Auth/public/js/form.socialprofiles.js displays wrong profile data

socialprofiles.js sends wrong data to http://yawik.local/en/applications/null?action=social-profile&network={network} for subsequent clicks on "view profile data" links (without reloading the page).
Possible solutions: replace bootstrap's $modal remote option (deprecated since v3.3.0) with regular jQuery $.post() method

Can I fix it?

Yes, please do so

Fixed in issue-199 branch


Feature/36 upload pdf file

PDF with no load works as intended. But we need to fix this:
We need to save the whole filesystem path (C:/exc) in lastOpenedURL because on hosted DEV it will try to go through the path of t he server like this:
image


Question about branches and PR

Hi guys,
I saw that @daniel-lewis-ab is working on the reversion and @atlasan is working on forwardcompatible. And I've sumitted a PR to the master. Is master the branch I should PR to? Did I do it right? Or, should I join @atlasan to fix things on forwardcompatible?
I need some suggestion. Thanks!

Hi @liusida, good to see you here ^ _ ^ I chose the name for the temporary branch I'm working on. Surely the intention is to be compatible and forward looking ^ _ ^ Please feel free to join, need some hands in testing, cleaning, and improving.

Sounds like a plan. Do you have any specific tasks that I can work on? I can try one of them first.

And, what do you think about the PR #19, since that PR can make litegraph.js runnable in plain html, and we won't need to start a http server for the development any more.
My thought is that we're going to get reversion caught up, and then start
porting over any features we want one at a time so that there's some
discipline in how they're integrated while still allowing us to dev
freely.  Both Atlasan and I have trouble doing just one thing at a time so
the commits and versioning are clean.
On Fri, Jun 7, 2024 at 1:14 AM Liu Sida @.***> wrote:

Hi guys,
I saw that @daniel-lewis-ab https://github.com/daniel-lewis-ab is
working on the reversion and @atlasan https://github.com/atlasan is
working on forwardcompatible. And I've sumitted a PR to the master. Is
master the branch I should PR to? Did I do it right? Or, should I join
@atlasan https://github.com/atlasan to fix things on forwardcompatible?
I need some suggestion. Thanks!
—
Reply to this email directly, view it on GitHub
https://github.com/daniel-lewis-ab/litegraph.js/issues/21, or
unsubscribe
https://github.com/notifications/unsubscribe-auth/AC36LNYCAODAOFQKXVTY2QDZGFMUTAVCNFSM6AAAAABI6DHHZSVHI2DSMVQWIX3LMV43ASLTON2WKOZSGMZTSNZWGA3TEMA
.
You are receiving this because you were mentioned.Message ID:
@.***>

think about the best way to allow different version of the library in ComfyUI ( I was imagining a setting in there where to specify the name of the folder/file to be included. This would help testing and switching to pre-release or custom UIs easily. eg. clone the repo in a folder and specify that folder name in the ComfyUI settings

Yeah. I naively thought that compiling this project into a litegraph.core.js file and replace the original one in ComfyUI would automatically bring new features to ComfyUI. (I've actually tried, but it doesn't work...)
How do you do this manually @atlasan ? Can the current forwardcompatible branch be applied to current ComfyUI?


cannot start triton server by using llama-2-7b-chat

Checklist

[ ] 1. I have searched related issues but cannot get the expected help.
[ ] 2. The bug has not been fixed in the latest version.

Describe the bug
cannot start triton server by using llama-2-7b-chat
Reproduction

convert:
 lmdeploy convert llama2 /nvme/qa_test_models/llama-2-7b-chat --dst-path /nvme/qa_test_models/autotest_model/workspace_llama-2-7b-chat
start triton server:
bash /nvme/qa_test_models/autotest_model/workspace_llama-2-7b-chat/service_docker_up.sh

Environment
sys.platform: linux
Python: 3.10.0 (default, Mar  3 2022, 09:58:08) [GCC 7.5.0]
CUDA available: True
numpy_random_seed:<PHONE_NUMBER>
GPU 0,1,2,3,4,5,6,7: NVIDIA A100-SXM4-80GB
CUDA_HOME: /usr/local/cuda-11.7
NVCC: Cuda compilation tools, release 11.7, V11.7.64
GCC: gcc (GCC) 4.8.5 20150623 (Red Hat 4.8.5-44)
PyTorch: 2.1.2+cu118
PyTorch compiling details: PyTorch built with:
  - GCC 9.3
  - C++ Version: 201703
  - Intel(R) oneAPI Math Kernel Library Version 2022.2-Product Build 20220804 for Intel(R) 64 architecture applications
  - Intel(R) MKL-DNN v3.1.1 (Git Hash 64f6bcbcbab628e96f33a62c3e975f8535a7bde4)
  - OpenMP 201511 (a.k.a. OpenMP 4.5)
  - LAPACK is enabled (usually provided by MKL)
  - NNPACK is enabled
  - CPU capability usage: AVX512
  - CUDA Runtime 11.8
  - NVCC architecture flags: -gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86;-gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_90,code=sm_90
  - CuDNN 8.7
  - Magma 2.6.1
  - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.8, CUDNN_VERSION=8.7.0, CXX_COMPILER=/opt/rh/devtoolset-9/root/usr/bin/c++, CXX_FLAGS= -D_GLIBCXX_USE_CXX11_ABI=0 -fabi-version=11 -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOROCTRACER -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Werror=bool-operation -Wnarrowing -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-strict-overflow -Wno-strict-aliasing -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=old-style-cast -Wno-invalid-partial-specialization -Wno-unused-private-field -Wno-aligned-allocation-unavailable -Wno-missing-braces -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_DISABLE_GPU_ASSERTS=ON, TORCH_VERSION=2.1.2, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=1, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF,

TorchVision: 0.16.2+cu118
LMDeploy: 0.2.0+
transformers: 4.33.0
gradio: 3.50.2
fastapi: 0.109.0
pydantic: 2.5.3

Error traceback
=============================
== Triton Inference Server ==
=============================

NVIDIA Release 22.12 (build 50109463)
Triton Server Version 2.29.0

Copyright (c) 2018-2022, NVIDIA CORPORATION & AFFILIATES.  All rights reserved.

Various files include modifications (c) NVIDIA CORPORATION & AFFILIATES.  All rights reserved.

This container image and its contents are governed by the NVIDIA Deep Learning Container License.
By pulling and using the container, you accept the terms and conditions of this license:
https://developer.nvidia.com/ngc/nvidia-deep-learning-container-license

NOTE: CUDA Forward Compatibility mode ENABLED.
  Using CUDA 11.8 driver version 520.61.05 with kernel driver version 515.86.01.
  See https://docs.nvidia.com/deploy/cuda-compatibility/ for details.

I0118 01:31:33.579726 1 pinned_memory_manager.cc:240] Pinned memory pool is created at '0x7f9c1c000000' with size 268435456
I0118 01:31:33.581627 1 cuda_memory_manager.cc:105] CUDA memory pool is created on device 0 with size 67108864
I0118 01:31:33.589732 1 model_lifecycle.cc:459] loading: turbomind:1
I0118 01:31:33.589769 1 model_lifecycle.cc:459] loading: postprocessing:1
I0118 01:31:33.589790 1 model_lifecycle.cc:459] loading: preprocessing:1
I0118 01:31:35.005354 1 libfastertransformer.cc:1747] TRITONBACKEND_Initialize: turbomind
I0118 01:31:35.005389 1 libfastertransformer.cc:1754] Triton TRITONBACKEND API version: 1.10
I0118 01:31:35.005397 1 libfastertransformer.cc:1758] 'turbomind' TRITONBACKEND API version: 1.10
I0118 01:31:36.185205 320 pb_stub.cc:245]  Failed to initialize Python stub for auto-complete: ModuleNotFoundError: No module named '1.tokenizer.utils'

At:
  /workspace/models/model_repository/postprocessing/1/tokenizer/tokenizer.py(10): <module>
  <frozen importlib._bootstrap>(219): _call_with_frames_removed
  <frozen importlib._bootstrap_external>(848): exec_module
  <frozen importlib._bootstrap>(686): _load_unlocked
  <frozen importlib._bootstrap>(975): _find_and_load_unlocked
  <frozen importlib._bootstrap>(991): _find_and_load
  /workspace/models/model_repository/postprocessing/1/model.py(13): <module>
  <frozen importlib._bootstrap>(219): _call_with_frames_removed
  <frozen importlib._bootstrap_external>(848): exec_module
  <frozen importlib._bootstrap>(686): _load_unlocked
  <frozen importlib._bootstrap>(975): _find_and_load_unlocked
  <frozen importlib._bootstrap>(991): _find_and_load

E0118 01:31:36.214051 1 model_lifecycle.cc:597] failed to load 'postprocessing' version 1: Internal: ModuleNotFoundError: No module named '1.tokenizer.utils'

At:
  /workspace/models/model_repository/postprocessing/1/tokenizer/tokenizer.py(10): <module>
  <frozen importlib._bootstrap>(219): _call_with_frames_removed
  <frozen importlib._bootstrap_external>(848): exec_module
  <frozen importlib._bootstrap>(686): _load_unlocked
  <frozen importlib._bootstrap>(975): _find_and_load_unlocked
  <frozen importlib._bootstrap>(991): _find_and_load
  /workspace/models/model_repository/postprocessing/1/model.py(13): <module>
  <frozen importlib._bootstrap>(219): _call_with_frames_removed
  <frozen importlib._bootstrap_external>(848): exec_module
  <frozen importlib._bootstrap>(686): _load_unlocked
  <frozen importlib._bootstrap>(975): _find_and_load_unlocked
  <frozen importlib._bootstrap>(991): _find_and_load

I0118 01:31:37.422799 397 pb_stub.cc:245]  Failed to initialize Python stub for auto-complete: ModuleNotFoundError: No module named '1.tokenizer.utils'

At:
  /workspace/models/model_repository/preprocessing/1/tokenizer/tokenizer.py(10): <module>
  <frozen importlib._bootstrap>(219): _call_with_frames_removed
  <frozen importlib._bootstrap_external>(848): exec_module
  <frozen importlib._bootstrap>(686): _load_unlocked
  <frozen importlib._bootstrap>(975): _find_and_load_unlocked
  <frozen importlib._bootstrap>(991): _find_and_load
  /workspace/models/model_repository/preprocessing/1/model.py(15): <module>
  <frozen importlib._bootstrap>(219): _call_with_frames_removed
  <frozen importlib._bootstrap_external>(848): exec_module
  <frozen importlib._bootstrap>(686): _load_unlocked
  <frozen importlib._bootstrap>(975): _find_and_load_unlocked
  <frozen importlib._bootstrap>(991): _find_and_load

I0118 01:31:37.455914 1 libfastertransformer.cc:1785] TRITONBACKEND_ModelInitialize: turbomind (version 1)
E0118 01:31:37.455918 1 model_lifecycle.cc:597] failed to load 'preprocessing' version 1: Internal: ModuleNotFoundError: No module named '1.tokenizer.utils'

At:
  /workspace/models/model_repository/preprocessing/1/tokenizer/tokenizer.py(10): <module>
  <frozen importlib._bootstrap>(219): _call_with_frames_removed
  <frozen importlib._bootstrap_external>(848): exec_module
  <frozen importlib._bootstrap>(686): _load_unlocked
  <frozen importlib._bootstrap>(975): _find_and_load_unlocked
  <frozen importlib._bootstrap>(991): _find_and_load
  /workspace/models/model_repository/preprocessing/1/model.py(15): <module>
  <frozen importlib._bootstrap>(219): _call_with_frames_removed
  <frozen importlib._bootstrap_external>(848): exec_module
  <frozen importlib._bootstrap>(686): _load_unlocked
  <frozen importlib._bootstrap>(975): _find_and_load_unlocked
  <frozen importlib._bootstrap>(991): _find_and_load

I0118 01:31:37.456626 1 libfastertransformer.cc:308] Instance group type: KIND_CPU count: 48
num_nodes=1
tp_pp_size=1
gpu_size=1
world_size=1
model_instance_size=1
I0118 01:31:37.456693 1 libfastertransformer.cc:347] Sequence Batching: disabled
I0118 01:31:37.456708 1 libfastertransformer.cc:358] Dynamic Batching: disabled
[TM][WARNING] [LlamaTritonModel] `max_context_token_num` = 4104.
[TM][WARNING] [LlamaTritonModel] `num_tokens_per_iter` is not set, default to `max_context_token_num` (4104).
Model:
head_num: 32
kv_head_num: 32
size_per_head: 128
inter_size: 11008
num_layer: 32
vocab_size: 32000
attn_bias: 0
max_batch_size: 64
max_context_token_num: 4104
session_len: 4104
step_length: 1
cache_max_entry_count: 0.5
cache_block_seq_len: 128
cache_chunk_size: -1
use_context_fmha: 1
start_id: 1
tensor_para_size: 1
pipeline_para_size: 1
enable_custom_all_reduce: 0
model_name: llama2
model_dir: /workspace/models/model_repository/turbomind/1/weights
quant_policy: 0
group_size: 128
I0118 01:31:37.456992 1 libfastertransformer.cc:388] Before Loading Weights:
after allocation    : free: 78.68 GB, total: 79.21 GB, used:  0.53 GB
I0118 01:31:39.923898 1 libfastertransformer.cc:397] After Loading Weights:
after allocation    : free: 74.88 GB, total: 79.21 GB, used:  4.33 GB
W0118 01:31:39.924039 1 libfastertransformer.cc:517] skipping model configuration auto-complete for 'turbomind': not supported for turbomind backend
I0118 01:31:39.924972 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 74.88 GB, total: 79.21 GB, used:  4.33 GB
[WARNING] gemm_config.in is not found; using default GEMM algo
[TM][INFO] NCCL group_id = 0
[TM][INFO] [BlockManager] block_size = 64 MB
[TM][INFO] [BlockManager] max_block_count = 633
[TM][INFO] [BlockManager] chunk_size = 633
[TM][INFO] LlamaBatch<T>::Start()
I0118 01:31:40.903172 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.78 GB, total: 79.21 GB, used: 44.43 GB
I0118 01:31:40.903286 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.903318 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_0 (count 48) (instance_id 0)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.903568 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.78 GB, total: 79.21 GB, used: 44.43 GB
I0118 01:31:40.903685 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.78 GB, total: 79.21 GB, used: 44.43 GB
I0118 01:31:40.903733 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.903744 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_1 (count 48) (instance_id 1)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.903875 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.78 GB, total: 79.21 GB, used: 44.43 GB
I0118 01:31:40.903922 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.78 GB, total: 79.21 GB, used: 44.43 GB
I0118 01:31:40.903962 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.903972 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_2 (count 48) (instance_id 2)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.904098 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.78 GB, total: 79.21 GB, used: 44.43 GB
I0118 01:31:40.904143 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.78 GB, total: 79.21 GB, used: 44.43 GB
I0118 01:31:40.904185 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.904195 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_3 (count 48) (instance_id 3)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.904869 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.78 GB, total: 79.21 GB, used: 44.43 GB
I0118 01:31:40.904934 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.78 GB, total: 79.21 GB, used: 44.43 GB
I0118 01:31:40.904981 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.904995 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_4 (count 48) (instance_id 4)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.905130 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.78 GB, total: 79.21 GB, used: 44.43 GB
I0118 01:31:40.905185 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.78 GB, total: 79.21 GB, used: 44.43 GB
I0118 01:31:40.905228 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.905237 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_5 (count 48) (instance_id 5)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.905350 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.78 GB, total: 79.21 GB, used: 44.43 GB
I0118 01:31:40.905390 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.78 GB, total: 79.21 GB, used: 44.43 GB
I0118 01:31:40.905429 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.905438 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_6 (count 48) (instance_id 6)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.905544 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.78 GB, total: 79.21 GB, used: 44.43 GB
I0118 01:31:40.905586 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.78 GB, total: 79.21 GB, used: 44.43 GB
I0118 01:31:40.905628 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.905642 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_7 (count 48) (instance_id 7)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.905763 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.78 GB, total: 79.21 GB, used: 44.43 GB
I0118 01:31:40.905796 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.78 GB, total: 79.21 GB, used: 44.43 GB
I0118 01:31:40.905828 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.905839 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_8 (count 48) (instance_id 8)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.905953 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.78 GB, total: 79.21 GB, used: 44.43 GB
I0118 01:31:40.905985 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.78 GB, total: 79.21 GB, used: 44.43 GB
I0118 01:31:40.906014 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.906028 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_9 (count 48) (instance_id 9)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.906136 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.78 GB, total: 79.21 GB, used: 44.43 GB
I0118 01:31:40.906188 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.78 GB, total: 79.21 GB, used: 44.43 GB
I0118 01:31:40.906227 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.906239 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_10 (count 48) (instance_id 10)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.906360 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.78 GB, total: 79.21 GB, used: 44.43 GB
I0118 01:31:40.906401 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.78 GB, total: 79.21 GB, used: 44.43 GB
I0118 01:31:40.906429 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.906444 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_11 (count 48) (instance_id 11)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.907090 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.907135 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.907168 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.907188 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_12 (count 48) (instance_id 12)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.907325 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.907374 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.907409 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.907420 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_13 (count 48) (instance_id 13)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.907549 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.907594 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.907630 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.907640 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_14 (count 48) (instance_id 14)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.907764 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.907795 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.907824 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.907834 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_15 (count 48) (instance_id 15)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.907982 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.908030 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.908063 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.908074 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_16 (count 48) (instance_id 16)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.908221 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.908259 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.908292 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.908304 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_17 (count 48) (instance_id 17)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.908432 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.908461 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.908492 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.908502 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_18 (count 48) (instance_id 18)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.908635 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.908681 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.908716 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.908728 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_19 (count 48) (instance_id 19)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.909407 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.909439 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.909471 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.909482 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_20 (count 48) (instance_id 20)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.909636 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.909671 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.909701 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.909711 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_21 (count 48) (instance_id 21)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.909841 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.909873 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.909901 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.909913 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_22 (count 48) (instance_id 22)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.910044 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.910079 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.910111 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.910120 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_23 (count 48) (instance_id 23)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.910278 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.910307 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.910339 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.910350 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_24 (count 48) (instance_id 24)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.910494 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.910540 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.910576 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.910588 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_25 (count 48) (instance_id 25)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.910763 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.910800 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.910833 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.910844 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_26 (count 48) (instance_id 26)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.910981 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.911021 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.911053 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.911065 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_27 (count 48) (instance_id 27)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.911689 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.911738 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.911777 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.911791 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_28 (count 48) (instance_id 28)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.911955 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.911992 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.912022 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.912031 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_29 (count 48) (instance_id 29)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.912173 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.912207 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.912244 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.912255 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_30 (count 48) (instance_id 30)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.912413 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.912444 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.912472 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.912481 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_31 (count 48) (instance_id 31)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.912647 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.912680 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.912712 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.912721 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_32 (count 48) (instance_id 32)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.912883 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.912917 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.912948 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.912959 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_33 (count 48) (instance_id 33)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.913111 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.913144 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.913172 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.913188 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_34 (count 48) (instance_id 34)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.913343 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.913376 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.913408 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.913418 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_35 (count 48) (instance_id 35)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.914096 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.914142 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.914184 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.914198 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_36 (count 48) (instance_id 36)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.914374 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.914418 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.914448 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.914459 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_37 (count 48) (instance_id 37)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.914626 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.914655 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.914686 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.914697 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_38 (count 48) (instance_id 38)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.914869 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.914916 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.914954 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.914967 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_39 (count 48) (instance_id 39)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.915159 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.915202 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.915241 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.915252 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_40 (count 48) (instance_id 40)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.915434 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.915481 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.915515 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.915526 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_41 (count 48) (instance_id 41)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.915697 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.915725 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.915757 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.915770 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_42 (count 48) (instance_id 42)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.915946 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.915990 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.916024 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.916036 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_43 (count 48) (instance_id 43)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.916702 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.916738 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.916773 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.916786 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_44 (count 48) (instance_id 44)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.916970 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.916999 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.917032 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.917045 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_45 (count 48) (instance_id 45)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.917222 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.917256 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.917288 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.917299 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_46 (count 48) (instance_id 46)
[TM][INFO] Skipping NCCL param creation.
I0118 01:31:40.917473 1 libfastertransformer.cc:422] Before Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.917507 1 libfastertransformer.cc:438] After Loading Model:
after allocation    : free: 34.77 GB, total: 79.21 GB, used: 44.44 GB
I0118 01:31:40.917538 1 libfastertransformer.cc:776] Model instance is created on GPU [ 0 ]
I0118 01:31:40.917549 1 libfastertransformer.cc:1840] TRITONBACKEND_ModelInstanceInitialize: turbomind_0_47 (count 48) (instance_id 47)
I0118 01:31:40.917721 1 model_lifecycle.cc:694] successfully loaded 'turbomind' version 1
I0118 01:31:40.917840 1 server.cc:563]
+------------------+------+
| Repository Agent | Path |
+------------------+------+
+------------------+------+

I0118 01:31:40.917906 1 server.cc:590]
+-----------+-------------------------------------------------------------+------------------------------------------------------------------------------------------------------------------------+
| Backend   | Path                                                        | Config                                                                                |
+-----------+-------------------------------------------------------------+------------------------------------------------------------------------------------------------------------------------+
| python    | /opt/tritonserver/backends/python/libtriton_python.so       | {"cmdline":{"auto-complete-config":"true","min-compute-capability":"6.000000","backend-directory":"/opt/tritonserver/b |
|           |                                                             | ackends","default-max-batch-size":"4"}}                                                                                |
| turbomind | /opt/tritonserver/backends/turbomind/libtriton_turbomind.so | {"cmdline":{"auto-complete-config":"true","min-compute-capability":"6.000000","backend-directory":"/opt/tritonserver/b |
|           |                                                             | ackends","default-max-batch-size":"4"}}                                                                                |
+-----------+-------------------------------------------------------------+------------------------------------------------------------------------------------------------------------------------+

I0118 01:31:40.918007 1 server.cc:633]
+----------------+---------+--------------------------------------------------------------------------------------------+
| Model          | Version | Status                                                                                |
+----------------+---------+--------------------------------------------------------------------------------------------+
| postprocessing | 1       | UNAVAILABLE: Internal: ModuleNotFoundError: No module named '1.tokenizer.utils'            |
|                |         |                                                                                |
|                |         | At:                                                                                |
|                |         |   /workspace/models/model_repository/postprocessing/1/tokenizer/tokenizer.py(10): <module> |
|                |         |   <frozen importlib._bootstrap>(219): _call_with_frames_removed                            |
|                |         |   <frozen importlib._bootstrap_external>(848): exec_module                                 |
|                |         |   <frozen importlib._bootstrap>(686): _load_unlocked                                       |
|                |         |   <frozen importlib._bootstrap>(975): _find_and_load_unlocked                              |
|                |         |   <frozen importlib._bootstrap>(991): _find_and_load                                       |
|                |         |   /workspace/models/model_repository/postprocessing/1/model.py(13): <module>               |
|                |         |   <frozen importlib._bootstrap>(219): _call_with_frames_removed                            |
|                |         |   <frozen importlib._bootstrap_external>(848): exec_module                                 |
|                |         |   <frozen importlib._bootstrap>(686): _load_unlocked                                       |
|                |         |   <frozen importlib._bootstrap>(975): _find_and_load_unlocked                              |
|                |         |   <frozen importlib._bootstrap>(991): _find_and_load                                       |
| preprocessing  | 1       | UNAVAILABLE: Internal: ModuleNotFoundError: No module named '1.tokenizer.utils'            |
|                |         |                                                                                |
|                |         | At:                                                                                |
|                |         |   /workspace/models/model_repository/preprocessing/1/tokenizer/tokenizer.py(10): <module>  |
|                |         |   <frozen importlib._bootstrap>(219): _call_with_frames_removed                            |
|                |         |   <frozen importlib._bootstrap_external>(848): exec_module                                 |
|                |         |   <frozen importlib._bootstrap>(686): _load_unlocked                                       |
|                |         |   <frozen importlib._bootstrap>(975): _find_and_load_unlocked                              |
|                |         |   <frozen importlib._bootstrap>(991): _find_and_load                                       |
|                |         |   /workspace/models/model_repository/preprocessing/1/model.py(15): <module>                |
|                |         |   <frozen importlib._bootstrap>(219): _call_with_frames_removed                            |
|                |         |   <frozen importlib._bootstrap_external>(848): exec_module                                 |
|                |         |   <frozen importlib._bootstrap>(686): _load_unlocked                                       |
|                |         |   <frozen importlib._bootstrap>(975): _find_and_load_unlocked                              |
|                |         |   <frozen importlib._bootstrap>(991): _find_and_load                                       |
| turbomind      | 1       | READY                                                                                |
+----------------+---------+--------------------------------------------------------------------------------------------+

I0118 01:31:40.950658 1 metrics.cc:864] Collecting metrics for GPU 0: NVIDIA A100-SXM4-80GB
I0118 01:31:40.951092 1 metrics.cc:757] Collecting CPU metrics
I0118 01:31:40.951199 1 tritonserver.cc:2264]
+----------------------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------+
| Option                           | Value                                                                                |
+----------------------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------+
| server_id                        | triton                                                                                |
| server_version                   | 2.29.0                                                                                |
| server_extensions                | classification sequence model_repository model_repository(unload_dependents) schedule_policy model_configuration system_shared_memory cuda_shared_memory binar |
|                                  | y_tensor_data statistics trace logging                                                                                |
| model_repository_path[0]         | /workspace/models/model_repository                                                                                |
| model_control_mode               | MODE_NONE                                                                                |
| strict_model_config              | 0                                                                                |
| rate_limit                       | OFF                                                                                |
| pinned_memory_pool_byte_size     | 268435456                                                                                |
| cuda_memory_pool_byte_size{0}    | 67108864                                                                                |
| response_cache_byte_size         | 0                                                                                |
| min_supported_compute_capability | 6.0                                                                                |
| strict_readiness                 | 1                                                                                |
| exit_timeout                     | 30                                                                                |
+----------------------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------+

I0118 01:31:40.951371 1 server.cc:264] Waiting for in-flight requests to complete.

[TM][INFO] [OutputThreadEntry] stop requested.
I0118 01:31:40.975529 1 libfastertransformer.cc:1808] TRITONBACKEND_ModelFinalize: MPI Finalize
I0118 01:31:41.021204 1 model_lifecycle.cc:579] successfully unloaded 'turbomind' version 1
I0118 01:31:41.951513 1 server.cc:302] Timeout 29: Found 0 live models and 0 in-flight non-inference requests
error: creating server: Internal - failed to load all models

same error when start 'internlm2-chat-20b'


Demo site doesn't keep changes made

"Try the interactive demo" goes to https://demo.decapcms.org.
Confirm please - editing seems possible of various nodes, but the changes are discarded right?
For example: can't add one more "post" even though filling all the pertinent fields is possible and [save] can be pressed

No changes are saved on the demo playground.


incorrect return type for DataType.getByDocId() method

Description
The type annotation (which is written manually) states that the return type is Promise<TDoc & { forks: string[] }> but the implementation can return undefined
Tasks

[ ] Either 1) Fix the type definition so that it's Promise<(TDoc & { forks: string[] }) | undefined> or 2) Update implementation so that it doesn't return undefined
[ ] Add test in test-types/datatypes to catch this?

Deciding to go with fixing the implementation to match the type, but not a huge fan of it philosophically, mostly because we don't have custom errors. For example, in most cases, "safe" usage of the method will look like this:
try {
  return observation.getByDocId(...)
} catch (err) {
  // We assume this threw because the observation could not be found
}

In my mind, getByDocId() could throw for any number of reasons, whether it's incorrect params, some issue in its implementation, or the fact that the desired value wasn't found. Without custom errors, we can't distinguish between these reasons in the catch block and unless we're meticulous, we'll just write code there that assumes the issue was that it couldn't be found.


IDP returned role must be identical to the internal role in Identity server

There is a limitation on Identity server which prevents role mappings from IDP to IS unless both role names are identical.
Steps to reproduce:

Install Identity Server pack
Create an IDP which points to an external IDP and do the basic SAML SSO configuration
Create an internal role A in IS
Map the IDP returned role into the internal role A in IDP role mappings
Enable JIT provisioning
Log into the SSO app (travelocity or similar)

Behavior:

User is created in the Identity Server
Role A won't be added to the created user

Thank you for your contribution!
We are closing this issue since it has not been prioritized for a long time. Chances are that it has already been solved in more recent versions. If not, we will be re-evaluating this when it becomes a priority.


Add: TV A Plateia [BR]

Channel Name
TV A Plateia
Alternative Names (optional)
TV A Platéia
Network (optional)
No response
Owners (optional)
Grupo A Platéia
Country
BR
Subdivision (optional)
BR-RS
City (optional)
Santana do Livramento
Broadcast Area
s/BR-RS
Languages
Por
Categories (optional)
General
NSFW
FALSE
Launched (optional)
No response
Closed (optional)
No response
Replaced By (optional)
No response
Website (optional)
https://www.aplateia.com.br/
Logo
https://i0.wp.com/directostv.teleame.com/wp-content/uploads/2017/11/tvplateia.png
Notes
https://video01.kshost.com.br:4443/kamal3366/kamal3366/playlist.m3u8

Thank you for the stream: it will be included in the next release.


Ctrl+F for chat

So I can find that epic chat message from 10 mins ago to screenshot it

#129 might be semi related in a second cousin kind of way


xHostsFile: The PowerShell DSC resource MSFT_xHostsFile from module <xNetworking,<IP_ADDRESS>> does not exist at the PowerShell module path nor is it registered as a WMI DSC resource

Details of the scenario you tried and the problem that is occurring:
I'm trying to apply this resource:
            xHostsFile WAHostEntry
            {
                HostName  =  $webAppHostName
                IPAddress = "<IP_ADDRESS>"
                Ensure    = "Present"
            }

It is successfully compiled on my dev machine into this:
instance of MSFT_xHostsFile as $MSFT_xHostsFile1ref
{
ResourceID = "[xHostsFile]WAHostEntry";
 Ensure = "Present";
 HostName = "SPWA_01.sp.local";
 SourceInfo = "D:\\Alex\\GitHub\\SPConfiStructurer\\SharePointOnPrem\\DSC\\SPFarm.ps1::75::13::xHostsFile";
 ModuleName = "xNetworking";
 IPAddress = "<IP_ADDRESS>";
 ModuleVersion = "<IP_ADDRESS>";

 ConfigurationName = "SPFarm";

};

However, when I start the configuration on the target machine in Azure, I get the error:
PS C:\Users\dauser1> Start-DscConfiguration "C:\DSC\SPFarm - Copy" -Wait -Force -Verbose
VERBOSE: Perform operation 'Invoke CimMethod' with following parameters, ''methodName' =
SendConfigurationApply,'className' = MSFT_DSCLocalConfigurationManager,'namespaceName' =
root/Microsoft/Windows/DesiredStateConfiguration'.
VERBOSE: An LCM method call arrived from computer SP2016Ent01sp01 with user sid
S-1-5-21-1446973221-797931035-2561853747-500.
VERBOSE: [SP2016Ent01sp01]: LCM:  [ Start  Set      ]
VERBOSE: [SP2016Ent01sp01]: LCM:  [ End    Set      ]
The PowerShell DSC resource MSFT_xHostsFile from module <xNetworking,<IP_ADDRESS>> does not exist at the PowerShell module
path nor is it registered as a WMI DSC resource.
    + CategoryInfo          : InvalidOperation: (root/Microsoft/...gurationManager:String) [], CimException
    + FullyQualifiedErrorId : DscResourceNotFound
    + PSComputerName        : SP2016Ent01sp01

VERBOSE: Operation 'Invoke CimMethod' complete.
VERBOSE: Time taken for configuration job to complete is 0.441 seconds

The resource looks available:
PS C:\Users\dauser1> Get-DscResource -Module xNetworking -Name xHostsFile | Format-List

ResourceType  : MSFT_xHostsFile
Name          : xHostsFile
FriendlyName  : xHostsFile
Module        : xNetworking
ModuleName    : xNetworking
Version       : <IP_ADDRESS>
Path          : C:\Program
                Files\WindowsPowerShell\Modules\xNetworking\DSCResources\MSFT_xHostsFile\MSFT_xHostsFile.psm1
ParentPath    : C:\Program Files\WindowsPowerShell\Modules\xNetworking\DSCResources\MSFT_xHostsFile
ImplementedAs : PowerShell
CompanyName   : Microsoft Corporation
Properties    : {HostName, DependsOn, Ensure, IPAddress...}

The DSC configuration that is using the resource (as detailed as possible):
How I create the configuration:

Create Azure Standard_D11_v2 machine.
Install some other extensions via Set-AzureRmVmDscExtension
Take an image of the machine
Create another machine via image
Running mof file

Version of the Operating System and PowerShell the DSC Target Node is running:
Windows Server 2016
PS C:\Users\dauser1> $PSVersionTable.PSVersion

Major  Minor  Build  Revision
-----  -----  -----  --------
5      1      14393  1613

Version of the DSC module you're using, or 'dev' if you're using current dev branch:
When I check with Get-DscResource, it shows version <IP_ADDRESS> if that was the question

I also checked more straight forward scenario:

Creating new Standard_D11_v2 machine
Runing Install-Module -Name xNetworking -Force
Starting mof

getting the same error.

Hi shurick81,
maybe on the Configuration File when you import xNetworking you have set the "ModuleVersion" switch to use  <IP_ADDRESS> .
Best Regards
Atdhe

instance of MSFT_xHostsFile as $MSFT_xHostsFile1ref
{
ResourceID = "[xHostsFile]WAHostEntry";
Ensure = "Present";
HostName = "SPWA_01.sp.local";
SourceInfo = "D:\Alex\GitHub\SPConfiStructurer\SharePointOnPrem\DSC\SPFarm.ps1::75::13::xHostsFile";
ModuleName = "xNetworking";
IPAddress = "<IP_ADDRESS>";
ModuleVersion = "<IP_ADDRESS>";
ConfigurationName = "SPFarm";
};

Hello and thank you for your reply.
I can see now that on my dev machine that I use for compilation, the version of the module is <IP_ADDRESS>.
PS C:\WINDOWS\system32> Get-DscResource -Module xNetworking -Name xHostsFile | Format-List

ResourceType  : MSFT_xHostsFile
Name          : xHostsFile
FriendlyName  : xHostsFile
Module        : xNetworking
ModuleName    : xNetworking
Version       : <IP_ADDRESS>
Path          : C:\Program Files\WindowsPowerShell\Modules\xNetworking\<IP_ADDRESS>\DSCResources\MSFT_xHostsFile\MSFT_xHostsFile.psm1
ParentPath    : C:\Program Files\WindowsPowerShell\Modules\xNetworking\<IP_ADDRESS>\DSCResources\MSFT_xHostsFile
ImplementedAs : PowerShell
CompanyName   : Microsoft Corporation
Properties    : {HostName, DependsOn, Ensure, IPAddress...}

Probably I should keep my compiling machine always up to date then?

Yes i would try to update the xNetworking Module and then look if it works.
I think that's the reason why it's not working because, it's searching for the Module xNetworking Version <IP_ADDRESS> .
Am 13.09.2017 um 15:49 schrieb Alex SaPozhkov <notifications<EMAIL_ADDRESS>Hello and thank you for your reply.
I can see now that on my dev machine that I use for compilation, the version of the module is <IP_ADDRESS>.
PS C:\WINDOWS\system32> Get-DscResource -Module xNetworking -Name xHostsFile | Format-List
ResourceType  : MSFT_xHostsFile
Name          : xHostsFile
FriendlyName  : xHostsFile
Module        : xNetworking
ModuleName    : xNetworking
Version       : <IP_ADDRESS>
Path          : C:\Program Files\WindowsPowerShell\Modules\xNetworking\<IP_ADDRESS>\DSCResources\MSFT_xHostsFile\MSFT_xHostsFile.psm1
ParentPath    : C:\Program Files\WindowsPowerShell\Modules\xNetworking\<IP_ADDRESS>\DSCResources\MSFT_xHostsFile
ImplementedAs : PowerShell
CompanyName   : Microsoft Corporation
Properties    : {HostName, DependsOn, Ensure, IPAddress...}
Probably I should keep my compiling machine always up to date then?
—
You are receiving this because you commented.
Reply to this email directly, view it on GitHubhttps://github.com/PowerShell/xNetworking/issues/267#issuecomment-329173425, or mute the threadhttps://github.com/notifications/unsubscribe-auth/AJ1kTHd4imokDnsWk3ywp5UZzfmkV54Sks5sh91DgaJpZM4PV-yM.

Yes that worked, thank you


Why is project.js file in "Creating a Cross-Platform Console App with DNX" so complicate?

I've seen that project.json file used in the Creating a Cross-Platform Console App with DNX is very complicate:
The app doesn't use Linq, Threading, Collection.
Also I don't understand what's the point of
  "commands": {
    "ConsoleApp1": "ConsoleApp1"
  }

since then the app is run with dnx run
Why not just leaving it to bare minimum needed to run the sample?
{
    "version": "1.0.0-*",
    "dependencies": {
    },
    "frameworks" : {
        "dnx451" : { },
        "dnxcore50" : {
            "dependencies": {
                "System.Console": "4.0.0-beta-*"
            }
        }
    }
}

This is all going to change now that we are moving to the new .NET CLI. Please watch for updated docs on http://dotnet.github.io.


Adds missing possible style variants.

According to the v3 specification, parameter styles can include a range of values not currently present in openapi::v3_0::schema::ParameterStyle.

sorry for the delay on this. looks good to me


failed to build

reproduce:
# GO111MODULE=on go mod download
# go build ./cmd/tk
../../sh0rez/go-jsonnet/desugarer.go:27:2: cannot find package "github.com/google/go-jsonnet/parser" in any of:
	/usr/lib/golang/src/github.com/google/go-jsonnet/parser (from $GOROOT)
	/deploy/go/src/github.com/google/go-jsonnet/parser (from $GOPATH)

Also, is it better to move sh0rez/go-jsonnet to grafana/go-jsonnet?

Hi, it looks like you are running INSIDE of GOPATH. Please make sure Tankas source is always located OUTSIDE of GOPATH

oh, it is totally different from helm!
Could i add this in build docs?

Wait a sec, it looks like there have been actually some changes to google/go-jsonnet that could indeed make imports fails ... I will look into it

also, is there a plan to move sh0rez/go-jsonnet to grafana/go-jsonnet?

No, not really, rather I would like to use the google upstream again.
Due to recent changes to the official compiler it might be possible to ditch the ugly patch I did to it and use the official version again.
sh0rez/go-jsonnet would be archived in that case


chore: bump to xcode 14 on ci

Description
This PR resolves []
Bump to xcode 14
PR Checklist

[ ] I tested my changes on iOS and Android.
[ ] I added screenshots or videos to illustrate my changes.
[ ] I added Tests and Stories for my changes.

To the reviewers 👀

[ ] I would like at least one of the reviewers to run this PR on the simulator or device.

Need help with something? Have a look at our docs, or get in touch with us.

noice


Bugfix handling if version information is None

The error handling when the version information is None is buggy. This is a quick fix, because a lot of home-assistant users complained (#4868, #4479). The latest commit https://github.com/open-homeautomation/miflora/commit/db9a32cbdaad584deed0575feda5e75c75de3786 was intended to fix this but failed.

I've created a new version 0.1.14 with this patch included.


Write a onnx parser test for FP8

Write a onnx parser test for FP8

Working on higher priority DLM issues and JIRA tickets so could not work on this one.

Working on higher priority DLM issues and JIRA tickets so could not work on this one.

Same as before, did not get a chance to work on this. Now that the other issues have been fixed, will pick this up again.

PR to update parse gemm and update gemm tests so I could address the comments on gemm_fp8 test: https://github.com/ROCm/AMDMIGraphX/pull/3158


Beta006 creates duplicate references for netstandard

Description
In Fake I'm seeing diffs like these:
-    <When Condition="$(TargetFrameworkIdentifier) == '.NETStandard' And ($(TargetFrameworkVersion) == 'v1.5' Or $(TargetFrameworkVersion) == 'v1.6' Or $(TargetFrameworkVersion) == 'v2.0')">
+    <When Condition="($(TargetFrameworkIdentifier) == '.NETStandard' And ($(TargetFrameworkVersion) == 'v1.5' Or $(TargetFrameworkVersion) == 'v1.6' Or $(TargetFrameworkVersion) == 'v2.0')) Or ($(TargetFrameworkIdentifier) == '.NETCoreApp' And ($(TargetFrameworkVersion) == 'v1.0' Or $(TargetFrameworkVersion) == 'v1.1' Or $(TargetFrameworkVersion) == 'v2.0'))">
       <ItemGroup>
         <Reference Include="System.Diagnostics.Tracing">
           <HintPath>..\..\..\packages\System.Diagnostics.Tracing\ref\netstandard1.5\System.Diagnostics.Tracing.dll</HintPath>
           <Private>False</Private>
           <Paket>True</Paket>
         </Reference>
+        <Reference Include="System.Diagnostics.Tracing">
+          <HintPath>..\..\..\packages\System.Diagnostics.Tracing\ref\netstandard1.5\System.Diagnostics.Tracing.xml</HintPath>
+          <Private>False</Private>
+          <Paket>True</Paket>
+        </Reference>
       </ItemGroup>

I don't think this is critical as I don't know anyone using this feature to build netcore/netstandard apps. But it should be fixed before releasing paket 5

I just noticed that the second one is a xml doc file... So should be easy to fix. I forgot to filter those somewhere.

Should be fixed with https://github.com/fsprojects/Paket/pull/2454


Fix bugs in Google extensions and RocketMQ extension

The bug with RocketMQ is here: https://github.com/druid-io/druid/pull/4340/files#diff-ec36d47acfde35fae048b6f64b9bdb8aL520 because of a typo (lhs on both sides) this Comparator always returns 0, so Messages are not ordered by offset, that might be important for event order-dependent rollout.
The bug in GoogleDataSegmentPusher is here: https://github.com/druid-io/druid/pull/4340/files#diff-9a74e9ae8d1cd3291d996a8cf9359b8eL147, prefix is compared to empty string "" referentially, and if the prefix is another instance of empty string, they don't match.

👍


Feature Request: GPX Track

Add a GPX Track will be more easy to scan a larger area, only where you want!
Great job with spawn points, really helps me so much

See PokemonGo-Map for further customization.


Bump version

Codecov Report

Merging #606 (dffa85b) into main (820bbf7) will increase coverage by 0.02%.
The diff coverage is n/a.

@@            Coverage Diff             @@
##             main     #606      +/-   ##
==========================================
+ Coverage   84.76%   84.79%   +0.02%
==========================================
  Files         299      299
  Lines       26894    26894
==========================================
+ Hits        22798    22804       +6
+ Misses       4096     4090       -6

Impacted Files
Coverage Δ

lib/hir-mir/src/expression_compiler.rs
86.10% <0.00%> (+0.63%)
:arrow_up:

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 820bbf7...dffa85b. Read the comment docs.


fixed setProps execption swallowing issue and added regression test

Let me know if there's a problem w this!

LGTM. @ljharb I'm thinking this is a patch-level change as it's fixing a bug. Thoughts?

I agree. I'm not entirely sure why the promise was there in the first place tho - is there some benefit it provided (beyond swallowing errors) that might make this a breaking change?


Linux version cannot autofill DOCTYPE

VSCode Version: 1.5.1
OS Version: Ubuntu 16.04, 64 bit

Steps to Reproduce:

Start Visual Studio Code.
Create an empty HTML file.
Input <!DOC for example.
Press TAB.
It should fill with the form below but nothing happens.

<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <title>Document</title>
</head>
<body>

</body>
</html>

@ViBE-HU Is this a regression? Was this working for you before and not in 1.5.1 anymore?
Pressing TAB after <!DOC gives me <!DOC></!DOC>
Pressing TAB after ! gives me
<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <title>Document</title>
</head>
<body>

</body>
</html>

@ramya-rao-a I just started to use on Linux, so I'm not sure, but the same Windows version can do it.

@ramya-rao-a I've tested both 1.4.0 and 1.5.1 and they work.
@ViBE-HU can you help check the right bottom of your Code window and there is a status bar indicating the language for current file, is it saying HTML? Besides, can you help provide us the list of extensions you installed as I don't see this issue with a clean install. Thanks in advance!

Closing as we're unable to repo this
@ViBE-HU Please let me know if you still see this issue in VSCode 1.8. If you are, try running code with --disable-extensions to see if an extension is the root cause
Thanks


Go get to install doesn't work on macOS

Hi there,
I just happened across this project and was keen to have a go (no pun intended), but the installation documentation wasn't very helpful.
Trying to go get github.com/asteris-llc/converge gave me this on a freshly-formatted, up-to-date macOS Sierra setup:
$ go get github.com/asteris-llc/converge

package github.com/grpc-ecosystem/grpc-gateway/third_party/googleapis/google/api: no buildable Go source files in /Users/rafael/code/go/src/github.com/grpc-ecosystem/grpc-gateway/third_party/googleapis/google/api

I'm a newbie to Go in general, so I can't figure out why this is failing.

Interesting! It seems like there's a bug somewhere. It'd probably be easiest if you download a pre-built release to get started.

See the issue here https://github.com/grpc-ecosystem/grpc-gateway/issues/331 for details on this


Handle POST data format for create/update

Need to ensure we're sending the correct format

Fixed in master


Fix deserialization of kebab case attributes by reverting attr renaming

Priority
High, the current version is broken for everyone using kebab case notation in API responses (I think).
What Changed & Why
In a well-intended approach to improve readability, the deserialization of kebab-case attributes was broken in https://github.com/twg/devour/pull/165. This reverts that change and adds a test case.
Testing
A test case was added to prevent this in the future.

Anyone else have thoughts on this?

This is definitely a bug. I'll run through the tests and see if we can get a minor release out to fix this.


Custom services setup: node from scratch

Create a node from scratch without installing any use-case based setup. Just preparing the node to install Stereum services.

Inbetween window for users to define

Installationspath
Network Selection

@David


getParts() fails in some cases

The function getParts() of src/Pop3.php fails when some header information is not written in lowercase, like Boundary=... instead of boundary=....
Solution is to replace
$extra[$key] = $value;
with
$extra[strtolower($key)] = $value;
//foreach extra
foreach ($extra as $i => $attr) {
	//transform the extra array to a key value pair
	$attr = explode('=', $attr, 2);
	if (count($attr) > 1) {
		list($key, $value) = $attr;
		$extra[strtolower($key)] = $value;
	}
	unset($extra[$i]);
}

Thanks @Schnoffel We are looking into the matter


Consider support of JdkClientHttpConnector in DefaultRestClient

Consider support of JdkClientHttpConnector in DefaultRestClient instead of Netty and make this dependency optional.
Asked by Finshape.

My concern is, that we have fine-tuned settings such as timeout for netty and JdkClientHttpConnector settings may differ.


Review models and refactor if needed

We reviewed the models and the DB structure. We found out the possible updates and improvements that we can do.


Upgrade to public_suffix 2.0

Re: https://trello.com/c/IJZ8a0qP
See also: https://github.com/clearbit/validators/pull/12
Required for company to use the latest validators gem, which depends on public_suffix ~> 2.0
Passing default_rule: nil to get the specs passing by emulating the 1.x public_suffix behavior.

/cc @harlow

Dig it! Keeps the original functionality w/ the newer lists 👍

Closing in favor of my upstream pull request https://github.com/blatyo/page_rankr/pull/53 because our fork is out of date. I can add this forced public_suffix upgrade change, but I think it's better to get back onto the upstream gem if/when they merge my pull request or some other version of it.

I changed my mind. Better to be on our clearbit fork and switch to the upstream if/when it's updated.


[vmware]device_id duplicated for multiple data disks after VM import

ISSUE TYPE

Bug Report

COMPONENT NAME

API

CLOUDSTACK VERSION

4.16

CONFIGURATION

OS / ENVIRONMENT

SUMMARY

STEPS TO REPRODUCE

1. Import a VM with multiple disks
2. Observe device_id has been duplicated

EXPECTED RESULTS

There shouldn't be duplication

ACTUAL RESULTS

MariaDB [cloud]> select id,instance_id,device_id from volumes where instance_id=9;
+----+-------------+-----------+
| id | instance_id | device_id |
+----+-------------+-----------+
| 11 |           9 |         0 |
| 12 |           9 |         1 |
| 13 |           9 |         1 |
| 14 |           9 |         2 |
+----+-------------+-----------+
4 rows in set (0.00 sec)

Merged in https://github.com/apache/cloudstack/pull/6123


Key Vault datasource for Azure Resource Manager Endpoint type

I am creating a custom build task where I would like to bind a picklist to a key vault datasource from an ARM endpoint. The ARM endpoint type does not appear to define a datasource for retrieving key vaults from an azure subscription. Am I missing something here? Is there an alternative other than creating a new, custom endpoint type? Are there any plans to implement this feature?
Thanks

@ogoodwin
There is no first class support for this today. @RoopeshNair for further details.
Alternative Today
Write an Azure PowerShell script that reads from key vault and saves them as Build/Release variables for the next tasks to consume. You can use Azure PowerShell task to execute this script.
How to pass secrets from one task to other
You have to consume the VSTS Task SDK to get and set the Build/Release variables.
In the script read from key vault and save the secret as a variable secretFromKeyVault using the Set-VstsTaskVariable cmdlet. Don't forget to pass the -secret flag.
You can consume this in the next task by passing $(secretFromKeyVault) in the appropriate field of the task. Or if you want to consume it in another script, you can use Get-VstsTaskVariable cmdlet.

Thanks @KrishnaAdityaB. I have that portion working. My question was around displaying a picklist of existing subscription key vaults in the task UI rather having the user specify the name of the vault in an input field. As far as I understand, my options are to either add a new key vault datasource to the ARM endpoint type, or create a new custom endoint type that exposes a key vault datasource.
Thanks,

@ogoodwin this should help https://blogs.msdn.microsoft.com/sriramb/2016/09/15/service-endpoints-data-sources/

@ogoodwin sorry, I misunderstood the question first time.
@GitHubSriramB can help you on this

@ogoodwin - We support defining the URL to query inline with data source binding. So in your case, the custom build task can define a data source binding that doesn't refer to a data source but defines the URL to query as part of the data source binding itself.
for e.g.:
{
"target": "keyvault",
"endpointUrl": "https://management.azure.com/subscriptions/$(endpoint.subscriptionId)/resourcegroups/$(ResourceGroupName)/providers/Microsoft.KeyVault/vaults?api-version=2016-02-01",
"resultSelector": "jsonpath:$.value[*].name"
},
Pl. check the api version to use (the version I have used in the example above might not be the right one).
Also, you can optionally use resultTemplate in case you want to return back value/displayvalue (to show display value in the task input but store the value as part of the release definition).


Issue50 Inclined boreholes

Closes #50.

Inclined boreholes are only implemented for the 'detailed' solver, since there is no known 'similarities' or 'equivalent' methods for inclined boreholes.
The initial implementation seems to be working and compares well with Eskilson's results (I will update the issue with figures).
The integral of the FLS solution had to be split between the real and image parts of the solution to avoid overflow flow errors in the product erfc(a*s)*exp(b*s**2) (see the code below). There could be a better implementation for this. It should be explored further before merging.
https://github.com/MassimoCimmino/pygfunction/blob/a847dfd70661f2dbf08e3cbb8f84f093a5b7e00c/pygfunction/heat_transfer.py#L772-L777

Remaining tasks:

[ ] Complete docstrings
[ ] Format code
[ ] Merge #191 and implement tests
[ ] Add an example
[ ] Update CHANGELOG
[ ] Check for more efficient integration approach

This is now ready for review.


siteValueModifier

[-]  moved to persistentdatastore - can't be done in a simple to manage way
[-]  fluctuates to represent market demand - dependent on above as storage
[-]  affected by passenger satisfaction - too complex for the value it would provide to game play

This will not get done.


Filter anonymous user on the backend

When getting all the users, the anonymous user is ignored.

Thanks @hdurix, I merge it.


Change ExeTera Notebook

Codecov Report

Merging #13 (6a13060) into master (4d0b202) will not change coverage.
The diff coverage is n/a.

@@           Coverage Diff           @@
##           master      #13   +/-   ##
=======================================
  Coverage   92.11%   92.11%
=======================================
  Files          17       17
  Lines         431      431
=======================================
  Hits          397      397
  Misses         34       34

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This app only works on WiFi.

I'm not sure if this is a problem specific to my phone, but whenever I try to run your app with my data connection I get the following error: "Unable to load feed. HTTP Error 500 Internal Server Error".
Is this expected behaviour?

Certainly not. It should work on any type of connection.
That's so bizarre. And it works fine on WiFi, you say?

Yup. I only noticed the problem when I was between networks and tried to load it up. To confirm I disabled WiFi when I was back home and the same error message showed up.

Well...I know that they've banned some IP addresses; perhaps they've done that a bit overzealously. That's my only guess as to what happened here. Theoretically, if you had an iPhone or an Android phone, it'd still be broken, but there's not really a way to test that.
I wish I could help, but there's nothing I can do here.

Alright. Thanks

I believe I am having the same issue


GeneralPrinter is slow

It takes almost 1min on my m1 machine to generate only 7k loc: https://github.com/Gnimuc/ClangCompiler.jl/blob/main/lib/17/LibClangEx.jl
whereas, the codegen process only takes seconds...

Anecdotally, I don't think it's ever taken that long to generate the CImGui.jl bindings, which are 14.5k LOC :thinking: Is it just TTFX? Or the printing itself really being slow?

The LOC of the generated file may not be a good metric because the number of nodes/symbols can be way larger.

I had something similar trying to wrap the win32 API, it took very long but only when I had a lot of entries in printer_blacklist. I then realized it was mostly spent compiling regular expressions, which should be fixed in #518. Could it be what made the printing case so slow here?


Update commons-io to 2.15.1

About this PR
📦 Updates commons-io:commons-io from 2.15.0 to 2.15.1
Usage
✅ Please merge!
I'll automatically update this PR to resolve conflicts as long as you don't change it yourself.
If you'd like to skip this version, you can just close this PR. If you have any feedback, just mention me in the comments below.
Configure Scala Steward for your repository with a .scala-steward.conf file.
Have a fantastic day writing Scala!

⚙ Adjust future updates
Add this to your .scala-steward.conf file to ignore future updates of this dependency:
updates.ignore = [ { groupId = "commons-io", artifactId = "commons-io" } ]

Or, add this to slow down future updates of this dependency:
dependencyOverrides = [{
  pullRequests = { frequency = "30 days" },
  dependency = { groupId = "commons-io", artifactId = "commons-io" }
}]

labels: library-update, early-semver-patch, semver-spec-patch, commit-count:1

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

Comparison is base (acc3840) 78.82% compared to head (1d35b58) 78.83%.

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Additional details and impacted files
@@           Coverage Diff           @@
##             main    #2791   +/-   ##
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  Coverage   78.82%   78.83%
=======================================
  Files         466      466
  Lines       15923    15921    -2
  Branches     2557     2575   +18
=======================================
- Hits        12552    12551    -1
+ Misses       3371     3370    -1

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how to enable max power?

heya good day! great job on getting a application going to interface with the cooler.\
but how can i get it to run at max power without humidity regulation and such? i want to test this on some external hardware and just run some tests in general.
also i thought these TEC's ran at about15 volts for max power and kinda assumed the pcb stepped that up to 15v.
i have a coolermaster ml360 here that i got torn down to parts.

Hey, thanks for the kind words :)

but how can i get it to run at max power without humidity regulation and such?

As far as i know there is no true full power mode supported by these coolers. You can get it to run at 100% in pretty much any realistic use case by setting the target offset to -30.

also i thought these TEC's ran at about15 volts for max power and kinda assumed the pcb stepped that up to 15v.

The TEC is powered by the 0-12V from the 6pin connector. The controller PCB can only down step the voltage, not increase it. In theory it might be possible to input 15V at the 6pin to get it to run the TEC at up to 15V, but i have not tested that and have no idea if it would work or damage something.


WARNING:tensorflow:Entity <function _CopyToDeviceDataset.init.._init_func at 0x7fadaffa7d90> could not be transformed and will be executed as-is.

The full error message:
WARNING:tensorflow:Entity <function _CopyToDeviceDataset.__init__.<locals>._init_func at 0x7f8069decd90> could not be transformed and will be executed as-is. Please report this to the AutoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: Bad argument number for Name: 3, expecting 4
WARNING:tensorflow:Entity <function _CopyToDeviceDataset.__init__.<locals>._remote_init_func at 0x7f8068094268> could not be transformed and will be executed as-is. Please report this to the AutoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: Bad argument number for Name: 3, expecting 4
WARNING:tensorflow:Entity <function _CopyToDeviceDataset.__init__.<locals>._next_func at 0x7f80680949d8> could not be transformed and will be executed as-is. Please report this to the AutoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: Bad argument number for Name: 3, expecting 4
WARNING:tensorflow:Entity <function _CopyToDeviceDataset.__init__.<locals>._remote_next_func at 0x7f7df0609158> could not be transformed and will be executed as-is. Please report this to the AutoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: Bad argument number for Name: 3, expecting 4
WARNING:tensorflow:Entity <function _CopyToDeviceDataset.__init__.<locals>._finalize_func at 0x7f7df0609bf8> could not be transformed and will be executed as-is. Please report this to the AutoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: Bad argument number for Name: 3, expecting 4
WARNING:tensorflow:Entity <function _CopyToDeviceDataset.__init__.<locals>._remote_finalize_func at 0x7f7df0609ea0> could not be transformed and will be executed as-is. Please report this to the AutoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: Bad argument number for Name: 3, expecting 4

There are also logs for other function names. The full list:

_init_func
_remote_init_func
_next_func
_remote_next_func
_finalize_func
_remote_finalize_func

As a workaround, I can comment out this part of my data set transformation code:
    dataset_training = dataset_training.apply(
        transformation_func=tf.data.experimental.prefetch_to_device(
            device='/gpu:0',
            buffer_size=1,
        )
    )

This makes all warnings disappear from the log.

@Bengt this might be caused by https://github.com/tensorflow/autograph/issues/1. Could you try to see if running this fixes it:
pip install --user gast==0.2.2

Hi, @mdanatg! Thanks for the quick reply. Yes, downgrading gast actually solved my issue. I thought I had done that already, but I didn't. Prefetching to a device works now and actually gave me a measurable speedup.
The documentation states that "this transformation must be the final dataset in the input pipeline." I use two GPUs and thus call the map twice per dataset with the device parameter set to each GPU once. Is this the correct usage?
    for device in ('/gpu:0', '/gpu:1'):
        dataset_training = dataset_training.apply(
            transformation_func=tf.data.experimental.prefetch_to_device(
                device=device, buffer_size=tf.data.experimental.AUTOTUNE,
            )
        )
        dataset_validation = dataset_validation.apply(
            transformation_func=tf.data.experimental.prefetch_to_device(
                device=device, buffer_size=tf.data.experimental.AUTOTUNE,
            )
        )
        dataset_testing = dataset_testing.apply(
            transformation_func=tf.data.experimental.prefetch_to_device(
                device=device, buffer_size=tf.data.experimental.AUTOTUNE,
            )
        )

@jsimsa for the dataset transformation question
@Bengt good to hear! We're working on permanently fixing that in TF 2.2.

Regarding your tf.data usage, you program will create separate instances of the dataset to feed each GPU. Is that your intention?
If not, I recommend that you take a look at tf.distribute.MirroredStrategy, which can be used to create a single instance of the dataset and prefetch its data to the GPU.

Thanks for the advice,  @jsimsa! I do not mind fetch the whole dataset to all GPUs since my samples are small and VRAM thus plenty. Yes, I already use the MirroredStrategy to create the model. However, I am affected by a bug with TensorFlow, where it does not work, but prefetch_to_device does: https://github.com/tensorflow/tensorflow/issues/28782

That bug should be fixed in TF 2.1 which was released on January 8th. Could you try with the latest version?

Yes, I can use tensorflow-rocm==2.1.0-rc1 from PyPI, that solves this issue and I run into this one:
https://github.com/tensorflow/tensorflow/issues/35100
https://github.com/tensorflow/tensorflow/issues/24570
I guess I will have to wait at least for the final 2.1 for a proper fix.

For reference, using the broken prefetch (at 14 seconds per epoch) like this is about 14 times slower than prefetch_to_device (at 1 seconds per epoch) for me:
    dataset_training = dataset_training.prefetch\
        (buffer_size=tf.data.experimental.AUTOTUNE)
    dataset_validation = dataset_validation.prefetch\
        (buffer_size=tf.data.experimental.AUTOTUNE)

The GeneratorDataset warning can be safely ignored. Unfortunately, it looks like my fix (https://github.com/tensorflow/tensorflow/commit/b6edd34c5858ab0ab4380da774e7e2fd81a92da0) that silences the warning didn't make it into TF 2.1.


unable to preview a re-usable widget (shows the oh snap error)

https://studio.ensembleui.com/app/541d7525-31f7-4c6d-9f06-74fb07c2cacc/widget/zCcYmFP4udOS6KclpmCM
@amin-nas not sure who to assign it to, starting with you, feel free to re-assign

Seems to be from flutter side. @vinothvino42 - please take a look.

@amin-nas  @kmahmood74  It is fixed in this PR #578


par(xpd=TRUE) was in the wrong place

par(xpd=TRUE) was being set in draw_legend, but it was outside of the logic that checked if the legend was going to be drawn or not. The par reset was inside that logic so if you did not call legend(), xpd was never reset. Obviously we still need to revisit the problems with changing par here, but this fixes the immediate bug

Was this PR intended to go from your fork to mine? or to USGS-R?

I guess it would make sense to go to mine, since I still have the PR open....

Yep - that was on purpose!


(patterns) DRAFT

DRAFT, do not merge.

All of these are now in individual pull requests. Closing.


Restructure CubeServer branches to avoid beta code in production

New suggested workflow:

Changes are made in their own branches in response to issues
PR's are submitted to merge these into a development branch develop
For each release, a PR updates the version number and merges changes from develop into main

Thus, main will be identical to the latest release.

develop is ahead by f38eb8abe4bb267e00833e6dfb85dca30da36de8
merging main into develop...


Exposing kubelet garbage collection threshold via variables

📲 What
Exposing the kubelet garbage collection threshold settings via variables
🤔 Why
We keep getting Disk Pressure issues on our EKS node due as the pod images take a lot of space. With the default setting kubelet does the garbage collection when disk usage reaches 85% which might be quite high. So we want to reduce this threshold limit.
🛠 How
More in-depth discussion of the change or implementation.
👀 Evidence

🕵 How to test
We might get the kubelet logs from nodes but not sure if we will be able to confirm at what disk percent it triggered garbage collection.
[ ] Documentation has been updated to reflect the changes?
[ ] Passing all automated tests, including a successful deployment?
[ ] Passing any exploratory testing?
[ ] Rebased/merged with latest changes from development and re-tested?
[ ] Meeting the Coding Standards?

Are the default values you've specified here the default values for clusters if it's not specified?

Are the default values you've specified here the default values for clusters if it's not specified?

yup


Can we disable the italic text?

Hello, thanks for sharing the color-scheme. I love it.
Is there any way to disable the italics?
The font I'm using (Victor Mono) does not have good italic fonts, and so the code becomes difficult to read.
If there was any configuration option to disable the italics, it would be helpful.
Thanks!

Hi @aerosayan,
I've pushed new options, get the newest version of komau.vim and try these options 🥂
" Disable italic, enable by default
let g:komau_italic=0
" Disable bold, enable by default
let g:komau_bold=0

@ntk148v Thanks! It worked well!

@ntk148v Also, the red accent color you used, is really nice!
I modified the colorscheme little bit, and used it for the functions.


bug(mat-checkbox): noop clickAction prevents keyboard click event

Reproduction
noop clickAction prevents keyboard click event but doesn't prevent mouse events. If a click is done with the mouse, the handler is called.
https://stackblitz.com/edit/mat-checkbox-clickaction
Steps to reproduce:

press SPACE when focusing checkbox

Expected Behavior
Should call onClick() method (print 'test' in console)
Actual Behavior
click method is not called.
Environment

Angular: 9.1.1
CDK/Material: 9.2.4
Browser(s): Chrome
Operating System (e.g. Windows, macOS, Ubuntu): Windows

This is working as expected. Setting the click to noop disables the native checkbox behavior, but it doesn't change any listeners that you add in your application (in this case your click handler). The fact that pressing space on a checkbox triggers a click event is part of the native checkbox behavior that you're disabling with 'noop'.

the bug is that it doesn't trigger a click event.

Then why is that click event still works on some events (click or touch) and not on SPACE? It's a weird behavior when you can focus the checkbox but events don't bubble up.
What I expect when using noop is that the behavior of MatCheckbox is noop, not the click event.
As stated in the doc:
noop
Do not change the checked value or indeterminate value. Developers have the power to implement customized click actions.
I can't fully implement custom click event if keyboard events are disabled.

You would need to manually had a keyboard event listener. The fact that pressing space emits a "click" event is a special behavior of the underlying native <input type="checkbox">; other DOM elements don't emit click events when you press space on them. There's no way to preventDefault on the native checkbox toggling without also preventing the space-key-emits-click behavior.

button, radio also emit click event with space.
I didn't even realize with default mat-checkbox the keyboard click event is still lost.

Maybe there's a way to skip event.stopPropagation() for keyboard clicks, since it's there to prevent a double mouse click on label.

To me it also looks like a bug rather than a feature, since it effectively prevents using noop. (with noop my checkbox becomes less accessible)
From the comment in the component code I understand that the whole thing with stopPropagating is to prevent double click events.
Maybe a better approach would be to allow propagation of "click" event from the visually hidden input, but stop propagating the one originated from the wrapping label? Would such an approach also prevent double event while being better resembling the native checkbox behavior?

@amakhrov "change" event would mean the value was updated, which it isn't. In this case, they use stopPropagation() to cancel the double mouse click event on label + checkbox. IMO it's really weird/bug that it also cancels the single "keyboard" click event.


My PC can't open Unity Studio

Is this work with window XP? I can't open it and it doesn't even say what error is it.
https://imgur.com/aq0JGb0.png
My PC have framework 4 and C++ 2012. I read readme and it say required 2013 and 2015, but my sister PC is wondow 7, have framework 4 and only C++ 2008 but still can open it.

Window XP is too old, I don't have to think about whether UnityStudio can run on XP at all.


ARROW-3964: [Go] show input data in CSV reader examples

oops, sorry @c-bata, I didn't see https://github.com/apache/arrow/pull/3131 before crafting this PR...


Error dialing Google

Problem
Executing terraform plan or terraform apply results in the following error:

Error: dialing: google: could not find default credentials. See https://developers.google.com/accounts/docs/application-default-credentials for more information.
on main.tf line 18, in provider "cdap":
18: provider "cdap" {

In the example code below, removing the cdap resource prevents the script from failing and builds the data fusion instance so there is no issue with the google provider configuration.
Version
Terraform v0.12.24

provider.cdap v0.5.0
provider.google-beta v3.22.0

Minimum Code To Reproduce
provider "google-beta" {
  credentials = "<credentials>"
  project     = "<project-id>"
  region      = "us-west1"
}

resource "google_data_fusion_instance" "instance" {
  provider = google-beta
  name     = "example"
  region   = "us-west1"
  type     = "BASIC"
}

data "google_client_config" "current" {
  provider = google-beta
}

provider "cdap" {
  host  = "${google_data_fusion_instance.instance.service_endpoint}/api/"
  token = data.google_client_config.current.access_token
}

resource "cdap_namespace" "dev3" {
  provider = cdap
  name     = "dev"
}

Did you try removing the cdap provider and resource but keeping the google_client_config data source? It seems that is the one that's failing to find credentials.
If you're running locally try running gcloud auth application-default login.

Hi thanks for your help. Yes, as I mentioned in the problem statement, if I remove the cdap resource it executes successfully and creates the data fusion instance. I'm trying to run it locally and from a docker container. Neither one is working.

This is unusual because in the code we don't search for the default credentials and instead just rely on the token being passed in.
What happens if you use this resource instead:
resource "local_file" "foo" {
    content     = data.google_client_config.current.access_token
    filename = "/tmp/token"
}

Does /tmp/token get populated correctly?

It does.

Thanks, I did a bit of digging and believe I found the cause. Sent #82

I released v0.6.0. Please give it a try

Wow! I step into a meeting and come back to find the problem is solved! Thanks so much. Yes, v0.6.0 is working for me now.

Glad to hear it! Hope you find the provider useful.


Tables with names beginning with "q" and indexes generate invalid code

"q.Scan undefined (type Queue has no field or method Scan)"
If the table name is such that shortname is "q" that clashes with the use of "q" to hold the result of db.Query in code generated from postgres.query.go.tpl.
(Changing "q" to "_q" in a local copy of the template used with --template-path works around it easily enough.)

Yeah, oops. Will fix.

An update: this is actually a fairly difficult thing to do, in many ways, as I'm not happy with just 'renaming' every variable used within scopes to have an underscore (or similar), as I want the generated code to look like it was written by a person. I have a solution that is roughly 50% complete, and I am hoping to get this pushed out soon.

BTW -- I apologize this fix took so long to come out. It required a lot of attention and I did not have much time to work on this over the last month.  I'd appreciate feedback on this, if you have it. Thanks!


Dynamic runners scaling

Ensure functions can set some cap for the number of executing runners - globally in the instance.

Runners are self-regulated.


Stacked area plot for Icecup, extra denominator

In some cases we may want to plot dice that effectively have a denominator greater than the sum of the quantities, i.e. there is some amount of "missing" quantity that was filtered out. I'm not sure yet whether there are use cases for this outside of plotting.
Package-side options:

A variant of reroll() / filter() that removes outcomes but not their contribution to the denominator.

A variant of the Reroll object that does the same.

A variant of reroll() / filter() that also returns the removed quantity.

The trouble is there's not really been use for this so far, and it would touch a large portion of the codebase.
Icecup-side options:

A separate denominator or filter argument for output() and area().
Expect outcomes to area to be (actual_outcome, filter).
Global function similar to matplotlib xlim to set the range.

I went with the limit approach for Icecup, since I think it will be rare to want to exclude outcomes in the middle, and at the same time choosing a side to exclude from is beneficial for plotting the CDF / SF. This approach also dodges the normalization question.
There's still an issue with e.g. this situation. Unfortunately solving this would would require allowing normalization to be broken.