[Bug] Random Segmentation Faults During OneDiff (OneFlow) Inference in Multi-threaded Python Program

Your current environment information
Collecting environment information...
PyTorch version: 2.1.1+cu118
Is debug build: False
CUDA used to build PyTorch: 11.8
ROCM used to build PyTorch: N/A
OneFlow version: path: ['/opt/conda/lib/python3.10/site-packages/oneflow'], version: 0.9.1.dev20240515+cu118, git_commit: ec7b682, cmake_build_type: Release, rdma: True, mlir: True, enterprise: False
Nexfort version: none
OneDiff version: 1.2.0.dev202407160130
OneDiffX version: 1.2.0.dev1
OS: Ubuntu 20.04.6 LTS (x86_64)
GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0
Clang version: Could not collect
CMake version: version 3.28.1
Libc version: glibc-2.31
Python version: 3.10.13 (main, Sep 11 2023, 13:44:35) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.15.0-97-generic-x86_64-with-glibc2.31
Is CUDA available: True
CUDA runtime version: 11.8.89
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: GPU 0: NVIDIA GeForce RTX 3090
Nvidia driver version: 535.161.07
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.8.9.0
/usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.9.0
/usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.9.0
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.9.0
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.9.0
/usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.9.0
/usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.9.0
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True
CPU:
Architecture:                       x86_64
CPU op-mode(s):                     32-bit, 64-bit
Byte Order:                         Little Endian
Address sizes:                      46 bits physical, 57 bits virtual
CPU(s):                             112
On-line CPU(s) list:                0-111
Thread(s) per core:                 2
Core(s) per socket:                 28
Socket(s):                          2
NUMA node(s):                       2
Vendor ID:                          GenuineIntel
CPU family:                         6
Model:                              106
Model name:                         Intel(R) Xeon(R) Gold 6330 CPU @ 2.00GHz
Stepping:                           6
CPU MHz:                            800.000
CPU max MHz:                        3100.0000
CPU min MHz:                        800.0000
BogoMIPS:                           4000.00
Virtualization:                     VT-x
L1d cache:                          2.6 MiB
L1i cache:                          1.8 MiB
L2 cache:                           70 MiB
L3 cache:                           84 MiB
NUMA node0 CPU(s):                  0-27,56-83
NUMA node1 CPU(s):                  28-55,84-111
Vulnerability Gather data sampling: Mitigation; Microcode
Vulnerability Itlb multihit:        Not affected
Vulnerability L1tf:                 Not affected
Vulnerability Mds:                  Not affected
Vulnerability Meltdown:             Not affected
Vulnerability Mmio stale data:      Mitigation; Clear CPU buffers; SMT vulnerable
Vulnerability Retbleed:             Not affected
Vulnerability Spec rstack overflow: Not affected
Vulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl and seccomp
Vulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:           Mitigation; Enhanced IBRS, IBPB conditional, RSB filling, PBRSB-eIBRS SW sequence
Vulnerability Srbds:                Not affected
Vulnerability Tsx async abort:      Not affected
Flags:                              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 invpcid_single intel_ppin ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb intel_pt avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local split_lock_detect wbnoinvd dtherm ida arat pln pts avx512vbmi umip pku ospke avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg tme avx512_vpopcntdq la57 rdpid fsrm md_clear pconfig flush_l1d arch_capabilities
Versions of relevant libraries:
[pip3] diffusers==0.21.0
[pip3] numpy==1.26.0
[pip3] onnx==1.15.0
[pip3] onnxruntime-gpu==1.17.0
[pip3] torch==2.1.1+cu118
[pip3] torchaudio==2.1.1+cu118
[pip3] torchelastic==0.2.2
[pip3] torchsde==0.2.6
[pip3] torchvision==0.16.1+cu118
[pip3] transformers==4.35.2
[pip3] triton==2.1.0
[conda] blas                      1.0                         mkl
[conda] ffmpeg                    4.3                  hf484d3e_0    pytorch
[conda] libjpeg-turbo             2.0.0                h9bf148f_0    pytorch
[conda] mkl                       2023.1.0         h213fc3f_46343
[conda] mkl-service               2.4.0           py310h5eee18b_1
[conda] mkl_fft                   1.3.8           py310h5eee18b_0
[conda] mkl_random                1.2.4           py310hdb19cb5_0
[conda] numpy                     1.26.0          py310h5f9d8c6_0
[conda] numpy-base                1.26.0          py310hb5e798b_0
[conda] pytorch-cuda              11.8                 h7e8668a_5    pytorch
[conda] pytorch-mutex             1.0                        cuda    pytorch
[conda] torch                     2.1.1+cu118              pypi_0    pypi
[conda] torchaudio                2.1.1+cu118              pypi_0    pypi
[conda] torchelastic              0.2.2                    pypi_0    pypi
[conda] torchsde                  0.2.6                    pypi_0    pypi
[conda] torchtriton               2.1.0                     py310    pytorch
[conda] torchvision               0.16.1+cu118             pypi_0    pypi
🐛 Describe the bug
I'm experiencing random segmentation faults when using OneDiff to accelerate SDXL inference in a multi-threaded Python environment. The issue appears to be related to memory allocation and deallocation without properly handling the Python Global Interpreter Lock (GIL).
When the issue occurs, the command window outputs one of the following messages:

Stack trace (most recent call last) in thread 31:
   Object "/opt/conda/lib/python3.10/site-packages/oneflow/_oneflow_internal.cpython-310-x86_64-linux-gnu.so", at 0x7f22c10d3962, in functional::from_dlpack(_object*, *object*, *object*)
   Object "/opt/conda/lib/python3.10/site-packages/oneflow/_oneflow_internal.cpython-310-x86_64-linux-gnu.so", at 0x7f22c0fcc6ed, in
   Object "/opt/conda/lib/python3.10/site-packages/oneflow/_oneflow_internal.cpython-310-x86_64-linux-gnu.so", at 0x7f22c118bf64, in PyTensor_New(std::shared_ptr<Tensor> const&)
Segmentation fault (Address not mapped to object [0x1])

Segmentation fault (Address not mapped to object [0x2])

Since there isn't much information, I used GDB to debug and captured the following stack trace when the segmentation fault occurs:
#0  0x00000000004d6b65 in pymalloc_alloc (ctx=0x0, nbytes=32) at /usr/local/src/conda/python-3.10.13/Objects/obmalloc.c:1961
#1  _PyObject_Malloc (nbytes=32, ctx=0x0) at /usr/local/src/conda/python-3.10.13/Objects/obmalloc.c:1961
#2  PyObject_Malloc (size=32) at /usr/local/src/conda/python-3.10.13/Objects/obmalloc.c:685
#3  0x00000000004deb00 in PyType_GenericAlloc (type=0x780fc80eff30, nitems=0) at /usr/local/src/conda/python-3.10.13/Objects/typeobject.c:1159
#4  0x0000781117628945 in oneflow::one::PyTensor_New(std::shared_ptr<oneflow::one::Tensor> const&) () from /opt/conda/lib/python3.10/site-packages/oneflow/_oneflow_internal.cpython-310-x86_64-linux-gnu.so
#5  0x0000781117444cbe in ?? () from /opt/conda/lib/python3.10/site-packages/oneflow/_oneflow_internal.cpython-310-x86_64-linux-gnu.so
#6  0x000078111756aae3 in oneflow::one::functional::from_dlpack(_object*, _object*, _object*) () from /opt/conda/lib/python3.10/site-packages/oneflow/_oneflow_internal.cpython-310-x86_64-linux-gnu.so
#7  0x00000000004fc697 in cfunction_call (func=<built-in method from_dlpack of module object at remote 0x7811215629d0>, args=<optimized out>, kwargs=<optimized out>) at /usr/local/src/conda/python-3.10.13/Objects/methodobject.c:543
#8  0x00000000004f614b in _PyObject_MakeTpCall (tstate=0x6b1eee0, callable=<built-in method from_dlpack of module object at remote 0x7811215629d0>, args=<optimized out>, nargs=<optimized out>, keywords=0x0) at /usr/local/src/conda/python-3.10.13/Objects/call.c:224
#9  0x00000000004f2376 in _PyObject_VectorcallTstate (kwnames=<error reading variable: dwarf2_find_location_expression: Corrupted DWARF expression.>, nargsf=<error reading variable: dwarf2_find_location_expression: Corrupted DWARF expression.>, args=0x780ef056a3c0, callable=<error reading variable: dwarf2_find_location_expression: Corrupted DWARF expression.>, tstate=<error reading variable: dwarf2_find_location_expression: Corrupted DWARF expression.>) at /usr/local/src/conda/python-3.10.13/Include/cpython/abstract.h:112
#10 _PyObject_VectorcallTstate (kwnames=0x0, nargsf=<optimized out>, args=0x780ef056a3c0, callable=<built-in method from_dlpack of module object at remote 0x7811215629d0>, tstate=<optimized out>) at /usr/local/src/conda/python-3.10.13/Include/cpython/abstract.h:99
#11 PyObject_Vectorcall (kwnames=0x0, nargsf=<optimized out>, args=0x780ef056a3c0, callable=<built-in method from_dlpack of module object at remote 0x7811215629d0>) at /usr/local/src/conda/python-3.10.13/Include/cpython/abstract.h:123
#12 call_function (kwnames=0x0, oparg=<optimized out>, pp_stack=<synthetic pointer>, trace_info=0x7804ff4d8850, tstate=<optimized out>) at /usr/local/src/conda/python-3.10.13/Python/ceval.c:5893
#13 _PyEval_EvalFrameDefault (tstate=<optimized out>, f=Frame 0x780ef056a240, for file /opt/conda/lib/python3.10/site-packages/oneflow/utils/tensor/from_or_to_torch_tensor.py, line 65, in from_torch (torch_tensor=<Tensor at remote 0x780ba07b84f0>, torch=<module at remote 0x7812c97500e0>), throwflag=<optimized out>) at /usr/local/src/conda/python-3.10.13/Python/ceval.c:4181

The program consistently crashes in the pymalloc_alloc function, trying to access an invalid memory address.
I suspect the issue may be related to the handling of the Python Global Interpreter Lock (GIL) during memory allocation and deallocation processes.
To verify this hypothesis, I've created a test program (sdxl_onediff_test.py) based on the examples of Diffusers and OneDiffX that simulates using OneFlow for accelerated inference while another thread performs Python memory allocation and deallocation:
# sdxl_onediff_test.py
import os
import cv2
import time
import torch
import random
import argparse
import threading
import numpy as np
from PIL import Image
from diffusers.utils import load_image
from diffusers import StableDiffusionXLControlNetPipeline, ControlNetModel, AutoencoderKL
from onediffx import compile_pipe, save_pipe, load_pipe

# download images
image_t2i = load_image(
    "https://hf.co/datasets/hf-internal-testing/diffusers-images/resolve/main/sd_controlnet/hf-logo.png"
)

pipe_t2i = None

class TestMemAlloc:
    def __init__(self):
        pass

    def allocate_and_free_small_mem(self):
        dic = dict()
        for k in range(65536):
            s = random.randint(2, 256)
            dic[k] = bytearray(s)
        del dic

def run_t2i(compile_and_save=False):
    global pipe_t2i
    # initialize the models and pipeline
    if pipe_t2i is None:
        controlnet = ControlNetModel.from_pretrained(
            "diffusers/controlnet-canny-sdxl-1.0",
            torch_dtype=torch.float16
        )
        vae = AutoencoderKL.from_pretrained(
            "madebyollin/sdxl-vae-fp16-fix",
            torch_dtype=torch.float16
        )
        pipe_t2i = StableDiffusionXLControlNetPipeline.from_pretrained(
            "stabilityai/stable-diffusion-xl-base-1.0",
            controlnet=controlnet,
            vae=vae,
            torch_dtype=torch.float16
        ).to('cuda')

        pipe_t2i = compile_pipe(pipe_t2i)
        if not compile_and_save:
            load_pipe(pipe_t2i, dir="cached_t2i_pipe")

    controlnet_conditioning_scale = 0.5  # recommended for good generalization
    prompt = "aerial view, a futuristic research complex in a bright foggy jungle, hard lighting"
    negative_prompt = "low quality, bad quality, sketches"
    # get canny image
    image = np.array(image_t2i)
    image = cv2.Canny(image, 100, 200)
    image = image[:, :, None]
    image = np.concatenate([image, image, image], axis=2)
    canny_image = Image.fromarray(image)

    # generate image
    image = pipe_t2i(
        prompt,
        controlnet_conditioning_scale=controlnet_conditioning_scale,
        image=canny_image,
        num_inference_steps=8,
    ).images[0]

    if compile_and_save:
        save_pipe(pipe_t2i, dir="cached_t2i_pipe")

    return image

def test_mem_alloc():
    t = threading.current_thread()
    while not getattr(t, "stop_thread", False):
        time.sleep(0.1)
        test_ma = TestMemAlloc()
        test_ma.allocate_and_free_small_mem()

if __name__ == "__main__":
    parser = argparse.ArgumentParser()
    parser.add_argument("--compile_and_save", action="store_true", default=False,
                        help="compile and save the compiled pipe.")
    input_args = parser.parse_args()

    thread_pool = []
    if not input_args.compile_and_save:
        for num in range(1):
            t = threading.Thread(target=test_mem_alloc)
            t.start()
            thread_pool.append(t)

    out_dir = "./outputs"
    os.makedirs(out_dir, exist_ok=True)
    total_rounds = 10000
    for i in range(total_rounds):
        out_t2i = run_t2i(input_args.compile_and_save)

        if input_args.compile_and_save:
            break

        out_t2i.save(os.path.join(out_dir, f"t2i_{i}.jpg"))
        print(f"onediff test - {i+1}/{total_rounds}...")

    for t in thread_pool:
        t.stop_thread = True

To reproduce:

Run python sdxl_onediff_test.py --compile_and_save to compile and save the compiled pipe.
Run python sdxl_onediff_test.py to start the test.

The segmentation fault typically occurs within a few seconds to minutes.

Additional Debugging
When running the test program with PYTHONMALLOC=debug environment variable, Python will check the status of the GIL when performing memory allocation and deallocation:
PYTHONMALLOC=debug python sdxl_onediff_test.py

The captured stack trace is as follows:
#0  __GI_raise (sig=sig@entry=6) at ../sysdeps/unix/sysv/linux/raise.c:50
#1  0x000072fcf0ac7859 in __GI_abort () at abort.c:79
#2  0x00000000004a6ef3 in fatal_error_exit (status=<error reading variable: dwarf2_find_location_expression: Corrupted DWARF expression.>) at /usr/local/src/conda/python-3.10.13/Python/pylifecycle.c:2556
#3  fatal_error (fd=<optimized out>, header=header@entry=1, prefix=prefix@entry=0x6b6a90 <__func__.5.lto_priv.0> "_PyMem_DebugFree", msg=msg@entry=0x627e68 "Python memory allocator called without holding the GIL", status=status@entry=-1) at /usr/local/src/conda/python-3.10.13/Python/pylifecycle.c:2667
#4  0x00000000004a727d in _Py_FatalErrorFunc (func=func@entry=0x6b6a90 <__func__.5.lto_priv.0> "_PyMem_DebugFree", msg=msg@entry=0x627e68 "Python memory allocator called without holding the GIL") at /usr/local/src/conda/python-3.10.13/Python/pylifecycle.c:2753
#5  0x0000000000423122 in _PyMem_DebugCheckGIL (func=<error reading variable: dwarf2_find_location_expression: Corrupted DWARF expression.>) at /usr/local/src/conda/python-3.10.13/Objects/obmalloc.c:2646
#6  0x00000000004dd024 in _PyMem_DebugFree (ctx=0x743040 <_PyMem_Debug+96>, ptr=0x72f37c77f4c0) at /usr/local/src/conda/python-3.10.13/Objects/obmalloc.c:2670
#7  0x000072f57c11946c in ?? () from /opt/conda/lib/python3.10/site-packages/oneflow/_oneflow_internal.cpython-310-x86_64-linux-gnu.so
#8  0x000072f45e27ec0d in std::_Sp_counted_ptr_inplace<oneflow::one::LocalTensor, std::allocator<oneflow::one::LocalTensor>, (__gnu_cxx::_Lock_policy)2>::_M_dispose() () from /opt/conda/lib/python3.10/site-packages/oneflow/../oneflow.libs/liboneflow-d0782696.so
#9  0x000072f57c097a1a in oneflow::deleter(DLManagedTensor*) () from /opt/conda/lib/python3.10/site-packages/oneflow/_oneflow_internal.cpython-310-x86_64-linux-gnu.so
#10 0x000072fc54ddb28c in c10::deleteInefficientStdFunctionContext(void*) () from /opt/conda/lib/python3.10/site-packages/torch/lib/libc10.so
#11 0x000072fcbf9bb7b6 in c10::StorageImpl::~StorageImpl() () from /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_python.so
#12 0x000072fc54e02ca7 in c10::intrusive_ptr<c10::StorageImpl, c10::detail::intrusive_target_default_null_type<c10::StorageImpl> >::reset_() () from /opt/conda/lib/python3.10/site-packages/torch/lib/libc10.so
#13 0x000072fc54dfacb3 in c10::TensorImpl::~TensorImpl() () from /opt/conda/lib/python3.10/site-packages/torch/lib/libc10.so
#14 0x000072fc54dfae49 in c10::TensorImpl::~TensorImpl() () from /opt/conda/lib/python3.10/site-packages/torch/lib/libc10.so
#15 0x000072fcbfc6b738 in THPVariable_clear(THPVariable*) () from /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_python.so
#16 0x000072fcbfc6bac5 in THPVariable_subclass_dealloc(_object*) () from /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_python.so
#17 0x00000000004dd8e4 in _Py_Dealloc (op=<error reading variable: dwarf2_find_location_expression: Corrupted DWARF expression.>) at /usr/local/src/conda/python-3.10.13/Objects/object.c:2295
#18 _Py_DECREF (op=<error reading variable: dwarf2_find_location_expression: Corrupted DWARF expression.>) at /usr/local/src/conda/python-3.10.13/Include/object.h:500
#19 _Py_XDECREF (op=<error reading variable: dwarf2_find_location_expression: Corrupted DWARF expression.>) at /usr/local/src/conda/python-3.10.13/Include/object.h:567
#20 list_dealloc (op=0x72f37c78b200) at /usr/local/src/conda/python-3.10.13/Objects/listobject.c:355
#21 0x00000000004f1820 in _Py_Dealloc (op=<error reading variable: dwarf2_find_location_expression: Corrupted DWARF expression.>) at /usr/local/src/conda/python-3.10.13/Objects/object.c:2295
#22 _Py_DECREF (op=<optimized out>) at /usr/local/src/conda/python-3.10.13/Include/object.h:500
#23 _Py_XDECREF (op=<optimized out>) at /usr/local/src/conda/python-3.10.13/Include/object.h:567
#24 _PyEval_EvalFrameDefault (tstate=<optimized out>, f=Frame 0x6c043530, for file /opt/conda/lib/python3.10/site-packages/diffusers/pipelines/controlnet/pipeline_controlnet_sd_xl.py, line 1100, in __call__ (self=<StableDiffusionXLControlNetPipeline(_internal_dict=<FrozenDict(vae=('diffusers', 'AutoencoderKL'), text_encoder=('onediff', 'MixedOneflowDeployableModule'), text_encoder_2=('onediff', 'MixedOneflowDeployableModule'), tokenizer=('transformers', 'CLIPTokenizer'), tokenizer_2=('transformers', 'CLIPTokenizer'), unet=('onediff', 'MixedOneflowDeployableModule'), controlnet=('onediff', 'MixedOneflowDeployableModule'), scheduler=('diffusers', 'EulerDiscreteScheduler'), force_zeros_for_empty_prompt=True, _name_or_path='stabilityai/stable-diffusion-xl-base-1.0', _FrozenDict__frozen=True) at remote 0x72f8b83427b0>, vae=<AutoencoderKL(_internal_dict=<FrozenDict(in_channels=3, out_channels=3, down_block_types=['DownEncoderBlock2D', 'DownEncoderBlock2D', 'DownEncoderBlock2D', 'DownEncoderBlock2D'], up_block_types=['UpDecoderBlock2D', 'UpDecoderBlock2D', 'UpDecoderBloc...(truncated), throwflag=<optimized out>) at /usr/local/src/conda/python-3.10.13/Python/ceval.c:1882

This reveals that the Python memory allocator is being called without holding the GIL.

Additional Debugging
When running the test program with PYTHONMALLOC=debug environment variable, Python will check the status of the GIL when performing memory allocation and deallocation:
PYTHONMALLOC=debug python sdxl_onediff_test.py

The captured stack trace is as follows:
#0  __GI_raise (sig=sig@entry=6) at ../sysdeps/unix/sysv/linux/raise.c:50
#1  0x000072fcf0ac7859 in __GI_abort () at abort.c:79
#2  0x00000000004a6ef3 in fatal_error_exit (status=<error reading variable: dwarf2_find_location_expression: Corrupted DWARF expression.>) at /usr/local/src/conda/python-3.10.13/Python/pylifecycle.c:2556
#3  fatal_error (fd=<optimized out>, header=header@entry=1, prefix=prefix@entry=0x6b6a90 <__func__.5.lto_priv.0> "_PyMem_DebugFree", msg=msg@entry=0x627e68 "Python memory allocator called without holding the GIL", status=status@entry=-1) at /usr/local/src/conda/python-3.10.13/Python/pylifecycle.c:2667
#4  0x00000000004a727d in _Py_FatalErrorFunc (func=func@entry=0x6b6a90 <__func__.5.lto_priv.0> "_PyMem_DebugFree", msg=msg@entry=0x627e68 "Python memory allocator called without holding the GIL") at /usr/local/src/conda/python-3.10.13/Python/pylifecycle.c:2753
#5  0x0000000000423122 in _PyMem_DebugCheckGIL (func=<error reading variable: dwarf2_find_location_expression: Corrupted DWARF expression.>) at /usr/local/src/conda/python-3.10.13/Objects/obmalloc.c:2646
#6  0x00000000004dd024 in _PyMem_DebugFree (ctx=0x743040 <_PyMem_Debug+96>, ptr=0x72f37c77f4c0) at /usr/local/src/conda/python-3.10.13/Objects/obmalloc.c:2670
#7  0x000072f57c11946c in ?? () from /opt/conda/lib/python3.10/site-packages/oneflow/_oneflow_internal.cpython-310-x86_64-linux-gnu.so
#8  0x000072f45e27ec0d in std::_Sp_counted_ptr_inplace<oneflow::one::LocalTensor, std::allocator<oneflow::one::LocalTensor>, (__gnu_cxx::_Lock_policy)2>::_M_dispose() () from /opt/conda/lib/python3.10/site-packages/oneflow/../oneflow.libs/liboneflow-d0782696.so
#9  0x000072f57c097a1a in oneflow::deleter(DLManagedTensor*) () from /opt/conda/lib/python3.10/site-packages/oneflow/_oneflow_internal.cpython-310-x86_64-linux-gnu.so
#10 0x000072fc54ddb28c in c10::deleteInefficientStdFunctionContext(void*) () from /opt/conda/lib/python3.10/site-packages/torch/lib/libc10.so
#11 0x000072fcbf9bb7b6 in c10::StorageImpl::~StorageImpl() () from /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_python.so
#12 0x000072fc54e02ca7 in c10::intrusive_ptr<c10::StorageImpl, c10::detail::intrusive_target_default_null_type<c10::StorageImpl> >::reset_() () from /opt/conda/lib/python3.10/site-packages/torch/lib/libc10.so
#13 0x000072fc54dfacb3 in c10::TensorImpl::~TensorImpl() () from /opt/conda/lib/python3.10/site-packages/torch/lib/libc10.so
#14 0x000072fc54dfae49 in c10::TensorImpl::~TensorImpl() () from /opt/conda/lib/python3.10/site-packages/torch/lib/libc10.so
#15 0x000072fcbfc6b738 in THPVariable_clear(THPVariable*) () from /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_python.so
#16 0x000072fcbfc6bac5 in THPVariable_subclass_dealloc(_object*) () from /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_python.so
#17 0x00000000004dd8e4 in _Py_Dealloc (op=<error reading variable: dwarf2_find_location_expression: Corrupted DWARF expression.>) at /usr/local/src/conda/python-3.10.13/Objects/object.c:2295
#18 _Py_DECREF (op=<error reading variable: dwarf2_find_location_expression: Corrupted DWARF expression.>) at /usr/local/src/conda/python-3.10.13/Include/object.h:500
#19 _Py_XDECREF (op=<error reading variable: dwarf2_find_location_expression: Corrupted DWARF expression.>) at /usr/local/src/conda/python-3.10.13/Include/object.h:567
#20 list_dealloc (op=0x72f37c78b200) at /usr/local/src/conda/python-3.10.13/Objects/listobject.c:355
#21 0x00000000004f1820 in _Py_Dealloc (op=<error reading variable: dwarf2_find_location_expression: Corrupted DWARF expression.>) at /usr/local/src/conda/python-3.10.13/Objects/object.c:2295
#22 _Py_DECREF (op=<optimized out>) at /usr/local/src/conda/python-3.10.13/Include/object.h:500
#23 _Py_XDECREF (op=<optimized out>) at /usr/local/src/conda/python-3.10.13/Include/object.h:567
#24 _PyEval_EvalFrameDefault (tstate=<optimized out>, f=Frame 0x6c043530, for file /opt/conda/lib/python3.10/site-packages/diffusers/pipelines/controlnet/pipeline_controlnet_sd_xl.py, line 1100, in __call__ (self=<StableDiffusionXLControlNetPipeline(_internal_dict=<FrozenDict(vae=('diffusers', 'AutoencoderKL'), text_encoder=('onediff', 'MixedOneflowDeployableModule'), text_encoder_2=('onediff', 'MixedOneflowDeployableModule'), tokenizer=('transformers', 'CLIPTokenizer'), tokenizer_2=('transformers', 'CLIPTokenizer'), unet=('onediff', 'MixedOneflowDeployableModule'), controlnet=('onediff', 'MixedOneflowDeployableModule'), scheduler=('diffusers', 'EulerDiscreteScheduler'), force_zeros_for_empty_prompt=True, _name_or_path='stabilityai/stable-diffusion-xl-base-1.0', _FrozenDict__frozen=True) at remote 0x72f8b83427b0>, vae=<AutoencoderKL(_internal_dict=<FrozenDict(in_channels=3, out_channels=3, down_block_types=['DownEncoderBlock2D', 'DownEncoderBlock2D', 'DownEncoderBlock2D', 'DownEncoderBlock2D'], up_block_types=['UpDecoderBlock2D', 'UpDecoderBlock2D', 'UpDecoderBloc...(truncated), throwflag=<optimized out>) at /usr/local/src/conda/python-3.10.13/Python/ceval.c:1882

This reveals that the Python memory allocator is being called without holding the GIL.

Hi @yingchingl  Could you able to solve it? Would you mind kindly to give some advice about it?

@strint Would you mind to give a loot at the issue? Deeply grateful!

Hi @yingchingl Were you able to solve it? Would you mind kindly to give some advice about it?

Hi @bigmover ,
No, I can't solve it yet. Because the code of oneflow used by onediff is not public, I cannot debug into it and see where the problem occurs.

Hi @yingchingl Were you able to solve it? Would you mind kindly to give some advice about it?

Hi @bigmover ,
No, I can't solve it yet. Because the code of oneflow used by onediff is not public, I cannot debug into it and see where the problem occurs.

Multi-threaded Python Program

Please don't try to use cuda/python/onediff with Multi-thread because it's usually blocked by the Python GIL or not thread-safe.
Using multi-process is recommended.

@strint  OK Thank you for your kindly reply! Onediff have flash attention ? It will use more GPU memory when using oneflow.compile?

Multi-threaded Python Program

Please don't try to use cuda/python/onediff with Multi-thread because it's usually blocked by the Python GIL or not thread-safe.
Using multi-process is recommended.

@strint OK Thank you for your kindly reply! Onediff have flash attention ? It will use more GPU memory when using oneflow.compile?

Yes, we are using a customized flash attention.
Compileing UNet won't use more GPU memory, but compiling VAE does because VAE has a large output tensor. oneflow compile share model weight memory with torch but doesn't share output tensor memory with torch.

Hi @bigmover @yingchingl  , I have the same problem, I want to ask if you have any solution or idea.


set Thread Settings

Hi Sir,
How to code "Thread Settings" with Greeting Text and Persistent Menu

Pls check Documentation as I have not been doing bot thing for long time.


Search SDK: Allow null search text, support MinimumCoverage, and use fully-qualified OData URLs

Hi @brjohnstmsft, I'm your friendly neighborhood Azure Pull Request Bot (You can call me AZPRBOT). Thanks for your contribution!

It looks like you're working at Microsoft (brjohnst). If you're full-time, we DON'T require a contribution license agreement.

If you are a vendor, or work for Microsoft Open Technologies, DO please sign the electronic contribution license agreement. It will take 2 minutes and there's no faxing! https://cla.azure.com.

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[!] No podspec found for mecab_for_dart in .symlinks/plugins/mecab_for_dart/ios

issue
I could not flutter run and pod install.
fluter doctor
Doctor summary (to see all details, run flutter doctor -v):
[✓] Flutter (Channel stable, 3.27.0, on macOS 15.1.1 24B91 darwin-arm64, locale ja-JP)
[✓] Android toolchain - develop for Android devices (Android SDK version 35.0.0)
[✓] Xcode - develop for iOS and macOS (Xcode 16.2)
[✓] Chrome - develop for the web
[✓] Android Studio (version 2024.1)
[✓] VS Code (version 1.95.3)
[✓] Connected device (5 available)
[✓] Network resources

• No issues found!

pubspec.yaml
mecab_for_dart: ^1.0.0

error
[!] No podspec found for `mecab_for_dart` in `.symlinks/plugins/mecab_for_dart/ios`

It was fixed by latest package


SSLProtocolException

I am having this issue when switch to CloudFlare. It should be the signature algorithm differences. CF using SHA256withECDSA. Any workaround?
javax.net.ssl.SSLHandshakeException: javax.net.ssl.SSLProtocolException: SSL handshake aborted: ssl=0x53371710: Failure in SSL library, usually a protocol error

SSL routines:SSL23_GET_SERVER_HELLO:tlsv1 alert internal error (external/openssl/ssl/s23_clnt.c:741 0x4176976a:0x00000000)

ECDSA may be problem with Android devices, see the capabilities of different versions of Android in providing ECDSA ciphers and combinations. https://www.ssllabs.com/ssltest/clients.html
Also test your backend URL with https://www.ssllabs.com/ssltest/analyze.html
Which should tell you if the ssl algorithm chain is properly configured, and if there is correct fallback for different Android version.

I'm trying to call api with URL with https
and i'm getting similar error
Here is my log:
javax.net.ssl.SSLProtocolException: SSL handshake aborted: ssl=0xb98d0440: Failure in SSL library, usually a protocol error
error:14077410:SSL routines:SSL23_GET_SERVER_HELLO:sslv3 alert handshake failure (external/openssl/ssl/s23_clnt.c:741 0x9dd99d4d:0x00000000)
Can you give me any work around?
Thanks


Why do you choose Zookeeper

Hi, i am reading your project, why do you choose Zookeeper instead of Eureka or Consul in your project, can you tell me your purpose when using Zookeeper, the pros and cons of Zookeeper

这是提供的demo,如果有切到zookeeper的需要可以参照，这里也有consul\eureka\nacos具体的demo，谢谢


Separate endpoints into different APIs

In this issue the topic of separating the different endpoints into separate APIs should be covered.
The split makes sense to be aligned with the other Camara Subprojects like "Device Location". On the other hand this will also helps the productization of the APIs and a clear offering from the telco industries.
Suggestion:

1 API for Roaming + Roaming subscription
1 API for Connectivity + Connectivity subscription

Thanks Noel for opening back this discussion. We totally support this approach based on this rationale:

CAMARA is pushing for atomic and use case driven APIs
→ Current scope of this API is fulfilling separate use cases and more complex functionality than an atomic feature

Validation of APIs, based on ATPs and certification process, requires full support of all the features of each API
→ Forcing operators/developers to implement additional use cases only because of a version evolution or, worst situation, partial deployments

Atomic endpoint evolution is currently tied to the full API evolution
→ New features of specific use cases / endpoints cannot be included until the complete API is agreed, delaying use case evolution even for bug fixing

Based on this, Telefonica proposes to follow the same strategy as other APIs (like location, SIM Swap...), separating features and use cases in separated atomic APIs:

Device Status (roaming)
Device Status (connectivity)
Device Status (roaming) subscription
Device Status (connectivity) subscription

This is opening up the discussion from last summer #https://github.com/camaraproject/DeviceStatus/discussions/55. Is there anything that has changed since then? At that time there was a summary written in #https://github.com/camaraproject/DeviceStatus/blob/main/documentation/SupportingDocuments/decision-support-1-or-2-apis.md

Hello
Totally support also from my side as well to have 4 APIs like suggested by @jgarciahospital.
@JoachimDahlgren - since we discussed months ago we coded/implemented this APIs and this effort changed our perspective on this. We shared the rationales listed by Jorge.
I believe that the "All or Nothing" approach for an API implementation is a key to adoption and partial implementation is not manageable for our consumer.

@bigludo7 @jgarciahospital  from dt side we also supporting the approach with 4 APIs and will commit to this.
We need to check if it makes sense to have the API-Name in the event or coming here more from the functional side.

I believe this is a common issue across all APIs, with each API handling these issues differently. To address this, I've initiated a discussion focusing on commonalities to establish a design pattern for addressing these issues, which can then be referenced by other APIs.

Any update on this one?
I saw support from DT (@NoelWirzius ), Telefonica (@jgarciahospital ) & Orange.
@sachinvodafone and @JoachimDahlgren as steady attendees to this WG do you have any blocking points to split the API?
As we have preparing the September release better to tackle this point soon.
Thanks

We could do the split after v0.6.0.
But we should first agree on the API names, do we want to have them so long, like this?

device-status-roaming.yaml
device-status-connectivity.yaml
device-status-roaming-subscriptions.yaml
device-status-connectivity-subscriptions.yaml

I support the idea of having four separate YAML files to address separation of concerns. However, without clear API design rules for our Camara project, different teams might opt for different approaches  (such as separate endpoints versus separate YAML files)when dealing with the same design problem.

@akoshunyadi looking of what we add for Device Location project (here) we can probably remove device-status in the name.
What about

roaming.yaml
connectivity.yaml
roaming-subscriptions.yaml
connectivity-subscriptions.yaml

The interesting point raised by @shilpa-padgaonkar here make me like simple api name :)

LGTM

Reachability sounds good:

roaming.yaml
reachability.yaml
roaming-subscriptions.yaml
reachability-subscriptions.yaml

We could introduce product categories in Camara, like device, home, network, etc...
So the api name would be prefixed like -.yaml:
device-roaming.yaml
device-connectivity.yaml
device-roaming-subscriptions.yaml
device-connectivity-subscriptions.yaml
the same for location
so we only have to have a unique feature name within the category

Good point @shilpa-padgaonkar
I'm fine with @jgarciahospital  proposal for reachability
@akoshunyadi as it will impact other API isn't a topic for commonalities?
I tend to prefer simplicity but get your point.
Perhaps we can explore other means to categorize the API? in meta release description for example or on a CAMARA page...

I think we should use now the chance with the new names to enhance the structure/organization of our APIs.
Sure, I'll create an issue in Commonalities.

https://github.com/camaraproject/Commonalities/issues/178

@akoshunyadi shell the version be:

version: 0.6.0-alpha.2
url: "{apiRoot}/device-status/v0.6alpha2"

?

Following discussion with @fernandopradocabrillo on the PR #152, here a proposal for the API naming:
API to retrieve 'on the fly' reachability status. Name: reachability-status endpoint: /retrieve
API to retrieve 'on the fly ' roaming status. Name: roaming-status endpoint: /retrieve
API to subscribe to reachability notification. Name: reachability-status-subscriptions (the endpoint is /subscriptions)
API to subscribe to roaming notification. Name: roaming-status-subscriptions

@akoshunyadi shell the version be:
* `version: 0.6.0-alpha.2`

* `url: "{apiRoot}/<...>/v0.6alpha2"`

?

@maxl2287 it should be wip for now, and the release-preparation PR will set the correct ones

Following discussion with @fernandopradocabrillo on the PR #152, here a proposal for the API naming:
API to retrieve 'on the fly' reachability status. Name: reachability-status endpoint: /retrieve API to retrieve 'on the fly ' roaming status. Name: roaming-status endpoint: /retrieve API to subscribe to reachability notification. Name: reachability-status-subscriptions (the endpoint is /subscriptions) API to subscribe to roaming notification. Name: roaming-status-subscriptions
Looking for team feedback to close this work.

Fine for me.

@akoshunyadi I removed device to be aligned with device location.
For me it depends also the name of the subprojet. If we keep Device Status as the API family name we can avoid the word device in the api-name.
On this topic we probably need to review @hdamker proposal here
https://github.com/camaraproject/Governance/issues/142 as I guess we need one lead repository for Device Status (without API directly described in it) and 4 child repo for our 4 APIs.... but this is not exactly what Herbert is describing.


Some disjointness information between classes is missing from OLS.

Describe the bug
There are different scenarios under which disjointness information is missing:
Scenario 1
primary systemic mycosis is disjoint with opportunistic mycosis. Disjointness information is displayed for primary systemic mycosis, but not for opportunistic mycosis. See screenshots below:

Scenario 2

I suspect Mondo does not include all reasoned inferences (such as disjointness) probably because the EL++ does not support full negation.


object_storage: remove boto3 dependency

About this change - What it does
Remove the boto3 dependency, there are no functional changes,
Why this way
The boto3 dependency is not needed, since we also use the botocore dependency. Additionally the boto3 dependency is more likely to result in dependency mismatches.

Codecov Report
Patch coverage: 55.55% and project coverage change: -0.22 :warning:

Comparison is base (1e0e20f) 62.98% compared to head (329d461) 62.77%.

Additional details and impacted files
@@            Coverage Diff             @@
##             main     #111      +/-   ##
==========================================
- Coverage   62.98%   62.77%   -0.22%
==========================================
  Files          30       30
  Lines        3458     3457       -1
==========================================
- Hits         2178     2170       -8
- Misses       1280     1287       +7

Impacted Files
Coverage Δ

rohmu/object_storage/s3.py
53.01% <55.55%> (-0.15%)
:arrow_down:

... and 3 files with indirect coverage changes

:umbrella: View full report in Codecov by Sentry.
:loudspeaker: Do you have feedback about the report comment? Let us know in this issue.


Xiao statement should be removed

I have noticed that the contact info has a similar description in the readme, we'd better remove it before starting the first informal release.

Thank your for your reporting. I think this issue is fixed by https://github.com/apache/incubator-pegasus/pull/600/files. Reopen this issue if there are other license problems.


[ONNX] Fix roi_align ONNX export

Allow export of roi_align when sampling rate is negative

@KsenijaS is the PR ready for review?

@KsenijaS is the PR ready for review?

@fmassa  Yes, PR is ready for a review. It would be also good that some one from my team review it as well.
@neginraoof @BowenBao


[BUG] Action is evaluating branch instead of sha

Is there an existing issue for this?

[X] I have searched the existing issues

Does this issue exist in the latest version?

[X] I'm using the latest release

Describe the bug?
After upgrading from v35.4.1 to v35.4.3, my workflows are failing with the following error:
  fatal: couldn't find remote ref <BRANCH NAME>
  Error: Process completed with exit code 128.

The reason git can't find this ref, is because my repository is configured to delete HEAD branches after merging.
The changed-files action is configured to use the sha of the HEAD branch, rather than the ref.
This worked fine until upgrading. It would appear that something has changed which makes the action look for the ref instead of using the sha.
To Reproduce
My use case is described in #944. To reproduce, use this workflow and merge a pull request in a repository that deletes HEAD branches:
name: example

on:
  pull_request: {}

jobs:
  example:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
        with:
          ref: ${{ github.event.pull_request.base.sha }}
      - uses: actions/checkout@v3
        with:
          ref: ${{ github.event.pull_request.head.sha }}

      - id: changed-files
        uses<EMAIL_ADDRESS>        with:
          sha: ${{ github.event.pull_request.head.sha }}
          base_sha: ${{ github.event.pull_request.base.sha }}
          json: true

What OS are you seeing the problem on?
ubuntu-latest or ubuntu-20.04
Expected behavior?
The workflow code referenced above should work like, like it did in v35.4.1, where it is able to fetch the HEAD sha, despite the branch having been deleted.
Relevant log output
# The failing log outputs look like this

  Verifying git version...
  Valid git version found: (2.39.1)
  Running on a pull request event...
  Fetching remote refs...
  fatal: couldn't find remote ref <BRANCH NAME>
  Error: Process completed with exit code 128.

# The log outputs from a successful run after rolling back to `v35.4.1` looks like this:

  Verifying git version...
  Valid git version found: (2.39.0)
  Running on a pull request event...
  Fetching remote refs...
  From https://github.com/<ORG>/<REPO>
   * [new ref]         refs/pull/1808/head -> <BRANCH NAME>

Anything else?
Thank you for a very useful GitHub action.
Code of Conduct

[X] I agree to follow this project's Code of Conduct

@djfinnoy This should be resolved in the latest release.

Indeed, thank you for the swift resolution.


nix-janitor: 0.3.1 -> 0.3.2

Upstream released an update (but messed up the changelog)
https://github.com/NobbZ/nix-janitor/blob/0.3.2/CHANGELOG.md#unreleased---unreleased
Things done

Built on platform(s)

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

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

[ ] sandbox = relaxed
[ ] sandbox = true

[ ] Tested, as applicable:

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

[x] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[x] Tested basic functionality of all binary files (usually in ./result/bin/)
25.05 Release Notes (or backporting 24.11 and 25.05 Release notes)

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

[x] Fits CONTRIBUTING.md.

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

nixpkgs-review result
Generated using nixpkgs-review.
Command: nixpkgs-review pr 360440

x86_64-linux

:white_check_mark: 1 package built:

nix-janitor


Dsd 856/pagination alignment

Fixes JIRA ticket DSD-856.
This PR does the following:

The first link in the Pagination component was slightly lower than the rest. This change fixes that alignment issue.

How has this been tested?

Locally.

Accessibility concerns or updates

No accessibility concerns. This was a very minor update. However, I am curious why the marginTop I deleted was added to begin with. There may be some unintended consequences of removing it. Would love to hear from Marty + Edwin on this front.

Checklist:

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

Front End Review:

[ ] View the example in Storybook

Tugboat has finished building the preview for this pull request!
Link:

https://pr910-amxmz8hs2qqzzq0bgksa1qlkvtci0lrr.tugboat.qa

Dashboard:

https://dashboard.tugboat.qa/6238d440fa61ec8fbf1a6577

Tugboat has finished building the preview for this pull request!
Link:

https://pr910-amxmz8hs2qqzzq0bgksa1qlkvtci0lrr.tugboat.qa

Dashboard:

https://dashboard.tugboat.qa/6238d440fa61ec8fbf1a6577

The spacing changes look good. One nit, however. With the removal of the spacing built into the component, the Go to Page 1 button in the last example now abuts the pagination. Can you use VStack or SimpleGrid to separate the two? Also make sure to bump up the Latest Version number to 0.25.13.

Gotcha! Fixed, on both fronts. Thanks, Marty.


Stop building the "x86-64-unknown-linux-gnu" ponyc package

The "x86-64-unknown-linux-gnu" package was intended to be "generic", however, it is not actually generic. It is a glibc version that is built on "some glibc using Linux" and will work if it is installed on a Linux that is compatible at a library level withthe system that we built the package on.
Quite some time ago, Theo and I (who made the initial decision to include a "x86-64-unknown-linux-gnu" package) realized that the
"x86-64-unknown-linux-gnu" package idea was "a very bad idea".
There are a couple large problems with this approach:
1- anyone using the pacakge on glibc distro that isn't library compatible with our "x86-64-unknown-linux-gnu" build will have the installed ponyc fail in interesting and confounding ways. That's a bad user experience.
2- in order to not fall horribly behind, from time to time, we need to "rev" the environment used to build our "x86-64-unknown-linux-gnu" packages. For us that has meant changing the Ubuntu version periodically. That then means that people who had an environment that worked will do an update and install a ponyc that doesn't work because it is for a different set of libraries. That's a bad user experience as well.
This PR drops "x86-64-unknown-linux-gnu" from being built and mirrors a change in ponyup that dropped support for using the package via ponyup. See https://github.com/ponylang/ponyup/pull/245 for more information about the ponyup change.

This is going to fail until https://github.com/ponylang/ponyc is merged and this is rebased.


Documentation for LAUNCH_DIALLER workflow on patient profile

IMPORTANT: Where possible all PRs must be linked to a Github issue
Fixes issue https://github.com/opensrp/fhircore/issues/2869
Background
Issue raised: https://github.com/opensrp/fhircore/issues/2822
Implementing Pull request: https://github.com/opensrp/fhircore/pull/2856
Engineer Checklist

[ ] I have written Unit tests for any new feature(s) and edge cases for bug fixes
[ ] I have added any strings visible on UI components to the strings.xml file
[ ] I have updated the  CHANGELOG.md file for any notable changes to the codebase
[ ] I have run ./gradlew spotlessApply and ./gradlew spotlessCheck to check my code follows the project's style guide
[ ] I have built and run the FHIRCore app to verify my change fixes the issue and/or does not break the app
[ ] I have checked that this PR does NOT introduce breaking changes that require an update to Content and/or Configs? If it does add a sample here or a link to exactly what changes need to be made to the content.

Code Reviewer Checklist

[ ] I have verified Unit tests have been written for any new feature(s) and edge cases
[ ] I have verified any strings visible on UI components are in the strings.xml file
[ ] I have verifed the CHANGELOG.md file has any notable changes to the codebase
[ ] I have verified the solution has been implemented in a configurable and generic way for reuseable components
[ ] I have built and run the FHIRCore app to verify the change fixes the issue and/or does not break the app

Member

LGTM

Thank you for reviewing my work!


Failed execution when the price < 100 sats in trading on xxxBTC pairs

For example, on XVGBTC pair (current price = 0.00000079).
I've got notifications in Slack, as follows:
XVGBTC Buy Action (16:36:19.890): STOP_LOSS_LIMIT

Order Params:
{
"symbol": "XVGBTC",
"side": "buy",
"type": "STOP_LOSS_LIMIT",
"quantity": 1233,
"stopPrice": 8.1e-7,
"price": 8.1e-7,
"timeInForce": "GTC"
}

Execution failed (16:36:20.813)
Job: Trailing Trade
Code: -1100
Message:
Illegal characters found in parameter 'price'; legal range is '^([0-9]{1,20})(.[0-9]{1,20})?$'.
Stack:
Error: Illegal characters found in parameter 'price'; legal range is '^([0-9]{1,20})(.[0-9]{1,20})?$'.
at /srv/node_modules/binance-api-node/dist/http-client.js:93:17
at runMicrotasks ()
at processTicksAndRejections (internal/process/task_queues.js:95:5)
at async execute (/srv/dist/server.js:1:25474)
at async /srv/dist/server.js:1:3023
at async Promise.all (index 27)
at async execute (/srv/dist/server.js:1:1712)
at async /srv/dist/server.js:1:65227
at async CronJob. (/srv/dist/server.js:1:65065)
BTW, many thanks for your awesome bot.

Oh, that seems a bug you found.
I will fix up when I get time.


Use new bugbug pipeline

@marco-c there is an error in CI, could you check ?

@calixteman @marco-c From the error message:
  ERROR: Could not find a version that satisfies the requirement rs_parsepatch==0.2.0 (from bugbug==0.0.27->-r requirements.txt (line 18)) (from versions: 0.1.0, 0.1.1)
ERROR: No matching distribution found for rs_parsepatch==0.2.0 (from bugbug==0.0.27->-r requirements.txt (line 18))

And checking the distributions files on pypi, rs_parsepatch stopped distributing python 2.7 wheels with version 0.1.2. And the build seems to be running Python 2.7.14

scikit-learn 0.21.1 also doesn't have a Python 2 package.
I guess we have to wait until the switch to Python 3 in order to merge this.

Depends on #282.

Coverage remained the same at 26.027% when pulling ad8222afeea4a8116ac473b82195bc06ddd960c4 on marco-c:use_new_data_pipeline into a941d4f2b33a841b1374a7c1ce8d78e4715d64d2 on mozilla:master.


KeyError: 'QG_RCNN is not in the detector registry'

This repo does not support model outside mmdetection.


Implement example completion for zsh

Related issue #8871
Demo

Thanks for the pull request, and welcome! The Rust team is excited to review your changes, and you should hear from @alexcrichton (or someone else) soon.
Please see the contribution instructions for more information.

Thanks!
@bors r+

:pushpin: Commit b8df3cbfd5fbcb673af2d34d6f57e3aeb3ecc810 has been approved by ehuss

:hourglass: Testing commit b8df3cbfd5fbcb673af2d34d6f57e3aeb3ecc810 with merge 0121d66aa2ef5ffa9735f86c2b56f5fdc5a837a6...

:sunny: Test successful - checks-actions
Approved by: ehuss
Pushing 0121d66aa2ef5ffa9735f86c2b56f5fdc5a837a6 to master...


⚠ Bofrost.fr has degraded performance

In 89b5987, Bofrost.fr (https://www.bofrost.fr) experienced degraded performance:

HTTP code: 200
Response time: 1430 ms

Resolved: Bofrost.fr performance has improved in 481e405.


Add a depot_url property to the hab_install resource.

This additional optional property allows a user to install the initial core/hab package from an alternate Depot (currently for Linux only).

LGTM but travis seems angry for some reason...

travis has other issues...

Yeah, I think Travis might have been having issues. I'd restart the task, but I think that requires ownership of the org/repo. I could rebase and push if all else fails.

reran travis and all is well.

@mwrock @fnichol you're both admins now


Print nix reminder when starting devbox shell

Nix prints:
---- Reminders -----------------------------------------------------------------
[ 1 ]
Nix won't work in active shell sessions until you restart them.

Devbox should print something similar.

We currently print this after running our Nix installation with devbox setup nix, so I think this we can close this. We also now notify developers to restart their shell or source shellenv if they add a new package while in a Devbox Shell.
Will open a separate issue if we need to print additional messages.


⚠ Bofrost.fr has degraded performance

In 3de16d5, Bofrost.fr (https://www.bofrost.fr) experienced degraded performance:

HTTP code: 200
Response time: 2036 ms

Resolved: Bofrost.fr performance has improved in 50bbfff after 18 minutes.


[demo] mset early&initial support on OpenKh.Game

Segments → Func<double, Segment[]> GetSegmentsByTime
I'm not good at extending high level library like Engine.

.mset is loaded inside FromEntity. It would be better on loading separately or upper layer.
https://github.com/Xeeynamo/OpenKh/blob/4f1add3f22307a9437dfb3493bf65e51ae6a393d/OpenKh.Engine/Parsers/MdlxParser.cs#L88

Both .mdlx and .mset binaries are required because KH2's PS2 code needs (or eats) it.

This is a very good start as a proof of concept! Are you planning to refactor it and make it ready to be merged into master?

This is a very good start as a proof of concept! Are you planning to refactor it and make it ready to be merged into master?

Thanks for checking. I got animation implementation idea by googling MonoGame.
Model class has native support of Bones and Draw using matrices. So current MSET support code will be more simple a little.

Model and ModelBone
In my interpretation, ModelBone is to be used to connect body and parts (having parent and child relationship).

SkinnedEffect is useful if we pass SubModels into GPU like KH2 does in VPU.

Untransformed vertices (as vertex buffer) and matrices (as constant buffer) can be processed on SkinnedEffect's specific vertex shader.
SkinnedEffect supports up to 72 matrices at once.
WeightsPerVertex is 1, 2, or 4.
An issue is that KH2 uses WeightsPerVertex = 5 at most!

I am happy to see that the Model Matrix multiplication is now performed in the GPU! That is a good practice for 3D applications since it increases the performance.
I did not looked yet to your implementation, but usually the original meshes are stored into a Vertex Buffer. Then for each mesh, you send to the shader the Matrix animation and draw only the portion of the vertex buffer associated to the mesh it needs to be transformed.
This is done to obtain great performance, but it is not needed to OpenKH engine yet. Sorry if my explanation was not clear.
I am really excited for this pull request 😁

Hello @kenjiuno 😃are you still working on this? If you need to pair with someone to carry on with this, we can both work together! If not, take your time. We look forward on this pull request!

Closed in favor of #256


Remove flake8-pytest

@lk-geimfari do you have the time to remove flake8-pytest from our dev dependencies?
Related: https://github.com/wemake-services/wemake-python-styleguide/issues/1221

Consider it done!

@sobolevn I have created PR #157


Visual Studio Extension reporting on Undesired files for the solution

The VS Extension is telling us about these
It's undesired

haha, Opened files! Never mind


fix(api): update code to improve performance

:tada: This PR is included in version 2.7.3 :tada:
The release is available on GitHub release
Your semantic-release bot :package::rocket:


Global tags dupplication

Adding global tag make it repeat many time. One for each endpoint.
Code
services.SwaggerDocument(o =>
        {
 o.TagDescriptions = t => t["Partners"] = "Manage partners";
}

Result in Swagger.json
{
 "tags": [
    {
      "name": "Partners",
      "description": "Manage partners"
    },
    {
      "name": "Partners",
      "description": "Manage partners"
    },
    {
      "name": "Partners",
      "description": "Manage partners"
    },
    {
      "name": "Partners",
      "description": "Manage partners"
    }
  ]
}

I guess the issue is here
https://github.com/FastEndpoints/FastEndpoints/blob/103e4c4a41a2564f30b7295c2054fc169b92a1bb/Src/Swagger/Extensions.cs#L71-L77
Maybe just check if tag key is already in collection.
Can I do a PR ?

Thanks for reporting the issue. It has been solved in v<IP_ADDRESS>-beta.
Went in a different route than checking for duplicates:
https://github.com/FastEndpoints/FastEndpoints/blob/6aec23783b1cf3a13dd4fb4e3c734e48ddf72dd8/Src/Swagger/Extensions.cs#L66-L78


Revert "Make input a dictionary for multi-modal object detection (#95)"

This reverts commit de77a9d1363f4bbfc94f5301263323c4ce291956.
What does this PR do?
We don't really have multi-modal training working, so revert this until we do. This makes main at least usable with our other work.
Type of change
Please check all relevant options.

[ ] Improvement (non-breaking)
[ ] Bug fix (non-breaking)
[ ] New feature (non-breaking)
[ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
[ ] This change requires a documentation update

Testing
Please describe the tests that you ran to verify your changes. Consider listing any relevant details of your test configuration.

[ ] pytest
[ ] CUDA_VISIBLE_DEVICES=0 python -m mart experiment=CIFAR10_CNN_Adv trainer=gpu trainer.precision=16 reports 70% (21 sec/epoch).
[ ] CUDA_VISIBLE_DEVICES=0,1 python -m mart experiment=CIFAR10_CNN_Adv trainer=ddp trainer.precision=16 trainer.devices=2 model.optimizer.lr=0.2 trainer.max_steps=2925 datamodule.ims_per_batch=256 datamodule.world_size=2 reports 70% (14 sec/epoch).

Before submitting

[ ] The title is self-explanatory and the description concisely explains the PR
[ ] My PR does only one thing, instead of bundling different changes together
[ ] I list all the breaking changes introduced by this pull request
[ ] I have commented my code
[ ] I have added tests that prove my fix is effective or that my feature works
[ ] New and existing unit tests pass locally with my changes
[ ] I have run pre-commit hooks with pre-commit run -a command without errors

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

I released v0.5.1 that reverts the same PR: https://github.com/IntelLabs/MART/releases/tag/v0.5.1

I would like to merge this PR into main, because Adversary can perform transforms internally in #203
It's better to keep the datamodule transforms simple and consistent with the Armory input format.

You can merge then :)


HTC "Internet" application touch issues.

I'm running Android 4.4.2, HTC Sense version 6.0,
When I use use touch to zoom in I get a very weird effect. It seems to put a static version of the image over top of the zoomable part of the image. Here's a video of it: https://www.youtube.com/watch?v=tM3aiS-au6Q

@crswll any news on this? Do we still care about it? :-)


Switch to pyproject.toml from setup.py

Refs:

#33

Error:
  × Getting requirements to build wheel did not run successfully.
  │ exit code: 1
  ╰─> [14 lines of output]
      error: Multiple top-level modules discovered in a flat-layout: ['asgi_csrf', 'test_asgi_csrf'].

I'm building a wheel in the tests so I can test that the wheel installs cleanly.

  with:
    name: python-packages
    path: dist/
    if-no-files-found: warn
    compression-level: 6
    overwrite: false
    include-hidden-files: false
  env:
    pythonLocation: /opt/hostedtoolcache/Python/3.10.15/x64
    PKG_CONFIG_PATH: /opt/hostedtoolcache/Python/3.10.15/x64/lib/pkgconfig
    Python_ROOT_DIR: /opt/hostedtoolcache/Python/3.10.15/x64
    Python2_ROOT_DIR: /opt/hostedtoolcache/Python/3.10.15/x64
    Python3_ROOT_DIR: /opt/hostedtoolcache/Python/3.10.15/x64
    LD_LIBRARY_PATH: /opt/hostedtoolcache/Python/3.10.15/x64/lib
With the provided path, there will be 2 files uploaded
Artifact name is valid!
Root directory input is valid!
Error: Failed to CreateArtifact: Received non-retryable error: Failed request: (409) Conflict: an artifact with this name already exists on the workflow run

Looks like the name needs to differ for each build. I'm going to upload the wheel just for the Python 3.12 one.

A pip install of those generated files worked. I'm going to land this.


Send Title as caption for reddit images

The current solution adds a button with a link, that opens the image in a webbrowser.
Is there a way to load the image directly in the app?

Also, the inline feature (@Bot)  seems to be broken.

The current solution adds a button with a link, that opens the image in a webbrowser.
Is there a way to load the image directly in the app?

I tried some things but it doesn't seem there is a solution for this. You can upload the image as a Document (via send_document) with the blurred image as a thumbnail, but as soon as you specify the file format as an image format, the thumnail gets ignored and the full image is shown.


Few ideas as enhancements

Ability to delete a folder completely.
Ability to have more than one remote link in a remote json, its for patches or something.
Auto supersede files from downloaded zip patches.

Delete downloaded zip files after extract to save space.

Moving existing files from folder to a different folder.

Ability to have more than one remote link in a remote json, its for patches or something.

As this is just a remote substitute for a local config, this is not planned. You could always stuff everything inside one bundle.json and point at it with a remote.json to keep config counts minimal.

Auto supersede files from downloaded zip patches.

Not entirely sure what you are getting at. Automatic overwriting of old files?

Ability to have more than one remote link in a remote json, its for patches or something.

As this is just a remote substitute for a local config, this is not planned. You could always stuff everything inside one bundle.json and point at it with a remote.json to keep config counts minimal.

Auto supersede files from downloaded zip patches.

Not entirely sure what you are getting at. Automatic disabling of already present files when extracting?

Automatic overrides of old files.

For extracting archives, that‘s already a thing, actually. I‘m going to streamline this with an overwrite installation policy for the upcoming update.


Translation in work

[ ] Russian by Tlya

[ ] Italian by ilyNerY

[ ] German by Derko

[ ] Spanish by ?

[ ] French by ?

[ ] Chinese by ?

[ ] Japanese by ?

[ ] Portugese by ?

etc etc

I may try to translate to Simplified Chinese after I finish the game.But I'm preparing for the exam recently, so it may take a little longer.

Cool!
I may play it first just to give me some context and them I should be able to do it.


Flaky Tests

Whenever I run GOCACHE=off go test ./... it fails every once in a while. In my testing it fails about 1/5 of the time.
nati:~/golang/src/github.com/natnaelg/tracy$ GOCACHE=off go test ./...
?       github.com/natnaelg/tracy       [no test files]
--- FAIL: TestAddEventNodeName (0.00s)
        event_test.go:296: Got an error while getting tracer with ID 1s
--- FAIL: TestAddEventJSON (0.00s)
        event_test.go:296: Got an error while getting tracer with ID 1s
--- FAIL: TestAddEventDataJSON (0.00s)
        event_test.go:106: no such table: raw_events
--- FAIL: TestAddEventDataHTML (0.00s)
        event_test.go:122: no such table: raw_events
--- FAIL: TestGetEvents (0.00s)
        event_test.go:296: Got an error while getting tracer with ID 1s
FAIL
FAIL    github.com/natnaelg/tracy/api/common    0.168s
[ERROR]:2018/07/08 10:19:40 error.go:12: no such table: requests
[ERROR]:2018/07/08 10:19:40 error.go:23: no such table: errors
--- FAIL: TestAddEvent (0.00s)
        rest_server_helper_test.go:49: the following request did not pass it's test: AddTracer returned the wrong status code: got 500, but wanted 200. Request body: {"Message":"Internal Server Error", "Reference":"41396"}
[ERROR]:2018/07/08 10:19:40 error.go:12: no such table: requests
[ERROR]:2018/07/08 10:19:40 error.go:23: no such table: errors
--- FAIL: TestDuplicateEvent (0.00s)
        rest_server_helper_test.go:49: the following request did not pass it's test: AddTracer returned the wrong status code: got 500, but wanted 200. Request body: {"Message":"Internal Server Error", "Reference":"62042"}
[ERROR]:2018/07/08 10:19:40 error.go:12: no such table: requests
[ERROR]:2018/07/08 10:19:40 error.go:23: no such table: errors
--- FAIL: TestAddTracer (0.00s)
        rest_server_helper_test.go:49: the following request did not pass it's test: AddTracer returned the wrong status code: got 500, but wanted 200. Request body: {"Message":"Internal Server Error", "Reference":"36348"}
FAIL
FAIL    github.com/natnaelg/tracy/api/rest      0.071s

I added a store.DB.Close() to one of the test helpers in 1dbf7016304e2839564d3e201e9c6706c71ae450. I can't reproduce these errors, but can you try again and see if that resolves the issue?

nati:~/golang/src/github.com/natnaelg/tracy$ GOCACHE=off go test ./...
?       github.com/natnaelg/tracy       [no test files]
--- FAIL: TestAddEventDataJSON (0.00s)
        event_test.go:106: no such table: raw_events
--- FAIL: TestAddEventDataHTML (0.00s)
        event_test.go:122: no such table: raw_events
FAIL
FAIL    github.com/natnaelg/tracy/api/common    0.172s
--- FAIL: TestAddEvent (0.01s)
        rest_server_helper_test.go:50: the following request did not pass it's test: The inserted tracer has the wrong ID. Expected 1, got: 2. Request body: {"ID":2,"CreatedAt":"2018-07-08T18:06:40.234097373-04:00","UpdatedAt":"2018-07-08T18:06:40.234097373-04:00","DeletedAt":null,"RawRequest":"GET / HTTP/1.1\nHost: gorm.io\nUser-Agent: Mozilla/5.0 (X11; Linux x86_64; rv:58.0) Gecko/20100101 Firefox/58.0\nAccept: text/html,application/xhtml+xml,application/xml;q=0.9,;q=0.8\nAccept-Language: en-US,en;q=0.5\nAccept-Encoding: gzip, deflate\nConnection: keep-alive\nPragma: no-cacheCache-Control: no-cache","RequestURL":"http://example.com","RequestMethod":"GET","Tracers":[{"ID":2,"CreatedAt":"2018-07-08T18:06:40.234417115-04:00","UpdatedAt":"2018-07-08T18:06:40.234417115-04:00","DeletedAt":null,"TracerString":"","OverallSeverity":0,"RequestID":2,"TracerEvents":null,"TracerPayload":"blahblah","TracerLocationType":0,"TracerLocationIndex":0,"HasTracerEvents":false}]}
--- FAIL: TestDuplicateEvent (0.01s)
        rest_server_helper_test.go:50: the following request did not pass it's test: The inserted tracer has the wrong ID. Expected 1, got: 2. Request body: {"ID":2,"CreatedAt":"2018-07-08T18:06:40.239706183-04:00","UpdatedAt":"2018-07-08T18:06:40.239706183-04:00","DeletedAt":null,"RawRequest":"GET / HTTP/1.1\nHost: gorm.io\nUser-Agent: Mozilla/5.0 (X11; Linux x86_64; rv:58.0) Gecko/20100101 Firefox/58.0\nAccept: text/html,application/xhtml+xml,application/xml;q=0.9,;q=0.8\nAccept-Language: en-US,en;q=0.5\nAccept-Encoding: gzip, deflate\nConnection: keep-alive\nPragma: no-cacheCache-Control: no-cache","RequestURL":"http://example.com","RequestMethod":"GET","Tracers":[{"ID":2,"CreatedAt":"2018-07-08T18:06:40.241436506-04:00","UpdatedAt":"2018-07-08T18:06:40.241436506-04:00","DeletedAt":null,"TracerString":"","OverallSeverity":0,"RequestID":2,"TracerEvents":null,"TracerPayload":"blahblah","TracerLocationType":0,"TracerLocationIndex":0,"HasTracerEvents":false}]}
--- FAIL: TestAddTracer (0.01s)
        rest_server_helper_test.go:50: the following request did not pass it's test: The inserted tracer has the wrong ID. Expected 1, got: 2. Request body: {"ID":2,"CreatedAt":"2018-07-08T18:06:40.251614954-04:00","UpdatedAt":"2018-07-08T18:06:40.251614954-04:00","DeletedAt":null,"RawRequest":"GET / HTTP/1.1\nHost: gorm.io\nUser-Agent: Mozilla/5.0 (X11; Linux x86_64; rv:58.0) Gecko/20100101 Firefox/58.0\nAccept: text/html,application/xhtml+xml,application/xml;q=0.9,;q=0.8\nAccept-Language: en-US,en;q=0.5\nAccept-Encoding: gzip, deflate\nConnection: keep-alive\nPragma: no-cacheCache-Control: no-cache","RequestURL":"http://example.com","RequestMethod":"GET","Tracers":[{"ID":2,"CreatedAt":"2018-07-08T18:06:40.251744756-04:00","UpdatedAt":"2018-07-08T18:06:40.251744756-04:00","DeletedAt":null,"TracerString":"","OverallSeverity":0,"RequestID":2,"TracerEvents":null,"TracerPayload":"blahblah","TracerLocationType":0,"TracerLocationIndex":0,"HasTracerEvents":false}]}
FAIL
FAIL    github.com/natnaelg/tracy/api/rest      0.083s
?       github.com/natnaelg/tracy/api/store     [no test files]
?       github.com/natnaelg/tracy/api/types     [no test files]
?       github.com/natnaelg/tracy/configure     [no test files]
?       github.com/natnaelg/tracy/log   [no test files]
ok      github.com/natnaelg/tracy/proxy 0.032s

nati:~/golang/src/github.com/natnaelg/tracy$ GOCACHE=off go test ./...
?       github.com/natnaelg/tracy       [no test files]
--- FAIL: TestAddTracer (0.00s)
        tracer_test.go:102: Got an error while adding a tracer.
FAIL
FAIL    github.com/natnaelg/tracy/api/common    0.177s
[ERROR]:2018/07/08 18:08:09 error.go:12: no such table: requests
[ERROR]:2018/07/08 18:08:09 error.go:23: no such table: errors
--- FAIL: TestAddEvent (0.00s)
        rest_server_helper_test.go:50: the following request did not pass it's test: AddTracer returned the wrong status code: got 500, but wanted 200. Request body: {"Message":"Internal Server Error", "Reference":"49592"}
FAIL
FAIL    github.com/natnaelg/tracy/api/rest      0.069s

Nope =\ seems to still happen consistently. For more context
Platform: MacOS
Go Version: go version go1.10.1 darwin/amd64

@jacobheath Why don't you put all the tests in the same test so you can ensure they run in series? And go with a more TableDrivenTest methodology https://github.com/golang/go/wiki/TableDrivenTests

Gotcha. I'll try that. In the meantime, here's an example DB file.
prod-tracer-db.zip

@natnaelg mind try these again? I tried to make them more table driven per your suggestion.

@heathj lgtm, can't reproduce, closing.


chore: bump core and rm ssz feat

Motivation
Ref #1166

Solution
Bump core to 0.8.0, rm ssz feature from meta-crate.

PR Checklist

[ ] Added Tests
[ ] Added Documentation
[ ] Breaking changes

I want to block this until we have a date for new release


Question: How to use Alamofire after installing with CocoaSeeds?

Sorry to start a new thread, but the other one was an issue, and this one is only a question.
I've succesfully installed Alamofire, JLToast and SwiftyJson. All three with CocoaSeeds (seed install)
I open mi project and go check the usage of these three (invokations), and this is what I see:

When I'm using JLToast.makeText(...), thats fine, no errors.

When I'm using JSON (which is a struct from SwiftyJson), eg:
static func fromJSON(json: JSON) -> Place {
     var place:Place = Place()
     place.placeId = json["placeId"].intValue // SwiftyJson method
    ...etc

Thats fine too. No errors.

When I'm using Alamofire.request(.GET, "http://....", parameters: ....), there is this error:
Use of unresolved identifier 'Alamofire'

So... with SwiftyJson is more clear to see that there arent errors because SwiftyJson just declares a type that I'm later using. But how come JLToast isn't throwing any errors too?
The real question, though, is:
How can I use Alamofire? I've read that I should wrap it in a struct to simulate a namespace, but what do you recommend? I ask because in the README you've put Alamofire as a seed example so you must have use it (I guess)
Thanks!
by the way, I really appreciate that this is the only project out there trying to solve the "pods + IOS7" problem.

Oooh, hate when this happends (ask something and solve it instantly).
I've changed Alamofire.request(.GET, ....) with request(.GET, ....)

Yeah, CocoaSeeds doesn't use dynamic framework. There's no namespace for third party frameworks.


Dev version of optifine is incompatible with AccessTransformers of deobfCompile dependencies (when using it without forcePublic)

Because forge doesn't really apply their ATs at runtime because they are applied during setupDecompWorkspace and the deobfuscator isn't aware of them. Unless I'm doing something wrong there. Adding the mod ATs to the OptiFine's jar doesn't seem to work for some reason (OptiFine's jar doesn't have the AT runtime-deobfuscated by forge(gradle)?)
Maybe it would be better to be able to supply AccessTransformer list to the deobfuscator and have it apply the access transformers normally? forcePublic won't work as previously shown because there are way too many corner cases (forge actually tried to do that in much earlier versions and if was failing in the same way)

I think it can be closed as user error...
It didn't work because I needed to add --noCoreSearch argument to have malisiscore work in dev environment because of the way mixin works, and with that argument forge didn't actually load the AccessTransformers even when log explicitly said they are loaded.


prettier-plugin?

I recently stumbled upon a prettier plugin for jsdoc and I’m quite impressed. However there are some compatibility issues with typedoc. Most notable is the @example block does not use fences (fails at parsing) so the output examples won’t be displayed as code. If—on the other hand—you write your examples without the block, the plugin will ruin your indents.
I was wondering is there any effort into creating a prettier plugin for typedoc comments? (or—better yet—does one exist already)?
If not, is there an interest in creating one?

As far as I know, there hasn't been any effort in creating something like this. I don't plan on working on anything like this - TypeDoc is also moving towards being (mostly) conformant to TSDoc, so any formatting attempt would likely be better spent there.


Use config.logger if present

unless we have a better unified logging concept (see https://github.com/adobe/helix-cli/issues/79) it would be great if the config.logger would be used by git-server, to at least harmonize the hlx up message.

thanks.


Failed to locate libpython within timeout period when execute pyflame -p PID in python 2.7

1.pyflame -v pyflame 1.6.6 linux-gnu x86_64 (ABI list: 26)
2.python2.7
3.when execute pyflame -p PID, prompt "Failed to locate libpython within timeout period."

nitin@thinkpad:~/home/pyflame$ ./pyflame -v
pyflame 1.6.6 linux-gnu x86_64 (ABI list: 26 36)

i built pyflame from source same error with me, i guess i am using anaconda's python distribution that might be the issue.
As while building pyflame from source it showed only default linux python paths
while i installed python 3.7 using anaconda.
i tried to install pyflame with conda but it unable to do so as it get's stuck at solving environment


Rerender and update to v2.0.1

Checklist

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

add myself as a maintainer

@conda-forge-admin, please rerender

@conda-forge-admin, please rerender

@conda-forge-admin, please rerender

Hi @ricklupton
Could you review and merge please. Version 2.0,1 was released over 18 months ago, and this PR updates the recipe. I am happy to help keep this feedstock updated too.
Thanks and regards.


padrino-gen plugin not working.

I tried to install a plugin and was getting an error that the template was  not found, even with it was there. I create a clean app and tried it again, and didn't work, pasting the whole process.
terminus-2 ~/Code $ padrino-gen project test_padrino
      create
      create  .gitignore
      create  config.ru
      create  config/apps.rb
      create  config/boot.rb
      create  public/favicon.ico
      create  public/images
      create  public/javascripts
      create  public/stylesheets
      create  tmp
      create  .components
      create  app
      create  app/app.rb
      create  app/controllers
      create  app/helpers
      create  app/views
      create  app/views/layouts
      create  Gemfile
      create  Rakefile
    skipping  orm component...
    skipping  test component...
    skipping  mock component...
    skipping  script component...
    applying  slim (renderer)...
       apply  renderers/slim
      insert  Gemfile
    skipping  stylesheet component...
   identical  .components
       force  .components

=================================================================
test_padrino is ready for development!
=================================================================
$ cd ./test_padrino
$ bundle
=================================================================

terminus-2 ~/Code $ cd test_padrino/
terminus-2 ~/Code/test_padrino $ ls
Gemfile      	app		config.ru	tmp
Rakefile	config		public
terminus-2 ~/Code/test_padrino $ bundle
Fetching gem metadata from https://rubygems.org/...........
Fetching gem metadata from https://rubygems.org/..
Resolving dependencies...
Using rake (10.0.4)
Using i18n (0.6.4)
Using multi_json (1.7.2)
Using activesupport (3.2.12)
Using bundler (1.3.4)
Using rack (1.5.2)
Using url_mount (0.2.1)
Using http_router (0.11.0)
Using mime-types (1.21)
Using polyglot (0.3.3)
Using treetop (1.4.12)
Using mail (2.5.3)
Using rack-protection (1.5.0)
Using tilt (1.3.6)
Using sinatra (1.4.2)
Using thor (0.17.0)
Using padrino-core (0.11.0)
Using padrino-helpers (0.11.0)
Using padrino-admin (0.11.0)
Using padrino-cache (0.11.0)
Using padrino-gen (0.11.0)
Using padrino-mailer (0.11.0)
Using padrino (0.11.0)
Installing temple (0.5.5)
Installing slim (1.3.6)
Your bundle is complete!
It was installed into /Users/adolfobuiles/.rvm/gems/ruby-1.9.3-p194
terminus-2 ~/Code/test_padrino $ padrino plugin bootstrap
Could not find task "plugin".
terminus-2 ~/Code/test_padrino $ padrino-gen plugin bootstrap
       apply  https://github.com/padrino/padrino-recipes/raw/master/plugins/bootstrap_plugin.rb
  The template at https://github.com/padrino/padrino-recipes/raw/master/plugins/bootstrap_plugin.rb could not be found!
terminus-2 ~/Code/test_padrino $

Btw, https://github.com/padrino/padrino-recipes/raw now redirects to
https://raw.github.com/padrino/padrino-recipes/master/ I think the problem is somewhere around that, I tried to fix it, but just changing the path didn't work. Maybe I could have a better look later.

Chiming it 3 years later - same issue, with a solution.
Confirming the same issue on Windows 7 with ruby 2.2.3 & Rubygems 2.4.4 . Upgrading rubygems (current 2.6.4) and setting SSL env  - solves the underlying problem - SSL issue. The error - is just not propagated properly - so it was a bit of a mystery.
Certificate can be obtained here: https://curl.haxx.se/ca/cacert.pem ( or search google)
Option 1 - session ENV - in the file or in a console
ENV["SSL_CERT_FILE"] = "C:\tools\local\ruby\223\cacert.pem"
my Ruby live in c:\tools , your's might be in a different folder.
Option2 - System ENV  via console ( make sure you use cmd and not powershell - there is a conflit with one of the powershell cmdlets)
set SSL_CERT_FILE C:\tools\local\ruby\223\cacert.pem
You can also do this in powershell:
CMD /C “ set SSL_CERT_FILE C:\tools\local\ruby\223\cacert.pem”
Don't forget to restart your console ( completely!)
My Debian boxes didn't have any issues ( using rbenv), but I'm guessing it might be a similar issue.


Fixes example snippets in UnsafePointer.swift

Fixes example snippets in UnsafePointer.swift

@swift-ci smoke test and merge


Build virtual Zarr store using Xarray's dataset.to_zarr(region="...") model

I'm wondering how we can build virtualization pipelines as a map rather than a map-reduce process. The map paradigm would follow the structure below from Earthmover's excellent blog post on serverless datacube pipelines, where the virtual dataset from each worker would get written directly to an Icechunk Virtual Store rather than being transferred back to the coordination node for a concatenation step. Similar to their post, the parallelization between workers during virtualization could leverage a serverless approach like lithops or coiled. Dask concurrency could speed up virtualization within each worker. I think the main feature needed for this to work is an analogue to xr.Dataset.to_zarr(region="..."), complementary to xr.Dataset.to_zarr(append_dim="...")(documented in https://docs.xarray.dev/en/latest/generated/xarray.Dataset.to_zarr.html)  (xref https://github.com/zarr-developers/VirtualiZarr/issues/21, https://github.com/zarr-developers/VirtualiZarr/pull/272).

I tried to check that this feature request doesn't already exist, but apologies if I missed something.

This is a really extremely good question that I have also thought about a bit.
I think a big difference is that this "map" approach assumes more knowledge the structure of the dataset up front. To use zarr regions you have to know how big the regions are in advance to create an empty zarr array that will be filles, but In the "map-reduce" approach you are able to concatenate files whose shapes you don't know until you open them. Whether that actually matters much in practice is another question.
One thing to note is that IIUC having each worker write a region of virtual references would mean one icechunk commit per region, whereas transferring everything back to one node means one commit per logical version of the dataset, which seems a little nicer.

I think the main feature needed for this to work is an analogue to xr.Dataset.to_zarr(region="...")

I agree.

I really like the idea behind this approach @maxrjones! Being able to skip transferring all the references back to a 'reduce' step seem great. Also wondering about how all the commits between workers would work with icechunk.

This also seems like a good way to protect against a single failed reference killing the entire job.

I think a big difference is that this "map" approach assumes more knowledge the structure of the dataset up front.

:+1:

IIUC having each worker write a region of virtual references would mean one icechunk commit per region,

It does not, once https://github.com/earth-mover/icechunk/pull/357 is in

IIUC having each worker write a region of virtual references would mean one icechunk commit per region,

It does not, once https://github.com/earth-mover/icechunk/pull/357 is in. Though in practice, that also does map-reduce on changesets which will contain virtual references in this case...

Thanks for this information! Do you think it's accurate that map-reduce on changesets would still be more performant than map-reduce on virtual datasets when operating on thousands or more of files, such that this feature would be helpful despite not truly by a map operation? Also, do you anticipate there being other prerequisites in addition to your PR before VirtualiZarr could have something like dataset_to_icechunk(region="...")?


Outgoing network connection when used in offline mode

I followed instructions to install atuin in standalone mode, and expected it won't be making any network connections.
To my surprise, an outgoing network connection was detected by Little snitch to https://api.atuin.sh the moment I invoked history by pressing ctrl+R.
I went through config and found that there is an update check, which is probably what caused this outgoing network connection. (Please correct me if I'm wrong).
Perhaps you should mention this in the readme to allow user to disable update check, and let the package manager deal with updates; or ask user on first run if automated update checking should be enabled.

I went through config and found that there is an update check, which is probably what caused this outgoing network connection. (Please correct me if I'm wrong).

Update check will make a connection but so will auto_sync = true if you`re using sync (This will make a connection to the set server sync_address which is defaulted to api.atuin.sh)! auto_sync will every command run if the set time (sync_frequency = "1h") has elapsed since the last check (afaik).

I followed instructions to install atuin in standalone mode

so will auto_sync = true if you`re using sync

I did not login to any server, therefore I expected this wouldn't apply to me. Am I wrong?

It only will if you’re using sync - so in your case, it’s just the update
check
I can make the docs more prominent later, and make a compile time feature
so package managed releases don’t need it
Since making it default-on, the number of issues we’ve had due to people
running out of date versions has gone down massively, so I’m loathe to
change it
On Mon, May 8, 2023 at 18:08, Aleks Bunin @.***> wrote:

I followed instructions to install atuin in standalone mode
so will auto_sync = true if you`re using sync
I did not login to any server, therefore I expected this wouldn't apply to
me. Am I wrong?
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@ellie I made #960 to mention option to disable update check in the offline installation instructions. This should be sufficient.

There is the sync feature that is default enabled. You can disable it if you're comfortable building atuin yourself.
cargo install atuin --no-default-features --features client

Would disable the server and sync features so you only get the local client only features

With the merge of #960, I probably will close this.


Docs: Add more tutorials

fixes #236

Codecov Report
Patch and project coverage have no change.

Comparison is base (9001050) 100.00% compared to head (69e1bcd) 100.00%.

Additional details and impacted files
@@            Coverage Diff            @@
##              main      #285   +/-   ##
=========================================
  Coverage   100.00%   100.00%
=========================================
  Files           33        33
  Lines         1356      1356
  Branches       316       284   -32
=========================================
  Hits          1356      1356

Help us with your feedback. Take ten seconds to tell us how you rate us. Have a feature suggestion? Share it here.

:umbrella: View full report in Codecov by Sentry.
:loudspeaker: Do you have feedback about the report comment? Let us know in this issue.


[Feature] Support application roles for Identity Server and support RBAC for apps

Is your feature request related to a problem? Please describe.
Role-based access control (RBAC) is a widely used access control mechanism for B2E and B2B applications. To support RBAC, API resource management, API Authorization to applications, application role management, and application role-based scope validation are key features to have in the IAM solution.
Describe the solution you would prefer

Implement application roles management
Ability to assign local groups and users to application roles
Ability to assign federated users to application roles
Use application roles for scope validation and support RBAC
Ability to share roles (selectively) of B2B applications when sharing the app with sub org
Use application roles in XACML policies
Add an adaptive script functions to consume application roles of a user during adaptive scripts

Design
Wireframe
https://docs.google.com/document/d/1Jt1ksVptBHmcrsitva_r4Aa7UjAFwVcr_rdlvkgh0Ns/edit

Front-End PR's

https://github.com/wso2/identity-apps/pull/4162
https://github.com/wso2/identity-apps/pull/4147
https://github.com/wso2/identity-apps/pull/4152
https://github.com/wso2/oxygen-ui/pull/165

BE PRs
SCIM and Charon Changes for Role V2 support

https://github.com/wso2/charon/pull/392
https://github.com/wso2-extensions/identity-inbound-provisioning-scim2/pull/486

Add access control and /o/ path support for /scim2/v2/Roles endpoint

https://github.com/wso2/carbon-identity-framework/pull/4917
https://github.com/wso2/carbon-identity-framework/pull/4998

Capability to associate roles in the new model with an application

https://github.com/wso2/carbon-identity-framework/pull/5001
https://github.com/wso2/identity-api-server/pull/504

Shared role managing event handler

https://github.com/wso2-extensions/identity-organization-management/pull/255

Migration Issues

https://github.com/wso2/product-is/issues/16865
https://github.com/wso2/product-is/issues/16864

Pending Items

[ ] Cache fixes such as https://github.com/wso2/carbon-identity-framework/pull/4965#discussion_r1359897996
[ ] Add Audit logs in the new pattern
[ ] Integration Tests

Improvements :

[ ] Organization validation improvement - https://github.com/wso2/carbon-identity-framework/pull/5043
[ ] Invalid application cache after application audience role added - https://github.com/wso2/carbon-identity-framework/pull/5043

Improvements/ Bug Fixes :
[X] Fix permission not getting replaced when empty permission list is sent -  https://github.com/wso2-extensions/identity-inbound-provisioning-scim2/pull/495
[X] Fix 500 returns when empty value object is sent in patch replace operation - https://github.com/wso2/charon/pull/395

Identified bugs
1.UI issues in groups assign section in the roles tab - https://github.com/wso2/product-is/issues/17235

Creating issues for pending tasks

[ ] Add a caching layer for role management
[ ] Add audit logs for role management
[ ] Support federated group to role mapping
[ ] Use the newly introdicued roles in XACML policies with new authz runtime
[ ] Add an adaptive script function to consume roles of a user during adaptive scripts


⚠ ClamAV has degraded performance

In e8fa2d3, ClamAV (https://spamassassin.apache.org/) experienced degraded performance:

HTTP code: 200
Response time: 63 ms

Resolved: ClamAV performance has improved in a971f91.


Correct dimensions for custom login icon

Description
I'm attempting to implement a custom icon on the login screen, via the Icon URL field on the Auth0 -> Settings -> Appearance screen in the WordPress admin area.
This field recommends a size "less than 120px tall", but I'm struggling to find the correct icon dimensions and ratio. It appears that the icon's height is forced to 58px and its width is forced to auto, which results in strange behaviour when uploading an image that's too wide for the container.
Can you advise on the exact dimensions for the custom icon please? And can you consider an option to hide this icon and the Form Title value so that neither appear? That way, custom of the standard WordPress login screen icon can simply be used.
Environment

WP-Auth0 version: 3.8.0
WordPress version: 4.9.8

Hi @johnbillion, nice to see a familiar name using the plugin!
The embedded form that's there is built completely in JS and can be styled with either an external CSS sheet loaded on the login page (recommended) or using the "Login Page CSS" field under wp-admin > Auth0 > Settings > Appearance. Here's what worked for me:
.auth0-lock.auth0-lock .auth0-lock-header {display: none}
.auth0-lock-header-avatar {display: none}

Regardless of the CSS you use, make sure to turn off "Enable Gravatar Integration" on that same settings page or you get some interesting behavior.
The icon image description is unhelpful, I agree. I would stick with something square, that seems to work the best. Any size is fine, smaller the better ... I would recommend just using double what's enforced in the CSS, 116px square, to account for higher pixel density screens.
Let me know if there's anything else I can help with or if you have any feedback!

We went with full-on customisation in the end :-)

Thanks for the pointers about the custom icon. Some improvements to the helper text there would help a lot I think. Cheers!

Looks great! Thanks for the suggestion and checking back in.


Revert "Remove the old HaTS implementation on API docs"

Reverts flutter/flutter#28683
This included the new survey as well. Partial revert leaves out old hats.

Thanks 😅!


Create article scope

Problem
We have tried multiple approaches to fix tailor navigation structure, including changing navigation in different scopes. This has proved to be confusing, because people have to constantly switch back and forth between scopes just to see the article.
Hiding navigation items or changing structure is bad for search indexing and discovery.
Instead we should keep the navigation structure static, but have a very explicit label in the top header area that highlights the n, please create a scopes part in the header that works like Gitlab:
---
title: Application Access Role-Based Access Control
description: Role-Based Access Control (RBAC) for Teleport Application Access.
scopes: oss, enterprise, cloud
---

Here is how title should look like approximately:

Supported scope and description:
scope: oss, enterprise
The title should render on-hover "Available in OSS and Enterprise editions"

Special case is all, renders as: ALL
scope: all
The title should render on-hover "Available in OSS, Enterprise, Cloud editions"

I think this would be great, and have some thoughts:

I think we should also indicate in the navigation sidebar that a page only applies to a particular edition. This way, a user won't need to navigate to a page to realize that it doesn't apply to their use-case. One way we could do this is below (just to illustrate what I mean). This will reduce the space we have in the nav bar for text, so we can think of alternatives as well.

The banner indicating which edition a page supports should be as clear as possible, since some users may be arriving at the docs site without knowing that we have three editions. The majority of users already ignore the scope dropdown menu, so we should minimize the risk that users ignore this banner as well.

@ptgott we can try this, but because there are a lot of nav sections like that, we should make it more subtle, a small gray label will be better.

Banner blindness may be keeping people from looking at our header and missing the edition selector on top.
To increase visibility, how about listing all sections for all editions neatly in the left navbar (perhaps also increasing contrast and making the sidebar wider), but adding bold text ""This feature is only available in the Enterprise edition." as a one-line 2nd paragraph of the article near the top of the page - in the same font as the article.

@ulysseskan good point. I think we can try a simple solution to this problem by making a header to be a more regular header. @Alqanar  can you try the style above to see if it works better.

@klizhentas I would like to clarify.

What version of the header do we make?

header with the grey gradient:

header with the white gradient:

header with extra line, where we specify scope

Do we make any changes to the navigation? Something like that?

@Alqanar header with white background with extra line, where we specify scope looks great, let's try this one

@Alqanar re: icons, let's try those, but move the icons in front of the text


5.10.25 is now Stable

Hi
Cloud you update to 5.10.25 please
https://community.ui.com/releases/UniFi-Network-Controller-Stable-5-10-25/fc76945d-c918-4d8d-8cd1-094d05287f45
Thanks!

Awesome, not only does the new "community" software totally suck for anything resembling usability, it nuked the blog posts and e-mail notifications I was using to monitor releases...
Updated image should be available ~1h after this post. Thanks for giving me a heads-up.


Remove Suspense when freeze false

More of a question than an issue I would say. Why do we need Suspense here https://github.com/software-mansion/react-freeze/blob/main/src/index.tsx#L39?
The react-freeze is used by react-navigation. I don't use the freeze option but my screens go to suspense in this library and render null. I believe there would be a way to propagate placeholder and display something, but I already have suspense in my app. I want that suspense to catch the promise.
I can submit a PR with something like this:
if (!freeze) {
  return <Fragment>{props.children}</Fragment>
}

I just wanted to validate first

Found this comment - https://github.com/software-mansion/react-native-screens/pull/1538#issuecomment-1212001180. Which I guess answers my question.


Video Embed (YouTube)-Alignment issue

Hi Team,
I have noticed that there is an issue in the alignment. In the legacy, the YouTube video is aligned in the center but in EDS it is aligned to the left.
EDS:-

LEGACY:-

Hi @Kummu007 . Please try to apply the default template in metadata and check whether it is working or not. Assigning you for this observation.

@teshukatepalli1  thanks for the update and this is working as expected.


Small bubbles goes under the big ones after indicator was changed

Severity: Major.
Platform where was tested: MacBook Air
Browsers: Safari, Chrome
Steps to reproduce:

Open Bubble chart - http://tools-dev.gapminderdev.org/tools .
Select "For advanced users" -> "Injury deaths by gender, age, road user" -> "Murdered children, 0-14" indicator for X-axis.
Select "For advanced users" -> "Injury deaths by gender, age, road user" -> "Murdered men" indicator for X-axis.

Actual result:
Small bubbles got hovered by China.

Sometimes some of bubbles got not full opacity.

Expected result:
Small bubbles shouldn't be hovered by China.

https://github.com/Gapminder/vizabi/pull/1698

Retested. Fixed.


Enhance Object.assign static method signature

Fixes #12109

There's a glitch: Object.assign mutates the target assignee directly. So it should really look something like this (which is actually correct mod a missing object | Function type constraint where object is implemented in this PR:
interface Object {
    assign<T>(target: T, ...sources: Partial<T>): T;
}

@sandersn is working on a fix for this as tracked by https://github.com/Microsoft/TypeScript/issues/11100. I would rather wait for that change.


adr-0039: app dev privilege elevation

⚠ IMPORTANT ⚠: This is a public repository. Make sure to not disclose:

[x] personal data beyond what is necessary for interacting with this Pull Request;
[x] business confidential information, such as customer names.

I added one additional line
diff --git a/docs/adr/0039-application-dev-permissions.md b/docs/adr/0039-application-dev-permissions.md
index 202544a4..510548cc 100644
--- a/docs/adr/0039-application-dev-permissions.md
+++ b/docs/adr/0039-application-dev-permissions.md
@@ -28,6 +28,7 @@ How should we manage such requests and when should the core permissions granted
 1. Elevate privileges on a case-by-case basis
    - Application developers can request additional privileges.
      The request can be accepted or rejected by the Platform administrators.
+     If accepted, the elevated privileges should, if possible, be implemented into the core platform.


[Feature] Info title for every titles in build/deploy configuration

I think @theweaver19 is confused with the term Workspace which I feel from his feedback list.

We should put up a doc for these details so that future devs can understand the use of each field in the build/deploy config form before deploying.

Another way is to put an info icon beside the field label for more info about the particular field.

@izrake what would you suggest to tackle this issue?

Released in v2.2