[Bug]: An EXTREMELY WEIRD bug when I import evaluate before vllm

Your current environment

The output of `python collect_env.py`
2024-10-25 10:53:08.913038: I tensorflow/core/util/port.cc:153] 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.
2024-10-25 10:53:08.930326: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:485] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
2024-10-25 10:53:08.951819: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:8454] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
2024-10-25 10:53:08.958215: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1452] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
2024-10-25 10:53:08.973693: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
2024-10-25 10:53:10.049917: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
PyTorch version: 2.4.0+cu121
Is debug build: False
CUDA used to build PyTorch: 12.1
ROCM used to build PyTorch: N/A
OS: Ubuntu 22.04.3 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: Could not collect
CMake version: version 3.30.0
Libc version: glibc-2.35
Python version: 3.11.7 | packaged by conda-forge | (main, Dec 15 2023, 08:38:37) [GCC 12.3.0] (64-bit runtime)
Python platform: Linux-6.8.0-45-generic-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: 12.4.131
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration:
GPU 0: NVIDIA RTX 6000 Ada Generation
GPU 1: NVIDIA RTX 6000 Ada Generation
GPU 2: NVIDIA RTX 6000 Ada Generation
GPU 3: NVIDIA RTX 6000 Ada Generation
Nvidia driver version: 550.107.02
cuDNN version: Probably one of the following:
/usr/local/cuda-11.6/targets/x86_64-linux/lib/libcudnn.so.8
/usr/local/cuda-11.6/targets/x86_64-linux/lib/libcudnn_adv_infer.so.8
/usr/local/cuda-11.6/targets/x86_64-linux/lib/libcudnn_adv_train.so.8
/usr/local/cuda-11.6/targets/x86_64-linux/lib/libcudnn_cnn_infer.so.8
/usr/local/cuda-11.6/targets/x86_64-linux/lib/libcudnn_cnn_train.so.8
/usr/local/cuda-11.6/targets/x86_64-linux/lib/libcudnn_ops_infer.so.8
/usr/local/cuda-11.6/targets/x86_64-linux/lib/libcudnn_ops_train.so.8
/usr/local/cuda-12.4/targets/x86_64-linux/lib/libcudnn.so.8
/usr/local/cuda-12.4/targets/x86_64-linux/lib/libcudnn_adv_infer.so.8
/usr/local/cuda-12.4/targets/x86_64-linux/lib/libcudnn_adv_train.so.8
/usr/local/cuda-12.4/targets/x86_64-linux/lib/libcudnn_cnn_infer.so.8
/usr/local/cuda-12.4/targets/x86_64-linux/lib/libcudnn_cnn_train.so.8
/usr/local/cuda-12.4/targets/x86_64-linux/lib/libcudnn_ops_infer.so.8
/usr/local/cuda-12.4/targets/x86_64-linux/lib/libcudnn_ops_train.so.8
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True
CPU:
架构：                                x86_64
CPU 运行模式：                        32-bit, 64-bit
Address sizes:                        46 bits physical, 48 bits virtual
字节序：                              Little Endian
CPU:                                  80
在线 CPU 列表：                       0-79
厂商 ID：                             GenuineIntel
型号名称：                            Intel(R) Xeon(R) Gold 5218R CPU @ 2.10GHz
CPU 系列：                            6
型号：                                85
每个核的线程数：                      2
每个座的核数：                        20
座：                                  2
步进：                                7
CPU 最大 MHz：                        4000.0000
CPU 最小 MHz：                        800.0000
BogoMIPS：                            4200.00
标记：                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cdp_l3 intel_ppin ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm mpx rdt_a avx512f avx512dq rdseed adx smap clflushopt clwb intel_pt avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local dtherm ida arat pln pts vnmi pku ospke avx512_vnni md_clear flush_l1d arch_capabilities
虚拟化：                              VT-x
L1d 缓存：                            1.3 MiB (40 instances)
L1i 缓存：                            1.3 MiB (40 instances)
L2 缓存：                             40 MiB (40 instances)
L3 缓存：                             55 MiB (2 instances)
NUMA 节点：                           2
NUMA 节点0 CPU：                      0,2,4,6,8,10,12,14,16,18,20,22,24,26,28,30,32,34,36,38,40,42,44,46,48,50,52,54,56,58,60,62,64,66,68,70,72,74,76,78
NUMA 节点1 CPU：                      1,3,5,7,9,11,13,15,17,19,21,23,25,27,29,31,33,35,37,39,41,43,45,47,49,51,53,55,57,59,61,63,65,67,69,71,73,75,77,79
Vulnerability Gather data sampling:   Mitigation; Microcode
Vulnerability Itlb multihit:          KVM: Mitigation: VMX disabled
Vulnerability L1tf:                   Not affected
Vulnerability Mds:                    Not affected
Vulnerability Meltdown:               Not affected
Vulnerability Mmio stale data:        Mitigation; Clear CPU buffers; SMT vulnerable
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed:               Mitigation; Enhanced IBRS
Vulnerability Spec rstack overflow:   Not affected
Vulnerability Spec store bypass:      Mitigation; Speculative Store Bypass disabled via prctl
Vulnerability Spectre v1:             Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:             Mitigation; Enhanced / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI SW loop, KVM SW loop
Vulnerability Srbds:                  Not affected
Vulnerability Tsx async abort:        Mitigation; TSX disabled
Versions of relevant libraries:
[pip3] mypy-extensions==1.0.0
[pip3] numpy==1.26.2
[pip3] nvidia-cublas-cu12==<IP_ADDRESS>
[pip3] nvidia-cuda-cupti-cu12==12.1.105
[pip3] nvidia-cuda-nvrtc-cu12==12.1.105
[pip3] nvidia-cuda-runtime-cu12==12.1.105
[pip3] nvidia-cudnn-cu12==<IP_ADDRESS>
[pip3] nvidia-cufft-cu12==<IP_ADDRESS>
[pip3] nvidia-curand-cu12==<IP_ADDRESS>
[pip3] nvidia-cusolver-cu12==<IP_ADDRESS>
[pip3] nvidia-cusparse-cu12==<IP_ADDRESS>
[pip3] nvidia-ml-py==12.550.52
[pip3] nvidia-nccl-cu12==2.20.5
[pip3] nvidia-nvjitlink-cu12==12.5.82
[pip3] nvidia-nvtx-cu12==12.1.105
[pip3] onnxruntime==1.16.3
[pip3] optree==0.11.0
[pip3] pynvml==11.5.0
[pip3] pyzmq==25.1.2
[pip3] sentence-transformers==3.0.0
[pip3] torch==2.4.0
[pip3] torchaudio==2.1.2
[pip3] torchsde==0.2.6
[pip3] torchvision==0.19.0
[pip3] transformers==4.45.2
[pip3] transformers-stream-generator==0.0.4
[pip3] triton==3.0.0
[conda] blas                      1.0                         mkl    defaults
[conda] cuda-cudart               12.1.105                      0    nvidia
[conda] cuda-cupti                12.1.105                      0    nvidia
[conda] cuda-libraries            12.1.0                        0    nvidia
[conda] cuda-nvcc                 12.1.105                      0    nvidia
[conda] cuda-nvrtc                12.1.105                      0    nvidia
[conda] cuda-nvtx                 12.1.105                      0    nvidia
[conda] cuda-opencl               12.3.101                      0    nvidia
[conda] cuda-runtime              12.1.0                        0    nvidia
[conda] faiss-gpu                 1.8.0           py3.11_h4c7d538_0_cuda12.1.1    pytorch
[conda] ffmpeg                    4.3                  hf484d3e_0    pytorch
[conda] libcublas                 <IP_ADDRESS>                     0    nvidia
[conda] libcufft                  <IP_ADDRESS>                      0    nvidia
[conda] libcufile                 <IP_ADDRESS>                       0    nvidia
[conda] libcurand                 <IP_ADDRESS>                    0    nvidia
[conda] libcusolver               <IP_ADDRESS>                     0    nvidia
[conda] libcusparse               <IP_ADDRESS>                     0    nvidia
[conda] libfaiss                  1.8.0           h046e95b_0_cuda12.1.1    pytorch
[conda] libjpeg-turbo             2.0.0                h9bf148f_0    pytorch
[conda] libnpp                    <IP_ADDRESS>                     0    nvidia
[conda] libnvjitlink              12.1.105                      0    nvidia
[conda] libnvjpeg                 <IP_ADDRESS>                     0    nvidia
[conda] mkl                       2023.1.0         h213fc3f_46344    defaults
[conda] mkl-service               2.4.0           py311h5eee18b_1    defaults
[conda] mkl_fft                   1.3.8           py311h5eee18b_0    defaults
[conda] mkl_random                1.2.4           py311hdb19cb5_0    defaults
[conda] numpy                     1.26.2          py311h08b1b3b_0    defaults
[conda] numpy-base                1.26.2          py311hf175353_0    defaults
[conda] nvidia-cublas-cu12        <IP_ADDRESS>                 pypi_0    pypi
[conda] nvidia-cuda-cupti-cu12    12.1.105                 pypi_0    pypi
[conda] nvidia-cuda-nvrtc-cu12    12.1.105                 pypi_0    pypi
[conda] nvidia-cuda-runtime-cu12  12.1.105                 pypi_0    pypi
[conda] nvidia-cudnn-cu12         <IP_ADDRESS>                 pypi_0    pypi
[conda] nvidia-cufft-cu12         <IP_ADDRESS>                pypi_0    pypi
[conda] nvidia-curand-cu12        <IP_ADDRESS>               pypi_0    pypi
[conda] nvidia-cusolver-cu12      <IP_ADDRESS>               pypi_0    pypi
[conda] nvidia-cusparse-cu12      <IP_ADDRESS>               pypi_0    pypi
[conda] nvidia-nccl-cu12          2.20.5                   pypi_0    pypi
[conda] nvidia-nvjitlink-cu12     12.5.82                  pypi_0    pypi
[conda] nvidia-nvtx-cu12          12.1.105                 pypi_0    pypi
[conda] optree                    0.11.0                   pypi_0    pypi
[conda] pynvml                    11.5.0                   pypi_0    pypi
[conda] pytorch-cuda              12.1                 ha16c6d3_5    pytorch
[conda] pytorch-mutex             1.0                        cuda    pytorch
[conda] pyzmq                     25.1.2          py311h34ded2d_0    conda-forge
[conda] sentence-transformers     3.0.0                    pypi_0    pypi
[conda] torch                     2.4.0                    pypi_0    pypi
[conda] torchaudio                2.1.2               py311_cu121    pytorch
[conda] torchsde                  0.2.6                    pypi_0    pypi
[conda] torchvision               0.19.0                   pypi_0    pypi
[conda] transformers              4.45.2                   pypi_0    pypi
[conda] transformers-stream-generator 0.0.4                    pypi_0    pypi
[conda] triton                    3.0.0                    pypi_0    pypi
ROCM Version: Could not collect
Neuron SDK Version: N/A
vLLM Version: 0.6.3.post1
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled
GPU Topology:
GPU0    GPU1    GPU2    GPU3    CPU Affinity    NUMA Affinity   GPU NUMA ID
GPU0     X      NODE    SYS     SYS     0,2,4,6,8,10    0               N/A
GPU1    NODE     X      SYS     SYS     0,2,4,6,8,10    0               N/A
GPU2    SYS     SYS      X      NODE    1,3,5,7,9,11    1               N/A
GPU3    SYS     SYS     NODE     X      1,3,5,7,9,11    1               N/A
Legend:
X    = Self
SYS  = Connection traversing PCIe as well as the SMP interconnect between NUMA nodes (e.g., QPI/UPI)
NODE = Connection traversing PCIe as well as the interconnect between PCIe Host Bridges within a NUMA node
PHB  = Connection traversing PCIe as well as a PCIe Host Bridge (typically the CPU)
PXB  = Connection traversing multiple PCIe bridges (without traversing the PCIe Host Bridge)
PIX  = Connection traversing at most a single PCIe bridge
NV#  = Connection traversing a bonded set of # NVLinks

Model Input Dumps
No response
🐛 Describe the bug
evaluate == 0.4.3
vllm == 0.6.3.post1

If I import evaluate before vllm:
import evaluate
import vllm
vllm.LLM('my_local_path_of_mistral_7b_base')

A bug will be raised:
2024-10-25 10:55:49.480431: I tensorflow/core/util/port.cc:153] 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`.
2024-10-25 10:55:49.497640: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:485] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
2024-10-25 10:55:49.518802: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:8454] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
2024-10-25 10:55:49.525222: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1452] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
2024-10-25 10:55:49.540380: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
2024-10-25 10:55:50.763501: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
ERROR 10-25 10:55:54 registry.py:267] Error in inspecting model architecture 'MistralForCausalLM'
ERROR 10-25 10:55:54 registry.py:267] Traceback (most recent call last):
ERROR 10-25 10:55:54 registry.py:267]   File "/home/lzc/.conda/envs/workspace/lib/python3.11/site-packages/vllm/model_executor/models/registry.py", line 428, in _run_in_subprocess
ERROR 10-25 10:55:54 registry.py:267]     returned.check_returncode()
ERROR 10-25 10:55:54 registry.py:267]   File "/home/lzc/.conda/envs/workspace/lib/python3.11/subprocess.py", line 502, in check_returncode
ERROR 10-25 10:55:54 registry.py:267]     raise CalledProcessError(self.returncode, self.args, self.stdout,
ERROR 10-25 10:55:54 registry.py:267] subprocess.CalledProcessError: Command '['/home/lzc/.conda/envs/workspace/bin/python', '-m', 'vllm.model_executor.models.registry']' returned non-zero exit status 1.
ERROR 10-25 10:55:54 registry.py:267]
ERROR 10-25 10:55:54 registry.py:267] The above exception was the direct cause of the following exception:
ERROR 10-25 10:55:54 registry.py:267]
ERROR 10-25 10:55:54 registry.py:267] Traceback (most recent call last):
ERROR 10-25 10:55:54 registry.py:267]   File "/home/lzc/.conda/envs/workspace/lib/python3.11/site-packages/vllm/model_executor/models/registry.py", line 265, in _try_inspect_model_cls
ERROR 10-25 10:55:54 registry.py:267]     return model.inspect_model_cls()
ERROR 10-25 10:55:54 registry.py:267]            ^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 10-25 10:55:54 registry.py:267]   File "/home/lzc/.conda/envs/workspace/lib/python3.11/site-packages/vllm/model_executor/models/registry.py", line 227, in inspect_model_cls
ERROR 10-25 10:55:54 registry.py:267]     return _run_in_subprocess(
ERROR 10-25 10:55:54 registry.py:267]            ^^^^^^^^^^^^^^^^^^^
ERROR 10-25 10:55:54 registry.py:267]   File "/home/lzc/.conda/envs/workspace/lib/python3.11/site-packages/vllm/model_executor/models/registry.py", line 431, in _run_in_subprocess
ERROR 10-25 10:55:54 registry.py:267]     raise RuntimeError(f"Error raised in subprocess:\n"
ERROR 10-25 10:55:54 registry.py:267] RuntimeError: Error raised in subprocess:
ERROR 10-25 10:55:54 registry.py:267] Error: mkl-service + Intel(R) MKL: MKL_THREADING_LAYER=INTEL is incompatible with libgomp-a34b3233.so.1 library.
ERROR 10-25 10:55:54 registry.py:267]   Try to import numpy first or set the threading layer accordingly. Set MKL_SERVICE_FORCE_INTEL to force it.
ERROR 10-25 10:55:54 registry.py:267]
Traceback (most recent call last):
  File "/home/lzc/workspace/LESS/test.py", line 3, in <module>
    model = vllm.LLM(
            ^^^^^^^^^
  File "/home/lzc/.conda/envs/workspace/lib/python3.11/site-packages/vllm/entrypoints/llm.py", line 177, in __init__
    self.llm_engine = LLMEngine.from_engine_args(
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/lzc/.conda/envs/workspace/lib/python3.11/site-packages/vllm/engine/llm_engine.py", line 570, in from_engine_args
    engine_config = engine_args.create_engine_config()
                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/lzc/.conda/envs/workspace/lib/python3.11/site-packages/vllm/engine/arg_utils.py", line 903, in create_engine_config
    model_config = self.create_model_config()
                   ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/lzc/.conda/envs/workspace/lib/python3.11/site-packages/vllm/engine/arg_utils.py", line 839, in create_model_config
    return ModelConfig(
           ^^^^^^^^^^^^
  File "/home/lzc/.conda/envs/workspace/lib/python3.11/site-packages/vllm/config.py", line 200, in __init__
    self.multimodal_config = self._init_multimodal_config(
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/lzc/.conda/envs/workspace/lib/python3.11/site-packages/vllm/config.py", line 219, in _init_multimodal_config
    if ModelRegistry.is_multimodal_model(architectures):
       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/lzc/.conda/envs/workspace/lib/python3.11/site-packages/vllm/model_executor/models/registry.py", line 386, in is_multimodal_model
    return self.inspect_model_cls(architectures).supports_multimodal
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/lzc/.conda/envs/workspace/lib/python3.11/site-packages/vllm/model_executor/models/registry.py", line 355, in inspect_model_cls
    return self._raise_for_unsupported(architectures)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/lzc/.conda/envs/workspace/lib/python3.11/site-packages/vllm/model_executor/models/registry.py", line 317, in _raise_for_unsupported
    raise ValueError(
ValueError: Model architectures ['MistralForCausalLM'] are not supported for now. Supported architectures: ['AquilaModel', 'AquilaForCausalLM', 'ArcticForCausalLM', 'BaiChuanForCausalLM', 'BaichuanForCausalLM', 'BloomForCausalLM', 'CohereForCausalLM', 'DbrxForCausalLM', 'DeciLMForCausalLM', 'DeepseekForCausalLM', 'DeepseekV2ForCausalLM', 'ExaoneForCausalLM', 'FalconForCausalLM', 'GemmaForCausalLM', 'Gemma2ForCausalLM', 'GPT2LMHeadModel', 'GPTBigCodeForCausalLM', 'GPTJForCausalLM', 'GPTNeoXForCausalLM', 'GraniteForCausalLM', 'GraniteMoeForCausalLM', 'InternLMForCausalLM', 'InternLM2ForCausalLM', 'JAISLMHeadModel', 'JambaForCausalLM', 'LlamaForCausalLM', 'LLaMAForCausalLM', 'MambaForCausalLM', 'MistralForCausalLM', 'MixtralForCausalLM', 'QuantMixtralForCausalLM', 'MptForCausalLM', 'MPTForCausalLM', 'MiniCPMForCausalLM', 'MiniCPM3ForCausalLM', 'NemotronForCausalLM', 'OlmoForCausalLM', 'OlmoeForCausalLM', 'OPTForCausalLM', 'OrionForCausalLM', 'PersimmonForCausalLM', 'PhiForCausalLM', 'Phi3ForCausalLM', 'Phi3SmallForCausalLM', 'PhiMoEForCausalLM', 'Qwen2ForCausalLM', 'Qwen2MoeForCausalLM', 'RWForCausalLM', 'StableLMEpochForCausalLM', 'StableLmForCausalLM', 'Starcoder2ForCausalLM', 'SolarForCausalLM', 'XverseForCausalLM', 'BartModel', 'BartForConditionalGeneration', 'Gemma2Model', 'MistralModel', 'Qwen2ForRewardModel', 'Phi3VForCausalLM', 'Blip2ForConditionalGeneration', 'ChameleonForConditionalGeneration', 'ChatGLMModel', 'ChatGLMForConditionalGeneration', 'FuyuForCausalLM', 'InternVLChatModel', 'LlavaForConditionalGeneration', 'LlavaNextForConditionalGeneration', 'LlavaNextVideoForConditionalGeneration', 'LlavaOnevisionForConditionalGeneration', 'MiniCPMV', 'MolmoForCausalLM', 'NVLM_D', 'PaliGemmaForConditionalGeneration', 'PixtralForConditionalGeneration', 'QWenLMHeadModel', 'Qwen2VLForConditionalGeneration', 'UltravoxModel', 'MllamaForConditionalGeneration', 'EAGLEModel', 'MedusaModel', 'MLPSpeculatorPreTrainedModel']

But it would be ok if I import vllm first:
import vllm
import evaluate
vllm.LLM('my_local_path_of_mistral_7b_base')

The result is:
2024-10-25 10:58:41.972433: I tensorflow/core/util/port.cc:153] 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`.
2024-10-25 10:58:41.989092: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:485] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
2024-10-25 10:58:42.009503: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:8454] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
2024-10-25 10:58:42.015482: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1452] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
2024-10-25 10:58:42.030683: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
2024-10-25 10:58:43.098735: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
INFO 10-25 10:58:54 llm_engine.py:237] Initializing an LLM engine (v0.6.3.post1) with config: model='/home/lzc/workspace/LESS/out/mistral-7b-less-p0.05-lora-tydiqa/full', speculative_config=None, tokenizer='/home/lzc/workspace/LESS/out/mistral-7b-less-p0.05-lora-tydiqa/full', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, override_neuron_config=None, rope_scaling=None, rope_theta=None, tokenizer_revision=None, trust_remote_code=False, dtype=torch.bfloat16, max_seq_len=32768, download_dir=None, load_format=LoadFormat.AUTO, tensor_parallel_size=1, pipeline_parallel_size=1, disable_custom_all_reduce=False, quantization=None, enforce_eager=False, kv_cache_dtype=auto, quantization_param_path=None, device_config=cuda, decoding_config=DecodingConfig(guided_decoding_backend='outlines'), observability_config=ObservabilityConfig(otlp_traces_endpoint=None, collect_model_forward_time=False, collect_model_execute_time=False), seed=0, served_model_name=/home/lzc/workspace/LESS/out/mistral-7b-less-p0.05-lora-tydiqa/full, num_scheduler_steps=1, chunked_prefill_enabled=False multi_step_stream_outputs=True, enable_prefix_caching=False, use_async_output_proc=True, use_cached_outputs=False, mm_processor_kwargs=None)
INFO 10-25 10:58:54 selector.py:247] Cannot use FlashAttention-2 backend due to sliding window.
INFO 10-25 10:58:54 selector.py:115] Using XFormers backend.
/home/lzc/.conda/envs/workspace/lib/python3.11/site-packages/xformers/ops/fmha/flash.py:211: FutureWarning: `torch.library.impl_abstract` was renamed to `torch.library.register_fake`. Please use that instead; we will remove `torch.library.impl_abstract` in a future version of PyTorch.
  @torch.library.impl_abstract("xformers_flash::flash_fwd")
/home/lzc/.conda/envs/workspace/lib/python3.11/site-packages/xformers/ops/fmha/flash.py:344: FutureWarning: `torch.library.impl_abstract` was renamed to `torch.library.register_fake`. Please use that instead; we will remove `torch.library.impl_abstract` in a future version of PyTorch.
  @torch.library.impl_abstract("xformers_flash::flash_bwd")
INFO 10-25 10:58:55 model_runner.py:1056] Starting to load model /home/lzc/workspace/LESS/out/mistral-7b-less-p0.05-lora-tydiqa/full...
INFO 10-25 10:58:55 selector.py:247] Cannot use FlashAttention-2 backend due to sliding window.
INFO 10-25 10:58:55 selector.py:115] Using XFormers backend.
Loading safetensors checkpoint shards:   0% Completed | 0/3 [00:00<?, ?it/s]
Loading safetensors checkpoint shards:  33% Completed | 1/3 [00:01<00:02,  1.31s/it]
Loading safetensors checkpoint shards:  67% Completed | 2/3 [00:02<00:01,  1.38s/it]
Loading safetensors checkpoint shards: 100% Completed | 3/3 [00:04<00:00,  1.34s/it]
Loading safetensors checkpoint shards: 100% Completed | 3/3 [00:04<00:00,  1.35s/it]

INFO 10-25 10:59:00 model_runner.py:1067] Loading model weights took 13.4966 GB
INFO 10-25 10:59:03 gpu_executor.py:122] # GPU blocks: 12871, # CPU blocks: 2048
INFO 10-25 10:59:03 gpu_executor.py:126] Maximum concurrency for 32768 tokens per request: 6.28x
INFO 10-25 10:59:06 model_runner.py:1395] Capturing the model for CUDA graphs. This may lead to unexpected consequences if the model is not static. To run the model in eager mode, set 'enforce_eager=True' or use '--enforce-eager' in the CLI.
INFO 10-25 10:59:06 model_runner.py:1399] CUDA graphs can take additional 1~3 GiB memory per GPU. If you are running out of memory, consider decreasing `gpu_memory_utilization` or enforcing eager mode. You can also reduce the `max_num_seqs` as needed to decrease memory usage.

I just cannot find out why
Before submitting a new issue...

[X] Make sure you already searched for relevant issues, and asked the chatbot living at the bottom right corner of the documentation page, which can answer lots of frequently asked questions.

ERROR 10-25 10:55:54 registry.py:267] RuntimeError: Error raised in subprocess:
ERROR 10-25 10:55:54 registry.py:267] Error: mkl-service + Intel(R) MKL: MKL_THREADING_LAYER=INTEL is incompatible with libgomp-a34b3233.so.1 library.
ERROR 10-25 10:55:54 registry.py:267]   Try to import numpy first or set the threading layer accordingly. Set MKL_SERVICE_FORCE_INTEL to force it.

You should update your numpy version.


headerHTML

it is very inconvenient that headerHTML must be provided as a URL, not as a simple HTML String. Great, if you could change that.

That's already possible. You just need to pass a HTML string that starts with <html>, otherwhise it can not be detected. See this regex:
https://github.com/mikehaertl/phpwkhtmltopdf/blob/3f9c96656259712324eda99978ccd90c79227203/src/Pdf.php#L20-L21

Closing this as there was no further feedback. If you think there's still something to fix or improve feel free to add  another comment. But please provide a full (minimal) code example to reproduce the problem.


fix handling of some TLS options in Component configs

Codecov Report

Merging #848 into master will decrease coverage by 0.01%.
The diff coverage is 20%.

@@            Coverage Diff             @@
##           master     #848      +/-   ##
==========================================
- Coverage   62.93%   62.91%   -0.02%
==========================================
  Files          73       73
  Lines       12512    12516       +4
  Branches     1975     1976       +1
==========================================
+ Hits         7874     7875       +1
- Misses       3981     3984       +3
  Partials      657      657

Impacted Files
Coverage Δ

autobahn/wamp/component.py
45.64% <ø> (ø)
:arrow_up:

autobahn/twisted/component.py
38.61% <20%> (-0.28%)
:arrow_down:

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merged via https://github.com/crossbario/autobahn-python/pull/850


Are all tweets collected?

When I ran the query I get 85% of total tweets? However, after analysis, I could see that I could get only those tweets which are "replies" by twitter handle to the general public or "tweet" by twitter handle.
How to collect the incoming messages to the twitter handle and how to gather all the retweets to the tweet originated by the twitter handle?

When I queried for the tweets between June 1 2018 to till date, I got the tweets similar to the advanced search option of the Twitter when queried for the same period. But when I went on the @amazon on twitter , it included those tweets "amazon.com retweeted" mentioned. But when I clicked on the retweets i could not find the @amazon but its other handles like @amazonnews, amazonfiretv. And these tweets where it says that "amazon.com retweeted" are not included in tweets that we gather using twitterscraper.

As you can see in above image marked with blue color, these tweets are not included in our search criteria .

Did you try what I suggested in the other comments?
Here:

This library gets tweets from profiles rather than search:
https://github.com/kennethreitz/twitter-scraper

And Here:

You should try this library which gets from profiles rather than search
https://github.com/kennethreitz/twitter-scraper
Please report back whether it works for you

As we discussed with you in those threads, twitter search doesn't  show retweets, so you should try the library which gets the tweets from specific profiles which I am pointing out to you again:
https://github.com/kennethreitz/twitter-scraper

@NileshJorwar twitterscraper does not scrape retweets, as also discussed in https://github.com/taspinar/twitterscraper/issues/92

This issue should be fixed in version 0.9.0


New functionality and output improvements

New parameters IncludeManuallyInstalledUpdates & KeepPriorModuleVersions (self-explanatory)
Improved window title UI and console output
Overall cleanup
Enumerate old module versions that the script uninstalled or force-removed
Script can now update existing installed modules that weren't originally installed from the gallery

This change is

Codecov Report

Merging #24 into master will not change coverage.
The diff coverage is n/a.


connect to multiple peers in case first peer is not responding

with node.connect({host: "remote_ip", port: remote_port}) we can connect to the network with one other node, if that node goes offline, then it will not connect. would it be possible to use an Array[] and connect to multiple nodes, in case the first node does not work?

node.connect can be used more than once to connect to multiple nodes, you could loop through your array of nodes and connect to each of them.
The connect function returns an event emitter that will emit a "connected" event once connected to a node otherwise a "timeout" event will be emitted if the remote node is unreachable.


"Costinești" is listed in the drop-down menu

Description:
When user writes "Costinești" the location appears in the drop-down menu next to the comune and the county witch is a part according to the law
Precondition:
The website is up an running.

Step 1
Write in the search bar "Costinești"

Expected results
The location appears in the drop-down menu as "Comuna Costinești, CONSTANȚA"


"zero downtime"

from your README "It's been made with zero downtime in mind, meaning that when an unikernel is updated, a new instance is started while keeping the old one alive, and the switch to the new instance is managed using a port redirection to the new IP."
Now, I wonder: how does this work? Did you already solve the halting problem?
More seriously, how do you detect that a new unikernel is working nicely and switch over to the new IP address? Is there a generic path to do this?
I'm stumbling upon this due to the huge variance of unikernels and when they may be ready (some may need to clone a git repository, etc.) - plus interaction (the old may write to a git repo while the new cloned an old revision, is such a scenario handled?) of old and new.
Do you handle TCP connection to the old unikernel still working smoothly?

looks like there's a lack of interest to clarify the meaning, but I don't really care about it.


Gulp support

is there a way too put this in a .pipe() in gulp?
my use case is i want a local file to be watched and on file change for my css to be re-bundled.

I haven't tested it, but https://github.com/hughsk/vinyl-source-stream might work.

Before #13 is resolved, a way to get it working would be to use vinyl-source-stream:
const source = require('vinyl-source-stream')
const fromString = require('from2-string')
const gulp = require('gulp')

gulp.task('sheetify', function() {
  sheetify('./index.css').bundle(function (err, css) {
  if (err) throw err
  fromString(css)
    .pipe(source('index.css'))
    .pipe(gulp.dest('./'))
  })
})

Let me know if this works for you. Cheers!


Check lower bound returned by atoi()

A potential negative value returned by atoi() may cause an excessive memory allocation. This PR adds a check that the returned value is nonnegative.

We should really remove the atoi() call entirely and instead use metadata.parseAs<uint>().


net: lwm2m: lower priority of engine thread

The LwM2M engine thread is used for various periodic triggers.
None of these are in a critical path that requires super sensitive
timing and the current K_PRIO_COOP(7) setting was causing the
Bluetooth RX thread to have to wait too long for certain actions
to complete.
Let's lower the priority to -1 (effectively) to eliminate these
conflicts.
Signed-off-by: Michael Scott<EMAIL_ADDRESS>

NOTE: I considered moving the priority of this thread to preemptible.  But I'm not sure that anyone is actually using preemptible threads atm in Zephyr.  And initial testing seemed like it was breaking the thread (nothing was happening when it should be).
I still might move it to a higher priority preemptible thread with a bit of testing, but to be frank I'm really tired of working on scheduler bugs atm, so I'm just going to lower this to -1 for now to avoid having this thread get prioritized in the runq over most other cooperative threads.

Codecov Report

Merging #8230 into master will not change coverage.
The diff coverage is n/a.

@@           Coverage Diff           @@
##           master    #8230   +/-   ##
=======================================
  Coverage   64.53%   64.53%
=======================================
  Files         420      420
  Lines       40109    40109
  Branches     6762     6762
=======================================
  Hits        25884    25884
  Misses      11108    11108
  Partials     3117     3117

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NOTE: I considered moving the priority of this thread to preemptible.

Well, in my comment https://github.com/zephyrproject-rtos/zephyr/issues/8190#issuecomment-394971724 I didn't call to make it preemptive right away, just shared my opinion that if we want to get the priorities right, we should for each thread which uses cooperative prio, have a clear understanding why.

But I'm not sure that anyone is actually using preemptible threads atm in Zephyr.

What do you mean? The main thread is preemptive by default, so everyone uses preemptive threads in unbound number of cases, while in finite (and small) number of cases, for system threads, cooperative threads are used.

@MaureenHelm:

Does this patch fix any failures?

My understanding that no, it's a motion towards https://github.com/zephyrproject-rtos/zephyr/issues/8190 (to get prios right, we first need to get them not unright).

@MaureenHelm On real HW with BT interface, I was seeing conflicts with the BT RX thread which currently has a lower priority than the LwM2M engine service.   This was most notable where a long operation would take place and k_sleep() in the engine service would effectively turn into a k_yield():
See:
k_yield() usage in k_sleep: https://github.com/zephyrproject-rtos/zephyr/blob/master/kernel/sched.c#L764
LwM2M engine can return a 0 for the service sleep length: https://github.com/zephyrproject-rtos/zephyr/blob/master/subsys/net/lib/lwm2m/lwm2m_engine.c#L3720
Prior to the scheduler re-write k_yield() would call _move_thread_to_end_of_prio_q() where now it's removed and re-added based on it's priority.  The key difference being: lower priority cooperative threads don't get a chance to run.
@andyross Did I explain this correctly?
I'd like to take this patch for 1.12 if possible.

@pfalcon This was the last part of fixing actual delays seen on real HW using BT interface for networking where the bluetooth interrupt would be deferred for longer than 1 second if the LwM2M engine was hogging the scheduler.   As you mention, this should eventually be moved to a preemptable thread in v1.13 once more of the scheduler issues have been worked out.

What do you mean? The main thread is preemptive by default, so everyone uses preemptive threads in unbound number of cases, while in finite (and small) number of cases, for system threads, cooperative threads are used.

@pfalcon I was obviously exaggerating here. ;)

@andyross Did I explain this correctly?

Perfectly.  Note that if you really really really want a thread to get out of the way but come back as soon as possible, block on a semaphore in k_sem_take(), then have a thread at a lower priority (a system work_q item works well for this) do a k_sem_give().
Alternatively you can reprioritize a thread dynamically with k_thread_priority_set(), which will reschedule synchronously if needed (i.e. it acts like a blocking call if you drop your own priority below that of something on the run queue).
Both are voodoo.  But when you're actually out of CPU time sometimes voodoo is needed.
But changing default priorities is low risk and sane and if that works for you stay away from the voodoo.


Version 2.0.12 Is not generating errors on the console.

@bencompton First of all, kudos on adding a reporting in json! I noticed when I run my test and it has errors, I only see that it failed but I don't see any error messages on my console, so it's hard to debug my test.  The way I go around is by adding try-catches to log the errors, but it also passes the test even though it failed the assertion.  I'm not sure if this is a known error but would love to know if there's a configuration I could do to force the reporter to log errors.

@bencompton

I think this is the same issues I'm seeing. When expect fails, the exception is swallowed and the console just points the failure at test() without any useful output (eg. expected x but received y). only workaround is as mentioned above, to wrap the expect in try/catch

There might be a regression or a change of behavior, 2.0.11 would point to which part of the test failed (ie. given), but 2.0.12 point to the overall test.
For my same code and error, 2.0.11 would return
`    ReferenceError: getByText is not defined
  50 |
  51 |
> 52 |         given('my given step', () => {
     |                                                     ^
  53 |             ({getByText} = render(<MyComponent />))
  54 |         });
  55 |

`
while 2.0.12 now returns
     48 |      > 49 |     test.only('My test', ({ given, when, then, and }) => {          |          ^       50 |        51 |        52 |         given('my given step', () => {
without indication of what the error actually is

#27 is still in preview, and 2.0.11 is still the latest stable version. Sounds like there is a regression in 2.0.12 with with error reporting. My apologies to everyone for not being very responsive with this project lately. I hope to carve out some time to finish up #27 soon.

@nguillemin and @sibyldawn I'm trying to reproduce this by creating a simple test that fails:
specs/features/test.feature
Feature: Test feature

  Scenario: My test
    Given my given step

specs/step-definitions/test.steps.js
import { loadFeature, defineFeature } from 'jest-cucumber';

const feature = loadFeature('./specs/features/test.feature');

defineFeature(feature, (test) => {
    test('My test', ({ given }) => {
        given('my given step', () => {
            expect(true).toBe(false);
         });
    });
});

package.json
{
  "name": "test",
  "version": "1.0.0",
  "main": "index.js",
  "scripts": {
    "test": "jest"
  },
  "devDependencies": {
    "@babel/core": "^7.8.6",
    "@babel/preset-env": "^7.8.6",
    "babel-jest": "^25.1.0",
    "jest-cucumber": "2.0.12"
  },
  "jest": {
    "clearMocks": true,
    "testEnvironment": "node",
    "testMatch": [
      "**/*.steps.js"
    ]
  }
}

babel.config.js
module.exports = {
  presets: [
    [
      '@babel/preset-env',
      {
        targets: {
          node: 'current',
        },
      },
    ],
  ],
};

but it fails with, I believe, the expected information:
  FAIL  specs/step-definitions/test.steps.js
  Test feature
    ✕ My test (10ms)

  ● Test feature › My test

    Failed: Object {
      "matcherResult": Object {
        "actual": true,
        "expected": false,
        "message": [Function anonymous],
        "name": "toBe",
        "pass": false,
      },
      "message": "An error occurred while executing step \"my given step\": expect(received).toBe(expected) // Object.is equality

    Expected: false
    Received: true",
    }

      4 |
      5 | defineFeature(feature, (test) => {
    > 6 |     test('My test', ({ given }) => {
        |     ^
      7 |         given('my given step', () => {
      8 |             // let test;
      9 |             // console.log(test.undefined);

      at Env.it (node_modules/jest-jasmine2/build/jasmineAsyncInstall.js:91:24)
      at defineScenario (node_modules/jest-cucumber/src/feature-definition-creation.ts:119:5)
      at test (node_modules/jest-cucumber/src/feature-definition-creation.ts:227:13)
      at Object.<anonymous>.test (specs/step-definitions/test.steps.js:6:5)
      at Suite.<anonymous> (node_modules/jest-cucumber/src/feature-definition-creation.ts:314:9)
      at defineFeature (node_modules/jest-cucumber/src/feature-definition-creation.ts:313:5)

Test Suites: 1 failed, 1 total
Tests:       1 failed, 1 total
Snapshots:   0 total
Time:        0.577s, estimated 1s
Ran all test suites.

I'm using version 2.0.12 from npm. Is your setup different?


[SPARK-34627][SQL] Use FunctionIdentifier in UnresolvedTableValuedFunction

What changes were proposed in this pull request?
This PR updates UnresolvedTableValuedFunction's name to be a FunctionIdentifier instead of a string.
Why are the changes needed?
To make UnresolvedTableValuedFunction consistent with UnresolvedFunction that uses FunctionIdentifier as the function name.
Does this PR introduce any user-facing change?
No
How was this patch tested?
Unit test.

Test build #135785 has started for PR 31749 at commit 72fed75.

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This patch merges cleanly.
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thanks, merging to master!

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Enables set next statement feature.

Our UI tests caught a regression with breakpoints on Python 2.7 as well as problems with set next statement (adapter bug).
Let's wait for the breakpoint bug fix, and run the tests again before merging this.

This fix to ptvsd should improve the behavior, but does not entirely fix it.
https://github.com/Microsoft/ptvsd/pull/1267

We'll close and do another PR when the issues are fixed.
In the new PR, you should enable DebuggerUITests.DebugProjectUITests.SetNextLine for VSC debugger, ie. remove this code from the top of the test:
            if (useVsCodeDebugger) {
                // https://github.com/Microsoft/ptvsd/issues/18
                // This is not implemented in the experimental debugger
                Assert.Inconclusive();
                return;
            }


AttributeError: Can't get attribute 'task_func' on <module 'mp_main' from ./manage.py

Django 3.2.9
python 3.10.4
django-q 1.3.9
macOS Monterey Version 12.5
Hello, when i run manage.py qcluster i get error, does somebody know what could be source of it and how to resolve it?
19:38:41 [Q] INFO Q Cluster harry-high-fanta-mockingbird starting.
19:38:44 [Q] INFO Process-1 guarding cluster harry-high-fanta-mockingbird
19:38:44 [Q] INFO Q Cluster harry-high-fanta-mockingbird running.
19:38:48 [Q] INFO Process-1:1 ready for work at 92075
19:38:48 [Q] INFO Process-1:2 ready for work at 92076
19:38:48 [Q] INFO Process-1:4 ready for work at 92078
19:38:48 [Q] INFO Process-1:3 ready for work at 92077
19:38:48 [Q] INFO Process-1:5 monitoring at 92079
19:38:48 [Q] INFO Process-1:6 pushing tasks at 92080
Process Process-1:6:
Traceback (most recent call last):
  File "/Users/foo/.pyenv/versions/3.10.4/lib/python3.10/multiprocessing/process.py", line 315, in _bootstrap
    self.run()
  File "/Users/foo/.pyenv/versions/3.10.4/lib/python3.10/multiprocessing/process.py", line 108, in run
    self._target(*self._args, **self._kwargs)
  File "/Users/foo/Library/Caches/pypoetry/virtualenvs/flux-backend-7x6GG3SE-py3.10/lib/python3.10/site-packages/django_q/cluster.py", line 356, in pusher
    task = SignedPackage.loads(task[1])
  File "/Users/foo/Library/Caches/pypoetry/virtualenvs/flux-backend-7x6GG3SE-py3.10/lib/python3.10/site-packages/django_q/signing.py", line 25, in loads
    return signing.loads(
  File "/Users/foo/Library/Caches/pypoetry/virtualenvs/flux-backend-7x6GG3SE-py3.10/lib/python3.10/site-packages/django_q/core_signing.py", line 44, in loads
    return serializer().loads(data)
  File "/Users/foo/Library/Caches/pypoetry/virtualenvs/flux-backend-7x6GG3SE-py3.10/lib/python3.10/site-packages/django_q/signing.py", line 39, in loads
    return pickle.loads(data)
AttributeError: Can't get attribute 'task_func' on <module '__mp_main__' from '/Users/foo/Documents/projects/flux/flux_backend/manage.py'>
19:38:49 [Q] ERROR reincarnated pusher Process-1:6 after sudden death

Hi,
It could be that you have created a task passing the function as an object, not the name. If the function definition at the time of the creation of the task references an attribute of a global or local symbol that does not exist anymore at the time the task is run (because you have updated the code and restarted the cluster in between), you could get this king of error.
Try to delete the faulty task an recreate it.

have created a task passing the function as an object, not the name. If the function de

I did exactly that and it worked, but I did not know the specific reason for that...I was afraid it could be a side effect of a feature change. But thanks a lot for the explanation, really reassuring it was just an old queued task from another branch :)


Feature to collect deployment metrics from Jenkins

This feature is an alternate solution to HygieiaJenkinsPlugin. An enterprise might restrict installation of Hygieia Jenkins Plungin for a number of reasons - compliance, stability, governance, SOX etc...
HygieiaJenkinsPluginAlt is called by Jenkins pipeline, it capture metrics (same as collected by Hygieia Jenkins plugin)  and push it to Hygieia by calling Hygieia API's to persist data in Hygieia Mongo database.
Please refer readme document for details.

@premyadav1
Can you separate out the pull request into the code into this branch, and convert the word doc into a markdown file. We place all relevant documentation for users in the gh-pages branch:
https://github.com/Hygieia/Hygieia/tree/gh-pages/pages/hygieia/collectors

Created pull request to add documentation for HygieiaJenkinsPluginAlt within gh-pages. Here is the pull request url https://github.com/Hygieia/Hygieia/pull/2785

@premyadav1 Any update on the review comments?


[BUG] Sessions and PHP7/7.1

Hello when i switch from php 5.6 to 7 or 7.1 my sessions stop working correctly.
What is happening? On every reload ci_session cookie is changing and php session too.
I tried files session storage,database, memcached no difference.
I also tried fresh codeigniter without modifications and problem still persists.
My webserver setup is managed with serverpilot.io and php-fpm services with provides me fast php swithing.
I use latest 3.1.0 ci.

Related to #4179?
Even so, I recommend post your question on CodeIgniter forums, it's more likely you are having an issue with your own project, rather than a CodeIgniter issue.

There's a thousand things that can break sessions.
PHP 7.1 has a release candidate, but is not officially out yet.
PHP 7.0 runs just fine for other people using CodeIgniter's sessions.
How did you determine that this is a bug?
And also, you don't need to prefix your title with [bug] - we don't welcome non-bug threads here.

https://github.com/bcit-ci/CodeIgniter/issues/3649
In php 7.1 are new session configuration values:
session.sid_length
session.sid_bits_per_character
http://php.net/manual/en/session.configuration.php#ini.session.sid-length
and by default values regex: /^[0-9a-f]{40}$/ is not working.

... and that has nothing to do with 7.0.

I meet the same problem.
I spent whole day on this, currently I find the cookie value 'ci_session' not visible. ( through cookie helper ).
I see the session_start() call database helper's read() function with new session_id every time.  I think it may because PHP not found session id information in cookie.
is there any changes to PHP 7.1 on cookie part?

Just to confirm: Everything works perfect with 3.1.1, no more problems with sessions.
👍 Good job! 💃

Well, it wasn't so perfect.
2f760877c313871e5066b93b0b1aa76428c09fb6

ola a todos, tive o mesmo problema, com a versão php 7.1, estranho, que em algumas paginas, minhas sessões funcionavam corretamente, mas na maioria as sessões não estavam sendo guardadas, mas mas nas versões anteriores sim. até mesmo na versão 7.0, meu projeto funcionava bem, apenas quando mudava para 7.1, as sessões não eram mostradas. ATUALMENTE ESTOU USANDO A VERSÃO 7.0 ESTA OK PRA MIM ATÉ O MOMENTO.

@joedes English only, thanks. Don't know what you are saying.

Hi all, the problem is the same, with a php 7.1 version, strange, that on some pages, my functions work correctly, but mostly as sessions are not being used, but in previous versions of php 5.2, 5.6 and 7.0 my project worked well, only when it changed to 7.1, as sessions not presented in SOME PAGES OF THE PROJECT. CURRENTLY I'M USING VERSION 7.0 IS OK TO ME UNTIL THE TIME.

@joedes this still happened to me with lasted 3.x ci, seems only with redirects! do you use redirects? or cookies kind of configurations?

This is almost a 4 year old issue and it was fixed, 10 releases ago. Whatever problem you're having now, it's not the same thing and randomly commenting on old bug reports isn't going to help you.


No such file or directory Error when createing new app

tried to D:\phonegap> phonegap create myApp. This error occured:
Error: ENOENT, no such file or directory 'D:\phonegap\D:'

Interesting find @silentred. I'm having trouble reproducing this error.

What version of Windows are you using?
Do you happen to also have access to C:\? Can you try to create a project there?

Thank you for replying.
The version is Window 7. The create command works fine under C:\.

Hey @silentred,
Thanks for the info. It's good to know that the issue is related to the drive letters. I've got a VM of Windows 7, so I should be able to reproduce this issue.


dependencies and nuget updates

Hello, can you update this to latest please.
Also do you have ASP MVC version

@mrholek any updatyes


python bindings

I am trying to build python binding for android armv7 I have modified the script adding the option --enable-python-binding but it gives me an error and I do not know how to solve it.
configure: error:
  Could not link test program to Python. Maybe the main Python library has been
  installed in some non-standard library path. If so, pass it to configure,
  via the LIBS environment variable.
  Example: ./configure LIBS="-L/usr/non-standard-path/python/lib"
  ============================================================================
   ERROR!
   You probably have to install the development version of the Python package
   for your distribution.  The exact name of this package varies among them.
  ============================================================================

Do you have any idea how to make it work?
Thank you

I have the same question with you.


Built in converter - Array

We should add Array in our builtin converter. Archius has this support and it is universally useful.

+1 for supporting Arrays/Lists.
It's quite common to have lists in the configuration, and we should have an out of the box support for them. However, we should consider if a converter is the correct choice for this. When retrieving a list we would most likely like to specify the concrete type of the List (e.g. List, ...) we want to retrieve. With the way the current Config API methods are defined (getValue), you cannot pass in a class with a concrete generic type as the propertyType argument due to type erasure. You can only pass the base List class, which will either cause an "Unchecked assignment" warning by the compiler (if we assign the result to List<String>) or the returned list won't be parameterised or parsed as we would like (it would be List<Object>).
For CDI injecting of the config Lists however, it would work great as generic type information is preserved in class fields.

There might be other aspects, which I think is worth thinking about. To illustrate image the following example:
ConfigSource 1
list=a,b
ConfigSource 2
list=c,d
What is the final array value, if ConfigSource1.ordinal < ConfigSource2.ordinal ?
Options
list=c,d       // override
list=a,b,c,d // combining

To have more flexibility than always using the overriding mechanics, in Tamaya we have the PropertyValueCombinationPolicy   added.
How about supporting also:

Sets (would work OOTB since it could be done by the corresponding converters by implicitly removing any duplicates)
Maps

We had this discussion in MP config as well. We ended up intentionally not supporting it as it adds tons of complexity.
In DeltaSpike Config there is support for simple lists via asList()
http://deltaspike.apache.org/documentation/configuration.html#_list_values_handling
Although this could also easily be provided on the client side.

We did not do it because we ran out of time in v1 release, IIRC. Supporting Arrays or List is not that complicated.

The usage will be:
myPets: Fish, Hamster
ConfigProvider.getValue("myPet", String[])

Why not using similar signature as for getValue:
<T>  List<T> getListValue("myPet", Class<T> propertyType);

How about the semantics if no value exists? Returning an empty array/list?

If no value exists, return an empty array or list.

not sure about:
 List getListValue("myPet", Class propertyType);
or
 T[] getListValue("myPet", Class propertyType);
In this format, we just pass in prop name and type, we don't know we also need to convert to an array. We would expect the return type is Class though. Besides, it adds more methods.

Not sure I get your point, because

my example used generics...
the method is called getListValue instead of getValue. Couldn't it be clearer, what you get back...?

<T> List<T> getListValue("myPet", Class<T> propertyType);
or
<T> T[] getListValue("myPet", Class<T> propertyType);

Using primitive arrays like that should work yes. Although we would need to create an extra array converter for each type we already support out of the box. Same goes for the end users/application. They would need to write two converters of each type; one for single and one for an array.
If we wanted to retrieve the List or Set class, the current getValue(String, Class) won't work, as the List element type is supplied with a generic which is lost on compile time and such not possible to pass as a class. So with the current API in we won't know the type of the elements of the list requested.
We can only do:
List values = ConfigProvider.getValue("values", List.class);

Additionally I think we should be able to reuse the converters for single values for each element in the list.
It could be as simple as @atsticks suggested or done in some other way.
This way the implementation of the method would first parse the config value into a list of elements and use the existing converters to parse each element.

I still like what I proposed
String[] myPets = ConfigProvider.getValue("myPet", String[])
This is so simple and easy to implement.


subnet_size() and underlying function

Transparent tightening/enhancement. Added function subnet_size_from_netmask and modified existing function to use it.

Added a version of this that uses IP type and bit size rather than a string containing a subnet. More useful where $bits is known but base IP is irrelevant, which is the case in some DHCP/CARP/VPN code where we just want a for (i=0; i<=$count-1; i++) loop.
Rewrote existing function to use this (avoids duplication)
Added transparent optional argument $exact=false that allows calling code to specify an exact INT is required. This may be needed for loop control and some IP calculations, because for large subnets a FLOAT may be returned. (It's hard to think where exactness will matter on such a huge subnet that INT overflows, but this guarantees for calling code that the result will be an int, and may be useful in future)
Use ** operator (PHP 5.6) rather than exp(log). Tested and appears this returns INT where possible, up to 2^63 on x64, and a FLOAT if larger. (pow() seems identical. 1<< $bits wraps round to negative at 31/63 of course)

Calls to subnet_size() must be adjusted to deal with return 0, for example:
https://github.com/pfsense/pfsense/blob/master/src/usr/local/www/firewall_aliases_edit.php#L368
will always consider 0 <= max allowed items

The original code used return 0 as error (not an IP), so I retained that. Presumably it should be okay because it shouldn't be possible for any valid input data to return 0, because no valid CIDR covers 0 IPs.
If calling code does needs this issue addressing as you identify (which makes sense) then I'll switch it to use empty string for "bad data" at the same time, to ensure consistency with many of the other IP functions which use the same return for bad data. I'll look at this in a bit and sort it out somehow :)


How to understand inverse predictive loss

I've read your paper but I'm having a hard time understanding inverse predictive loss. Judging from Figure 2, it seems to be a loss between the mapping of Zx to Zs, but in your code, it became MSE loss. Can you explain it a bit more please?

Hi, the idea of inverse predictive loss is from S to Z_X. Leveraging the existing network, we reuse the network S->Z_S. Hence, the inverse predictive loss becomes Z_S to Z_X. We use a Gaussian as the variational distribution from Z_S to Z_X. This choice admits a MSE loss between Z_S and Z_X.

Hi, the idea of inverse predictive loss is from S to Z_X. Leveraging the existing network, we reuse the network S->Z_S. Hence, the inverse predictive loss becomes Z_S to Z_X. We use a Gaussian as the variational distribution from Z_S to Z_X. This choice admits a MSE loss between Z_S and Z_X.

Hi, in your paper, you try to maximize the log conditional likelihood from the self-supervised signal S to the learned representation Zx for the inverse predictive learning. However, in the function "inverse_perdictive_loss", two MSE losses between Zx and Zs are used for inverse predictive learning. Can you give me some explanations about this? Moreover, in function "inverse_perdictive_loss", it seems that you compute the same MSE loss twice.

The adoption of MSE losses is because of assuming a Gaussian distribution between Z_X and Z_S. This approximation may not be the best one, but is the simplest one. Another common choice is Laplacian, when the loss becomes MAE loss.
The reason why the losses are performed between Z_X and Z_S (not between Z_X and S) is that we reuse the network S -> Z_S. You can also not have this choice. For example, you can perform the MSE losses between q(S) and Z_X, where q(\cdot) is another neural network that is different from the network in S -> Z_S.
The reason for two MSE losses is because in visual representation learning experiments, we can swap the input and the self-supervised signal.

ming a Gaussian distribution between Z_X and Z_S. This approximation may not be the best one, but is the simplest one. Another common choice is Laplacian, w

Thanks for your reply. If MSE is used in inverse predictive learning, it seems that inverse predictive learning makes it easy for the network to learn contrastive learning.  I am not sure whether I got the right understanding.

Why "makes it easy for the network to learn contrastive learning"? Can you elaborate on it more?

Why "makes it easy for the network to learn contrastive learning"? Can you elaborate on it more?

If MSE is properly optimized, then Zx and Zs would essentially be the same. And the output through G network would also be the same. So there is no need to use NT-Xent loss at the output.

This is incorrect. We don't want the outputs are the same given arbitrary inputs. We still need the contrastive loss to avoid the trivial solutions.

I'll close this issue as I don't think there's a confusion here.

Sorry if what I said before was unclear. In the case of SimCLR, what I meant is it seems like the optimization of inverse learning constitutes the optimization of NT-Xent. These two objectives don't seem to be complementary...

On the one hand, the contrastive loss maximizes the contrastiveness between the samples from the joint distribution and the samples from the product of marginal distributions. On the other hand, inverse predictive loss minimizes the redundant information in the input that is not relevant to the self-supervised signal. The two objectives are different and aim for various goals.

Thank you for your explanation! I can understand it now.

 And I will soon have a completely new version of the paper, where more analysis will be included and I will relax the strong assumption I had in the paper.

That's great to hear! Can you let us know (like leaving another comment in this thread) when your new paper will be released? We're currently working on the application of contrastive representation learning to speech and we're trying to incorporate the findings in your paper into our work.

Will do. Thanks!

Here's the updated version. It relaxes the strong conditional independence assumption.


Cannot install on Ubuntu 24.04 LTS Noble Numbat

The output of thefuck --version (something like The Fuck 3.1 using Python 3.5.0 and Bash 4.4.12(1)-release):
Cannot check
Your system (Debian 7, ArchLinux, Windows, etc.):
Distributor ID:	Ubuntu
Description:	Ubuntu 24.04 LTS
Release:	24.04
Codename:	noble
How to reproduce the bug:
~$ thefuck --version
Traceback (most recent call last):
  File "/usr/bin/thefuck", line 9, in <module>
    from thefuck.entrypoints.main import main
  File "/usr/share/thefuck/thefuck/entrypoints/main.py", line 8, in <module>
    from .. import logs  # noqa: E402
    ^^^^^^^^^^^^^^^^^^^
  File "/usr/share/thefuck/thefuck/logs.py", line 8, in <module>
    from .conf import settings
  File "/usr/share/thefuck/thefuck/conf.py", line 1, in <module>
    from imp import load_source
ModuleNotFoundError: No module named 'imp'
~$ pip3 install thefuck --user
error: externally-managed-environment

× This environment is externally managed
╰─> To install Python packages system-wide, try apt install
    python3-xyz, where xyz is the package you are trying to
    install.

    If you wish to install a non-Debian-packaged Python package,
    create a virtual environment using python3 -m venv path/to/venv.
    Then use path/to/venv/bin/python and path/to/venv/bin/pip. Make
    sure you have python3-full installed.

    If you wish to install a non-Debian packaged Python application,
    it may be easiest to use pipx install xyz, which will manage a
    virtual environment for you. Make sure you have pipx installed.

    See /usr/share/doc/python3.12/README.venv for more information.

note: If you believe this is a mistake, please contact your Python installation or OS distribution provider. You can override this, at the risk of breaking your Python installation or OS, by passing --break-system-packages.
hint: See PEP 668 for the detailed specification.

The output of The Fuck with THEFUCK_DEBUG=true exported (typically execute export THEFUCK_DEBUG=true in your shell before The Fuck):
ModuleNotFoundError: No module named 'imp'

Anything else you think is relevant:
I updated from Ubuntu 22 to 24 and now thefuck doesn't work due to missing imp in python3.12.3

systems: Ubuntu Budgie on a desktop, Ubuntu 24.04 on a laptop
Distributor ID: Ubuntu
Description: Ubuntu 24.04 LTS
Release: 24.04
Codename: noble
any command to do with thefuck or fuck triggers this
$ thefuck --version
Traceback (most recent call last):
  File "/home/stan/.local/bin/thefuck", line 5, in <module>
    from thefuck.entrypoints.main import main
  File "/home/stan/.local/lib/python3.12/site-packages/thefuck/entrypoints/main.py", line 8, in <module>
    from .. import logs  # noqa: E402
    ^^^^^^^^^^^^^^^^^^^
  File "/home/stan/.local/lib/python3.12/site-packages/thefuck/logs.py", line 8, in <module>
    from .conf import settings
  File "/home/stan/.local/lib/python3.12/site-packages/thefuck/conf.py", line 1, in <module>
    from imp import load_source
ModuleNotFoundError: No module named 'imp'

same issue as og post

Clean install of Nobel does the same. I can't get PIP3 to install thefuck.
Says the same error as the bottom half of the OP post.

Install it with pip directly from this repo: pip install git+https://github.com/nvbn/thefuck

$ pip install git+https://github.com/nvbn/thefuck
error: externally-managed-environment

× This environment is externally managed
╰─> To install Python packages system-wide, try apt install
    python3-xyz, where xyz is the package you are trying to
    install.

Would need to put it in virtualenv :/

I managed to install it by passing the --break-system-packages flag, but then it throws another error no module named 'imp'

I encountered the same issue when running the command:
thefuck --version
I received the following traceback:
Traceback (most recent call last):
  File "/home/tekylo/.local/bin/thefuck", line 5, in <module>
    from thefuck.entrypoints.main import main
ModuleNotFoundError: No module named 'thefuck'

It seems like the module is not being found. Any insights on how to resolve this?

I had the same error. I had installed on Ubuntu 22.04 with py3.10. When I upgraded to 24.04, python also got upgraded to 3.12 and that environment did not have thefuck installed.
On Friday, 30 August 2024 at 12:52, José Antonio López Molina @.***> wrote:

I encountered the same issue when running the command:
thefuck --version
I received the following traceback:
Traceback (most recent call last):
File "/home/tekylo/.local/bin/thefuck", line 5, in
from thefuck.entrypoints.main import main
ModuleNotFoundError: No module named 'thefuck'
It seems like the module is not being found. Any insights on how to resolve this?
—
Reply to this email directly, view it on GitHub, or unsubscribe.
You are receiving this because you commented.Message ID: @.***>

Install it with pip directly from this repo: pip install git+https://github.com/nvbn/thefuck
As you can see is https://github.com/nvbn/thefuck/blob/master/thefuck/conf.py updated using importlib

This method, but using pip3 install --user git+https://github.com/nvbn/thefuck fixed it for me, for now.

 Full pip output in file:
    /home/shalak/.local/state/pipx/log/cmd_2024-08-31_09.00.46_pip_errors.log

Some possibly relevant errors from pip install:
    ERROR: Could not find a version that satisfies the requirement distutils (from versions: none)
    ERROR: No matching distribution found for distutils

Error installing distutils.
$ pipx install setuptools

No apps associated with package setuptools or its dependencies. If you are attempting to install a library, pipx should not be used.  Full pip output in file:
/home/shalak/.local/state/pipx/log/cmd_2024-08-31_09.00.46_pip_errors.log
Some possibly relevant errors from pip install:
ERROR: Could not find a version that satisfies the requirement distutils (from versions: none)
ERROR: No matching distribution found for distutils
Error installing distutils.
$ pipx install setuptools
No apps associated with package setuptools or its dependencies. If you are attempting to install a library, pipx should not be used. Consider using pip or a similar tool instead.
—
Reply to this email directly, view it on GitHub, or unsubscribe.
You are receiving this because you commented.Message ID: @.***>

pip3 uninstall thefuck pip3 install --user git+nvbn/thefuck --break-system-packages Worked for me
…
 Full pip output in file: /home/shalak/.local/state/pipx/log/cmd_2024-08-31_09.00.46_pip_errors.log Some possibly relevant errors from pip install: ERROR: Could not find a version that satisfies the requirement distutils (from versions: none) ERROR: No matching distribution found for distutils Error installing distutils. $ pipx install setuptools No apps associated with package setuptools or its dependencies. If you are attempting to install a library, pipx should not be used. Consider using pip or a similar tool instead. — Reply to this email directly, [view it on GitHub](#1457 (comment)), or unsubscribe. You are receiving this because you commented.Message ID: @.>

without the linkifier:
pip3 install --user git+https://github.com/nvbn/thefuck --break-system-packages

You're right. we need to be VERY careful using that option. In my opinion, it's fine in this case because:

thefuck doesn't overwrite an existing system package
requirements.txt specifies a version for only one package: setup-tools, and it is a >= type so it is likely fine in py3.12

Still, it's good to be clear about these reasons, so thanks for bringing it up.

Uninstalling for now (my install via pipx was complaining about no distutils, and when I tried to install distutils in the virtuealenv it complained), but will return if it's fixed. :-)

Seems like the reason this is happening is that distutils was deprecated for Python 3.12. Fix for the pipx installed version without using --break-system-packages:
Navigate to the bin directory in thefuck's venv (usually  ~/.local/share/pipx/venvs/thefuck/bin), then run ./python3 -m pip install setuptools.
Should be something similar for other versions, basically you need to install setuptools, which will also install distutils.

Does seem to work for me:
✦ ❯ pipx runpip thefuck list
Package    Version
---------- -------
colorama   0.4.6
decorator  5.1.1
pip        24.3.1
psutil     6.1.0
pyte       0.8.2
setuptools 75.6.0
six        1.17.0
thefuck    3.32
wcwidth    0.2.13

~ via  v20.14.0 via 💎 v3.0.0 on ☁  (us-east-1)
✦ ❯ thefuck --help
Traceback (most recent call last):
  File "/home/sean/.local/bin/thefuck", line 5, in <module>
    from thefuck.entrypoints.main import main
  File "/home/sean/.local/pipx/venvs/thefuck/lib/python3.12/site-packages/thefuck/entrypoints/main.py", line 8, in <module>
    from .. import logs  # noqa: E402
    ^^^^^^^^^^^^^^^^^^^
  File "/home/sean/.local/pipx/venvs/thefuck/lib/python3.12/site-packages/thefuck/logs.py", line 8, in <module>
    from .conf import settings
  File "/home/sean/.local/pipx/venvs/thefuck/lib/python3.12/site-packages/thefuck/conf.py", line 1, in <module>
    from imp import load_source
ModuleNotFoundError: No module named 'imp'

https://discuss.python.org/t/how-do-i-migrate-from-imp/27885/9

@sean-abbott yours is a different issue. See https://github.com/nvbn/thefuck/issues/1449#issuecomment-2137634221 about fixing the use of the deprecated imp module.

Consider using a maintained alternative instead:

https://github.com/nvbn/thefuck/issues/1466#issuecomment-2473799114
https://github.com/iffse/pay-respects/


Metro apps don't work

Metro apps (like the Windows App Store) currently don't work.

WOOHOO! This seems to work now. Added an extra reboot at the end of the build and everything appears to work like magic.
I think this was just an early bug in Windows 10 that has since been fixed with an update.


Cannot Modify HtmlBuilder on Services\DataTable

I'm in much the same situation as described in #208. My tables are each in a separate tab on the page and load via AJAX if the tab is selected. The individual tables are each set in their own routes, so only one really exists per route. If loaded via the tab, I alter the X-Requested-With AJAX request header to make the initial load of the route return an HTML fragment. The value could be practically anything, so long as it is not "XMLHttpRequest". The HTML version loads up and the table tries to initialize itself. It then fails miserably when trying to load the data.
The trouble is that when the data table is set up, it tries to load its data via AJAX, but the "ajax" property is set to an empty string. I tried to set that on my instance of Yajra\Datatables\Services\DataTable, but it looks like the returned HtmlBuilder from the html method is a fresh instance with each invocation of the method. So, I can modify state on the builder, but it doesn't mean anything as the builder used when rendering the view is a new one with default state.
I'm overriding that function in my own subclass to cache the builder object and return the same instance on subsequent calls, but this seems like it ought to be handled in the base class.

Your case seems a bit complicated and can't clearly visualize it. ATM, DataTable Service implementation is a bit limited to a single DataTable per page. Will try to create a multiple tables in a single page on my free time to check this. If you have a solution in mind, the package is open to accept a PR. Thanks!

2 DataTables demo was contributed in docs. Please check it out on how to implement this. Thanks!


Add support for time map application/vnd.google-earth.kml+xml format

Link to Docs

https://github.com/traveltime-dev/traveltime-python-sdk/pull/136


Subclassing MapListModel

I am trying to create a custom ListModel which consists of a composition of other models chained together. The last model in the chain is a MapListModel, so I thought that instead of creating a wrapper type which does all the setup and having to manually pass through the methods and signals, I could simply subclass MapListModel, but it seems that it is impossible to do this as MapListModel doesn't implement IsSubclassable. Is this an easy fix or is MapListModel not subclassable due to some technical limitation?

MapListModel is declared as final by gtk itself (see https://docs.gtk.org/gtk4/class.MapListModel.html) so not being able to subclass it seems intentional

I can't believe I missed that annotation :facepalm:. I ended up going the wrapper route in the end anyways. Thanks for the reply!


Hello

Hello @emmanueltouzery. Congratulations on a very nice looking library! :+1:  I recently stumbled upon it and found it to be very interesting.
As you're aware I've created a library with an immutable list. I saw the really clever type you have for partition. I've just implemented it here. Thanks a lot for sharing the idea in your blog post!
I see that you've added List to your benchmarks :smile: I had already done so myself to see how the libraries compare. I'm going to work on improving performance in the cases where List is not as fast as your Vector.
I can see that you have "Non-empty vector?" on the "Wishlist/upcoming features". I have been thinking about adding such a feature to List. But, I'm now sure if it's worth it. What do you think? When does the feature help?

since the title of the issue is "hello" maybe I'm not off-topic here by asking this now. I've been looking at the implementations of prepend & append in your list library. Very very neat trick with comparing the prefix & suffix length with a value stored in the vector to allow for concurrent append/prepend without eagerly duplicating the prefix & suffix! I think I'll steal this from you ;-)
however to give credit, i'm wondering, did you come up with that idea (together with the idea of storing these lengths with the depth in a single number, pretty cool as well), or if this from some paper or something like that?

Slow response here :sweat: I've been busy with my exams and catching up afterward.

Hi, thank you for the feedback, I love this cross-pollination!

Me too :smile:
Thank you for sharing your thoughts with regards to non-empty structures. The way I have considered adding non-empty list is to do it completely at the type-level with no differences at run-time. To see what I mean look at this internal type MutableList. Values of type MutableList doesn't actually exist at run-time. When I create it I have to cast like here. The solution I had in mind is somewhat similar. A non-empty list would be defined like this:
type NonEmptyList<A> = List<A> & { "nonEmpty": true };

The nonEmpty property would never exist at run-time. It would only be there so that the type system could keep track of non-empty lists. Then all functions that always returns a list with elements would return a NonEmptyList (prepend, append, etc.). Additionally, all functions that benefit from this knowledge would be overloaded to take advantage of it. last would have this type:
function last<A>(l: NonEmptyList<A>): A;
function last<A>(l: List<A>): A | undefined;

What do you think about that? It seems to me that it would add extra type safe-type and isEmpty could be made into a type guard. On the other hand, it would add a lot of extra overloads and complicate the types.

Now, the annoyance... If you have three options... [option1, option2, option3]. This is Option[]. No problem. But now if the first one is somehow a Some. And the other two are only Option... Then you get a compile error... Can't put an Option in a Some array. For that reason I added on Option a method toOption(). Meant to transform Some & None to Option. Same on linkedlist and stream.
That's really a weakness of typescript's type inference (it really should unify to Option) but in the end that creates some inconvenience of being provided these more precise types even if you don't really need them, and the question is, do you get enough reward for these annoyances?

That sounds weird to me. I think that TypeScript should be able to handle that correctly as long as Some is a subtype of Option. At least in some cases it inferes it correctly.

since the title of the issue is "hello" maybe I'm not off-topic here by asking this now.

Not at all :smile:

however to give credit, i'm wondering, did you come up with that idea (together with the idea of storing these lengths with the depth in a single number, pretty cool as well), or if this from some paper or something like that?

The idea of storing some elements in both ends (what I call prefix and suffix) is not my own. It's described here for instance. The trick where List stores the length of the affixes separately and use it to avoid duplicating them it is my own idea :blush: I'm happy to hear that you like it. It does make prepend and append noticeably faster. But, since the affixes are mutated and since the array lengths are not necessarily right one has to be a bit careful in the rest of the implementation. I've had a few bugs where I accidentally used the array length instead of the stored length.
The trick where several integers are stored in a single bit field is not my own. I read about it at some point in this article by the author of Bluebird. I'm sure the idea proceeds that article though. It's supposed to reduce the allocation cost and memory usage. From my benchmarks, it did make a difference but definitely not a huge one.


Update frequency

Hi,
Just a question here… not so much an issue but a question from a potential vestaboard user.
Is it true you can only send out an update to your vestaboard once every 60 seconds?

Hi @icepick3000! Sorry for the slow response here - my understanding is that, yes, that’s the case! I’ll add that I am speaking just from my own knowledge and I am not a representative of Vestaboard, but I believe that one update per minute is what’s covered in the warranty, and so it can’t be overridden.
I think it’s enforced on an API level.


{bp-2909} apps:  migrate to SPDX identifier

Summary
Most tools used for compliance and SBOM generation use SPDX identifiers
This change brings us a step closer to an easy SBOM generation.
included
https://github.com/apache/nuttx-apps/pull/2879
https://github.com/apache/nuttx-apps/pull/2886
https://github.com/apache/nuttx-apps/pull/2882
https://github.com/apache/nuttx-apps/pull/2909
https://github.com/apache/nuttx-apps/pull/2920
Impact
RELEASE
Testing
CI

[Experimental Bot, please feedback here]
Fill In The Commit Message: This PR contains a Commit with an Empty Commit Message. Please fill in the Commit Message with the PR Summary.
This PR summary is missing crucial information. While it mentions SPDX identifiers and SBOM generation, it doesn't explain what code changes were made.  The summary needs to describe the how –  what files were modified and what the modifications do.  Linking to other PRs is helpful context, but not a substitute for describing the changes within this PR.
Here's a breakdown of the issues and how to fix them:

Summary:  Insufficient detail.  Instead of just saying "This change brings us a step closer," explain how.  For example: "This PR adds SPDX license identifiers to the license headers of files in the [specify directories/files] directory.  These identifiers will enable automated tools to generate a Software Bill of Materials (SBOM)."  Mention the specific license(s) added.

Impact:  Saying "RELEASE" is not descriptive.  While it might imply a change to the release process or versioning, it's ambiguous.  Address each impact point individually and thoroughly. For example:

Is new feature added? Is existing feature changed?: YES, Added support for SPDX license identifiers to facilitate SBOM generation.
Impact on user: NO (unless there's a user-facing change related to how licenses are displayed or accessed)
Impact on build:  NO (unless adding the identifiers changes the build process in some way)
Impact on hardware: NO
Impact on documentation: YES (Documentation should be updated to explain how the SPDX identifiers are used and how to generate an SBOM)
Impact on security:  Potentially YES.  Using standardized license identifiers can help in identifying and mitigating security risks associated with known vulnerabilities in specific open-source components. Explain further.
Impact on compatibility: NO (unless there's a specific reason why adding identifiers could break compatibility)
Anything else to consider?:  Mention any potential issues or considerations related to the SBOM generation process.

Testing: Saying "CI" isn't sufficient. While CI testing is important, it needs more context. Specify which CI systems were used and what tests were run. Ideally, provide a summary of the test results.  If the related nuttx-apps PRs have relevant test logs, link to them specifically. Don't just assume the reviewer will go through all of them. Since this likely impacts a large number of files, it's helpful to show examples of the changes and how they were tested.  A "before" and "after" example would be extremely beneficial.

In short,  rewrite the PR description to provide specific details about the changes, their impact, and how they were tested.  Don't rely on linked PRs to provide all the necessary information.  The PR description should be self-contained and easily understood.

@xiaoxiang781216 please ignore nxstyle errors

CI fixed by https://github.com/apache/nuttx/pull/15386


Readonly user account

Add the ability to define 'read-only' user accounts.
Such accounts have the following permissions:

Unable to start/alter/delete any resources (such as cannot create a container, execute actions against a container, remove an image...)
Ability to inspect resources (such as inspect image details, container stats, containers logs...)
An optional ability to use the container console

The 3rd option will be treated as an optional case during the user account creation (read only or read only with console access).

Related to #235

I was thinking about this too, having a public read-only view for people that you dont want to be messing with your container, and you have to login to be able to edit anything, able to turn this on and off in settings and off by default

With the introduction recently of RBAC, I think that this feature should be reviewed to create read-only users instead of a read-only mode when starting Portainer.

This is really helpful feature considering when different role as dev and system admin facing the same production environment.

Excuse me, when will the read-only user feature be added?

No ETA yet on this @zhy1991 although this is part of the next main features that will be added.

Great news!

Closing this issue and relocating the discussion in #1259

No ETA yet on this @zhy1991 although this is part of the next main features that will be added.

Any tentative timelines for next main feature release?

Has this been updated? is it possible to have read only?

Its a work in progress, literally.
Rgds,
Neil Cresswell
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Has this been updated? is it possible to have read only?
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Add schema for resource manager

Community Note

Please vote on this issue by adding a 👍 reaction to the original issue to help the community and maintainers prioritize this request
Please do not leave "+1" or "me too" comments, they generate extra noise for issue followers and do not help prioritize the request
If you are interested in working on this issue or have submitted a pull request, please leave a comment

Description
https://docs.cloud.oracle.com/en-us/iaas/Content/ResourceManager/Concepts/terraformconfigresourcemanager.htm

https://docs.oracle.com/en-us/iaas/Content/ResourceManager/Concepts/terraformconfigresourcemanager_topic-schema.htm

Added examples to 5.x user guide in https://github.com/oracle-terraform-modules/terraform-oci-oke/pull/703


Clarification on support for application/json encoded object properties in application/x-www-form-urlencoded messages

I have been trying to read the spec and understand this to understand if some tools are "broken" or if the spec is just ... unclear (or I am reading it wrong). I need to support an application/x-www-form-urlencoded message where some properties are application/json encoded objects. From what I can read in the spec, this should be the expected, default serialization. The section on Encoding Object says: "The Content-Type for encoding a specific property. Default value depends on the property type: for object - application/json; ". I will say that I am very confused by that line when reading the section on "explode":

When this is true, property values of type array or object generate separate parameters for each value of the array, or key-value-pair of the map. For other types of properties this property has no effect. When style is form, the default value is true. For all other styles, the default value is false. This property SHALL be ignored if the request body media type is not application/x-www-form-urlencoded or multipart/form-data. If a value is explicitly defined, then the value of contentType (implicit or explicit) SHALL be ignored.

That doesn't make sense to me since if I want my property to simply be a json string, then I need to set it to explode: false but then it ignores contentType so ... I guess I have to assume it is application/json but then what would be the point of this parameter.
So, could someone tell me how to make the system accept a application/x-www-form-urlencoded message where one of the properties is a json encoded object. I attached a sample spec I created which I tested in Postman and SwaggerUI and they behave differently. I also tried with a codegen tool to see what they did and it was different also. I want to know what is "right" and then maybe I can fix something :)
Thanks
NestedOpenAPISpec.yml.txt

To add, Postman always does comma delimted for the explode:false and explode:false, contentType:application/json. SwaggerUI on the other hand, also does json for the property value. It feels like I should be able to have either by using contentType attribute and it seems like the default should be application/json and not csv??

@LGraber
I agree that this is not very clear.  My reading is that this is the key part:

If a value is explicitly defined, then the value of contentType (implicit or explicit) SHALL be ignored.

This tells me that the text around defaults is a bit incomplete.  An explicit explode: false causes the contentType to be ignored, but omitting explode entirely allows contentType to take effect.
This is shown by the example, which has a JSON object for address without any entry in the Encoding Object, and includes the comment # default is application/json on that address field.  So that means that the value should be JSON text, without any further transformation or encoding (beyond what the multipart/form-data or application/x-www-form-urlencoded format requires, which is separate from the Encoding Object).
This is further supported by the Support for x-www-form-urlencoded Request Bodies, which uses a similar address example and states:

In this example, the contents in the requestBody MUST be stringified per [RFC1866] when passed to the server. In addition, the address field complex object will be stringified.

I think we should show the result of applying those examples (and probably clean up that text in the field table as well).
The confusion seems to have been introduced in OAS 3.1, as the text in 3.0.3 does not say anything about interactions with contentType and restricts it to just application/x-www-form-urlencoded.

PR merged for 3.0.4 and ported to 3.1.1 via PR #3921!


Flatten inheritance for DDPSharded strategy

What does this PR do?
DDPShardedStrategy now inherits from ParallelStrategy instead of DDPStrategy.
Part of #https://github.com/PyTorchLightning/pytorch-lightning/issues/11863
Does your PR introduce any breaking changes? If yes, please list them.

Before submitting

[x] Was this discussed/approved via a GitHub issue? (not for typos and docs)
[x] Did you read the contributor guideline, Pull Request section?
[x] Did you make sure your PR does only one thing, instead of bundling different changes together?
[ ] Did you make sure to update the documentation with your changes? (if necessary)
[ ] Did you write any new necessary tests? (not for typos and docs)
[ ] Did you verify new and existing tests pass locally with your changes?
[ ] Did you list all the breaking changes introduced by this pull request?
[ ] Did you update the CHANGELOG? (not for typos, docs, test updates, or internal minor changes/refactorings)

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Did you have fun?
Make sure you had fun coding 🙃

I'm not sure why the TPU tests are failing here :(

rebase on top of #11754


Manually changing the date in the Filter Points window

When in the Filter Points window, the dates can only be changed when using the calendar feature.  It would be helpful if the dates could manually be changed.  The program wont let you do this because it thinks you are inputting a date that is outside the series range.

Need to test in Windows and Mac.

I think this is still an issue, but I can't test until issue #238 is resolved, so I'll add it to that milestone.

Looks great. Closing.


Add ForceField.delete_parameter_handler

[x] Adds ForceField.delete_parameter_handler, which accepts either a string, ParameterHandler type, or ParameterHandler instance.
[x] Add tests
[x] Update changelog

@SimonBoothroyd Could you review and let me know if this covers your use case?


Clip screenshot not working for Mac OS

The Eclipse gets stuck on its screen without capturing screen appear.

fixed


Release Google.Cloud.TextToSpeech.V1Beta1 version 2.0.0-beta09

Changes in this release:
New features

Add low latency journey option to proto (commit dc529a6)
Add CustomPronunciationParams for upcoming feature work (commit dc529a6)

Created release for Google.Cloud.TextToSpeech.V1Beta1-2.0.0-beta09


opening nvim inside of tmux overwrites the tmux status bar

Hi folks, when using this setup, if I run nvim inside of tmux the status bar for tmux gets overwritten with the nvim status bar, and it doesn't revert after closing nvim.   Suggestions?

Hello @rhaynes74 👋
Can you verify the behavior doesn't happen when using the stock configuration, by e.g. launching tmux the following way:
$ tmux -L test -f /dev/null

Thank you

Hi Gregory - thanks for the message.   Would be difficult for me to test again, I changed my config quite a bit.  Removing tmuxline seemed to fix it.
Sincerely,
Dr. Ronald D. Haynes
Professor, Department of Mathematics and Statistics
Chair, MSc and PhD Scientific Computing Programs
Memorial University of Newfoundland
We acknowledge that the lands on which Memorial University’s campuses are situated are in the traditional territories of diverse Indigenous groups, and we acknowledge with respect the diverse histories and cultures of the Beothuk, Mi’kmaq, Innu, and Inuit of this province.
On Dec 6, 2020, 5:35 AM -0330, Gregory Pakosz<EMAIL_ADDRESS>wrote:

Hello @rhaynes74 👋
Can you verify the behavior doesn't happen when using the stock configuration, by e.g. launching tmux the following way:
$ tmux -L test -f /dev/null
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Hey @rhaynes74 👋
Alright. Feel free to reopen.


[FEATURE] Longhorn UI for SPDK feature

Is your feature request related to a problem? Please describe (👍 if you like this request)
Some updates and changes to Longhorn UI for SPDK feature

Dashboard

Separate storage information of block and filesystem disks

Node

hugepage usage (node.status.allocatable.hugepages-2Mi) (nice to have)
disks

disk type (node. Spec.disks[i].disktype)

set disk type for newly added disk
show disk type of each disk

Support sorting by disk type

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.

hugepage is not included in the returned data of the node, so I did not add it.
Support sorting by disk type  is not included, because the disk list is actually within the node and does not have a header for simplicity. (I think this can be implemented later on a separate page dedicated to disks.)

Verified Pass on longhorn master(longhorn-manager 64db91, longhorn-ui e6cc64)
From UI I can

Create SPDK volume
Enable/Disable SPDK

Storage Schedulable (Block) in dashboard

Different type of data engine(longhorn, spdk)

SPDK orphaned replica


Docs: Update docs for configuration deploy

Update docs for configuration deploy.  Default properties no longer get
filled in to configuration files.
Testing: make docs
@ebd2 @akshatnair

Looks good

merged

lgtm


fix: add unit tests to Row

What changes were proposed in this pull request?
https://github.com/apache/spark-connect-go/pull/75 shows that Row type has a bug.
I added tests to the Row types.

Why are the changes needed?
To guarantee bug free implementation of Row type.

Does this PR introduce any user-facing change?
No

How was this patch tested?
The PR adds unit-tests for the Row type.

fixes https://github.com/apache/spark-connect-go/issues/76
Signed-off-by: Mustafa Elbehery<EMAIL_ADDRESS>

Thanks for your contribution