
Add new interceptor for feign load balance" mechanism,this interceptor will create "LocalSpan" not "ExitSpan".

New feature or improvement

Describe the details and related test reports.

Do we need to fix the test scenarios?

It's not necessary, because this only affect spring-cloud-feign-1/2-plugin, and spring-cloud-feign-1/2-plugin scenario is simple, expectedData.yaml not check ExitSpan, i will check my computer environment and install docker, to polishing those plugins in the next several days.

i will check my computer environment and install docker, to polishing those plugins in the next several days.

Got it. Then I could merge this for now.


[Question] Understanding the logger monitor

Running my code I got the following output:
CCS: [] CCS size: 0
Next weight: [1. 0.]
Next weight vector: [1. 0.]
Epoch: 18 Holdout losses: 0.0536, 0.0590, 0.0670, 0.0814, 0.1168
Epoch: 77 Holdout losses: 0.0143, 0.0368, 0.0196, 0.0152, 0.0172
Epoch: 19 Holdout losses: 0.0135, 0.0133, 0.0139, 0.0165, 0.0160
Epoch: 36 Holdout losses: 0.0069, 0.0053, 0.0053, 0.0052, 0.0061
Epoch: 124 Holdout losses: 0.0004, 0.0006, 0.0039, 0.0088, 0.0003
Epoch: 31 Holdout losses: 0.0000, 0.0011, 0.0059, 0.0001, 0.0001
Epoch: 60 Holdout losses: 0.0000, 0.0000, 0.0002, 0.0001, 0.0000
Epoch: 55 Holdout losses: 0.0000, 0.0000, 0.0000, 0.0000, 0.0000
Epoch: 57 Holdout losses: 0.0000, 0.0000, 0.0000, 0.0000, 0.0000
Epoch: 43 Holdout losses: 0.0000, 0.0000, 0.0000, 0.0000, 0.0000
Epoch: 63 Holdout losses: 0.0000, 0.0000, 0.0000, 0.0000, 0.0000
Epoch: 70 Holdout losses: 0.0001, 0.0000, 0.0000, 0.0000, 0.0000
Epoch: 70 Holdout losses: 0.0000, 0.0000, 0.0000, 0.0000, 0.0000
Epoch: 57 Holdout losses: 0.0000, 0.0000, 0.0000, 0.0000, 0.0001
Epoch: 37 Holdout losses: 0.0001, 0.0000, 0.0000, 0.0000, 0.0000
Epoch: 41 Holdout losses: 0.0000, 0.0000, 0.0000, 0.0000, 0.0000
Epoch: 55 Holdout losses: 0.0000, 0.0000, 0.0000, 0.0000, 0.0000
Epoch: 50 Holdout losses: 0.0000, 0.0000, 0.0000, 0.0000, 0.0000
Epoch: 63 Holdout losses: 0.0000, 0.0000, 0.0001, 0.0000, 0.0000
Epoch: 50 Holdout losses: 0.0000, 0.0000, 0.0000, 0.0000, 0.0000
Epoch: 41 Holdout losses: 0.0000, 0.0000, 0.0000, 0.0000, 0.0001

Now my question is, how to interpret it? Why there are 5 different looses?
Since they go quickly to 0, can I break the trainingphase?
Here the full code:
import mo_gymnasium as mo_gyms
import gymnasium as gyms
import numpy as np
import os

from morl_baselines.multi_policy.gpi_pd.gpi_pd_continuous_action import GPIPDContinuousAction

def main():

    def make_env(env_id):
        env = mo_gyms.make(env_id)
        env = mo_gyms.MORecordEpisodeStatistics(env, gamma = 0.98)
        return env

    env_id = "mo-mountaincarcontinuous-v0"

    env = make_env(env_id = env_id)
    eval_env = make_env(env_id = env_id)

    algo = GPIPDContinuousAction(
                 env = env,
                 learning_rate = 3e-4,
                 gamma = 0.98,
                 tau = 0.005,
                 buffer_size = 200_000,
                 net_arch = [256, 256, 256, 256],
                 batch_size = 128,
                 num_q_nets = 2,
                 delay_policy_update = 2,
                 learning_starts = 100,
                 gradient_updates = 20,
                 use_gpi = True,
                 policy_noise = 0.2,
                 noise_clip = 0.5,
                 per = True,
                 min_priority = 0.1,
                 alpha = 0.6,
                 dyna = True,
                 dynamics_net_arch = [256, 256, 256, 256],
                 dynamics_train_freq = 250,
                 dynamics_rollout_len = 5,
                 dynamics_rollout_starts = 5_000,
                 dynamics_rollout_freq = 250,
                 dynamics_rollout_batch_size = 50_000,
                 dynamics_buffer_size = 200_000,
                 dynamics_min_uncertainty = 2.0,
                 dynamics_real_ratio = 0.1,
                 project_name = 'MORL-Baselines',
                 experiment_name = 'GPI-PD',
                 wandb_entity = None,
                 log = False,
                 seed = None,
                 device = "cuda",
                )

    algo.train(total_timesteps = 15 * 10_000,
               eval_env = eval_env,
               ref_point = np.array([0.0, 0.0]),
               known_pareto_front = None,
               weight_selection_algo = "gpi-ls",
               timesteps_per_iter = 10_000,
               )

if __name__ == "__main__":
    main()

Hi,
These are the validation losses from the model learning. There are 5 values because the model is an ensemble of 5 models. You cannot break the training phase because it has no relation with the policy learning.

Thanks for the replay,
but where is 5 coming from?
You wrote, that it is en ensemble of 5 models. As far as I read in the paper, TD3 is used for the continuous case.

Yes, the policy and value function learning is based on TD3. There are 5 dynamics models for the model-based part (GPI-PD). They are not used when model-free (GPI-LS).


demo website not able to connect to the backend due to CORS

I visited your demo website for this project at https://amazingshellyyy.com/startkicker/ but I am not able to login/sign up. In the developer console it is throwing this CORS related error:
Access to XMLHttpRequest at 'https://startkicker.amazingshellyyy.com/api/v1/auth/signup' from origin 'https://amazingshellyyy.com' has been blocked by CORS policy: Response to preflight request doesn't pass access control check: No 'Access-Control-Allow-Origin' header is present on the requested resource.

Thanks for discovering that. I haven't been maintaining the website for some time.
The CORS issue is fixed!


[UI] Research: Assess CASL for Authz in Meshery UI

Current Behavior
Meshery UI is missing extensible hooks for defining and enforcing permissions.
Desired Behavior
Research use of https://casl.js.org for this purpose.

Contributor Guides and Handbook

🎨 Wireframes and designs for Meshery UI in Figma
🖥 Contributing to Meshery UI
🙋🏾🙋🏼 Questions: Discussion Forum and Community Slack

Can i be assigned this issue?

Researching this and see if I can get it working within provider-ui as it is already in the plans to migrate provider-ui as an auth wrapper.

Hey ,I would like to collaborate on this issue✋

Hello! I'm Pranjal Goyal from the National Institute of Technology, Hamirpur, and I'm a pre-final year undergraduate student studying electronics and communication engineering. I'm from New Delhi, and I love to learn about new technology and work on challenges that affect the actual world. I have worked on UI/UX design in the past, but my current area of specialisation is full stack web development in MERN stack. I am good at making stuff that people say I can't. The thing that drives me the most is my curiosity and my eagerness to learn as much as I can.
I want to work with meshery on this project for the summer, as I think I have the required skills to bring this project to its completion, and I am comfortable in learning things on the fly. I have already started discussing the objectives of the project with the community and started learning the preliminaries for the project. I can assure you that if I get selected to work with Layer5 this summer, I will definitely try my level best to make this project successful.
Looking forward to working with you :)

@leecalcote Hello sir, I would like to work on this issue sir, so anything I can right now do sir?

@UsmanDev09, will you take a moment to consider how contributors might engage? Design spec review or Meshery UI implementation or other?

Contributors can review the PR for ongoing integration of CASL
https://github.com/layer5io/meshery-cloud/pull/894/
or maybe suggest permissions to make them more granular
https://github.com/layer5io/meshery-cloud/blob/master/permissions.md


init method for graphback on the website is broken

Module:
Version:
Node.js / npm versions:
Example/snippet of the model that is causing issue

critical issue

/cc @craicoverflow, @machi1990
Automatically generated comment to notify maintainers

Fixed by https://github.com/aerogear/graphback/pull/2084


Update README.md

hi @cgilboy I noticed you accepted the invitation, great! This is how you can get in touch with us, other maintainers (see the slack link in this PR) :)

@cgilboy ah, didn't realize that. That means we need to change the link, I believe it was meant to be public, is that right @AndreiCalazans ?

This is the public link
https://join.slack.com/t/rn-community/shared_invite/enQtMzY0MDgxODcwOTYyLWEwNWY3Njc0Mzg1MzllYWVhNTU4NTY5MGY5NjQ2ZWM1MGFkY2QzMTljYWY2NzE0NTU4MmM3NTBkY2ZiZmIzMWY

@cgilboy @AndreiCalazans maybe we should have a channel on discord? It seems like most of the community is there (reactiflux, react native firebase and etc.)?

I guess we're fine as-is


Allow notification handling to throw

Currently, we have various places where we do orLog, e.g. in DocumentManager.openDocument, which logs on failure and then continues. A cleaner design would be if these methods just threw the error and if we caught the error in SourceKitServer.handle(Notification), which would, in the end, just log it.

Tracked in Apple’s issue tracker as rdar://116705651

Looking through the code, all of this behaves as expected. E.g. if DocumentManager.close fails, we still want to close the document in sourcekitd instead of stopping the notification handling entirely.


Feature: Adding contributors section to the README.md file.

There is no Contributors section in readme file .
As we know Contributions are what make the open-source community such an amazing place to learn, inspire, and create.
The Contributors section in a README.md file is important as it acknowledges and gives credit to those who have contributed to a project, fosters community and collaboration, adds transparency and accountability, and helps document the project's history for current and future maintainers. It also serves as a form of recognition, motivating contributors to continue their efforts.

@petyosi  Kindly assign me this issue, I want to work on it. Thank You!

Thanks, but I will pass on your offer. I appreciate contributions, but the quality of those motivated by "I want to become a contributor and have my name listed there" is usually horrible.


Fix leak of BaseArFragment

Reported as https://github.com/google-ar/sceneform-android-sdk/issues/413
The ViewTreeObserver & listener kept a reference to the fragment after the view & activity were destroyed.

This is part of 1.7


Not compatible with UTF-8

When I try to enter text in Czech or Cyrillic, blog module shows ????? instead of text:
System Environment:
Server information Linux #1 SMP Tue Aug 15 17:50:02 EDT 2017 x86_64
Server software version Apache
PHP version 7.0.24
Memory limit 512M
Max execution time 30
MySQL version 10.1.24-MariaDB-cll-lve
MySQL server localhost
MySQL name vinazbul_thbe550
MySQL user vinazbul_thbe550
Tables prefix tbep_
MySQL engine InnoDB
MySQL driver DbPDO
thirty bees version 1.0.3
Default community theme

Hey,
Thanks for your report.
It looks like thirty bees didn't enforce force full UTF-8 in the database, so instead your database has used the default collation instead.
Since it's pure database stuff that is also where it can be fixed. I recommend executing the following queries:

Set the right default character set on the whole database: ALTER DATABASE <database name> CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci;
Set the right character set on the blog category table: ALTER TABLE `PREFIX_bees_blog_category` CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci;
Set the right character set on the image type table: ALTER TABLE `PREFIX_bees_blog_image_type` CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci;
Finally, set the right character set on the blog post table: ALTER TABLE `PREFIX_bees_blog_post` CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci;

(Replace PREFIX_ with your own prefix)
We will make sure thirty bees and this module will enforce UTF-8 instead of the database default, since that is more suitable for international software and almost every host seems to pick the smallest character set by default.

TB tables are ok, except those related to the beesblog:
bees_blog_category
bees_blog_category_lang
bees_blog_category_shop
bees_blog_image_type
bees_blog_image_type_shop
bees_blog_post
bees_blog_post_lang
bees_blog_post_shop
they are Latin1 and type MyISAM by default
rest of the tables are ok, and type InnoDB
Thanks for the assistance, could you please fix the module for the next releases ?

Apparently solved with pull request #29.
If not, please don't hesitate to re-open this issue.


Add Data Revenue to the blogged list

Added a reference to this blog post.

Link is not loading for me

Nevermind. Just loaded after a browser force refresh

My pleasure. :)


Sprite not visually centred

Issue
The following code results in the sprite being displayed center and bottom, instead of fully centered on the Window Canvas.
import aturtle
w = aturtle.Window(width=640, x=780)
s = aturtle.create_sprite(w.canvas, aturtle.shapes.vector.Star())

Moving / resizing the window leads to it finally ending up centered. Something related to canvas centering and window sizing is going on. Should be a simple fix, hopefully! :)

Fixed in #48, just merged. Closing.


Captcha service ERROR[BUG]

Captcha service ERROR.
I Bought Imagetypez Captcha service. I make config with puppeteer, But I got error: timeout.
Detail issues: https://discourse.openbullet.dev/t/captcha-service-error/1239
Thank you

As you provided no url or so i tried it with some other site:

and also the screenshot in the forum post

🤷 works for me

As you provided no url or so i tried it with some other site:

and also the screenshot in the forum post

🤷 works for me

Check with this captcha: https://alonhadat.com.vn/CaptchaGenerator.ashx?t=kvd

Can you give me the code.

here the one i used:
`BLOCK:PuppeteerOpenBrowser
ENDBLOCK
BLOCK:PuppeteerNavigateTo
url = "https://alonhadat.com.vn/CaptchaGenerator.ashx?t=kvd"
ENDBLOCK
BLOCK:PuppeteerScreenshotBase64
findBy = Selector
identifier = "body > img"
=> VAR @puppeteerScreenshotBase64Output
ENDBLOCK
BLOCK:PuppeteerCloseBrowser
ENDBLOCK
BLOCK:SolveImageCaptcha
base64 = @puppeteerScreenshotBase64Output
=> CAP @solveImageCaptchaOutput
ENDBLOCK
`

I dont know why you did close browser block

just to make sure the browser gets closed after ther config ran - to have no dead browsers in background.
As i also set no status yet or so cause then i could just use this setting

just to make sure the browser gets closed after ther config ran - to have no dead browsers in background.
As i also set no status yet or so cause then i could just use this setting

Can You So Me how Can you Find   identifier = "body > img"
Because I Dont know. I just find form#form1 div.value > img

i gone to the page you gave me - clicked right and selected inspect element.
And then

THANK YOU

@LittlePrinceOB usually after an issue is solved we close the issue. Next time please do it.


Super Text Block?

When reviewing the proposed mockups for the thematic landing pages, I noticed that the text size is different from the "body" of the current text block.
For reference:
https://drive.google.com/open?id=1d5dp-bPJi2e9qRNegCZdZRMKRNLxamdS&authuser=jgamboa%40gbif.org&usp=drive_fs
We need a block to include text in a single column that looks the same as the carrousel and media block with the ability to change the background to an image or different colors.
In this sense, I do not know if the most convenient is to include more options in the current text block: +text size, +include background image, +change background color, +change text color.
Or, create a new block called featured text block that allows us to include this type of options.
The proposed text size is the same as the carrousel block and the media block: text-size: 16px, line-height: 1.8em. Color options: current color: #4e565f and white: #f1f1f1. Background color: include black (#333333) to the current 3 colors available.
If it is just an image, it would be amazing to be able to define its height.

Here it is
text-img block.pdf

Examples from the file

Some text is centered. Other top aligned. Is that an additional setting?

Yep

Home Text-size updated:

Mobile version:

The majority of the images above isn't about this issue - right?

Not directly related. The image block we talked about is different

Please remove the custom style field from this block.
CSS for text should be:
text-size: 16px
line-height: 1.6em
font-weight: 400

I've added the style above (except changing text-size to font-size). If you no longer want the style field in Contentful then feel free to remove it from the model. The website supports it for now, but do not require it, so it can safely be removed from contentful.

Ups. font-size!
And I forgot, but can you include a margin-bottom for text as you had done for the traditional "Text block."
.body-text--markdown p {
margin-bottom: 1.5em;


fix(rbl): typo in rbl check selector

Fixes rbl provider always using httpbl

Hi @fzipi, thanks for this patch!
You are definitely right, that's a typo.
And it's relevant here, where the mentioned argument is used, and this is where the decision is made. It's clearly visible that the method runs the same block, no matter what is the operator argument.
I wasn't able to check the issue #3111 so I don't know whether this solves or not, but I'm going to merge this PR now.
Thanks again!

I think this only solves getting additional information from the provider in https://github.com/owasp-modsecurity/ModSecurity/blob/6217b4ec1eb7bce6d48716842d904caafc99c8ec/src/operators/rbl.cc#L182 method. The DNS query is not changed.


Initial support for private chain operation mode

Closes https://github.com/CasperLabs/product/issues/53
Closes https://github.com/CasperLabs/product/issues/54
Closes https://github.com/CasperLabs/product/issues/55
Closes https://github.com/CasperLabs/product/issues/56
This PR brings preliminary support for private chains by introducing multiple chainspec configuration flags that change the behavior of a chain.
These settings are orthogonal to each other; any particular combination (and all other pre-existing settings) is valid for a given network, for a wide variety of possible permutations.

Administrator accounts: by specifying accounts in a [[administrators]] section of accounts.toml accounts with special privileges are created and later referred to as 'administrative accounts'
core.allow_auction_bids disables add_bid, delegate entrypoints in auction contract if set to true
highway.compute_rewards rewards 0 tokens after each switch block. This means no new tokens are minted and validators aren't gaining more weight.
core.allow_unrestricted_transfers if set to false, the normal user can't send tokens to other normal users; the normal user can transfer only to the administrator; either source or target has to be an admin.
core.refund_handling defines how refunds are computed.

refund_handling = { type = "Refund", refund_ratio = [1, 1] } means 100% of payment_amount - gas_spent is refunded.
refund_handling = { type = "Refund", refund_ratio = [0, 100 ] } doesn't refund anything
Refund mode requires that the fraction specified is proper fraction (that is refund_ratio <= 1)

core.fee_handling defines how gas spent is processed after deploy is executed.

fee_handling = { type = "Accumulate" } creates special rewards purse in the mint system contract where fees are accumulated into
fee_handling = { type = "PayToProposer" } is a default setting for a public chain - rewards are transferred to block's proposer.
fee_handling = { type = "Burn" } fees are burned.

bors try

bors try


Autonomous

I have an autonomous, but I need to test it on our practice field so adjust it to work. If we get that soon enough I'll try to make the more advanced version.

its all working perfctly (exept the bucket being weak becaaue low batery) we just need to put in on a fiekd to adjust the fina 45* strafe elength

Will this ever be done?

finished testing on the field and it is perfect now


Wordmodels component title does not scale with viewport

This probably needs to be wrapped in a <container>: right now, a smaller viewpoint means that the buttons to switch back to search view (right of title) is hidden.

This seems to have been fixed in the meantime.


Add root saga docs file.

#1316
Root Saga docs.

Thanks for your great work!

Thank you @Andarist. I'm just starting to do more open source work, thanks for all your feedback and your responsiveness 😄


Add id to sidecard component

Add id to sidecard component

I think you're using two different accounts Shreyas? Not sure if you see the icons?

yea I'm ok to be using my normal github for this :)


Security Checkup (Software Management incl. Plugin Framework)

Entrance point: CIT-361 Questionare

Heya! You've linked a seemingly internal ticket, can you please update this issue with the information therein or otherwise make it public as right now one cannot access the link.
Thank you!


Update omnifocus to 2.8.2

After making all changes to the cask:

[x] brew cask audit --download {{cask_file}} is error-free.
[x] brew cask style --fix {{cask_file}} left no offenses.
[x] The commit message includes the cask’s name and version.

Verified locally due to… ah, you know what it is.

LOL


added mobile wedding web page

created wedding folder in client side
added .git ignore (had a comment)
will be refactored to polymer

review please.. T-T


404 https://nimiq.com/developer-reference

Hello,
Was trying to access your dev reference, but Im getting a 404 since this morning.
Also I was curious to know what do you use to generate your documentation (I've seen it last week and it looked really nice)

was able to access : https://nimiq-network.github.io/developer-reference


🚀 Feature: Switch to Next.js app directory

Bug Report Checklist

[X] I have tried restarting my IDE and the issue persists.
[X] I have pulled the latest main branch of the repository.
[X] I have searched for related issues and found none that matched my issue.

Overview
Next.js 13.4 makes the app directory stable. Let's update Next.js to the latest version & use the app directory! 🙌
I'd like to take this on as a fun exercise to help me re-familiarize myself with the app directory.
Additional Info
No response

Ah, this was done in https://github.com/OpenContributionsProject/opensourcecontributionssite/issues/114 🚀


Use accelerate for osx-arm64

Closes #52 and #55

Checklist

[X] Used a personal fork of the feedstock to propose changes
[X] Bumped the build number (if the version is unchanged)
[X] Reset the build number to 0 (if the version changed)
[ ] Re-rendered with the latest conda-smithy (Use the phrase @conda-forge-admin, please rerender in a comment in this PR for automated rerendering)
[X] Ensured the license file is being packaged.

@conda-forge-admin, please rerender

@conda-forge-admin, please rerender

Ok, I think this is ready for testing.
All artifacts
We should test these two artifacts in particular:

osx-arm64 py3.8 numpy1.22
osx-arm64 py3.11 numpy1.23

Testing instructions:
Download the artifact and extract it. Then run a command to the effect of
micromamba create -n pytensor-osxarm-test -c conda-forge osx-arm64/pytensor-2.12.3-py311hbee6d41_3.conda

making sure that you don't install the pytensor-base file, since that's the minimal version without BLAS or compilers. Then run python -c "import pytensor.configdefaults; import pytensor.tensor" to check for import errors.
In case you see the error
warning  libmamba Problem type not implemented SOLVER_RULE_STRICT_REPO_PRIORITY
error    libmamba Could not solve for environment specs
    The following package could not be installed
    └─ pytensor 2.12.3 py311hbee6d41_3 is uninstallable because it conflicts with any installable versions previously reported.
critical libmamba Could not solve for environment specs

then try
micromamba config remove-key channel_priority
micromamba create ...
micromamba config set channel_priority strict

>>micromamba create -n pytensor-osxarm-test -c conda-forge osx-arm64/pytensor-2.17.2-py311h20a70b2_1.conda

                                           __
          __  ______ ___  ____ _____ ___  / /_  ____ _
         / / / / __ `__ \/ __ `/ __ `__ \/ __ \/ __ `/
        / /_/ / / / / / / /_/ / / / / / / /_/ / /_/ /
       / .___/_/ /_/ /_/\__,_/_/ /_/ /_/_.___/\__,_/
      /_/

file:///Users/twiecki/Downloads/osx-arm64            1.7kB @   3.0MB/s  0.0s
file:///Users/twiecki/Downloads/noarch             127.0 B @ 841.1kB/s  0.0s
conda-forge/osx-arm64                                8.2MB @   7.6MB/s  1.3s
conda-forge/noarch                                  14.2MB @   8.0MB/s  2.1s
warning  libmamba Problem type not implemented SOLVER_RULE_STRICT_REPO_PRIORITY
error    libmamba Could not solve for environment specs
    The following package could not be installed
    └─ pytensor 2.17.2 py311h20a70b2_1 is uninstallable because it conflicts with any installable versions previously reported.
critical libmamba Could not solve for environment specs

>>micromamba activate pytensor-osxarm-test
(pytensor-osxarm-test) --(10:55:32)--(MacBook-Air-4)--(~/Downloads     )--()
>>python -c "import pytensor.configdefaults; import pytensor.tensor"
(pytensor-osxarm-test) --(10:56:03)--(MacBook-Air-4)--(~/Downloads     )--()
>>python -c "import pytensor; print(pytensor.config.blas__ldflags)"
-L/Users/twiecki/micromamba/envs/pytensor-osxarm-test/lib -lcblas -lblas -lcblas -lblas -Wl,-rpath,/Users/twiecki/micromamba/envs/pytensor-osxarm-test/lib

Seems to have worked!

In the [osx-arm64 py3.8 numpy1.22](https://artprodeus21.artifacts.visualstudio.com/A910fa339-c7c2-46e8-a579-7ea247548706/84710dde-1620-425b-80d0-4cf5baca359d/_apis/artifact/cGlwZWxpbmVhcnRpZmFjdDovL2NvbmRhLWZvcmdlL3Byb2plY3RJZC84NDcxMGRkZS0xNjIwLTQyNWItODBkMC00Y2Y1YmFjYTM1OWQvYnVpbGRJZC84MDQ5NTAvYXJ0aWZhY3ROYW1lL2NvbmRhX2FydGlmYWN0c18yMDIzMTAxNi4zLjFfb3N4X2FybTY0X251bXB5MS4yMnB5dGhvbjMuOC5fX19fY3B5dGhvbg2/content?format=zip) package, the osx-arm64 directory is empty.

Ah! We skip py<3.9, so of course the 3.8 artifact is empty.
Could you please test the py3.9 package instead of the py3.8 package?
Ah, and in addition to making sure the import succeeds, would it be possible to do a quick and dirty benchmark to verify that new=fast and old=slow?
Finally, excellent timing with PyTensor v2.17.3, so let's cherry-pick this into there.

@twiecki, could you please test the py3.9 package instead of the py3.8 package?

Tested and confirm it works.

Ah, and in addition to making sure the import succeeds, would it be possible to do a quick and dirty benchmark to verify that new=fast and old=slow?

I can confirm that accelerate gets installed and used and wasn't before.

Finally, excellent timing with PyTensor v2.17.3, so let's cherry-pick this into there.

Great!

Superseded by #72


Basic Profile Proposal

There are usually identical plugins and profile across different settings. In order to avoid duplicate profile, this feature is proposed. After reading the settings and documentation, a similar function was not found, hence this suggestion is proposed.

Looks like duplicate of #156144
See alse related to settings #176813

/duplicate

Thanks for creating this issue! We figured it's covering the same as another one we already have. Thus, we closed this one as a duplicate. You can search for similar existing issues. See also our issue reporting guidelines.
Happy Coding!


Async await analyze

Integrating the S3 check into analysis finally pushed me over the edge making the a/a transition. The way we need to fetch versions and weave the S3 results in with the rest is just a nightmare within the ELF pipeline.
This is a big change, nonetheless. It went well and the tests highlighted a couple of areas that needed care (continuation on error).
One thing I still need to do is check timing behaviour. ELFs are eager and I need to make sure we don't run things serially now where they weren't before. I think that's taken care of with the task group but I need to confirm timing.

[x] confirm batch timing

We'll want to let this run on staging for a day or two before pushing this to prod.

Interesting, this has even improved performance. Here's a release build ingestion of 25 packages run locally, 3 runs each:
Before:

5.46s
6.44s
6.32s

After:

4.41s
3.61s
3.77s

This is probably not due to the async/await change per se - we should have the same level of concurrency. If I had to guess it's rather due to less overhead passing around structs because of the way I've changed the processing. It's become much more linear (and readable, maintainable).
In ELF land, we pulled in 25 packages and then packages every processing step into an ever larger array of Results until we saved everything in the end. This was in order to be able to continue processing in case of errors.
In a/a I made an initial conversion using the same structure (but didn't time that, might be interesting to do) but then converted to something different when I realised I could ditch the whole shlepping around of the wide array.
Instead, we're now looping over each package and dealing with everything for a single package.
I.e. before

get all packages → pass result to next stage
update repository for all packages → pass result to next stage
update versions for all packages → pass result to next stage
...

Now:

for each package
update repository for that package
update version for that package
...


Story progress

Hi,
I'm loving what you are doing in here and I love to use this package.
But, in my honest opion, I think only missing part of this package is not having a fill animation in progress bar in full screen story view.
When I set displayProgress parameter to true, I can only see the step of the story. I believe that it could be very cool with a fill animation.
If any help is required, I'm willing to help!
Thanks in advance,
Fatih

Will try to add that if I can, but not sure when I can work on it. Meanwhile if you wish to contribute, go ahead, make required changes and submit a PR :)


[WIP] Attempt to implement the Manager Helpers

Description
This attempts to implement Dask-JobQueue manager helper script.
Not yet tested. but I wanted to get this up here so we can talk about it and refine as needed.
Todos
Notable points that this PR has either accomplished or will accomplish.

[ ] Test this on the ARC cluster

Questions

[x] Do these flags look reasonable.
[x] I've set this up to handle a single job submission, will Dask setup multiple submissions as needed?
[ ] What is the correct way to setup environments (e.g. Conda) for the workers once the Dask Job starts them?

Status

[ ] Changelog updated
[ ] Ready to go

This pull request introduces 3 alerts when merging 0d558e283124ae93de0c34243733696b7eab54ad into 57daf9241545e585115556559e9da26a793d0e85 - view on LGTM.com
new alerts:

2 for Unreachable code
1 for Unused import

Comment posted by LGTM.com

I think I fixed all the the obvious syntax issues testing on our local cluster (SLURM-based), this includes having a unified set of inputs and parsing them in the Manager backends. However, I can't get any of the tests to actually execute to completion.
Dask:
Starts up jobs which live for about 2 seconds and then receive the "cancel" command per this line in the slurm output file (to stdout, this is the complete log file):
slurmstepd: error: *** JOB {slurm job id} ON {node} CANCELLED AT 2019-02-25T12:28:18 ***

Two of the slurm jobs appear to start nannys, but they are not the first jobs, nor the last ones, just some intermediate jobs (this is also to stdout, and the complete log file):
distributed.nanny - INFO -         Start Nanny at: 'tcp://{ip}:{port}'

so the behavior is very strange. Dask also does not appear to be reporting a heartbeat back.
Parsl:
Spins up a block with workers, all the workers, the manager, the interchange, and the parsl log report starting normally, then nothing happens. They just wait. The heartbeat keeps going and eventually another block is started, but im worried multiple blocks would start and go nuts if I just let it run, and no work is ever returned.
Any ideas here @dgasmith ?

If you look at the logs the workers are unable to connect back to the scheduler and kill themselves off after 10-15 seconds. This is due to the fact that ARC decided eth0 was not a cool name so they used bond0.4049/bond0.4002 for their interface ID. It doesn't appear Parsl can change the interface name (which also mean no ib0/infiniband) unfortunately.

@Lnaden Looks like one combo is generating incorrect code, I can patch this tomorrow if needed.

I can fix it

I can fix it

That should fix it. dedent() doesn't like \n chars as part of the sting, so I had to escape them.
Yay tests!


Browser agnostic Baseline site & content

Most of the content was written by @rachelandrew and is pulled from https://web.dev/baseline and made to be browser agnostic. This content is not meant to replace the /docs folder, but to create a landing page that we can point web developers to that explains What is Baseline, How to use Baseline, and makes the Baseline icons and logos available for their use.
You can see the current draft content at https://petele.github.io/web-features/
This uses/d the default Minimal theme, with updates from @meyerweb to use CSS Grid, RWD, and font-size relativity.

I tried to fork in order to make some CSS upgrades and could not for the life of me figure out how to get gh-pages to come with the fork, or be created after I forked, which kept me from GH Paging the preview site to work on and then submitting a pull request.
So… how would you like me to suggest the CSS upgrades?  (Pointers to how to make the Pages preview work in a fork are welcome too.)

I tried to fork in order to make some CSS upgrades and could not for the life of me figure out how to get gh-pages to come with the fork

Ugh, yay. I think you may have to fork my fork, then go from there, which sounds like way more of a pain than it should be. To make it easier, if you want to either send the suggestions as comment, or email them to me, I can make that work. Or if you want to send me an updated file(s) by email, that works too.
I'll also add a readme to this folder with more info about how to build locally, which should work once this has been merged.

I tried to fork your fork, but maybe I did it wrong?  I dunno man, git is a land of infinite mystery to me.
Anyway, this is what I came up with to change or add so far (comments indicate things to remove outright):
.wrapper {
  width: 61.5em;
  display: grid;
  grid-template-columns: 19.25em auto;
  gap: 0 6.5em;
}

header {
  /* float: left; */
  width: 19.25em;
  grid-column: 1;
}

section {
  /* float: right; */
  grid-column: 2;
  padding-block-start: 1.33em;
}

It’ll need some responsiveness but let’s see what those changes look like first.

@meyerweb - I've added instructions for building locally. You'll need to clone my repo, then follow the instructions in the README.md should work.
In the mean time, I'll add the changes you just made.

@meyerweb - 100% agree on Git, there are days where I just delete my branch and start over. Sigh. One thing, you'll want to use the pages branch, not the gh-pages branch, which confusingly also exists in my repo.

incredibly, it still doesn’t work (not that I blame you, just letting you know).  I went to petele:pages and cloned it locally via git clone git@github.com:petele/web-features.git.  Here’s the directory listing of what I got, showing a complete lack of /gh-pages and its various resources:
drwxr-xr-x   29 emeyer  staff     928 Aug 29 16:30 .
drwxr-xr-x   30 emeyer  staff     960 Aug 29 16:30 ..
drwxr-xr-x   13 emeyer  staff     416 Aug 29 16:30 .git
-rw-r--r--    1 emeyer  staff      43 Aug 29 16:30 .gitattributes
drwxr-xr-x    6 emeyer  staff     192 Aug 29 16:30 .github
-rw-r--r--    1 emeyer  staff     243 Aug 29 16:30 .gitignore
-rw-r--r--    1 emeyer  staff       3 Aug 29 16:30 .node-version
-rw-r--r--    1 emeyer  staff       6 Aug 29 16:30 .nvmrc
-rw-r--r--    1 emeyer  staff     329 Aug 29 16:30 .prettierignore
-rw-r--r--    1 emeyer  staff       3 Aug 29 16:30 .prettierrc
drwxr-xr-x    3 emeyer  staff      96 Aug 29 16:30 .vscode
-rw-r--r--    1 emeyer  staff    5899 Aug 29 16:30 2022-backgrounder.md
-rw-r--r--    1 emeyer  staff   16532 Aug 29 16:30 GOVERNANCE.md
-rw-r--r--    1 emeyer  staff   11357 Aug 29 16:30 LICENSE.txt
-rw-r--r--    1 emeyer  staff    1941 Aug 29 16:30 README.md
drwxr-xr-x    7 emeyer  staff     224 Aug 29 16:30 docs
-rw-r--r--    1 emeyer  staff     674 Aug 29 16:30 eslint.config.js
drwxr-xr-x  925 emeyer  staff   29600 Aug 29 16:30 features
drwxr-xr-x   45 emeyer  staff    1440 Aug 29 16:30 groups
-rw-r--r--    1 emeyer  staff    7522 Aug 29 16:30 index.ts
-rw-r--r--    1 emeyer  staff  151313 Aug 29 16:30 package-lock.json
-rw-r--r--    1 emeyer  staff    2321 Aug 29 16:30 package.json
drwxr-xr-x    4 emeyer  staff     128 Aug 29 16:30 packages
drwxr-xr-x    3 emeyer  staff      96 Aug 29 16:30 schemas
drwxr-xr-x   13 emeyer  staff     416 Aug 29 16:30 scripts
drwxr-xr-x   13 emeyer  staff     416 Aug 29 16:30 snapshots
-rw-r--r--    1 emeyer  staff   19676 Aug 29 16:30 towards-features.md
-rw-r--r--    1 emeyer  staff     221 Aug 29 16:30 tsconfig.json
-rw-r--r--    1 emeyer  staff    2859 Aug 29 16:30 types.ts

So the Gemfile’s missing, which means bundle has nothing to work with, etc., etc.  It weirds me out that whether I fork or clone your repository, that directory just doesn’t make it over!

Did you do a git checkout pages?  I think you need to do that in order to switch to that branch once you've cloned the repo.

Did you do a git checkout pages? I think you need to do that in order to switch to that branch once you've cloned the repo. Then, you should see the /gh-pages/ folder.

DOH!  I hereby grant myself ALL the facepalms.  Thank you.

I really like the content. Thank you for getting this started.
A general comment I have about the PR though, is that it comes with a lot of new files, more than I would have expected. Seems like more code than we really need for a simple static site.
I'm not a huge fan of using Ruby/Gems/Jekyll here as it introduces a new dependency. Maintainers of this repo already have node/npm (since it's how we manage deps and build), so I would have preferred to stick with this if possible (eleventy seems like a good choice here for example).
Also, do we need to load a font file? I happened to have Noto Sans installed locally, so there's no perf hit for me. But, seeing how close to a system UI font it looks, and that our website is a simple information one, where design isn't super important, I would ask that we consider just using a system font instead.
Also, do we need to use Sass here? Given that we document the web platform, I would love it if we did an effort to use the platform instead of libraries. Scanning quickly through the code, I don't see obvious usage of Sass features here. Seems like we could just use CSS straight up.
Finally, the theme we use seems to be coming with a lot of CSS code, which, seeing the rendered site, feels surprising. I wouldn't expect us to need ~600 lines of CSS code for our content, which is mostly headers, paragraphs, and links, and a bit of complexity for the menu. (the Coverage tool in DevTools shows me 86% of unused CSS in style.css). Can we replace with a single CSS file with just the styles we need?

@captainbrosset - I completely understand your concern. As you mentioned, the site is based on GitHub pages and uses Jekyll, which is provided by the GitHub infrastructure, and includes a set of pre-defined themes/templates. That reduces the number of dependancies we need to keep up to date, and made creating the site much easier. To get something out somewhat quickly, I used the minimal theme which is provided by the infrastructure. I've used eleventy before, and yes, it is a good option, but would have had a higher complexity level for build/deployment, maintenance, and so forth.  I felt this was faster, and there were less potential things to break.

Also, do we need to load a font file?

This came from the theme, I'm happy to take PRs if you want to do the work to pull it out. I did add font-display: swap to ensure that there is no rendering hit if the font isn't available and needs to be loaded.

Also, do we need to use Sass here?

It comes for free as part of the GitHub Pages infrastructure, and was used as part of the template.

theme we use seems to be coming with a lot of CSS code

There are a lot of things in the template that could be cleaned up, we're not using a lot of the styling provided, but I kept it in so it was there if needed in the future. Most likely one of the biggest is the unused pieces is the code highlighting functionality, which I do suspect we'll want to include at some point, and taking that out now will cause headaches later. And even without cleaning up the (S)CSS, the entire landing page is about 30k, with the CSS file landing at only 2.2k.
For this PR, I focused on getting something up that looks good and is functional today, with as much flexibility for the future as possible.

I'm going to start on an actual content review after this but first some preliminaries:
I agree with @captainbrosset that the new dependencies are a problem and spooked me a bit, as the person reviewing nearly all the Dependabot PRs of late. I am OK with having it as a short-term thing, provided we have at least a vague plan for what follows. I know GitHub sort of blesses Jekyll as a way to do this, but the context switch and (at least in my experience on macOS) frequent local development breakages makes the tools somewhat unattractive to me.
One way to cope with this: if someone is willing to commit to reviewing such a PR (or a series of PRs), I'd be willing to port this over to something a bit more familiar (like Astro or the docs-specific Starlight) after we've landed the initial Jekyll site. If we're not committed to pixel-perfect equivalence, then we could probably get it done fairly quickly using some different Lego bricks.
In the mean time, I'll have a look at the content. I think it's important that we have something like this, so I won't hold up merging on the tools per se, but I do want to have some idea of where we're headed when we do land this.

At the risk of being the naysayer here, I don't see the value of merging a somewhat large Jekyll-based infra quickly here, fully knowing that we don't want to support it later and want to change it for something else soon.
To me, the right thing to do in this PR is to focus on the actual content (which is great, and which Daniel has made a bunch of comments about), put it into the /docs/ folder for now, and point people to that. My recollection is that github_pages can be setup to serve *.md files located under the /docs/ folder with just one configuration change in the repo, and no additional files.
I agree with the content direction and the stated goal to own the Baseline landing page. I just don't see the urgency for merging this PR as is.

@captainbrosset - if I switch this to Eleventy, will that get you on board?

@ddbeck & @captainbrosset - if I switch this to Eleventy, will that get you on board? I think I can make the change(s) within about an hour or so...

For my part, yes.

I've moved this to use 11ty, and removed the SCSS dependancy. Adding 11ty added 3 new packages and required some changes to the tsconfig.json files so that they ignore node modules.
I've integrated all of the suggestions & changes from @ddbeck and @captainbrosset.
I believe we should be good to go now.

@ddbeck - As requested, I've moved files into a separate folder, created a separate package.json, etc.
@jgraham - Removed the link as requested.


V3 Repo update

This PR does the following:

Prepares the repo for v3 of the DS.
Updates the url to use /v3 in its path and updates links to point to new version where applicable.

How has this been tested?
Locally.
Accessibility concerns or updates

N/A

Checklist:

[ ] I have updated the Storybook documentation accordingly.
[ ] I have added relevant accessibility documentation for this pull request.
[ ] All new and existing tests passed.

Front End Review:

[ ] Review the Vercel preview deployment once it is ready.

Vercel will break because we need to update the script. This is okay for now and will fix this once this PR gets merged into the feature branch.

The latest commit looks good @bigfishdesign13


Add .tpl suffix to files with <...> placeholders rather than updating them in place

Context
Currently we ask the project user to update certain files with placeholders such as the project-config and app-config's main.tf files, as well as the s3 backend configurations in the account, build-repository, and environment main.tf files. We ask the project user to update these files in place.
This ticket proposes to add the .tpl to the files with placeholders, and instead ask project users to copy and/or rename the .tpl files. The advantage of this approach is it will make it easier to pull updates from template-infra without overwriting the project's changes. And this further will make it easier to set up automated tests (#138)
Files to do this with:

all main.tf files with <...> placeholders, including:

account main.tf
build-repository main.tf
envs/*/main.tf

all files with commented out items, including:

cd.yml
Makefile
ci-infra.yml

As I'm refining this, I'm not sure this is such a good idea after all.


[WIP] multi-select pattern

Describe your changes
Experimentation of patterns to enable multi-select
Storybook link

Checklist

[ ] Read and check your code before tagging someone for review.
[ ] Run yarn format
[ ] Run yarn lint in the root of the repository to ensure tests are passing
[ ] Run yarn test to ensure tests are passing. Run yarn test -u to update any snapshots tests.
[ ] Add necessary tests
[ ] Run yarn changeset to create a changeset file
[ ] Write documentation (README.md)
[ ] Create stories for Storybook

For new components...

[ ] Preconstruct entrypoint has been created
[ ] Changeset file includes a minor
[ ] Export components for docs site and Playroom (docs/components/designSystemComponents.tsx)
[ ] Add snippets to Playroom (docs/playroom/snippets.js)
[ ] Add pictogram to Docs (docs/components/pictograms/index.tsx)

Closing in favour of #993


Add no-default-features yml workflow

Following up on https://github.com/microsoft/windows-rs/pull/3047#discussion_r1605448388 where @dpaoliello suggested we test crates with no default features.

@ChrisDenton here's some more fallout from the unexpected_cfgs thing.
https://github.com/microsoft/windows-rs/actions/runs/9207820449/job/25328694260?pr=3053

Actually looking closer it might be an unrelated nightly change.

Yeah, I think it's basically saying that unused_qualifications is redundant because it's already being set in rust_2018_idioms.

Aside: lint changes have been exhausting recently.

Yes, really losing the value for me.

Oh, looks like you were right the first time. It seems that any group has to be priority -1 even if it doesn't include the lint.

Yep, that's super confusing.


massload load twice

Hi Ivan,  I have a jstree using ajax search, it work fine, the ajax request return matched node's parent ids, the jstree load and open each of them. Then I think I can use then massload plugin to load them in one request, it also works, but when I inspect the network activity, I see the massload url was been loaded twice.
I have tried set the children and state property in the returned json to avoid this issue, but it doesn't work. I also find if I opened any node before search, this issue won't happen, in other words, this issue only happen when search before any node has been open.
Thank you for attention!

That is because with massload configured your "regular" data (the initial one for the tree) passes through massload (especially if you have the state plugin loaded). Do the two calls happen after searching? Could you please open the network panel while refreshing the page and confirm that the two calls only happen after searching, so that I can debug?

Thanks for reply!
Yes, I am sure that the two call only happen after searching, and I didn't use the state plugin, also I didn't do anything to trigger the load_all event.
I find out that without massload, jstree load nodes more intelligent. If I return 5 node in search result, but if one or more of this 5 nodes has been loaded where I expand it manually, then jstree just load the rest of them one by one, ordered by the tree level; but with massload, it seems doesn't check which nodes has been loaded, just load all the nodes in search result.

I may have some insight into massload issues.
First I will explain one cause everyone should check (at least until a fix is created). I store the path (IDs separated by /) for each node (it makes, for example, searching easier, as I only need to retrieve the path to know all parents - without consecutive database queries). I had a small error in the SQL query doing the paths update (when moving a node), which caused the path to not be updated properly.
As a result it was sending to jstree a node that jstree could not open so this._data.massload was not empty at the next search, and because of that (and the fact that jstree could not retrieve that node) it was falling back into core.data() calls. So I have added at the start of the search function this._data.massload = {}; to reset the previously loaded data (because even after I fixed the path I did observe that after search is completed massload() is fired again twice, which again makes this._data.massload not empty). After that hack the search consistenly uses massload() rather than the core.data().
I suppose that in the complete callback from _load_nodes this object should be emptied in case delete this._data.massload[obj.id]; isn't performed on all returned data :)
But now I was left with the consecutive firing of the massload() after the initial one. So I figured something is wrong with is_callback because in massload plugin there is this:
if(is_callback && !$.isEmptyObject(this._data.massload)) {
so when it iterates through the results is_callback is true and the object is not empty, but when it finishes with the iteration the object is empty and is_callback is always true anyway, so the code below that is executed again until massload object is not empty. So after that if I wrapped the code below in if(!is_callback) { and changed the is_callback parameter on the search call to _load_nodes into false (so that at the initial call this code is executed), and now it all seems to work properly.
Sorry if I am not making myself clear enough :D it is a bit convoluted.

This could be a temp solution, for me it works consistently.
Define a new hack plugin:
    $.jstree.plugins.reset_massload = function (options, parent) {
        this.reset_massload = function () {
            this._data.massload = {};
        };
    }

then make sure you define it in plugins as 'reset_massload', and then on the search.jstree event (fired after search is complete) add the reset call:
    .on('search.jstree', function (event, data) {
        data.instance.reset_massload();
    })

and now I always get one massload call every search.

Thanks!


freepad supported in deconz

supported in deconz: https://github.com/diyruz/freepad#support

that repro just removed deconz from the support list after i asked about it, so dont merge this one


Fix a typo in "Related Resources" doc page

Oh man these are awesome @gamtiq ! Thank you so much! Still traveling but I can’t wait to get these merged & released 😎

Thank you for comprehensive and useful documentation!


Website: update build script to install dependencies

For #

Background
If examples/gallery or playground are cleaned , website build fails, update the build script to install dependencies for these folders.

Change List

Coverage decreased (-2.9%) to 79.804% when pulling cb08135708169c79644cfcc2f768e479b9e6b2ae on FixWebsiteBuildScript into 00bf5fb988540ffa5ba8e0e8ea647b4de8b37452 on master.


How To: inspect request body

I have a module which ultimately uses fetch to post data to a resource. I would like to use fetch-mock to inspect the request body to assert the transformation that was to have happened in my module happened.
Currently I am doing:
const result = fetchMock.mock(url, 200);

then I inspected fecch-mock's internals to write this function to pluck the request object's body:
const getPostedDataFromFetchMock = (result) => {
  return JSON.parse(result._calls[0][1].body);
};

but this feels too hard, and I'm hacking since i'm accessing underscore property and unidentified 2-d array ref (and indeed my approach broke on recent upgrade to v7.0.6.)
is fetch-mock the wrong tool?  It doesn't seem like you are selling this type of inspection.
Thanks!

thanks @wheresrhys. i'm feeling a bit thick in the head ATM. now that I understand what .lastOptions() is, perhaps it is not necessary to add lastBody(), lest you add last* for everything on the request (method, headers, etc).  i am duly educated (RTFM), and would not press for adding lastBody() on my account.  Thanks for the help and the for fetch-mock.

Sorry to reopen an old issue, but has body been removed from the MockOptions being returned by .lastOptions()? Can't seem to find a way to grab the body of the last request anywhere.
For what it's worth, I'm using Typescript

@gunadic, I was seeing an empty body via JSON.stringify() until I started testing the body as a FormData object:
const expected = { "success": true, "id": itemId };
fetchMock.post(url, expected);
resourceHelpers
  .addResourceFromBlob(
    blob,
    itemId,
    folder,
    filename,
    MOCK_USER_REQOPTS
  )
  .then((response: any) => {
    expect(response).toEqual(expected);
    const options: RequestInit = fetchMock.lastOptions(url);
    expect(typeof options.body).toEqual("object");
    const form = options.body as FormData;
    expect(form.get("resourcesPrefix")).toEqual(folder);
    expect(form.get("fileName")).toEqual(filename);
    done();
  }, done.fail);

I'm using TypeScript 3.4.5 and tried multiple versions of fetch-mock from 5.13.1 to the latest.

Sorry to reopen an old issue, but has body been removed from the MockOptions being returned by .lastOptions()? Can't seem to find a way to grab the body of the last request anywhere.
For what it's worth, I'm using Typescript

I came looking to ask this exact question. There is no body field on the MockOptions definition, is there any reason why?

@danielwilliams94, this works for me:
fetchMock.post(updateUrl, expected);
getRequest(update)
  .then(() => {
    const options: fetchMock.MockOptions = fetchMock.lastOptions(updateUrl);
    const fetchBody = (options as fetchMock.MockResponseObject).body;
    console.warn(JSON.stringify(fetchBody,null,2));
        :                 :                   :
    done();
  }, done.fail);

Sorry to re-open this, but I am also struggling to read the request body from a post request
created using using ky`s post() method.
I have inspected that ky actually uses the passed (mocked) body as payload.
Anyhow, after the fetchMock catches the post request, lastOptions().body is undefined.
const mockedPayload = { hello: 'world' };
const mockedResponse = mockedPayload;

fetchMock.post('someRoute', mockedResponse);

const response = await ky.post('someRoute', {json: mockedPayload}).json();
const fetchOptions = fetchMock.lastOptions();

expect(fetchOptions.headers['content-type']).toContain(
  'application/json'
);
expect(fetchOptions.method).toEqual('POST');

expect(fetchOptions.body).toMatchObject(mockedPayload); // This fails. Jest throws:
// Matcher error: received value must be a non-null object

expect(response).toEqual(mockedResponse);

Any idea what went wrong here?
I am using<EMAIL_ADDRESS>
@sholladay Sorry for accidently posting this in https://github.com/sindresorhus/ky/issues/226, I mixed up browser tabs. I removed the encapsulation of ky within the test file, I still see the same error.

For anyone landing here, you get the body with const {body} = fetchMock.lastOptions(updateUrl); and you then have to use body.get() because a FormData is not a normal object so you can just inspect it. you have to get the specific value you want.


Unknown error: BAD_SESSION / Failure in verify PDPKA5 | Reset not working: "Link expired"

Tried to reset my account using the paper key but devs revoked it.
Tried to reset my account many times but always the same error: "Link expired."
Tried to email developers but no reply.
I have joined back in 2015.
My account: https://keybase.io/valentino

Thanks.

Waited another 7 days. Same error: Link expired.

Any updates?

bump


Fix link for TLS bootstrapping

The first commit do the minimal reformat for implementation-details.md file. (Only adjust spaces) (It's done by #34381)
The second commit replaced two invalid links for TLS Bootstrapping. (ref: PR #33130)
Checked visually the same (with intended space changes).
Preview: https://deploy-preview-34722--kubernetes-io-main-staging.netlify.app/docs/reference/setup-tools/kubeadm/implementation-details/
Production: https://kubernetes.io/docs/reference/setup-tools/kubeadm/implementation-details/
/kind cleanup
/label tide/merge-method-squash

I believe https://github.com/kubernetes/website/pull/34381 is already fixing one of the pages, but it is not reviewed yet.

Oh, sorry for missed that.
Hold until #34381 merged and rebase this one.
/hold

The PR #34381 is finally merged.
/unhold
The reformat is already done, this PR now have only one commit.
/remove-label tide/merge-method-squash

/lgtm
/approve


SCRCPY wifi

Environment

OS: Mac Os 14.4.1
scrcpy version:
installation method: Terminal brew install scrcpy
device model: Redmi note 12
Android version: 14

Good morning
I have a question regarding SCRCPY
If I don't let SCRCPY connect via USB to my computer, when I start my computer in the morning, I have to reconnect SCRCPY via USB and redo the adb tcpip 5555 procedure to be able to use SCRCPY via WIFI
Is there a way when I start my computer that SCRCPY detects and works automatically over Wi-Fi

You must execute adb tcpip 5555 on every phone reboot. But not on computer reboot.

Ok but my phone must always be connected to my computer!

If you don't want to connect over USB at all, as mentioned in the doc, from Android 11 you can pair wirelessly: https://developer.android.com/tools/adb#wireless-android11-command-line

If I type in my terminal adb pair <IP_ADDRESS>:5555 I don't receive any code association requests on my phone !

Did you enable wireless debugging?
Please follow the steps here, I cannot help more, it's the official Android documentation: https://developer.android.com/tools/adb#wireless-android11-command-line

Good morning
In the morning, when I start my computer, and I want to connect to SCRCPY directly via Wi-Fi, I have to each time in my terminal type adb connect <IP_ADDRESS>:5555 THEN scrcpy -s <IP_ADDRESS>:5555 to connect to my phone via wifi.
Why if I directly type scrcpy -s <IP_ADDRESS>:5555 do I not connect via Wi-Fi to my phone?

scrcpy -s XXXX just selects a device listed by adb devices (like adb -s XXXX shell would do), it does not create any new connection.
So if your device is not connected, you must connect using adb connect XXXX beforehand (so that it is listed by adb devices).
But instead, you can use scrcpy --tcpip=<IP_ADDRESS>:5555 and it will connect if necessary. See https://github.com/Genymobile/scrcpy/blob/master/doc/connection.md#tcpip-wireless

But instead, you can use scrcpy --tcpip=<IP_ADDRESS>:5555 and it will connect if necessary.

With this method it works really well. Thank you so much


Disable pagination in the report

Do what the title says

The report shows all the repositories by default, no pagination. Fixed in #51


babelRelayPlugin dose work with storybook

I try to use storybook in f8app,which is an app provided by Facebook for tutorial purpose.
I get this:
ERROR in ./.storybook/config.js Module build failed: ReferenceError: Unknown plugin "./server/schema/babelRelayPlugin" specified in "foreign" at 0, attempted to resolve relative to "/Users/Kathy/f8app/.storybook"     at /Users/Kathy/f8app/node_modules/babel-core/lib/transformation/file/options/option-manager.js:177:17     at Array.map (native)     at Function.normalisePlugins (/Users/Kathy/f8app/node_modules/babel-core/lib/transformation/file/options/option-manager.js:153:20)     at OptionManager.mergeOptions (/Users/Kathy/f8app/node_modules/babel-core/lib/transformation/file/options/option-manager.js:245:36)     at /Users/Kathy/f8app/node_modules/babel-core/lib/transformation/file/options/option-manager.js:254:17     at /Users/Kathy/f8app/node_modules/babel-core/lib/transformation/file/options/option-manager.js:316:22     at Array.map (native)     at OptionManager.resolvePresets (/Users/Kathy/f8app/node_modules/babel-core/lib/transformation/file/options/option-manager.js:305:20)     at OptionManager.mergeOptions (/Users/Kathy/f8app/node_modules/babel-core/lib/transformation/file/options/option-manager.js:253:29)     at OptionManager.init (/Users/Kathy/f8app/node_modules/babel-core/lib/transformation/file/options/option-manager.js:360:12)  @ multi preview
Please give me a hint.

React storybooks works with UI components. It can't handle Relay components. You have two options here.

Expose the original UI component from the module ( Before it wraps with Relay's higher order component)

Stub the Relay container: https://voice.kadira.io/stubbing-react-containers-for-testing-11bcd537e586#.pu21eacy6

I am having the same issue. The problem is in the .babelrc file:
{
  "passPerPreset": true,
  "presets": [
    {
      "plugins": [
        "./build/babelRelayPlugin"
      ]
    },
    "react",
    "es2015",
    "stage-0"
  ]
}

When I remove the "./build/babelRelayPlugin" line from plugins, storybook runs just fine (I used option 1 to expose original UI component). The problem is, the babelRelayPlugin is needed for the actual app to work.
Is there a way to exclude this plugin for storybook but keep it for the actual app?

@rohit-ravikoti You can create a custom .babelrc file for storybook. See: https://github.com/kadirahq/react-storybook/blob/master/docs/configure_storybook.md#custom-babel-config
I hope that'll work.

I think the bigger problem here is that babel plugins are being resolved relative to each file.
I'm running into the same sort of error message with a project-specific plugin ("plugins": ["./plugins/babel-code-example.js"] - but only when running Storybook. Running Webpack without stroybook behaves as expected.
For those blocked by this issue, I found a workaround, but it's terrible :)
plugins: [
  "babel-core/../../plugins/babel-code-example.js"
]

This relies on babel-core (you can use any other module, but I like babel-core because it's Babel config and thus likely to be there) being in node_modules, at which point we can traverse paths back to where we want to be. Obviously not an ideal solution, but it does work.

@dallonf I know the pain. Do you know anyway to fix that. May be changing our webpack config?
Would love to see a PR.

A solution that worked for me - I created a .storybook/.babelrc with {"extends": "../.babelrc"} and it seems to fully respect relative paths from the parent/project .babelrc file.

I think we can close this.
@eugene1g mentioned way it how it suppose to be.


Error in dbt run sample model on presto

Please make sure to fill out either the issue template or the feature template and delete the other one!
Issue
Issue description
I'm testing dbt for presto.
Just ran:
$ dbt init test
$ cd test && dbt run

Results
Running with dbt=0.13.0
Found 1 models, 0 tests, 0 archives, 0 analyses, 96 macros, 0 operations, 0 seed files, 0 sources

13:18:07 | Concurrency: 4 threads (target='dev')
13:18:07 |
13:18:07 | 1 of 1 START view model data_warehouse.my_first_dbt_model............ [RUN]
13:18:09 | 1 of 1 ERROR creating view model data_warehouse.my_first_dbt_model... [ERROR in 1.05s]
13:18:09 |
13:18:09 | Finished running 1 view models in 7.50s.

Completed with 1 errors:

Runtime Error in model my_first_dbt_model (models/example/my_first_dbt_model.sql)
  PrestoUserError(type=USER_ERROR, name=NOT_SUPPORTED, message="Unsupported combination of operations in a single transaction", query_id=20190414_131810_00009_qvqzx)

Done. PASS=0 ERROR=1 SKIP=0 TOTAL=1

System information
The output of dbt --version:
installed version: 0.13.0
   latest version: 0.13.0

Up to date!

The operating system you're running on:
docker image: amazonlinux
The python version you're using (probably the output of python --version)
$ python3 --version
Python 3.7.2

Steps to reproduce
In as much detail as possible, please provide steps to reproduce the issue. Sample data that triggers the issue, example models, etc are all very helpful here.

Thanks for the report @rmgpinto! Do you mind re-opening this issue in the dbt-presto repo? If you could also include the relevant portion of your logs/dbt.log file, that would be very helpful too. I see that the error is Unsupported combination of operations in a single transaction and I'm curious which statements dbt is running that results in this error.
Finally, when you re-open the issue in the dbt-presto repo, can you include your version of Spark? Thanks!


Problem with fonts loading for RapidPhotoDownloader AppImage

I am trying to provide an AppImage package for the Rapid Photo Downloader program, which is a PyQt5-based application that allows to copy and organize pictures from digital cameras.
The current AppImage build scripts can be found on GitHub here (the relevant scripts are bootstrap2.sh and mkappimage). They already allow to generate a working AppImage package, but I have an issue with fonts that is really driving me crazy... When running as an AppImage, the program uses an ugly monospace font instead of the one inherited from the desktop UI theme.
This is how the application should look like under Mint 17.2 with the default Mint-X theme:

and this is how the program looks like when executing the AppImage:

I have used strace to check which font files are actually accessed by the application , and here is the result (left is the normal application, right is the AppImage):

As one can see, the AppImage falls back to the MonoSpace font instead of loading the DejaVuSans.ttf one. Note that other fonts are loaded correctly...
Does anybody have an hint of what could be the cause of this, or has anybody already run into a similar issue?
Thanks in advance!

I'm clueless... trial end error is your friend here. I would start by sequentially deleting all font-related libraries from the AppImage, and retrying.


After enabling BVH in 2d physics, set monitorable to true for more than 4000 area through the Physic2DServer will cause an instantaneous permanent huge drop in performance

Godot version
3.4.rc(62f56af694)
System information
Windows 11, RTX 2060, GLES2/GLES3
Issue description
After enabling BVH in 2d physics, set monitorable to true for more than 4000 area through the Physic2DServer will cause an instantaneous and permanent huge drop in performance.
Steps to reproduce
Enable Bvh in 2D physics settings, and then use Physic2DServer to create some areas (more than 4000). Then gradually set monitorable to true for these areas. When the number of active areas reaches 4000 or more, the original 144fps will instantly drop below 15fps, and will drop below 5fps within 3 seconds.
After disabling BVH, the FPS does not start to decrease from 144 until there are 7000 active areas, and until 12000 active areas the FPS are still able to remain above 60.
Minimal reproduction project
I am using a C++ custom module to control the behavior of the area through Physics2DServer, so it may not be possible to provide a minimal project.
But I can guarantee that there is nothing in my module that will affect the physical behavior of Godot, because it simply calls Physic2DServer-related functions. And after many comparative tests, it is confirmed that this problem is caused by BVH
https://user-images.githubusercontent.com/44023235/138574787-dc642e09-616f-4dcc-b443-e22e227bc840.mp4
(In the video, due to screen recording, the base fps dropped to 90-100, but this problem is still very obvious)

I was about to open an issue on this, but after a search I believe this is also the issue I'm experiencing. In my case I am doing it all through the Physics2DServer while the BVH Collision Margin is 1. This results in significantly worse performance than using the Hash Grid.
I worked around this in my project: since all the testing in my game is done by the bullet testing their motion against enemies and enemies never actually collide, using a high collision margin (which I assumed would reduce collision accuracy) seems to have no effect so I can use that to gain back lost performance.
Attached is a video of the performance and the associated MRP for v3.5.beta5.official [815f7fe63]. To test with, apply some of these changes:

Toggle physics/2d/use_bvh
Change physics/2d/bvh_collision_margin 1 and then 20 (0 is the worst case)
Toggle Update Shape Transform Check Box

https://user-images.githubusercontent.com/3820082/171022867-7f0aecfa-7c7d-4f7d-a7d1-1a75e4ade6b0.mp4
bvh-regression-mrp.zip


Ghost roles stuck in ATS anchor room

Description
The anchor room on the ATS has no door and is surrounded by plastitanium walls. If a ghost role spawns in there, they have no way of getting out.
Reproduction

Spawn as a ghost role
You're in the ATS anchor room
Despair

Screenshots

Additional context
This damn room should have a door, an access chute or destructible walls/windows. Why is there an area in the game that cannot be interacted with ?

emisse said it shouldn’t be interacted with, but the real issue at hand is just making sure that ghost roles dont spawn on anything other than the station

emisse said it shouldn’t be interacted with, but the real issue at hand is just making sure that ghost roles dont spawn on anything other than the station

Thats gunna need a few pain exemptions for things like lone op and ninja spawn

Setting up a whitelist system for which grid ID a particular role is supposed to spawn on doesn't sound that complicated. And ninja could just come into the station map with a small ship like every station visitor event.

Setting up a whitelist system for which grid ID a particular role is supposed to spawn on doesn't sound that complicated. And ninja could just come into the station map with a small ship like every station visitor event.

I liked ninja spawning in space

Honestly if ninja ever gets a ship, it should be a disposable 5-tile shittle anyway.

need a thing to distinguish a stations actual main grids from things that it "owns", like cargo shuttle an ats, and shittles you make by splitting a main grid off


Add serviceType and service reference for Chart, Dashboard, Database, Pipeline, Table, and Topic

@harshach, as part of this change, the database field for table entity, and the service field for all the data asset entities have become default fields. It is returned whether fields query param has it in GET requests or not.