Test failed from //tensorflow/cc:gradients_linalg_grad_test on GPU

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Issue Type
Bug
Source
source
Tensorflow Version
master branch
Custom Code
No
OS Platform and Distribution
Linux 20.04 from docker tensorflow/tensorflow:devel-gpu
Mobile device
No response
Python version
No response
Bazel version
5.1.1
GCC/Compiler version
9.4.0
CUDA/cuDNN version
cuda 11.2 cuDNN 8
GPU model and memory
RTX 3090 2*24G
Current Behaviour?
When I test tensorflow under cuda, the GPU and CPU computation precision does not match and the precision error of GPU exceeds the threshold, causing the test to fail.

The same test code can pass in CPU environment.

I'm not sure if this is an operator implementation issue in TF or a CUDA issue, would appreciate any help :)

Standalone code to reproduce the issue
#run_cc_core.sh from official

set -e
set -x

N_JOBS=$(grep -c ^processor /proc/cpuinfo)

echo ""
echo "Bazel will use ${N_JOBS} concurrent job(s)."
echo ""

# Run configure.
export PYTHON_BIN_PATH=`which python3`
export CC_OPT_FLAGS='-mavx'

export TF_NEED_ROCM=0
export TF_NEED_CUDA=1
export TF_CUDA_COMPUTE_CAPABILITIES=8.6

yes "" | $PYTHON_BIN_PATH configure.py

bazel test --config=cuda //tensorflow/cc:gradients_linalg_grad_test

(`--config=opt` also failed)

Relevant log output
Here is the error log:

exec ${PAGER:-/usr/bin/less} "$0" || exit 1
Executing tests from //tensorflow/cc:gradients_linalg_grad_test
-----------------------------------------------------------------------------
2022-07-12 14:35:32.516505: I tensorflow/core/util/util.cc:169] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2022-07-12 14:35:32.517745: E tensorflow/stream_executor/cuda/cuda_blas.cc:2981] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
[==========] Running 10 tests from 1 test suite.
[----------] Global test environment set-up.
[----------] 10 tests from LinalgGradTest
[ RUN      ] LinalgGradTest.Einsum_Transpose
2022-07-12 14:35:32.563180: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  SSE3 SSE4.1 SSE4.2 AVX AVX2 AVX512F AVX512_VNNI FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2022-07-12 14:35:36.818279: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 16045 MB memory:  -> device: 0, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:25:00.0, compute capability: 8.6
2022-07-12 14:35:36.819707: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 22298 MB memory:  -> device: 1, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:5b:00.0, compute capability: 8.6
2022-07-12 14:35:36.822428: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 22298 MB memory:  -> device: 2, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:9b:00.0, compute capability: 8.6
2022-07-12 14:35:36.825100: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 22298 MB memory:  -> device: 3, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:c8:00.0, compute capability: 8.6
2022-07-12 14:35:37.183394: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 16045 MB memory:  -> device: 0, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:25:00.0, compute capability: 8.6
2022-07-12 14:35:37.184359: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 22298 MB memory:  -> device: 1, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:5b:00.0, compute capability: 8.6
2022-07-12 14:35:37.185297: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 22298 MB memory:  -> device: 2, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:9b:00.0, compute capability: 8.6
2022-07-12 14:35:37.186235: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 22298 MB memory:  -> device: 3, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:c8:00.0, compute capability: 8.6
[       OK ] LinalgGradTest.Einsum_Transpose (4672 ms)
[ RUN      ] LinalgGradTest.Einsum_TransposeBroadcast
2022-07-12 14:35:37.245616: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 16045 MB memory:  -> device: 0, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:25:00.0, compute capability: 8.6
2022-07-12 14:35:37.246561: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 22298 MB memory:  -> device: 1, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:5b:00.0, compute capability: 8.6
2022-07-12 14:35:37.247486: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 22298 MB memory:  -> device: 2, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:9b:00.0, compute capability: 8.6
2022-07-12 14:35:37.248417: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 22298 MB memory:  -> device: 3, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:c8:00.0, compute capability: 8.6
2022-07-12 14:35:37.309328: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 16045 MB memory:  -> device: 0, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:25:00.0, compute capability: 8.6
2022-07-12 14:35:37.310255: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 22298 MB memory:  -> device: 1, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:5b:00.0, compute capability: 8.6
2022-07-12 14:35:37.311183: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 22298 MB memory:  -> device: 2, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:9b:00.0, compute capability: 8.6
2022-07-12 14:35:37.312104: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 22298 MB memory:  -> device: 3, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:c8:00.0, compute capability: 8.6
[       OK ] LinalgGradTest.Einsum_TransposeBroadcast (108 ms)
[ RUN      ] LinalgGradTest.Einsum_MatMul
2022-07-12 14:35:37.350102: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 16045 MB memory:  -> device: 0, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:25:00.0, compute capability: 8.6
2022-07-12 14:35:37.351035: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 22298 MB memory:  -> device: 1, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:5b:00.0, compute capability: 8.6
2022-07-12 14:35:37.351955: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 22298 MB memory:  -> device: 2, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:9b:00.0, compute capability: 8.6
2022-07-12 14:35:37.352873: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 22298 MB memory:  -> device: 3, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:c8:00.0, compute capability: 8.6
2022-07-12 14:35:38.658637: I tensorflow/stream_executor/cuda/cuda_blas.cc:1614] TensorFloat-32 will be used for the matrix multiplication. This will only be logged once.
2022-07-12 14:35:38.683804: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 16045 MB memory:  -> device: 0, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:25:00.0, compute capability: 8.6
2022-07-12 14:35:38.684741: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 22298 MB memory:  -> device: 1, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:5b:00.0, compute capability: 8.6
2022-07-12 14:35:38.685664: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 22298 MB memory:  -> device: 2, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:9b:00.0, compute capability: 8.6
2022-07-12 14:35:38.686599: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 22298 MB memory:  -> device: 3, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:c8:00.0, compute capability: 8.6
tensorflow/cc/gradients/linalg_grad_test.cc:50: Failure
Expected: (max_error) < (1e-3), actual: 0.0205651 vs 0.001
[  FAILED  ] LinalgGradTest.Einsum_MatMul (1434 ms)
[ RUN      ] LinalgGradTest.Einsum_MatMulComplex
2022-07-12 14:35:38.786432: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 16045 MB memory:  -> device: 0, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:25:00.0, compute capability: 8.6
2022-07-12 14:35:38.787367: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 22298 MB memory:  -> device: 1, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:5b:00.0, compute capability: 8.6
2022-07-12 14:35:38.788284: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 22298 MB memory:  -> device: 2, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:9b:00.0, compute capability: 8.6
2022-07-12 14:35:38.789199: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 22298 MB memory:  -> device: 3, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:c8:00.0, compute capability: 8.6
2022-07-12 14:35:38.883969: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 16045 MB memory:  -> device: 0, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:25:00.0, compute capability: 8.6
2022-07-12 14:35:38.884917: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 22298 MB memory:  -> device: 1, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:5b:00.0, compute capability: 8.6
2022-07-12 14:35:38.885853: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 22298 MB memory:  -> device: 2, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:9b:00.0, compute capability: 8.6
2022-07-12 14:35:38.886794: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 22298 MB memory:  -> device: 3, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:c8:00.0, compute capability: 8.6
[       OK ] LinalgGradTest.Einsum_MatMulComplex (224 ms)
[ RUN      ] LinalgGradTest.Einsum_MatMulBroadcast
2022-07-12 14:35:39.010302: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 16045 MB memory:  -> device: 0, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:25:00.0, compute capability: 8.6
2022-07-12 14:35:39.011264: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 22298 MB memory:  -> device: 1, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:5b:00.0, compute capability: 8.6
2022-07-12 14:35:39.012205: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 22298 MB memory:  -> device: 2, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:9b:00.0, compute capability: 8.6
2022-07-12 14:35:39.013283: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 22298 MB memory:  -> device: 3, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:c8:00.0, compute capability: 8.6
2022-07-12 14:35:39.094568: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 16045 MB memory:  -> device: 0, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:25:00.0, compute capability: 8.6
2022-07-12 14:35:39.095516: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 22298 MB memory:  -> device: 1, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:5b:00.0, compute capability: 8.6
2022-07-12 14:35:39.096454: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 22298 MB memory:  -> device: 2, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:9b:00.0, compute capability: 8.6
2022-07-12 14:35:39.097393: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 22298 MB memory:  -> device: 3, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:c8:00.0, compute capability: 8.6
[       OK ] LinalgGradTest.Einsum_MatMulBroadcast (209 ms)
[ RUN      ] LinalgGradTest.Einsum_Trace
2022-07-12 14:35:39.217763: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 16045 MB memory:  -> device: 0, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:25:00.0, compute capability: 8.6
2022-07-12 14:35:39.218724: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 22298 MB memory:  -> device: 1, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:5b:00.0, compute capability: 8.6
2022-07-12 14:35:39.219663: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 22298 MB memory:  -> device: 2, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:9b:00.0, compute capability: 8.6
2022-07-12 14:35:39.220599: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 22298 MB memory:  -> device: 3, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:c8:00.0, compute capability: 8.6
2022-07-12 14:35:39.248566: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 16045 MB memory:  -> device: 0, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:25:00.0, compute capability: 8.6
2022-07-12 14:35:39.249511: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 22298 MB memory:  -> device: 1, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:5b:00.0, compute capability: 8.6
2022-07-12 14:35:39.250464: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 22298 MB memory:  -> device: 2, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:9b:00.0, compute capability: 8.6
2022-07-12 14:35:39.251406: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 22298 MB memory:  -> device: 3, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:c8:00.0, compute capability: 8.6
[       OK ] LinalgGradTest.Einsum_Trace (84 ms)
[ RUN      ] LinalgGradTest.Einsum_TraceBroadcast
2022-07-12 14:35:39.300791: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 16045 MB memory:  -> device: 0, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:25:00.0, compute capability: 8.6
2022-07-12 14:35:39.301769: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 22298 MB memory:  -> device: 1, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:5b:00.0, compute capability: 8.6
2022-07-12 14:35:39.302759: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 22298 MB memory:  -> device: 2, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:9b:00.0, compute capability: 8.6
2022-07-12 14:35:39.303709: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 22298 MB memory:  -> device: 3, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:c8:00.0, compute capability: 8.6
2022-07-12 14:35:39.348560: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 16045 MB memory:  -> device: 0, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:25:00.0, compute capability: 8.6
2022-07-12 14:35:39.349539: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 22298 MB memory:  -> device: 1, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:5b:00.0, compute capability: 8.6
2022-07-12 14:35:39.350526: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 22298 MB memory:  -> device: 2, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:9b:00.0, compute capability: 8.6
2022-07-12 14:35:39.351483: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 22298 MB memory:  -> device: 3, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:c8:00.0, compute capability: 8.6
[       OK ] LinalgGradTest.Einsum_TraceBroadcast (124 ms)
[ RUN      ] LinalgGradTest.Einsum_DotProduct
2022-07-12 14:35:39.423936: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 16045 MB memory:  -> device: 0, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:25:00.0, compute capability: 8.6
2022-07-12 14:35:39.424873: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 22298 MB memory:  -> device: 1, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:5b:00.0, compute capability: 8.6
2022-07-12 14:35:39.425802: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 22298 MB memory:  -> device: 2, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:9b:00.0, compute capability: 8.6
2022-07-12 14:35:39.426739: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 22298 MB memory:  -> device: 3, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:c8:00.0, compute capability: 8.6
2022-07-12 14:35:39.444904: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 16045 MB memory:  -> device: 0, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:25:00.0, compute capability: 8.6
2022-07-12 14:35:39.445840: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 22298 MB memory:  -> device: 1, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:5b:00.0, compute capability: 8.6
2022-07-12 14:35:39.446776: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 22298 MB memory:  -> device: 2, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:9b:00.0, compute capability: 8.6
2022-07-12 14:35:39.447707: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 22298 MB memory:  -> device: 3, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:c8:00.0, compute capability: 8.6
[       OK ] LinalgGradTest.Einsum_DotProduct (74 ms)
[ RUN      ] LinalgGradTest.Einsum_OuterProduct
2022-07-12 14:35:39.498038: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 16045 MB memory:  -> device: 0, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:25:00.0, compute capability: 8.6
2022-07-12 14:35:39.499049: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 22298 MB memory:  -> device: 1, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:5b:00.0, compute capability: 8.6
2022-07-12 14:35:39.499978: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 22298 MB memory:  -> device: 2, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:9b:00.0, compute capability: 8.6
2022-07-12 14:35:39.500903: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 22298 MB memory:  -> device: 3, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:c8:00.0, compute capability: 8.6
2022-07-12 14:35:39.551515: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 16045 MB memory:  -> device: 0, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:25:00.0, compute capability: 8.6
2022-07-12 14:35:39.552462: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 22298 MB memory:  -> device: 1, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:5b:00.0, compute capability: 8.6
2022-07-12 14:35:39.553387: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 22298 MB memory:  -> device: 2, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:9b:00.0, compute capability: 8.6
2022-07-12 14:35:39.554318: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 22298 MB memory:  -> device: 3, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:c8:00.0, compute capability: 8.6
tensorflow/cc/gradients/linalg_grad_test.cc:50: Failure
Expected: (max_error) < (1e-3), actual: 0.0340652 vs 0.001
[  FAILED  ] LinalgGradTest.Einsum_OuterProduct (104 ms)
[ RUN      ] LinalgGradTest.Einsum_TwoInputReduction
2022-07-12 14:35:39.602237: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 16045 MB memory:  -> device: 0, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:25:00.0, compute capability: 8.6
2022-07-12 14:35:39.603175: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 22298 MB memory:  -> device: 1, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:5b:00.0, compute capability: 8.6
2022-07-12 14:35:39.604102: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 22298 MB memory:  -> device: 2, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:9b:00.0, compute capability: 8.6
2022-07-12 14:35:39.605027: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 22298 MB memory:  -> device: 3, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:c8:00.0, compute capability: 8.6
2022-07-12 14:35:39.703831: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 16045 MB memory:  -> device: 0, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:25:00.0, compute capability: 8.6
2022-07-12 14:35:39.704745: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 22298 MB memory:  -> device: 1, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:5b:00.0, compute capability: 8.6
2022-07-12 14:35:39.705654: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 22298 MB memory:  -> device: 2, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:9b:00.0, compute capability: 8.6
2022-07-12 14:35:39.706568: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 22298 MB memory:  -> device: 3, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:c8:00.0, compute capability: 8.6
tensorflow/cc/gradients/linalg_grad_test.cc:50: Failure
Expected: (max_error) < (1e-3), actual: 0.353254 vs 0.001
[  FAILED  ] LinalgGradTest.Einsum_TwoInputReduction (238 ms)
[----------] 10 tests from LinalgGradTest (7272 ms total)

[----------] Global test environment tear-down
[==========] 10 tests from 1 test suite ran. (7273 ms total)
[  PASSED  ] 7 tests.
[  FAILED  ] 3 tests, listed below:
[  FAILED  ] LinalgGradTest.Einsum_MatMul
[  FAILED  ] LinalgGradTest.Einsum_OuterProduct
[  FAILED  ] LinalgGradTest.Einsum_TwoInputReduction

 3 FAILED TESTS
--
Coverage runner: Not collecting coverage for failed test.
The following commands failed with status 1
/root/.cache/bazel/_bazel_root/43801f1e35f242fb634ebbc6079cf6c5/execroot/org_tensorflow/bazel-out/k8-opt/bin/tensorflow/cc/gradients_linalg_grad_test.runfiles/org_tensorflow/tensorflow/cc/gradients_linalg_grad_test

INFO: Build completed, 1 test FAILED, 8831 total actions
//tensorflow/cc:gradients_linalg_grad_test                               FAILED in 3 out of 3 in 17.1s
  Stats over 3 runs: max = 17.1s, min = 15.1s, avg = 15.8s, dev = 0.9s
  /root/.cache/bazel/_bazel_root/43801f1e35f242fb634ebbc6079cf6c5/execroot/org_tensorflow/bazel-out/k8-opt/testlogs/tensorflow/cc/gradients_linalg_grad_test/test.log
  /root/.cache/bazel/_bazel_root/43801f1e35f242fb634ebbc6079cf6c5/execroot/org_tensorflow/bazel-out/k8-opt/testlogs/tensorflow/cc/gradients_linalg_grad_test/test_attempts/attempt_1.log
  /root/.cache/bazel/_bazel_root/43801f1e35f242fb634ebbc6079cf6c5/execroot/org_tensorflow/bazel-out/k8-opt/testlogs/tensorflow/cc/gradients_linalg_grad_test/test_attempts/attempt_2.log

</details>

The above test instructions are available in versions prior to TF2.11. Thanks.

Hi,
Thank you for opening this issue. Since this issue has been open for a long time, the code/debug information for this issue may not be relevant with the current state of the code base.
The Tensorflow team is constantly improving the framework by fixing bugs and adding new features. We suggest you try the latest TensorFlow version with the latest compatible hardware configuration which could potentially resolve the issue. If you are still facing the issue, please create a new GitHub issue with your latest findings, with all the debugging information which could help us investigate.
Please follow the release notes to stay up to date with the latest developments which are happening in the Tensorflow space.


Postgres Kafka Debezium Issue with Schema Registery

Hey
I have tried your example and I was able to register the connector and issue is I am not able to see schema in schema prehistory

curl -X GET http://localhost:8081/subjects/postgres.public.movies/versions/1
{"error_code":40401,"message":"Subject 'postgres.public.movies' not found."}%

ok will take a look thanks for reporting

Thanks

Ok so the schema is missing and is not getting registered. I will add the schema file soon :)

Thanks actually I used different docker image for my POC
in case if you are interested
version: '3'

services:
  fast-data-dev:
    image: dougdonohoe/fast-data-dev
    ports:
      - "3181:3181"
      - "3040:3040"
      - "7081:7081"
      - "7082:7082"
      - "7083:7083"
      - "7092:7092"
      - "8081:8081"
    environment:
      - ZK_PORT=3181
      - WEB_PORT=3040
      - REGISTRY_PORT=8081
      - REST_PORT=7082
      - CONNECT_PORT=7083
      - BROKER_PORT=7092
      - ADV_HOST=<IP_ADDRESS>

  postgres:
    image: postgres:latest
    restart: always
    container_name: postgres
    hostname: postgres
    ports:
      - "5432:5432"
    environment:
      POSTGRES_USER: postgres
      POSTGRES_PASSWORD: postgres
      POSTGRES_DB: postgres
    command: ["postgres", "-c", "wal_level=logical"]
    healthcheck:
      test: ["CMD", "psql", "-U", "postgres", "-c", "SELECT 1"]
      interval: 10s
      timeout: 5s
      retries: 5
    volumes:
      - ./scripts:/docker-entrypoint-initdb.d

Hey you could send me a PR if you find this useful for other people as well. I would definitely merge your PR 🎉

sure


Use with surfman

Is it possible to use pathfinder with surfman?

Working on porting it over right now, in fact. :)

Really nice 🙂, thank you.

Pathfinder uses surfman now.


Floating point exception (core dumped) during running prepare_reference.py

Hello, thank you very much for this nice work.
I'm trying to repeat your work, but I'm getting the following error: Floating point exception (core dumped).
I got this reason when I found an error in gdb python

Do you have any idea why is this happening?
Thanks a lot,
RobertWong

Hi, sorry for the late reply. Did you manage to resolve this?
I haven't seen this error before. Which version of tensorflow / cuda are you using?


Warnings of too many event-handlers

Due to the way the rules hook into SAXParser events, node.js's event system complains due to a soft limit of 10 event handlers...
work around:
require('events').EventEmitter.prototype._maxListeners = 100;

can be fixed properly with #6


Light theme

heathen.

Never. Close issue please

no.

Whenever one of ya'll have an appointment booked to an optometrist, please implement this for the 1 person that needs this for accessibility reasons.

Finishing everything for the new design is top priority right now

Didn't mean to close it lol

lol

I believe I saw someone in the discord server working on this before, but not sure if it was new design or old design.

It was me, and it was the old design. I did it as a joke (kinda).


Stock tft file for EU

Hi!
I tried to do some expiriments with NSPanel, and now i have replaced firmwre for Nextion display. I cant find the original stock tft file for EU version of NSpanel in internet. Maybe someone has something similar?

https://cdn.discordapp.com/attachments/538814618106331139/925351768852951050/ns-panel.tft
here it is...
found it myself in this post:
https://community.openhab.org/t/nxpanel-replacement-firmware-for-sonoff-nspanel/132869

https://cdn.discordapp.com/attachments/538814618106331139/925351768852951050/ns-panel.tft here it is... found it myself in this post: https://community.openhab.org/t/nxpanel-replacement-firmware-for-sonoff-nspanel/132869

Is this the red or blue version? And how can this be uploaded if tssmota has been flashed?

red or blue version?
It cannot be flashed with this berry driver, you have to use this one for example:
https://github.com/joBr99/nspanel-lovelace-ui/tree/main/tasmota

red or blue version?
It cannot be flashed with this berry driver, you have to use this one for example: https://github.com/joBr99/nspanel-lovelace-ui/tree/main/tasmota

The stock tft file of the nspanel has 2 different backgrounds.  The original stock has a Black/red background and the latest has a blue/White one.

The only version of the stock firmware that is around on the internet is an early version that has been extracted from the flash chip of the nextion screen. Probably the first firmware version that was out there from nextion.


flashing Beken BK7231N device

hello, this is parallel to the ESP question still open.
am trying to use pico-uart-bridge to flash beken chips, and so far no luck.
unfortunately i do not own any other uart-usb bridges, so am unable even to determine if the pico is the problem.
the BK7231N comes with two UARTs, one is the flash port and the second is used for debugging.
am able to read the debugging port on the second channel, so am fairly sure the pico bridge is working.
am now working through your code, looking for anything that might help me to work out what the problem is, and already i have a question - please forgive me, i am very new to this hardware level coding..
at line 304 in uart-bridge.c, you call set_sys_clock_khz(250000, false);
however i believe the picoW has a max clock rate of 133MHz
am i just not understanding how this works?

Hey. Idk if you are still looking for a solution, but I was having the exact same issue. While I didn't get it working with the pico, the knock-off FTDI FT232 Usb boards work just fine for this :)

I also had the problem, but somehow ltchiptool CLI version worked
ltchiptool docs


deprecation warnings by sequelize

emits:
"Utils deprecated Non-object references property found. Support for that will be removed in version 4. Expected { references: { model: "value", key: "key" } } instead of { references: "value", referencesKey: "key" }. node_modules/sequelize/lib/model.js:85:25

Hi,
Please use pg-generator module and it's sequelize template. pg-generator is successor of this module and it generates much more better sequelize code. Also it can be modified according to your needs easily.
About your question for this module. You can use sequelize 4 template to avoid this warning.
spgen ........ -t sequelize4

ah, thanks on both counts!


share/discovery: overly aggressive retrying

I was looking into the mocha network today and found out a few things we need to change in discovery:

We retry too often.

If we cannot get the needed value of peers, we retry every second. Instant retries are usually useless; no new peers would join the network or advertise themselves in the second timeframe. But they are not always useless, so
Instead, we should have a capped linear backoff.

Factor 5 starting from 5 seconds and capped by 10 mins

#2573 introduced a minor bug: discoveryLoop does not listen to triggerDisc channel anymore
We should aim to trigger discoveryLoop asynchronously. RIght now, we endlessly trigger the loop every second, even if we have enough peers. Instead, we should rely more on triggerDisc channel to reduce wasted cycles. (nice-to-have)

Will work on it, thx

hey @nodersteam, curious if you were feeling comfortable enough to open a new PR with the stuff we've been discussing for https://github.com/celestiaorg/celestia-node/pull/2766?

hey @nodersteam, curious if you were feeling comfortable enough to open a new PR with the stuff we've been discussing for #2766?

Whatever you say, we can do it this way
Then I close the old PR, divide it into two new ones that we discussed?

@ramin

@Wondertan Hello
As a result, we come to the conclusion that we are closing the old PR and making 2 new ones that will separately correct backoff and asynchrony?
We do not do this without your confirmation so as not to do something unnecessary


error on Depth.Quality.Tool 2.49 and Intel.RealSense.Viewer 2.49 but works fine on version 2.40

Required Info

Camera Model
D435i

Firmware Version
D400_Series_FW_5_12_15_50

Operating System & Version
Windows 10

Kernel Version (Linux Only)
NA

Platform
PC

SDK Version
2.49

Language
labview

Segment

Issue Description
I have error when I start demos
Depth.Quality.Tool  "device is not functional or busy"
Intel.RealSense.Viewer  " Program terminated due to an unrecoverable SEH exception: Access Violation!"
I tried version 2.4 and it seems to works fine (like people with old and slow computer)
But in my case I think that the problem is not exactli the same !
my configuartion :
CPU : Intel(R) Core(TM) i9-10900K
RAM :32,0 Go
HAve you an idea and could I expect that is jus an issue in 2.49 version and that will be OK on future versions ?

Hi @ngassend  I will direct you first to a recent discussion about this error at https://github.com/IntelRealSense/librealsense/issues/9672
If the advice in that discussion does not resolve the problem for you, please let me know and i will be pleased to continue helping you.

The problem is only on version 2.49 ! I tested 2.48 and it seems to works like 2.40 !

Thank you for the information.  If you are installing the SDK with the automated installer file on the SDK Releases page, you could either run the 2.49.0 installer again (which would overwrite the previous installation) or use 2.48.0 for now and wait for the next SDK version.


Issue filtering PairCreated events

I have an issue when getting the args coming from the event filtered.
This is my setup :
//ponder.config.ts
export default createConfig({
  networks: {
    bsc: {
      chainId: 56,
      transport: rateLimit(http(process.env.PONDER_RPC_URL_56), {
        requestsPerSecond: 60,
      }),
    },
  },
  contracts: {
    UniswapV2Factory: {
      network: "bsc",
      abi: UniswapV2FactoryAbi,
      startBlock: 5_000_000,
      filter: {
        event: "PairCreated",
      },
    },
  },
});

//UniswapV2FactoryAbi.ts
[...]
{
    anonymous: false,
    inputs: [
      {
        indexed: true,
        internalType: "address",
        name: "token0",
        type: "address",
      },
      {
        indexed: true,
        internalType: "address",
        name: "token1",
        type: "address",
      },
      {
        indexed: false,
        internalType: "address",
        name: "pair",
        type: "address",
      },
      { indexed: false, internalType: "uint256", name: "", type: "uint256" },
    ],
    name: "PairCreated",
    type: "event",
 }
[...]

The first issue is that the event.args structure is not named like in the docs

The second issue is that when I console.log event, I can see that token0 and token1 are not in event.args, they just show in event.log.topics[1] and [2], maybe because they are indexed in the ABI
//console.log(event)
{
name: 'PairCreated',
  args: [ '0xefD7aF98146279da592937a77fd8a4EBc8DA51C3', 3613n ],
  log: {
    address: '0xBCfCcbde45cE874adCB698cC183deBcF17952812',
    blockHash: '0xedbf6ec6a3d7145935e5a9f45f48f46f5144601427460ad4cb12cd47a829735b',
    blockNumber: 5000227n,
    data: '0x000000000000000000000000efd7af98146279da592937a77fd8a4ebc8da51c30000000000000000000000000000000000000000000000000000000000000e1d',
    id: '0xedbf6ec6a3d7145935e5a9f45f48f46f5144601427460ad4cb12cd47a829735b-0x113',
    logIndex: 275,
    removed: false,
    topics: [
      '0x0d3648bd0f6ba80134a33ba9275ac585d9d315f0ad8355cddefde31afa28d0e9',
      '0x000000000000000000000000a81f65da7f65b1d82dce8fef54f8ba921ebb927e',
      '0x000000000000000000000000bb4cdb9cbd36b01bd1cbaebf2de08d9173bc095c'
    ],
    transactionHash: '0xe7d983567a259df20185f6b1f7c8521ed1f1d70b2161922a3cbaba57c2b97aac',
    transactionIndex: 50
  },
}

Dupplicate of https://github.com/ponder-sh/ponder/issues/777


Fix codacy Undo Command

#95 #96 #98 #99 #139

Coverage decreased (-1.4%) to 83.42% when pulling 501469c7f1574209e06336b0f3e63ac159375800 on Fix_codacy into 14ac62e7bd8376d12330887c3405faeb9d6b4301 on V0.3_MainBranch.

Coverage decreased (-1.5%) to 83.333% when pulling 6475beee0147fb83213c69c3ff416fdb1d7f79de on Fix_codacy into 14ac62e7bd8376d12330887c3405faeb9d6b4301 on V0.3_MainBranch.

Coverage decreased (-1.5%) to 83.333% when pulling 6475beee0147fb83213c69c3ff416fdb1d7f79de on Fix_codacy into 14ac62e7bd8376d12330887c3405faeb9d6b4301 on V0.3_MainBranch.

Similar to UndoCommand without build errors


hi need help with   ThreeDeeTouch.enableLinkPreview();

Hi @EddyVerbruggen  i am keen to learn how the peek and pop works there is some detail in the Documentation but i cant figure out how to make a peek and pop work
Correct me if i am wrong
when you enable enableLinkPreview does that call
ThreeDeeTouch.watchForceTouches(function(result) {
   console.log("force touch % " + result.force); // 84
   console.log("force touch timestamp " + result.timestamp); //<PHONE_NUMBER>.706419
   console.log("force touch x coordinate " + result.x); // 213
   console.log("force touch y coordinate " + result.y); // 41
 });

or Does it automatically Popup but what is shown in popup
Its Really confusing me
Please Help as i have gone through the https://developer.apple.com/library/ios/documentation/UserExperience/Conceptual/Adopting3DTouchOniPhone/ where does this plugin fit in
how can one configure the peek and the peek options
Regards
Ezaz

Peek and Pop is only supported for links, just like in a browser on a mobile device supporting 3D Touch. The only thing this plugin can do is enabling that "press hard on a link to peek and pop" feature. watchForceTouches has nothing to do with that.

Ok thanks for clearing the doubts


programmer-calculator: init at 2.1

Motivation for this change
programmer-calculator is a terminal calculator for programmers.
Things done

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

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

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

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

[x] Fits CONTRIBUTING.md.

Comments
One concern I have is that this package contains a binary named pcalc. A different package named pcalc already exists in nixpkgs that also contains a binary with this name. I noticed priority in metadata which I think would prioritize one of these over the other? But it wasn't clear to me which is higher priority. Another option is to just rename this binary from pcalc -> programmer-calculator or something similar. I'm not sure what the usual approach to these sorts of problems is. Any guidance is welcome! Thank you! 😄

Result of nixpkgs-review pr 127355 at 5151f2cc run on x86_64-linux 1

1 package built successfully:

programmer-calculator

1 suggestion:

warning: missing-phase-hooks
installPhase should probably contain runHook preInstall and runHook postInstall.
Near pkgs/applications/science/math/programmer-calculator/default.nix:16:3:
   |
16 |   installPhase = ''
   |   ^

Build fails on macOS:
building '/nix/store/4ysqcig9hv69z232hslhw0cxjhsk4ljg-programmer-calculator-2.1.drv'...
unpacking sources
unpacking source archive /nix/store/wlwlah3xxfhwbm76sjzdm0r5hf29rk53-source
source root is source
patching sources
configuring
no configure script, doing nothing
building
build flags: SHELL=/nix/store/xxfxh4npdlp0w5winp2f17ji1yxdivn3-bash-4.4-p23/bin/bash
gcc -Wall -Wextra -g -Werror=missing-declarations -Werror=redundant-decls -Iinclude -c src/draw.c -o src/draw.o
/nix/store/xxfxh4npdlp0w5winp2f17ji1yxdivn3-bash-4.4-p23/bin/bash: gcc: command not found
make: *** [Makefile:41: src/draw.o] Error 127
builder for '/nix/store/4ysqcig9hv69z232hslhw0cxjhsk4ljg-programmer-calculator-2.1.drv' failed with exit code 2
error: build of '/nix/store/4ysqcig9hv69z232hslhw0cxjhsk4ljg-programmer-calculator-2.1.drv' failed

Adding ghc to the buildInputs fixes it for me.

Build fails on macOS:
building '/nix/store/4ysqcig9hv69z232hslhw0cxjhsk4ljg-programmer-calculator-2.1.drv'...
unpacking sources
unpacking source archive /nix/store/wlwlah3xxfhwbm76sjzdm0r5hf29rk53-source
source root is source
patching sources
configuring
no configure script, doing nothing
building
build flags: SHELL=/nix/store/xxfxh4npdlp0w5winp2f17ji1yxdivn3-bash-4.4-p23/bin/bash
gcc -Wall -Wextra -g -Werror=missing-declarations -Werror=redundant-decls -Iinclude -c src/draw.c -o src/draw.o
/nix/store/xxfxh4npdlp0w5winp2f17ji1yxdivn3-bash-4.4-p23/bin/bash: gcc: command not found
make: *** [Makefile:41: src/draw.o] Error 127
builder for '/nix/store/4ysqcig9hv69z232hslhw0cxjhsk4ljg-programmer-calculator-2.1.drv' failed with exit code 2
error: build of '/nix/store/4ysqcig9hv69z232hslhw0cxjhsk4ljg-programmer-calculator-2.1.drv' failed

Adding ghc to the buildInputs fixes it for me.

Thank you, fixed!


Build failed with podman 3.1.0

It seems podman in 3.1.0 broke this plugin - with message "can only set one of 'pull' or 'pull-always' or 'pull-never'"
Tracked to this commit: https://github.com/containers/podman/pull/9631/commits/4d5199537737b0cfef47d3d2700013a787126d21

Interesting, thanks for bringing this under my attention. Seems like a pretty straightforward fix. I will take a look at it.


Close the connection if an error occurs during the transfer of the HTTP response

Closes #14

Coverage remained the same at 100.0% when pulling d0be20ed43c359bdbc2a365970687f2d98f58f42 on 14-close-the-connection-if-an-error-occurs-during-the-transfer-of-the-http-response into 8c6bd61ea94a4a6f54bff1dc6ae2c9fbe1393ea5 on master.

Coverage remained the same at 100.0% when pulling d0be20ed43c359bdbc2a365970687f2d98f58f42 on 14-close-the-connection-if-an-error-occurs-during-the-transfer-of-the-http-response into 8c6bd61ea94a4a6f54bff1dc6ae2c9fbe1393ea5 on master.


[Bug Fix] - Clean up ENS names

After selecting ENS names for recovery they look like this:

A little strange.

#34 and other prior PRs addressed this issue.


using ngTasty in ControllerAs syntax?

Hi There,
I would like to use the grid without using the $scope inside my controller. Particularly, that I am using typescript and I would like to avoid mixing scope inside the controllers. Can I use controllerAs syntax to set the ngTasy resource. I would like to be able to use something like:
this.gridResource = {
                header: [],
                rows: thisController.Contacts; // Where this is an array
            };

And then inside the view as:
<div tasty-table bind-resource="VM.gridResource" bind-filters="VM.applyFilterTextbox">
</div>

Is this possible? Any examples would be appreciated.
Thanks

Honestly not a big fun of ControllerAs and I never use it before. Sorry!


chore: remove Optional typings

Description

This PR removes the Optional type hinter, as guidance for Python 3.10+ and PEP 604's introduction is to phase it out in favor of a simple None union type. Note that these are functionally identical and do not affect the method signature for existing integrations.
References

Review Checklist

[x] I have clicked on "allow edits by maintainers".
[ ] I have added documentation for new/changed functionality in this PR or in a PR to openfga.dev [Provide a link to any relevant PRs in the references section above]
[x] The correct base branch is being used, if not main
[ ] I have added tests to validate that the change in functionality is working as expected

If you haven't done so yet, we would appreciate it if you could star the OpenFGA repository. :)

Codecov Report
All modified and coverable lines are covered by tests :white_check_mark:

Project coverage is 69.16%. Comparing base (e49a77a) to head (02fc990).

Additional details and impacted files
@@            Coverage Diff             @@
##             main     #148      +/-   ##
==========================================
- Coverage   69.17%   69.16%   -0.01%
==========================================
  Files         122      122
  Lines        9751     9749       -2
==========================================
- Hits         6745     6743       -2
  Misses       3006     3006

:umbrella: View full report in Codecov by Sentry.
:loudspeaker: Have feedback on the report? Share it here.


Metal build pipeline enhancement

Problem
Build pipeline was implemented with a hardcoded paths and it stored binaries within the source code
Details
To enhance rust build configuration to make it compile and lint metal library as well with build.rs build script.
Acceptance criteria
build.rs metal build script tracking changes on metal files changes
Next steps (optional)
To drop all.metal header file and to config building script to combine the exact metal files instead.

Implemented in #14


[Impeller] Investigate removal of waitUntilScheduled in Metal backend.

This is necessary today because Impeller doesn't do resource hazard tracking across render passes. This introduces bubbles in execution on the GPU which wastes available concurrency.

"Something something synchronization/hazard tracking/dependencies." -> https://github.com/flutter/flutter/issues/120406

I added some additional tracing so that we account for the waitUntiLScheduled in the SubmitCommands method. It appears that the vast majority of the time is spent just waiting.

In the wonderous app, removing waitUntilScheduled reduces average raster time from 7-8ms down to 1-2ms.

Did you attach the wrong screenshot? That is showing the wait for the next drawable. That is the backpressure mechanism (the GPU telling us we are running ahead of its ability to render the stuff we are telling it to) and this issue isn't describing getting rid of it.
I got rid of the need for this wait as I am wiring up the Vulkan backend and have some notes on how we can do the same for Metal. We can discuss it in the weekly or an OOB sync perhaps?

No, take a look at the command buffer upload part. It's all waitUntilScheduled

Weekly sounds fine fyi, just doing some investigating

This is what I added for tracing, I believe it should be accurate.
@@ -164,6 +168,7 @@ bool CommandBufferMTL::OnSubmitCommands(CompletionCallback callback) {
   }

   [buffer_ commit];
+  TRACE_EVENT0("impeller", "CommandBufferMTL::waitUntilScheduled");
   [buffer_ waitUntilScheduled];
   buffer_ = nil;
   return true;

Note for myself to try to assimilate the ordering guarantees in Metal.

Fixed by @bdero in https://github.com/flutter/engine/pull/40781. We were on the wrong lines of investigation w.r.t hazard tracking.

The fix was reverted in https://github.com/flutter/engine/pull/40895.


feature: spin up Ceramic Mainnet Node

Summary

[x] Choose hosting provider
[x] Set up Docker and Ceramic Testnet
[x] Access mainnet

Expected behavior / User Story
No response

Inquiry has been sent to netcup for their VPS 4000 G10 found on this page. The providers we've been choosing from can be found in this sheet.

Node is up and running. Switch to our own API endpoint will be closed in: #414.


lib/modules: improve error message when option is being accessed that isn't defined

Description of changes
motivated by https://github.com/NixOS/nixpkgs/pull/329450#issuecomment-2319182334
Things done

Built on platform(s)

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

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

[ ] sandbox = relaxed
[ ] sandbox = true

[ ] Tested, as applicable:

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

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

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

[x] Fits CONTRIBUTING.md.

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

It is possible to add an additional field to options, overriding the message (Or just print the option description)? Then they would be able to provide additional contexts and links to documentations.

Thanks!


[FEAT]: Add Favicon in your website.

Clear and concise description of the problem
Favicon is missing in your website. Please assign it to me. I'll do that.
Suggested solution
No response
Alternative
No response
Additional context
No response
Validations

[X] Follow our Code of Conduct
[X] Read the Contributing Guide.
[X] Check that there isn't already an issue that request the same feature to avoid creating a duplicate.

@akashpatel25 This issue description is not concise. Where is the part that is missing the favicon that you want to add?


导致lodash全部引入（Resulting in the introduction of all lodash）

Describe the bug
安装vue-hooks-plus(v1.8.8)后，项目打包进行包分析，发现lodash被全部引入，大小接近100kb，gzip压缩后为49.32kb；如果去掉vue-hooks-plus再打包进行包分析，就没有lodash。(After installing Vue books plus, the project was packaged for package analysis and it was found that lodash was fully introduced, with a size close to 100kb. After gzip compression, it was 49.32kb; If we remove Vue books plus and package it for package analysis, there will be no lodash.)
Steps to reproduce
No response
System Info
win10 vscode

Used Package Manager
pnpm
Validations

[X] Follow our Code of Conduct.
[X] Read the Contributing Guidelines.
[X] Read the docs.
[X] Check that there isn't already an issue that reports the same bug to avoid creating a duplicate.
[X] Make sure this is a VueHooks Plus issue and not a framework-specific issue. For example, if it's a Vue SFC related bug, it should likely be reported to vuejs/core instead.
[X] Check that this is a concrete bug. For Q&A open a GitHub Discussion.
[X] The provided reproduction is a minimal reproducible example of the bug.

@zhangziyi123 感谢你的反馈，经过排查，大概率是在从 lodash 导入类型的时候写法有误，导致打包的时候进行 tree shaking 失败。

正在排查。

你好，经过排查发现，并未全部构建所有的 lodash 依赖在 vue-hooks-plus 中。
之所以会构建出如此大体积的 lodash 依赖包，是因为 vue-hooks-plus 中依赖的该库的方法在内部本身依赖了很多依赖，所以导致体积如此大。
感谢你的提出的意见，这块问题，后续我们会持续跟进改进 lodash 依赖体积大问题。

可否加我qq好友，可以一起再核对一下这个问题，方便的话加一下我哈  QQ:<PHONE_NUMBER>

好的。

问题最后在哪个版本解决的？


multiple arel conditions raise SystemStackError: stack level too deep

I am trying to build a query to search using multiple conditions.
I have tried use Active Record and Areal, both result same exception:
SystemStackError: stack level too deep

def search
    table = Model
    relation = table[:user_id].eq(user.id)
    params.each do |param|
      param.each do |attr, value|
        relation = relation.or(table[attr].eq(value).and(table[attr].eq(value)).and(table[attr].eq(value)))
      end
    end

    Model.where(relation)
  end

This should output a query like:

  WHERE (table.attr1 = '1' AND table.attr2 = '5' AND table.attr3 = '7') OR  (table.attr1 = '4' AND table.attr2 = '3' AND table.attr3.= '5')

It works when params has small number of hash conditions:
params=[{attr1: 1, attr2: 2, attr3: 4}, {attr1: 4, attr2: 2, attr3: 8}]
However my params has much more than 1000 hash inside for a big query and it this case i got the exception:
SystemStackError: stack level too deep:

/Users/kivanio/.rbenv/versions/2.4.2/lib/ruby/gems/2.4.0/gems/arel-8.0.0/lib/arel/visitors/reduce.rb:14:in `visit'
/Users/kivanio/.rbenv/versions/2.4.2/lib/ruby/gems/2.4.0/gems/arel-8.0.0/lib/arel/visitors/to_sql.rb:403:in `visit_Arel_Nodes_Grouping'
/Users/kivanio/.rbenv/versions/2.4.2/lib/ruby/gems/2.4.0/gems/arel-8.0.0/lib/arel/visitors/reduce.rb:14:in `visit'
/Users/kivanio/.rbenv/versions/2.4.2/lib/ruby/gems/2.4.0/gems/arel-8.0.0/lib/arel/visitors/to_sql.rb:620:in `visit_Arel_Nodes_Or'
/Users/kivanio/.rbenv/versions/2.4.2/lib/ruby/gems/2.4.0/gems/arel-8.0.0/lib/arel/visitors/reduce.rb:14:in `visit'

I have tried a lot of different ways to code this but I always got the same exception.
My question is if there is a limit of number of nodes/conditions or I am doing something really bad here?
Is there a way to make this work?

I solved it using DB IN:

SELECT * FROM table
WHERE (attr1, attr2, attr3) IN (('4368','00004694','00122641'));


Issue with MSE

Hi!
The Colab implementation of ThermoMPNN fails to run if MSE residue is present in the structure...
I found that renaming MSE to MET in the PDB is enough to make it work...
Perhaps some simple code could be added to account for this residue commonly found in X-ray structures.
Best

Hi, thanks for identifying this issue! I am surprised this is happening, since the ThermoMPNN PDB parser has some code to handle MSE residues. However, it looks like this was only catching residues labeled as HETATM, so I added a few lines to catch residues labeled as ATOM entries but identified as MSE or SEC residues.
Please let me know if this resolves your issue. Otherwise, if you could send me the offending PDB, I can try to troubleshoot this particular case. Thanks!


Victory charts support

Glad this exists. Some issues rendering with Victory charts
Example
const data = [
  { x: 1, y: 2, y0: 1 },
  { x: 2, y: 3, y0: 2 },
  { x: 3, y: 5, y0: 2 },
  { x: 4, y: 4, y0: 3 },
  { x: 5, y: 6, y0: 3 },
];

<ReactPDFChart>
  <VictoryChart>
    <VictoryBar
      data={data}
      width={100}
      height={100}
      style={{ data: { fill: "#c43a31" } }}
    />
  </VictoryChart>
</ReactPDFChart>

Rendering <VictoryChart /> component by itself in web looks like this

but in <ReactPFDChart/> / react-pdf it doesn't render the bars.

Might just be a color issue (white on white) or the bars aren't rendering at all

Thanks for report! I was planning on getting Victory support working but haven't had a chance to yet.
Looking at it briefly now, it seems that when you render a Victory chart with ReactDOMServer.renderToStaticMarkup -- it renders an empty <svg/> element for the bars... I'm not sure why that's happening. Might be something in Victory itself that blocks server-side rendering?

Thanks for the report! I was meaning to add support for Victory. I took a quick look and you are correct -- the styling wasn't being applied to the bars.
I just published v0.1.0 which includes some basic support for this. The result is a lot closer to your web-based image:


Guzzle ^7.0 support ?

Hello,
Possible to have a new release with guzzlehttp/guzzle in version ^7.0 ?
Many packages require them but your lib doesn't support over 6.5 😞
Thanks

im having the same exact problem

Someone have opened the #44 PR for that but not work 😞

The master support guzzle ^7.0.
Use dev-master tag or just patient for a release.

@zzantares Can you give me right to update this lib and release compat with newest PHP ?

Thanks @GothShoot, check your email, the invite was sent :)

Thanks :smile:

Hi,
Installing the package via composer still doesn't work.
Can anyone guide me on how to install this package on a Laravel 9 Project?
Thanks!

@iandk Please, open issue separately, and tell me what's happened, i probably can help you :smiley:

Just for all the People also Struggeling to install it in Laravel 9 (which needs obviously Guzzle 7.2) the solution is:
composer require zzantares/proxmoxve dev-master
Then it should be work :)

Hello, i probably can do this, let me check if master branch is ready for a release and i notify you when is okay :)

Fixed by new release v4.1.0 allow support of guzzle 7, i plan to release a v5 for fully drop previous v6 and port support of php higher by dropping old package compatibility (and probably nice other things)
Thanks for relaunch about guzzle @hall-of-code !

Thank you very Much. Unfortunatly 4.1 is not avaible in Composer Package, please hit the "Update" button on Packagist or so :)

Thank you so much for the support @GothShoot! 4.1 should be available now, I've updated it in packagist.
btw, I tried to add you as a project maintainer in packagist.org but it seems GothShoot refers to a different user account or is that your account?


Address validation to check that resident lives within City

Is your feature request related to a problem? Please describe.
The Fresh Bucks team receives 12,000 applications a year. They are not able to manually verify all 12,000 applicants reside in the City of Seattle, but they can only accept City residents. Is it possible to use the City's GIS webserver to validate current City addresses?
Describe the solution you'd like
If a resident enters a City of Seattle address, they would be able to proceed with the application. If a resident enters a non-City address, they would receive an alert "The address provided is not within City of Seattle limits. You must reside at a City of Seattle address to qualify for this program?" and it would off ramp the applicant so they cannot submit the application.
Additional context
The GIS team provided instructions when the Fresh Bucks team was getting their platform up and running. I included those instructions attached.
Done when
A resident receives a notice if they are not eligible based on address. Program staff do not receive applications from people outside the City of Seattle limits.

@elisekalstad for the GIS instructs you say " I included those instructions attached.". I'm not seeing them, can you point out what you mean?

@shanemc-goog --Yeah, we deleted it from the attachments since there is City-specific server and database information, just to be careful. I know @gwendolyngoetz is working on this one, I'll check with her to see what can be shared over github.

Closing this since it's redundant with the PRD and the tracking issue for the work at #4051


Create navbar

Create a navbar similar to RealDevSquad.com

Please review #150

Interested to work on this @whyDontI


Change via shape to round

I've been using a 1mm radius miter to do this. Is that a reasonable turning radius?

I was thinking about the via pads :) They seem to be squared. You can change the via shape of all the vias simultaneously with the command line.

Right! Thanks for clarifying. Somehow I read 'via' as 'trace'. Oops. I'll make sure all the traces are normal straight edges on 45 degree turns, and make sure the vias are all round :-)

done.


Increase the ELAPSED_MINUTES test limit from two hours to three hours

On the most recent commit to master, one job took 2h 20m 9s and another job took 2h 12m 46s.
So let's increase the limit from two hours to three hours.
(In the commit message, I wrote "two hours to four hours", which is a typo. As seen in the diff, the actual change in "two hours to three hours".)

That would be helpful for regression testing.
And as always, thanks for the PR.


cri-o: 1.18.1 -> 1.18.2

https://github.com/cri-o/cri-o/releases/tag/v1.18.2

Motivation for this change
Things done

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

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

[ ] Tested via one or more NixOS test(s) if existing and applicable for the change (look inside nixos/tests)
[ ] Tested compilation of all pkgs that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review wip"
[x] Tested execution of all binary files (usually in ./result/bin/)
[ ] Determined the impact on package closure size (by running nix path-info -S before and after)
[ ] Ensured that relevant documentation is up to date
[x] Fits CONTRIBUTING.md.

Result of nixpkgs-review pr 91137 1

2 packages built:
- cri-o
- cri-o-unwrapped


Why do some react so much in a negative way. Bed bugs are now not something to hide. They are there and more so in high class facilities, flights, homes, institutions and many others. https://www.jopestkil.com


add Dockerfile

It would be great if you could sign up to hub.docker.com and provide an "official" image. Should be fairly easy to do, the builds are automatic then.

Thanks for the PR!
I will look into the option of providing the image.


MRG, FIX: Fix bug with scale_data_colormap

Closes #281
On master the snippet from #281 gives:

And on this PR:

@mwaskom feel free to look/test/merge if you're happy.

Also @mwaskom I think this was listed as the only (?) blocker for release, so if you're okay with it once this is merged I'll push a new version out

I'm traveling for the next few days and won't have a chance to look closely but +1 on release and go ahead and merge if it resolves the issue.

Okay, onward we go!


fix: stop collecting docker engine logs for Windows nodes

Reason for Change:
Removing docker logs from the Windows log collection script.
Issue Fixed:
Fixes #150

/azp run

/azp run


Dialog's hideOnInteractOutside should exclude backdrop.

Current behavior
Dialog dismissed on mouse down, but not on click. Non-primary button also dismisses the dialog.
Steps to reproduce the bug

Open https://ariakit.org/examples/dialog
Open dialog
Right click or middle click on the backdrop

Expected behavior

Mouse down on the backdrop should not close the dialog, especially for right-click.

Possible solutions
Exclude backdrop element from hideOnInteractOutside's behavior.

After tinkering for a while, I'm not sure this should be the default behavior. For example, this would impact how context menus work. Do you have any specific use case that's not working because of this?
But this should be able to achieve in userland, which is not the case right now (at least, not in an easy way).
With #1378, which will be released next Monday, you will be able to do this:
const ref = useRef(null);
<Dialog
  state={dialog}
  backdropProps={{ ref }}
  hideOnInteractOutside={(event) => {
    return event.type === "click" || event.target !== ref.current;
  }}
>


stop triggerring all gestures for single tap, get tapped object and event args in code behind

By default all gestures will trigger for a single touch point but it can be expanded by using the GestureModifier dependency property.
How can we stop triggerring all gestures for a single tap in code behind.
for one finger tap. only one finger tap code should get execute ,,for two fingers, two finger tap should execute . how can we do this in code behind.
am doing like this. but all gesture getting triggering instead of single finger

<Canvas x:Name="home1" Width="1920">
    <i:Interaction.Triggers>
        <recognizer:GestureRecognizer TriggerOnGesture="Tap" GestureModifier="OneFinger">
            <ei:CallMethodAction TargetObject="{Binding ElementName=userControl}"  MethodName="canv_inkcanvas_boards_OneFinger" />
            <ei:ChangePropertyAction TargetName="TouchArea" PropertyName="Background" Value="LightPink" />
            <ei:ChangePropertyAction TargetName="GestureRecognizedAs" PropertyName="Text" Value="Last gesture was a OneFinger Tap" />
        </recognizer:GestureRecognizer>
        <recognizer:GestureRecognizer TriggerOnGesture="Tap" GestureModifier="TwoFingers">
            <ei:ChangePropertyAction TargetName="TouchArea" PropertyName="Background" Value="LightPink" />
            <ei:ChangePropertyAction TargetName="GestureRecognizedAs" PropertyName="Text" Value="Last gesture was a TwoFingers Tap" />
            <ei:CallMethodAction TargetObject="{Binding ElementName=userControl}"  MethodName="canv_inkcanvas_boards_TwoFingersTap" />
        </recognizer:GestureRecognizer>

        <recognizer:GestureRecognizer TriggerOnGesture="Tap" GestureModifier="ThreeFingers">
            <ei:ChangePropertyAction TargetName="TouchArea" PropertyName="Background" Value="LightPink" />
            <ei:ChangePropertyAction TargetName="GestureRecognizedAs" PropertyName="Text" Value="Last gesture was a ThreeFingers Tap" />
            <ei:CallMethodAction TargetObject="{Binding ElementName=userControl}"  MethodName="canv_inkcanvas_boards_ThreeFingers" />
        </recognizer:GestureRecognizer>

        <recognizer:GestureRecognizer TriggerOnGesture="Tap" GestureModifier="FourFingers">
            <ei:ChangePropertyAction TargetName="TouchArea" PropertyName="Background" Value="LightPink" />
            <ei:ChangePropertyAction TargetName="GestureRecognizedAs" PropertyName="Text" Value="Last gesture was a FourFingers Tap" />
            <ei:CallMethodAction TargetObject="{Binding ElementName=userControl}"  MethodName="canv_inkcanvas_boards_FourFingers" />
        </recognizer:GestureRecognizer>

        <recognizer:GestureRecognizer TriggerOnGesture="Tap" GestureModifier="FiveFingers">
            <ei:ChangePropertyAction TargetName="TouchArea" PropertyName="Background" Value="LightPink" />
            <ei:ChangePropertyAction TargetName="GestureRecognizedAs" PropertyName="Text" Value="Last gesture was a FiveFingers Tap" />
            <ei:CallMethodAction TargetObject="{Binding ElementName=userControl}"  MethodName="canv_inkcanvas_boards_FiveFingers" />
        </recognizer:GestureRecognizer>
    </i:Interaction.Triggers>
</Canvas>

code behind:
public void canv_inkcanvas_boards_TwoFingersTap()
{
   try {
       Console.WriteLine("canv_inkcanvas_boards_TwoFingersTap");
   }
   catch (Exception) {
   }
}

public void canv_inkcanvas_boards_ThreeFingers()
{
   try {
       Console.WriteLine("canv_inkcanvas_boards_ThreeFingers");
   }
   catch (Exception) {
   }
}

public void canv_inkcanvas_boards_FourFingers()
{
   try {
       Console.WriteLine("canv_inkcanvas_boards_FourFingers");
   }
   catch (Exception) {
   }
}

public void canv_inkcanvas_boards_FiveFingers()
{
   try {
       Console.WriteLine("canv_inkcanvas_boards_FiveFingers");
   }
   catch (Exception) {
   }
}

public void canv_inkcanvas_boards_OneFinger()
{
   try {
       Console.WriteLine("canv_inkcanvas_boards_OneFinger");
   }
   catch (Exception) {
   }
}

also how can we get the tapped object and eventargs in code behind.
public void canv_inkcanvas_boards_OneFinger( ?, ?) {  }

Please help me by replying with sample code ... awaiting for ur reply guys

Hi @appmazic,
Trying to understand your question a bit more as I am struggling to understand, are you asking how to recognize Tap for each modifier?
Tap+One Finger, Tap+TwoFinger and so on? Or are you getting swipes as well?

Hi @appmazic,
Have you read my previous comment? can you provide a bit more information?

I am going to close this issue as there was no feedback from @appmazic, will reopen it if anybody is interested


How to get the layers of attributes for manipulation?

Hi, thanks for your work!
In the colab example, we can manipulate attributes (age, eyeglasses, gender, pose, expression). We manipulate the attributes by adding values in the dimension of manipulate_layers. For instance, gender is manipulated using layer [2, 3, 4], while expression is manipulated using layer [2,3,4,5]. I wonder, how did you know that a certain attribute is associated with particular layers?
Thank you very much for your help!

https://github.com/genforce/idinvert/issues/12

Thanks for your answer!


Add basic Node.js test suite

Feature Request
This PR added some automated tests via Dockerhub, but we should have a basic Node.js test suite as well.
User Stories & Acceptance Criteria
Get tests working with each of the fixtures in tests/fixtures, and a few of the online servies as well.
Implementation Plan
We can use jest as mbgl-renderer does.

https://github.com/ConservationMetrics/mbgl-tile-renderer/pull/23 added the framework but I want to keep this issue open as a reminder to add more tests coverage.


Split session from SshTerminalView

Currently the session management happens in SshTerminalView, which is fine, but some features would benefit from a clearer separation between a terminal running over an ssh2/channel in the ssh2/session and the ssh2/session itself.
We could move the session management out, and make SshTerminalView just a shortcut for "Launch Session if needed, then terminal over the channel".
The above would make it easier to reuse the session for new connections (currently we start a new one), tunnels, snippet execution and status updates.

Tracking this on a document:
https://paper.dropbox.com/doc/SwiftTermApp-Split-Session--BhUopOLusaqdNydA394FhKSQAg-2QL6qQGuo5fQZI3KZEvlB


Remove title bar in macOS.

This removes the title bar from macOS, while retaining draggability and the close, minimize, and maximize window options.

@chrisnojima, what problems did we run into last time we tried to do this?

Originally electron had a bug where hover in the title bar area didn't register. so if you had a hover color on the buttons it wouldn't work. We haven't revisited recently so its possible they fixed it.
Also nothing about this pr gates this to just osx so i'm assuming this affect linux and windows incorrectly

Let me spin up some virtual machines to test on other platforms.

After much weeping and gnashing of teeth, I was able to get this branch running on Ubuntu and Windows 10. These settings don't affect either, only macOS.
That said, my placement of -webkit-app-region: 'drag' will need to be finessed before asking for another review. Tapping and dragging on words in a chat (for highlighting to copy) drags the entire window, as you'd expect with that style.

@chrisnojima, this is ready for another review. I've placed window dragging where it makes sense (headers, the tab bar, etc.). Hover styles in the title bar area work, with one exception: cursor: "pointer" has no affect. Otherwise, colors change on hover (not sure what else to check). Is that a showstopper?

Just noticed the Flow error. I'll fix that tomorrow.

@chrisnojima, this is ready for another review.

I'm closing this based on Nojima's concern about needing to add the drag styles for every possible view.


Can't unsubscribe from topic

Bug report
Current behavior:
I have tried unsubscribing from certain topics, but I still get new notifications from that topic. I use the .subscribe(topicName) method to subscribe to a topic and .unsubscribe(topicName) to unsubscribe.
Expected behavior:
After unsubscribing from the topic I expect that I won't receive new notifications from that topic.
Steps to reproduce:

Subscribe to a topic, e.g. bugReport
Send test notification to confirm the registration is completed
Unsubscribe from the topic
Send a new test notification, you still receive this notification

Environment information

Cordova CLI version

9.0.0<EMAIL_ADDRESS>

Cordova platform version

  android 8.1.0
  ios 5.0.1
Available platforms:
  browser ^6.0.0
  electron ^1.0.0
  osx ^5.0.0
  windows ^7.0.0

Plugins & versions installed in project (including this plugin)

cordova-plugin-add-swift-support 2.0.2 "AddSwiftSupport"
cordova-plugin-advanced-http 2.1.1 "Advanced HTTP plugin"
cordova-plugin-androidx 1.0.2 "cordova-plugin-androidx"
cordova-plugin-androidx-adapter 1.1.0 "cordova-plugin-androidx-adapter"
cordova-plugin-app-version 0.1.9 "AppVersion"
cordova-plugin-appsflyer-sdk 4.4.15 "AppsFlyer"
cordova-plugin-device 2.0.3 "Device"
cordova-plugin-file 6.0.2 "File"
cordova-plugin-firebasex 6.1.0 "Google Firebase Plugin"
cordova-plugin-geolocation 4.0.2 "Geolocation"
cordova-plugin-inappbrowser 3.0.0 "InAppBrowser"
cordova-plugin-ionic-keyboard 2.1.3 "cordova-plugin-ionic-keyboard"
cordova-plugin-ionic-webview 4.1.1 "cordova-plugin-ionic-webview"
cordova-plugin-network-information 2.0.2 "Network Information"
cordova-plugin-screen-orientation 3.0.2 "Screen Orientation"
cordova-plugin-settings-hook 0.2.7 "Cordova Settings Hooks"
cordova-plugin-splashscreen 5.0.3 "Splashscreen"
cordova-plugin-statusbar 2.4.3 "StatusBar"
cordova-plugin-whitelist 1.3.4 "Whitelist"
cordova-plugin-x-socialsharing 5.4.7 "SocialSharing"
cordova-realm-plugin 1.0.0 "CordovaRealm"
cordova-sqlite-storage 3.2.1 "Cordova sqlite storage plugin - cordova-sqlite-storage plugin version"
cordova-user-preferences-plugin 1.0.0 "CordovaPreferences"
es6-promise-plugin 4.2.2 "Promise"
im.ltdev.cordova.UserAgent 1.0.1 "User-Agent"
ionic-plugin-deeplinks 1.0.20 "Ionic Deeplink Plugin"
phonegap-plugin-barcodescanner 8.1.0 "BarcodeScanner"

Dev machine OS and version, e.g.

OSX

ProductVersion: 10.14.6
BuildVersion:   18G103

iOS build issue:

Node JS version

v10.15.3

XCode version

11.0 (11A420a)

Console output:
[Assert] Unsupported use of UIKit API off the main thread: UIAccessibilityIsAssistiveTouchRunning()

I'm having the same problem, trying updating pods with no luck

same error

Hi @dpa99c, thanks for your response! Do you also have a ionic test project? I have the latest versions of your cordova plugin and @ionic-native layer.
I have two very simple methods which subscribe and unsubscribe from TEST_CHANNEL topic. The outcome in the console:
2019-10-29 14:37:03.930892+0100 MyApp[697:94092] 6.3.0 - [Firebase/Messaging][I-FCM004003] Successfully subscribed to topic /topics/TEST_CHANNEL
2019-10-29 14:37:03.931873+0100 MyApp[697:94092] 6.3.0 - [Firebase/Performance][I-PRF100009] Recording network trace: https://iid.googleapis.com/iid/register
2019-10-29 14:37:03.940954+0100 MyApp[697:94041] [Assert] Unsupported use of UIKit API off the main thread: UIAccessibilityIsAssistiveTouchRunning()
2019-10-29 14:37:03.941421+0100 MyApp[697:94041] [Assert] Unsupported use of UIKit API off the main thread: UIAccessibilityIsGuidedAccessEnabled()

And unsubscribing:
2019-10-29 14:38:06.901604+0100 MyApp[697:94240] 6.3.0 - [Firebase/Messaging][I-FCM004002] Successfully unsubscribed from topic /topics/TEST_CHANNEL
2019-10-29 14:38:06.901669+0100 MyApp[697:94240] 6.3.0 - [Firebase/Performance][I-PRF100009] Recording network trace: https://iid.googleapis.com/iid/register
2019-10-29 14:38:06.905442+0100 MyApp[697:94240] [Assert] Unsupported use of UIKit API off the main thread: UIAccessibilityIsAssistiveTouchRunning()
2019-10-29 14:38:06.905809+0100 MyApp[697:94240] [Assert] Unsupported use of UIKit API off the main thread: UIAccessibilityIsGuidedAccessEnabled()

Do you also have a ionic test project?

There's currently only a basic example for Ionic 3 however you can verify the plugin works correctly by directly calling the plugin's JS API as demonstrated in that example.


Added include file for msgraph migration

Docs Build status updates of commit 530849f:
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Details

includes/msgraph-migration-banner.md
:white_check_mark:Succeeded

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Oxygen Sensor, why not blood oxygen sensor (oximeter) instead?

Since your primary concern is the oxygenation of the patients blood, couldn't you use a solenoid valve on an oxygen tank, which would be controlled by a blood oxygen sensor like the max30100 or max30102. That way you wouldn't have to worry about the oxygen in the flow of air (the inspiration), but instead could just add oxygen, at a constant rate, to the stream until the patients' levels began increasing or hit a threshold set by a clinician. Then the system could continuously open and close the valve on the oxygen tank in response to the patients need; in a feedback loop between the patient and the oxygen tank.

2 comments:

This is going to be quite laggy

All the medical device standards call for direct control of Fi02

A pulse oximeter works by measuring the hemoglobin 02 saturation through light refraction tuned to hemoglobin.
Oxygen sensors for devices are measuring the gas concentration.

I would like to suggest that will it be effective if a feedback from blood oxygen level monitor is taken via Bluetooth and the same could be used to control the speed of blower?

See point 1 above.
Response time is going to be >1minute.  Have fun tuning that PID loop.  PS you can't just adjust blower speed to force more air in, you'll rupture the patient's lungs.  You'd need to be much more advanced than that - increasing PIP until a limit is reached, then increasing cycling rate between PIP and PEEP after that.

Since your primary concern is the oxygenation of the patients blood...

The clinical standard is to get an arterial blood gas which measures paO2, paCO2 and HCO3.  If the patient has chemical poisonings the hemoglobin, specifically the pulse oximeter is not an accurate measure of oxygenation.

There is annoxygen sensor controlled by an App. It could work using an Arduino module to read the value of the sensor

 jcrubino is correct. Pulse oximeters estimate oxyhemoglobin saturation (SpO2) non-invasively. An arterial blood gas (ABG) is an invasive test that measures PaO2 (partial pressure of oxygen in arterial blood) plus other things. There is a relationship between arterial blood oxygen saturation, SaO2 (dependent variable), and PaO2 (independent variable); it is called the oxyhemoglobin dissociation curve. It is an S-shaped, non-linear curve (although the middle is relatively linear). In the upper region of the curve, large changes in PaO2 (which could be diagnostically important in a sick patient) result in only small changes in SaO2. For a patient breathing room air (21% FIO2) a pulse oximeter provides valuable information. But once a patient is on elevated FIO2, the PaO2 can easily be 150 to 300 mmHg or more and the SpO2 doesn't mean as much as changes in PaO2 relative to FIO2.
 There have been attempts at making miniaturized PO2 electrodes that can be inserted intra-arterially to enable continuous real-time PaO2 readouts, but a reliable device has yet to be developed. All past designs have had difficulty with maintaining accurate measurements over time due to protein buildup over the poles of the micro-Clark electrode or micro-FET. As mentioned by others, real-time SpO2 monitoring is too slow to pick up clinically significant changes in PaO2. And real-time PaO2 monitoring just doesn't work for very long. Thus, closed-loop feedback control of O2 therapy and ventilatory devices has not become an everyday reality at this time.
 Besides, a ventilator regulates ventilation, which controls CO2 excretion. If you wanted to control the ventilator via feedback from a physiological parameter, you would want to use the arterial carbon dioxide tension (PaCO2) as an indicator since PaCO2 is inversely related to minute ventilation (rate x tidal volume) and directly related to CO2 production. There are devices known as capnographs or capnometers that measure CO2 in respiratory gases and considerable research has been done and is underway with respect to closed-loop control of the ventilator based upon exhaled CO2. However, it turns out to not be quite so simple as there is a multitude of inputs that go into managing a ventilator patient, and doing so on the basis of a couple of physiologic transducer signals ignores many other important factors.
 I'm a respiratory therapist and pulmonary physiologist; most of you are engineers. To solve certain problems, we need each other.

I just spent 20 minutes writing a nice little piece on SpO2, PaO2, the oxyhemoglobin dissociation curve, and closed-loop control of mechanical ventilators. Somehow it got lost in the ether. I'm too tired to do it again.  Anyway, at the end I said I'm a respiratory therapist and pulmonary physiologist and many of you are engineers. To solve many of these issues, we need each other.


Stream Health event log seems to get stuck after a while on "Waiting for events"

Stream Health event log seems to get stuck after a while on "Waiting for events"

What do you mean exactly with getting stuck? Was there any data there that should have been displayed and wasn't? Right now we only log when the stream becomes active/inactive, and any transcoding error that happened.
If you open the stream health page 5 minutes after the stream has started (which is the amount we look back for events), and are not getting any transcoding errors, that's exactly what's going to show up on that logs view. What did you expect to happen exactly? We can increase that "look back" time so you are more likely to find the "active" event, perhaps, but opening the stream health page could get considerably more expensive on the user network, downloading all the historical events from stream health (say, 15KB of events for each minute that the stream has been active + we look back).


Better memory usage + better function usage

The line 131 contained an error ! It is now solved and working correctly :)
The document ID (around line 120) was only used ones. To improve memory usage and variables readability, there are some little changes there.
Some commentaries are now formatted as the others were.

Sorry for my english, it may not be perfect...


Failed to render yc error when sending a GraphQL endpoint

Expected Behavior
When we try to open our workspace and hit our graphql endpoint, we just get a failed to render yc error, and then can't make any reuqests.
Actual Behavior
The program errors out and we can't do anything
Reproduction Steps
Just open it and try to open a GQL query
Is there an existing issue for this?

[X] I have searched the issue tracker for this problem.

Additional Information
Here is what we get upon opening

Then going to any other request we just get this

Insomnia Version
2022.7.0
What operating system are you using?
Windows
Operating System Version
Windows 10 & 11
Installation method
Download from insomnia
Last Known Working Insomnia version
2022.6.0

I have the same issue.
Stack trace:
Error: Type Query must define one or more fields.
    at nR (file:///Applications/Insomnia.app/Contents/Resources/app.asar/index.7cb7367d.js:504:12630)
    at y_ (file:///Applications/Insomnia.app/Contents/Resources/app.asar/index.7cb7367d.js:506:43944)
    at AK (file:///Applications/Insomnia.app/Contents/Resources/app.asar/index.7cb7367d.js:635:356)
    at FK (file:///Applications/Insomnia.app/Contents/Resources/app.asar/index.7cb7367d.js:641:211)
    at Object.DTe (file:///Applications/Insomnia.app/Contents/Resources/app.asar/index.7cb7367d.js:641:147)
    at file:///Applications/Insomnia.app/Contents/Resources/app.asar/index.7cb7367d.js:646:2557
    at x (file:///Applications/Insomnia.app/Contents/Resources/app.asar/index.7cb7367d.js:431:14293)
    at ii.<anonymous> (file:///Applications/Insomnia.app/Contents/Resources/app.asar/index.7cb7367d.js:431:16262)
    at file:///Applications/Insomnia.app/Contents/Resources/app.asar/index.7cb7367d.js:407:10355
    at ii.setOption (file:///Applications/Insomnia.app/Contents/Resources/app.asar/index.7cb7367d.js:412:1978)
    at file:///Applications/Insomnia.app/Contents/Resources/app.asar/index.7cb7367d.js:671:5056
    at mE (file:///Applications/Insomnia.app/Contents/Resources/app.asar/index.7cb7367d.js:67:24458)
    at nh (file:///Applications/Insomnia.app/Contents/Resources/app.asar/index.7cb7367d.js:67:42799)
    at file:///Applications/Insomnia.app/Contents/Resources/app.asar/index.7cb7367d.js:67:41058
    at A (file:///Applications/Insomnia.app/Contents/Resources/app.asar/index.7cb7367d.js:52:1648)
    at Immediate.ce [as _onImmediate] (file:///Applications/Insomnia.app/Contents/Resources/app.asar/index.7cb7367d.js:52:2022)
    at process.processImmediate (node:internal/timers:466:21)
    ```

Same, this is super annoying.
As a workaround to disable all checks and autocompletion:

Navigate to a query that isn't broken
Restart Insomnia or reopen the project to load that query
Click on "schema"
Disable "Automatic Fetch"
Click "Load schema from JSON"
Load an empty file

That will cause an error but also disable all checks and autocompletion.
Now you can fix the query and re-enable "Automatic Fetch".

@fluidsonic we ended up rolling back a version so we could have auto complete and what not but that's good to know. Just uninstall and install this version if you want. https://github.com/Kong/insomnia/releases/tag/core%402022.6.0

Thanks, I was looking for that one! 🙏

I just updated and it seems to be fixed for me. Thanks!

Same here, version 2022.7.0.
I just typed wrong argument to field in variables, without sending request and I got these permanently error - i can not do anything without reinstalling whole app.
GraphQLError: Enum "Currency" cannot represent non-string value: 2137.     at Yl.parseValue (file:///Applications/Insomnia.app/Contents/Resources/app.asar/index.7cb7367d.js:502:10673)     at Vm (file:///Applications/Insomnia.app/Contents/Resources/app.asar/index.7cb7367d.js:646:20522)     at file:///Applications/Insomnia.app/Contents/Resources/app.asar/index.7cb7367d.js:646:19879     at Array.map (<anonymous>)     at H5 (file:///Applications/Insomnia.app/Contents/Resources/app.asar/index.7cb7367d.js:646:20809)     at Vm (file:///Applications/Insomnia.app/Contents/Resources/app.asar/index.7cb7367d.js:646:19659)     at Vm (file:///Applications/Insomnia.app/Contents/Resources/app.asar/index.7cb7367d.js:646:19335)     at file:///Applications/Insomnia.app/Contents/Resources/app.asar/index.7cb7367d.js:646:19019     at Array.forEach (<anonymous>)     at UCe (file:///Applications/Insomnia.app/Contents/Resources/app.asar/index.7cb7367d.js:646:18928)     at file:///Applications/Insomnia.app/Contents/Resources/app.asar/index.7cb7367d.js:646:18866     at x (file:///Applications/Insomnia.app/Contents/Resources/app.asar/index.7cb7367d.js:431:14293)     at ii.<anonymous> (file:///Applications/Insomnia.app/Contents/Resources/app.asar/index.7cb7367d.js:431:16262)     at file:///Applications/Insomnia.app/Contents/Resources/app.asar/index.7cb7367d.js:407:10355     at ii.setOption (file:///Applications/Insomnia.app/Contents/Resources/app.asar/index.7cb7367d.js:412:1978)     at file:///Applications/Insomnia.app/Contents/Resources/app.asar/index.7cb7367d.js:671:5056     at mE (file:///Applications/Insomnia.app/Contents/Resources/app.asar/index.7cb7367d.js:67:24458)     at nh (file:///Applications/Insomnia.app/Contents/Resources/app.asar/index.7cb7367d.js:67:42799)     at file:///Applications/Insomnia.app/Contents/Resources/app.asar/index.7cb7367d.js:67:41058     at A (file:///Applications/Insomnia.app/Contents/Resources/app.asar/index.7cb7367d.js:52:1648)     at Immediate.ce [as _onImmediate] (file:///Applications/Insomnia.app/Contents/Resources/app.asar/index.7cb7367d.js:52:2022)     at process.processImmediate (node:internal/timers:466:21)


Sdc gallery app, implement dropdown component workflow.

Is your feature request related to a problem? Please describe.

User click on dropdown component.
It launches dropdown screen with questionnaire, which demonstrate dropdown uses.
click on navigation back key in action bar, it takes user back on landing page.

Design dropdown questionnaire json.
Write api to fetch dropdown questionnaire json file name.
Apply custom style at application side.
Describe the solution you'd like
A clear and concise description of what you want to happen.
Describe alternatives you've considered
A clear and concise description of any alternative solutions or features you've considered.
Additional context
Add any other context or screenshots about the feature request here.
Would you like to work on the issue?
Please state if this issue should be assigned to you or who you think could help to solve this issue.

@shelaghm
I am thinking not to have first field which is name(input type EditText) in the questionnaire screen, and just to add drop down questionnaire item which is relationship. As this workflow is mainly design for drop down questionnaire view.
Please let me know your input on it.

When item get clicked from drop down list, it shows blue color background on click. At this moment I tried to find the way to change it but not sure about the option, I need to look into it further.

@santosh-pingle

Yes, let's remove text field above.
Can you upload a screenshot of what it looks like on click? If it is the default material blue background it might be okay.


[DOCFIX] Tweak FUSE metric and property descriptions

Minor tweaks to metric descriptions to the metric FUSE_CACHED_PATH_COUNT.

Codecov Report

Merging #14399 (7c9f9ad) into master (f24cc71) will decrease coverage by 18.54%.
The diff coverage is 66.87%.

@@              Coverage Diff              @@
##             master   #14399       +/-   ##
=============================================
- Coverage     35.49%   16.95%   -18.55%
+ Complexity     7672     2704     -4968
=============================================
  Files          1493     1495        +2
  Lines         87361    87492      +131
  Branches      10420    10427        +7
=============================================
- Hits          31012    14831    -16181
- Misses        53747    71421    +17674
+ Partials       2602     1240     -1362

Impacted Files
Coverage Δ

.../java/alluxio/master/block/DefaultBlockMaster.java
40.62% <0.00%> (-0.07%)
:arrow_down:

...main/java/alluxio/master/job/plan/PlanTracker.java
0.00% <0.00%> (-66.28%)
:arrow_down:

...in/java/alluxio/master/AlluxioExecutorService.java
33.33% <33.33%> (ø)

...in/java/alluxio/master/ExecutorServiceBuilder.java
55.40% <55.40%> (ø)

...common/src/main/java/alluxio/conf/PropertyKey.java
98.05% <100.00%> (-1.39%)
:arrow_down:

...ommon/src/main/java/alluxio/metrics/MetricKey.java
97.57% <100.00%> (-0.38%)
:arrow_down:

...n/src/main/java/alluxio/metrics/MetricsSystem.java
51.50% <100.00%> (-9.94%)
:arrow_down:

...main/java/alluxio/master/AlluxioMasterProcess.java
67.64% <100.00%> (-2.15%)
:arrow_down:

...mon/src/main/java/alluxio/shell/CommandReturn.java
0.00% <0.00%> (-100.00%)
:arrow_down:

...mon/src/main/java/alluxio/util/ExceptionUtils.java
0.00% <0.00%> (-100.00%)
:arrow_down:

... and 574 more

Continue to review full report at Codecov.

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Δ = absolute <relative> (impact), ø = not affected, ? = missing data
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alluxio-bot, merge this please

@Xenorith cherry-pick?

alluxio-bot, cherry-pick this to branch-2.7 please


Don't Merge! PR real time test for webhook case

Docs Build status updates of commit d345a69:
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Docs Build status updates of commit d345a69:
:clock10: Full build: the average full build time is 7 min(s) 33 sec(s), this is based on the last 30 build(s) for this repository.

Docs Build status updates of commit d345a69:
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Details

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:white_check_mark:Succeeded
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Starting work on PyCon Taiwan 2016

Closes #25

We need descriptions and speakers for this PR before we can merge.

I'd like to merge this in with descriptions. However, I'm not sure when those will come around and I only speak english. In the hopes of getting these seen and descriptions added and getting the resources out on pyvideo, I'm merging this in sans descriptions.


[FEATURE] Text Splitter

Please add a Text splitting service for breaking up text into chunks for LLMs that have a token input limit beneath the size of the data, that takes:

A large piece of text as input
Parameters such as the size of each chunk
Separators to split text by
Optionally splitting into chunks measured by the maximum number of tokens (with tokenizer)

See RecursiveTextSplitter in langchain as the most popular option for splitting with langchain.

@tonybaloney it is all already implemented, please take a look here.
"RecursiveTextSplitter" can be created like this or this.


phpDoc for Request::validate

Hi, can you please finally add for lluminate\Http\Request::validate phpDoc. You officially suggest to call this method for Request class, but because this is macros. IDE like PhpStorm don't understand this method. Can you please add something like this.
namespace Illuminate\Http;

/**
 * @method array validate(array $rules)
 */
class Request extends SymfonyRequest implements Arrayable, ArrayAccess

It will be very useful, for IDE and autocompletion. If you add this tiny phpDoc above the class Request implementation. My IDE always show me warnings... very annoying. :)
Thank you! Very waiting.

If you feel that something should be added feel free to send in a PR.


Some changes about the dynamic libraries generated by gpu.cpp project and header-only source code 'gpu.hpp'

feat: 1. Modified the 'lib' rule in the Makefile file located in the root directory of the project, allowing it to generate gpu.cpp dynamic libraries with different suffixes based on the system.
      2. By the build.py script, the header files in the gpu.hpp file are expanded in order to make gpu.hpp become true header-only source code.
      3. 'install' and 'uninstall' rules are provided for scientific researchers who do not care about how to package applications, enabling them to quickly utilize gpu.cpp for gpu computation.

Thanks, very pro- researchers experimenting with gpu computation. I suspect there might be other ways to make header-only work but we can start with this approach. Targeting the dev branch for now to experiment + check if anything breaks before merging to main.