[Bug]: Empty prompt kills vllm server (AsyncEngineDeadError: Background loop is stopped.)

Your current environment
python3 collect_env.py
Collecting environment information...
PyTorch version: 2.3.1+cu121
Is debug build: False
CUDA used to build PyTorch: 12.1
ROCM used to build PyTorch: N/A

OS: Ubuntu 20.04.6 LTS (x86_64)
GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.2) 9.4.0
Clang version: Could not collect
CMake version: version 3.30.1
Libc version: glibc-2.31

Python version: 3.10.14 (main, Apr  6 2024, 18:45:05) [GCC 9.4.0] (64-bit runtime)
Python platform: Linux-<IP_ADDRESS>-4.cm2-x86_64-with-glibc2.31
Is CUDA available: True
CUDA runtime version: Could not collect
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: GPU 0: NVIDIA A100-SXM4-80GB
Nvidia driver version: 525.85.12
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

CPU:
Architecture:                       x86_64
CPU op-mode(s):                     32-bit, 64-bit
Byte Order:                         Little Endian
Address sizes:                      48 bits physical, 48 bits virtual
CPU(s):                             256
On-line CPU(s) list:                0-255
Thread(s) per core:                 2
Core(s) per socket:                 64
Socket(s):                          2
NUMA node(s):                       8
Vendor ID:                          AuthenticAMD
CPU family:                         25
Model:                              1
Model name:                         AMD EPYC 7763 64-Core Processor
Stepping:                           1
Frequency boost:                    enabled
CPU MHz:                            3096.040
CPU max MHz:                        3529.0520
CPU min MHz:                        1500.0000
BogoMIPS:                           4900.05
Virtualization:                     AMD-V
L1d cache:                          4 MiB
L1i cache:                          4 MiB
L2 cache:                           64 MiB
L3 cache:                           512 MiB
NUMA node0 CPU(s):                  0-15,128-143
NUMA node1 CPU(s):                  16-31,144-159
NUMA node2 CPU(s):                  32-47,160-175
NUMA node3 CPU(s):                  48-63,176-191
NUMA node4 CPU(s):                  64-79,192-207
NUMA node5 CPU(s):                  80-95,208-223
NUMA node6 CPU(s):                  96-111,224-239
NUMA node7 CPU(s):                  112-127,240-255
Vulnerability Gather data sampling: Not affected
Vulnerability Itlb multihit:        Not affected
Vulnerability L1tf:                 Not affected
Vulnerability Mds:                  Not affected
Vulnerability Meltdown:             Not affected
Vulnerability Mmio stale data:      Not affected
Vulnerability Retbleed:             Not affected
Vulnerability Spec rstack overflow: Mitigation; safe RET, no microcode
Vulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl and seccomp
Vulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:           Mitigation; Retpolines, IBPB conditional, IBRS_FW, STIBP always-on, RSB filling, PBRSB-eIBRS Not affected
Vulnerability Srbds:                Not affected
Vulnerability Tsx async abort:      Not affected
Flags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 invpcid_single hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 invpcid cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload vgif v_spec_ctrl umip pku ospke vaes vpclmulqdq rdpid overflow_recov succor smca

Versions of relevant libraries:
[pip3] flashinfer==0.0.9+cu121torch2.3
[pip3] numpy==1.26.4
[pip3] nvidia-nccl-cu12==2.20.5
[pip3] pyzmq==26.0.3
[pip3] torch==2.3.1
[pip3] torchvision==0.18.1
[pip3] transformers==4.43.2
[pip3] triton==2.3.1
[conda] Could not collect
ROCM Version: Could not collect
Neuron SDK Version: N/A
vLLM Version: 0.5.3.post1
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled
GPU Topology:
GPU0    CPU Affinity    NUMA Affinity
GPU0     X      48-63,176-191   3

Legend:

  X    = Self
  SYS  = Connection traversing PCIe as well as the SMP interconnect between NUMA nodes (e.g., QPI/UPI)
  NODE = Connection traversing PCIe as well as the interconnect between PCIe Host Bridges within a NUMA node
  PHB  = Connection traversing PCIe as well as a PCIe Host Bridge (typically the CPU)
  PXB  = Connection traversing multiple PCIe bridges (without traversing the PCIe Host Bridge)
  PIX  = Connection traversing at most a single PCIe bridge
  NV#  = Connection traversing a bonded set of # NVLinks

🐛 Describe the bug
Spin up the vllm server in a pod using the vllm base image (vllm/vllm-openai:v0.5.3.post1)
python3 -m vllm.entrypoints.openai.api_server --model $MODEL_PATH --port 8000 --trust-remote-code

where $MODEL_PATH points to some model. I've tried gpt2-medium and Meta-Llama-3-8B.
Generation works fine, but if you pass in an empty prompt, it immediately kills the server and is unrecoverable:
curl -X 'POST' \
  'http://localhost:8080/v1/completions' \
  -H 'accept: application/json' \
  -H 'Content-Type: application/json' \
  -d '{
  "model": "/models/gpt2-medium",
  "prompt": "",
  "max_tokens": 50,
  "temperature": 0.9,
  "top_p": 1
}'

INFO 08-07 20:13:55 logger.py:36] Received request cmpl-662a1639b80b47539cc099bdf6347cc0-0: prompt: '', params: SamplingParams(n=1, best_of=1, presence_penalty=0.0, frequency_penalty=0.0, repetition_penalty=1.0, temperature=0.9, top_p=0.9, top_k=20, min_p=0.0, seed=None, use_beam_search=False, length_penalty=1.0, early_stopping=False, stop=[], stop_token_ids=[], include_stop_str_in_output=False, ignore_eos=False, max_tokens=100, min_tokens=0, logprobs=None, prompt_logprobs=None, skip_special_tokens=True, spaces_between_special_tokens=True, truncate_prompt_tokens=None), prompt_token_ids: [], lora_request: None, prompt_adapter_request: None.
INFO 08-07 20:13:55 async_llm_engine.py:173] Added request cmpl-662a1639b80b47539cc099bdf6347cc0-0.
ERROR 08-07 20:13:55 async_llm_engine.py:56] Engine background task failed
ERROR 08-07 20:13:55 async_llm_engine.py:56] Traceback (most recent call last):
ERROR 08-07 20:13:55 async_llm_engine.py:56]   File "/usr/local/lib/python3.10/dist-packages/vllm/engine/async_llm_engine.py", line 46, in _log_task_completion
ERROR 08-07 20:13:55 async_llm_engine.py:56]     return_value = task.result()
ERROR 08-07 20:13:55 async_llm_engine.py:56]   File "/usr/local/lib/python3.10/dist-packages/vllm/engine/async_llm_engine.py", line 637, in run_engine_loop
ERROR 08-07 20:13:55 async_llm_engine.py:56]     result = task.result()
ERROR 08-07 20:13:55 async_llm_engine.py:56]   File "/usr/local/lib/python3.10/dist-packages/vllm/engine/async_llm_engine.py", line 580, in engine_step
ERROR 08-07 20:13:55 async_llm_engine.py:56]     request_outputs = await self.engine.step_async(virtual_engine)
ERROR 08-07 20:13:55 async_llm_engine.py:56]   File "/usr/local/lib/python3.10/dist-packages/vllm/engine/async_llm_engine.py", line 238, in step_async
ERROR 08-07 20:13:55 async_llm_engine.py:56]     virtual_engine].schedule()
ERROR 08-07 20:13:55 async_llm_engine.py:56]   File "/usr/local/lib/python3.10/dist-packages/vllm/core/scheduler.py", line 978, in schedule
ERROR 08-07 20:13:55 async_llm_engine.py:56]     scheduler_outputs = self._schedule()
ERROR 08-07 20:13:55 async_llm_engine.py:56]   File "/usr/local/lib/python3.10/dist-packages/vllm/core/scheduler.py", line 953, in _schedule
ERROR 08-07 20:13:55 async_llm_engine.py:56]     return self._schedule_default()
ERROR 08-07 20:13:55 async_llm_engine.py:56]   File "/usr/local/lib/python3.10/dist-packages/vllm/core/scheduler.py", line 795, in _schedule_default
ERROR 08-07 20:13:55 async_llm_engine.py:56]     remaining_waiting, prefills = self._schedule_prefills(
ERROR 08-07 20:13:55 async_llm_engine.py:56]   File "/usr/local/lib/python3.10/dist-packages/vllm/core/scheduler.py", line 690, in _schedule_prefills
ERROR 08-07 20:13:55 async_llm_engine.py:56]     num_new_tokens = self._get_num_new_tokens(seq_group,
ERROR 08-07 20:13:55 async_llm_engine.py:56]   File "/usr/local/lib/python3.10/dist-packages/vllm/core/scheduler.py", line 1232, in _get_num_new_tokens
ERROR 08-07 20:13:55 async_llm_engine.py:56]     assert num_new_tokens > 0
ERROR 08-07 20:13:55 async_llm_engine.py:56] AssertionError
Exception in callback functools.partial(<function _log_task_completion at 0x7b3f96884790>, error_callback=<bound method AsyncLLMEngine._error_callback of <vllm.engine.async_llm_engine.AsyncLLMEngine object at 0x7b3f7e2f7be0>>)
INFO 08-07 20:13:55 async_llm_engine.py:180] Aborted request cmpl-662a1639b80b47539cc099bdf6347cc0-0.
handle: <Handle functools.partial(<function _log_task_completion at 0x7b3f96884790>, error_callback=<bound method AsyncLLMEngine._error_callback of <vllm.engine.async_llm_engine.AsyncLLMEngine object at 0x7b3f7e2f7be0>>)>
Traceback (most recent call last):
  File "/usr/local/lib/python3.10/dist-packages/vllm/engine/async_llm_engine.py", line 46, in _log_task_completion
    return_value = task.result()
  File "/usr/local/lib/python3.10/dist-packages/vllm/engine/async_llm_engine.py", line 637, in run_engine_loop
    result = task.result()
  File "/usr/local/lib/python3.10/dist-packages/vllm/engine/async_llm_engine.py", line 580, in engine_step
    request_outputs = await self.engine.step_async(virtual_engine)
  File "/usr/local/lib/python3.10/dist-packages/vllm/engine/async_llm_engine.py", line 238, in step_async
    virtual_engine].schedule()
  File "/usr/local/lib/python3.10/dist-packages/vllm/core/scheduler.py", line 978, in schedule
    scheduler_outputs = self._schedule()
  File "/usr/local/lib/python3.10/dist-packages/vllm/core/scheduler.py", line 953, in _schedule
    return self._schedule_default()
  File "/usr/local/lib/python3.10/dist-packages/vllm/core/scheduler.py", line 795, in _schedule_default
    remaining_waiting, prefills = self._schedule_prefills(
  File "/usr/local/lib/python3.10/dist-packages/vllm/core/scheduler.py", line 690, in _schedule_prefills
    num_new_tokens = self._get_num_new_tokens(seq_group,
INFO:     <IP_ADDRESS>:58497 - "POST /v1/completions HTTP/1.1" 500 Internal Server Error
  File "/usr/local/lib/python3.10/dist-packages/vllm/core/scheduler.py", line 1232, in _get_num_new_tokens
    assert num_new_tokens > 0
AssertionError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "uvloop/cbhandles.pyx", line 63, in uvloop.loop.Handle._run
  File "/usr/local/lib/python3.10/dist-packages/vllm/engine/async_llm_engine.py", line 58, in _log_task_completion
    raise AsyncEngineDeadError(
vllm.engine.async_llm_engine.AsyncEngineDeadError: Task finished unexpectedly. This should never happen! Please open an issue on Github. See stack trace above for theactual cause.
ERROR:    Exception in ASGI application
Traceback (most recent call last):
  File "/usr/local/lib/python3.10/dist-packages/uvicorn/protocols/http/httptools_impl.py", line 399, in run_asgi
    result = await app(  # type: ignore[func-returns-value]
  File "/usr/local/lib/python3.10/dist-packages/uvicorn/middleware/proxy_headers.py", line 70, in __call__
    return await self.app(scope, receive, send)
  File "/usr/local/lib/python3.10/dist-packages/fastapi/applications.py", line 1054, in __call__
    await super().__call__(scope, receive, send)
  File "/usr/local/lib/python3.10/dist-packages/starlette/applications.py", line 123, in __call__
    await self.middleware_stack(scope, receive, send)
  File "/usr/local/lib/python3.10/dist-packages/starlette/middleware/errors.py", line 186, in __call__
    raise exc
  File "/usr/local/lib/python3.10/dist-packages/starlette/middleware/errors.py", line 164, in __call__
    await self.app(scope, receive, _send)
  File "/usr/local/lib/python3.10/dist-packages/starlette/middleware/cors.py", line 85, in __call__
    await self.app(scope, receive, send)
  File "/usr/local/lib/python3.10/dist-packages/starlette/middleware/exceptions.py", line 65, in __call__
    await wrap_app_handling_exceptions(self.app, conn)(scope, receive, send)
  File "/usr/local/lib/python3.10/dist-packages/starlette/_exception_handler.py", line 64, in wrapped_app
    raise exc
  File "/usr/local/lib/python3.10/dist-packages/starlette/_exception_handler.py", line 53, in wrapped_app
    await app(scope, receive, sender)
  File "/usr/local/lib/python3.10/dist-packages/starlette/routing.py", line 756, in __call__
    await self.middleware_stack(scope, receive, send)
  File "/usr/local/lib/python3.10/dist-packages/starlette/routing.py", line 776, in app
    await route.handle(scope, receive, send)
  File "/usr/local/lib/python3.10/dist-packages/starlette/routing.py", line 297, in handle
    await self.app(scope, receive, send)
  File "/usr/local/lib/python3.10/dist-packages/starlette/routing.py", line 77, in app
    await wrap_app_handling_exceptions(app, request)(scope, receive, send)
  File "/usr/local/lib/python3.10/dist-packages/starlette/_exception_handler.py", line 64, in wrapped_app
    raise exc
  File "/usr/local/lib/python3.10/dist-packages/starlette/_exception_handler.py", line 53, in wrapped_app
    await app(scope, receive, sender)
  File "/usr/local/lib/python3.10/dist-packages/starlette/routing.py", line 72, in app
    response = await func(request)
  File "/usr/local/lib/python3.10/dist-packages/fastapi/routing.py", line 278, in app
    raw_response = await run_endpoint_function(
  File "/usr/local/lib/python3.10/dist-packages/fastapi/routing.py", line 191, in run_endpoint_function
    return await dependant.call(**values)
  File "/usr/local/lib/python3.10/dist-packages/vllm/entrypoints/openai/api_server.py", line 144, in create_completion
    generator = await openai_serving_completion.create_completion(
  File "/usr/local/lib/python3.10/dist-packages/vllm/entrypoints/openai/serving_completion.py", line 175, in create_completion
    async for i, res in result_generator:
  File "/usr/local/lib/python3.10/dist-packages/vllm/utils.py", line 329, in consumer
    raise e
  File "/usr/local/lib/python3.10/dist-packages/vllm/utils.py", line 320, in consumer
    raise item
  File "/usr/local/lib/python3.10/dist-packages/vllm/utils.py", line 304, in producer
    async for item in iterator:
  File "/usr/local/lib/python3.10/dist-packages/vllm/engine/async_llm_engine.py", line 772, in generate
    async for output in self._process_request(
  File "/usr/local/lib/python3.10/dist-packages/vllm/engine/async_llm_engine.py", line 888, in _process_request
    raise e
  File "/usr/local/lib/python3.10/dist-packages/vllm/engine/async_llm_engine.py", line 884, in _process_request
    async for request_output in stream:
  File "/usr/local/lib/python3.10/dist-packages/vllm/engine/async_llm_engine.py", line 93, in __anext__
    raise result
  File "/usr/local/lib/python3.10/dist-packages/vllm/engine/async_llm_engine.py", line 46, in _log_task_completion
    return_value = task.result()
  File "/usr/local/lib/python3.10/dist-packages/vllm/engine/async_llm_engine.py", line 637, in run_engine_loop
    result = task.result()
  File "/usr/local/lib/python3.10/dist-packages/vllm/engine/async_llm_engine.py", line 580, in engine_step
    request_outputs = await self.engine.step_async(virtual_engine)
  File "/usr/local/lib/python3.10/dist-packages/vllm/engine/async_llm_engine.py", line 238, in step_async
    virtual_engine].schedule()
  File "/usr/local/lib/python3.10/dist-packages/vllm/core/scheduler.py", line 978, in schedule
    scheduler_outputs = self._schedule()
  File "/usr/local/lib/python3.10/dist-packages/vllm/core/scheduler.py", line 953, in _schedule
    return self._schedule_default()
  File "/usr/local/lib/python3.10/dist-packages/vllm/core/scheduler.py", line 795, in _schedule_default
    remaining_waiting, prefills = self._schedule_prefills(
  File "/usr/local/lib/python3.10/dist-packages/vllm/core/scheduler.py", line 690, in _schedule_prefills
    num_new_tokens = self._get_num_new_tokens(seq_group,
  File "/usr/local/lib/python3.10/dist-packages/vllm/core/scheduler.py", line 1232, in _get_num_new_tokens
    assert num_new_tokens > 0
AssertionError
INFO 08-07 20:13:57 metrics.py:396] Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 0.0 tokens/s, Running: 0 reqs, Swapped: 0 reqs, Pending: 1 reqs, GPU KV cache usage: 0.0%, CPU KV cache usage: 0.0%.
INFO:     <IP_ADDRESS>:43785 - "GET /health HTTP/1.1" 500 Internal Server Error
ERROR:    Exception in ASGI application
Traceback (most recent call last):
  File "/usr/local/lib/python3.10/dist-packages/uvicorn/protocols/http/httptools_impl.py", line 399, in run_asgi
    result = await app(  # type: ignore[func-returns-value]
  File "/usr/local/lib/python3.10/dist-packages/uvicorn/middleware/proxy_headers.py", line 70, in __call__
    return await self.app(scope, receive, send)
  File "/usr/local/lib/python3.10/dist-packages/fastapi/applications.py", line 1054, in __call__
    await super().__call__(scope, receive, send)
  File "/usr/local/lib/python3.10/dist-packages/starlette/applications.py", line 123, in __call__
    await self.middleware_stack(scope, receive, send)
  File "/usr/local/lib/python3.10/dist-packages/starlette/middleware/errors.py", line 186, in __call__
    raise exc
  File "/usr/local/lib/python3.10/dist-packages/starlette/middleware/errors.py", line 164, in __call__
    await self.app(scope, receive, _send)
  File "/usr/local/lib/python3.10/dist-packages/starlette/middleware/cors.py", line 85, in __call__
    await self.app(scope, receive, send)
  File "/usr/local/lib/python3.10/dist-packages/starlette/middleware/exceptions.py", line 65, in __call__
    await wrap_app_handling_exceptions(self.app, conn)(scope, receive, send)
  File "/usr/local/lib/python3.10/dist-packages/starlette/_exception_handler.py", line 64, in wrapped_app
    raise exc
  File "/usr/local/lib/python3.10/dist-packages/starlette/_exception_handler.py", line 53, in wrapped_app
    await app(scope, receive, sender)
  File "/usr/local/lib/python3.10/dist-packages/starlette/routing.py", line 756, in __call__
    await self.middleware_stack(scope, receive, send)
  File "/usr/local/lib/python3.10/dist-packages/starlette/routing.py", line 776, in app
    await route.handle(scope, receive, send)
  File "/usr/local/lib/python3.10/dist-packages/starlette/routing.py", line 297, in handle
    await self.app(scope, receive, send)
  File "/usr/local/lib/python3.10/dist-packages/starlette/routing.py", line 77, in app
    await wrap_app_handling_exceptions(app, request)(scope, receive, send)
  File "/usr/local/lib/python3.10/dist-packages/starlette/_exception_handler.py", line 64, in wrapped_app
    raise exc
  File "/usr/local/lib/python3.10/dist-packages/starlette/_exception_handler.py", line 53, in wrapped_app
    await app(scope, receive, sender)
  File "/usr/local/lib/python3.10/dist-packages/starlette/routing.py", line 72, in app
    response = await func(request)
  File "/usr/local/lib/python3.10/dist-packages/fastapi/routing.py", line 278, in app
    raw_response = await run_endpoint_function(
  File "/usr/local/lib/python3.10/dist-packages/fastapi/routing.py", line 191, in run_endpoint_function
    return await dependant.call(**values)
  File "/usr/local/lib/python3.10/dist-packages/vllm/entrypoints/openai/api_server.py", line 88, in health
    await openai_serving_chat.engine.check_health()
  File "/usr/local/lib/python3.10/dist-packages/vllm/engine/async_llm_engine.py", line 950, in check_health
    raise AsyncEngineDeadError("Background loop is stopped.")
vllm.engine.async_llm_engine.AsyncEngineDeadError: Background loop is stopped.

Expected Behavior
If an empty prompt is not allowed, I would expect a 400 invalid input response vs. a 500 that stops the server.

This also happens for the offline LLM entrypoint:
>>> from vllm import LLM
>>> model = LLM("gpt2")
>>> model.generate("")
Processed prompts:   0%|                                                                                | 0/1 [00:00<?, ?it/s, est. speed input: 0.00 toks/s, output: 0.00 toks/s][rank0]: Traceback (most recent call last):
[rank0]:   File "<stdin>", line 1, in <module>
[rank0]:   File "/home/mgoin/code/vllm/vllm/utils.py", line 996, in inner
[rank0]:     return fn(*args, **kwargs)
[rank0]:   File "/home/mgoin/code/vllm/vllm/entrypoints/llm.py", line 339, in generate
[rank0]:     outputs = self._run_engine(use_tqdm=use_tqdm)
[rank0]:   File "/home/mgoin/code/vllm/vllm/entrypoints/llm.py", line 620, in _run_engine
[rank0]:     step_outputs = self.llm_engine.step()
[rank0]:   File "/home/mgoin/code/vllm/vllm/engine/llm_engine.py", line 1287, in step
[rank0]:     0].schedule()
[rank0]:   File "/home/mgoin/code/vllm/vllm/core/scheduler.py", line 963, in schedule
[rank0]:     scheduler_outputs = self._schedule()
[rank0]:   File "/home/mgoin/code/vllm/vllm/core/scheduler.py", line 938, in _schedule
[rank0]:     return self._schedule_default()
[rank0]:   File "/home/mgoin/code/vllm/vllm/core/scheduler.py", line 798, in _schedule_default
[rank0]:     prefills = self._schedule_prefills(budget,
[rank0]:   File "/home/mgoin/code/vllm/vllm/core/scheduler.py", line 696, in _schedule_prefills
[rank0]:     num_new_tokens = self._get_num_new_tokens(seq_group,
[rank0]:   File "/home/mgoin/code/vllm/vllm/core/scheduler.py", line 1234, in _get_num_new_tokens
[rank0]:     assert num_new_tokens > 0
[rank0]: AssertionError

Just curious, I think LLM always starts with a start_of_sentence token? What does empty prompt mean then?

@youkaichao this depends on the tokenizer. I just tested llama 3.1 8b instruct and it doesn't have this issue because it has a BOS token:
>>> from vllm import LLM
>>> model = LLM("meta-llama/Meta-Llama-3.1-8B-Instruct")
>>> model.generate("")
Processed prompts: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00,  7.37it/s, est. speed input: 7.38 toks/s, output: 118.09 toks/s]
[RequestOutput(request_id=0, prompt='', prompt_token_ids=[128000], encoder_prompt=None, encoder_prompt_token_ids=None, prompt_logprobs=None, outputs=[CompletionOutput(index=0, text='Cloud bathroom mirror is designed to bring a fresh perspective to bathroom essentials. Its fog', token_ids=(16440, 15197, 18327, 374, 6319, 311, 4546, 264, 7878, 13356, 311, 15197, 59886, 13, 11699, 31349), cumulative_logprob=None, logprobs=None, finish_reason=length, stop_reason=None)], finished=True, metrics=RequestMetrics(arrival_time=1723074368.5084124, last_token_time=1723074368.5084124, first_scheduled_time=1723074368.5245223, first_token_time=1723074368.5398314, time_in_queue=0.016109943389892578, finished_time=1723074368.6597202), lora_request=None)]

You can see the prompt is empty but the prompt token ids is not prompt='', prompt_token_ids=[128000]

Crashing LLM or the server is not good behavior

agree. we should never let user request crash the engine.

Good catch that this depends on the tokenizer. The models I tested do not have the bos token defined in the tokenizer_config.json.

Same as this: https://github.com/vllm-project/vllm/issues/7632

#7632 was closed after the fix in https://github.com/vllm-project/vllm/pull/7746. This issue can be closed too.

Thanks for ping, closing as resolved


fix: update migration file path for dbdev compatibility

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

Project coverage is 82.73%. Comparing base (b3d2b08) to head (25d324a).

Additional details and impacted files
@@           Coverage Diff           @@
##             main      #19   +/-   ##
=======================================
  Coverage   82.73%   82.73%
=======================================
  Files           3        3
  Lines         388      388
  Branches       70       70
=======================================
  Hits          321      321
  Misses         67       67

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options to watchify

I want to plug in https://github.com/traducer/browserify-livereload but don't see an easy way to get options to watchify.

$ bankai -j [ --plugin browserify-livereload ]

switching out the usual -p flag for --plugin made it "work" on my end.
as far as passing subargs through to the plugin itself, I'm out of luck with this:
$ bankai -j [ --plugin [ browserify-livereload --outfile=tmp.js ] ]

browserify cannot find the plugin [object Object].
should work for a simple no-opt transform/plugin though.

Yeah, we should alias the -p and -t flags to --plugin and --transform
respectively. The browserify JS API fails to understand them. Patch would
be very welcome!
On Thu, May 11, 2017 at 8:45 AM Kasper Lewau<EMAIL_ADDRESS>wrote:

$ bankai -j [ --plugin browserify-livereload ]
switching out the usual -p flag for --plugin made it "work" on my end.
as far as passing subargs through to the plugin itself, I'm out of luck
with this:
$ bankai -j [ --plugin [ browserify-livereload --outfile=tmp.js ] ]
browserify cannot find the plugin [object Object].
should work for a simple no-opt transform/plugin though.
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closing since we don't have cli args anymore in v9. #359 is about using custom plugins in v9. thanks & happy new year! 🎆


ERROR: No inspection system is available for object of type <class 'method'>

 [2020-04-08 14:09:37,442] {{__init__.py:51}} INFO - Using executor CeleryExecutor
webserver_1  | [2020-04-08 14:09:37,442] {{dagbag.py:403}} INFO - Filling up the DagBag from /usr/local/airflow/dags
webserver_1  | Traceback (most recent call last):
webserver_1  |   File "/usr/local/bin/airflow", line 37, in <module>
webserver_1  |     args.func(args)
webserver_1  |   File "/usr/local/lib/python3.7/site-packages/airflow/utils/cli.py", line 75, in wrapper
webserver_1  |     return f(*args, **kwargs)
webserver_1  |   File "/usr/local/lib/python3.7/site-packages/airflow/bin/cli.py", line 900, in webserver
webserver_1  |     app = cached_app_rbac(None) if settings.RBAC else cached_app(None)
webserver_1  |   File "/usr/local/lib/python3.7/site-packages/airflow/www/app.py", line 233, in cached_app
webserver_1  |     app = create_app(config, testing)
webserver_1  |   File "/usr/local/lib/python3.7/site-packages/airflow/www/app.py", line 103, in create_app
webserver_1  |     models.Chart, Session, name="Charts", category="Data Profiling"))
webserver_1  |   File "/usr/local/lib/python3.7/site-packages/flask_admin/contrib/sqla/view.py", line 330, in __init__
webserver_1  |     menu_icon_value=menu_icon_value)
webserver_1  |   File "/usr/local/lib/python3.7/site-packages/flask_admin/model/base.py", line 818, in __init__
webserver_1  |     self._refresh_cache()
webserver_1  |   File "/usr/local/lib/python3.7/site-packages/flask_admin/model/base.py", line 913, in _refresh_cache
webserver_1  |     self._search_supported = self.init_search()
webserver_1  |   File "/usr/local/lib/python3.7/site-packages/flask_admin/contrib/sqla/view.py", line 581, in init_search
webserver_1  |     if tools.is_hybrid_property(self.model, name):
webserver_1  |   File "/usr/local/lib/python3.7/site-packages/flask_admin/contrib/sqla/tools.py", line 209, in is_hybrid_property
webserver_1  |     return last_name in get_hybrid_properties(last_model)
webserver_1  |   File "/usr/local/lib/python3.7/site-packages/flask_admin/contrib/sqla/tools.py", line 190, in get_hybrid_properties
webserver_1  |     for key, prop in inspect(model).all_orm_descriptors.items()
webserver_1  |   File "/usr/local/lib/python3.7/site-packages/sqlalchemy/inspection.py", line 72, in inspect
webserver_1  |     "available for object of type %s" % type_
webserver_1  | sqlalchemy.exc.NoInspectionAvailable: No inspection system is available for object of type <class 'method'>

Found the solution to this is to pin the SQLAlchemy==1.3.15 from https://github.com/apache/airflow/issues/8211
This is recent issue, and I'll keep this issue open for users who might find it.

Good catch @gnomeria!

Found the solution to this is to pin the SQLAlchemy==1.3.15 from apache/airflow#8211
This is recent issue, and I'll keep this issue open for users who might find it.

I have uninstalled SQLAlchemy==1.3.16 then installed SQLAlchemy==1.3.15 as the following:
pip uninstall -y SQLAlchemy
&& pip install SQLAlchemy==1.3.15
It worked well without issues

This was fixed with 1.10.10 via https://github.com/apache/airflow/pull/8230

Where do you specify the correct SQLAlchemy version or the new airflow version where this is fixed?
Can someone post an example of patched Dockerfile or wherever you do the change.

Ok, so extending the Dockerfile to pip uninstall/install the right SQLAlchemy version works.  Can someone post how fix this by specifying the new airflow version where this was fixed?

You can actually just set the new airflow version, like my unmerged pr here:
https://github.com/puckel/docker-airflow/pull/537 based on https://github.com/gnomeria/docker-airflow/tree/bump-airflow-1-10-10

Found the solution to this is to pin the SQLAlchemy==1.3.15 from apache/airflow#8211
This is recent issue, and I'll keep this issue open for users who might find it.

Thanks @gnomeria


Guide to generate informers

I would like to generate a new informer(pod) for my pr to knative/serving but have no clue on the guide to generate those. Would be appreciated for any help regarding to this guide!

I'm not sure what you're looking for; would the generated client in serving work for you:
https://github.com/knative/serving/blob/master/pkg/client/informers/externalversions/serving/v1alpha1/service.go

The stuff under ./pkg/injection/informers/ is mostly hand-rolled copy/pasta while we work on generating the injection logic for out-of-tree types.  For in-tree types we have a guide.
That said, we have one for pods already here: https://github.com/knative/pkg/tree/master/injection/informers/kubeinformers/corev1/pod

Thanks for the follow-up. I found that pod informer is already generated.


Release 3.1.5 not available in maven repository

Probably an issue while publishing last release, it still not available in maven repository: http://repo.maven.apache.org/maven2/com/github/vanroy/spring-data-jest/

Hi @DanielFran , it's fixed. Thanks.

@VanRoy the release is not yet available. Does it take so long usually?

Normally since 16h30 ( CEST ) it's available on maven central : https://repo1.maven.org/maven2/com/github/vanroy/spring-data-jest/3.1.5.RELEASE/
Can you send me your log of your failed download please.

OK, it hapears for me now! Sorry about it... Thanks

Great. Thx.


Make a unified UITableView performBatchUpdates func

A really small PR to make a unified UITableView performBatchUpdates func.
I think we could rely on this API when it is possible:
https://developer.apple.com/documentation/uikit/uitableview/2887515-performbatchupdates

@iKiKi These changes will be included through #298.


[shape_poly] Add shape polymorphism support for jax.nn.one_hot

@voutcn PTAL

I don't have permission to approve it. LGTM.


MG + MIS - Chloride Exposure Database Generation Module Do Multiple Service

This module performs calculations and data saving. It would be better to split it into two separate modules.

Yes you are correct, I separate them in f44c978770eba4675dfa931a8d2ebd225d60bbaa


move pmp tests to src directory

Description

Provide a detailed description of the changes performed by the PR.

As mentioned in #554, the new PMP tests do not follow the directory structure of all other tests. This moves them into a src folder to align with the rest of the test suite.
2 of the rv32 pmp tests were also titled using capital PMP instead of lowercase pmp like all of the other tests (including their rv64 equivalents), so this updates their file name to align with everything else.
Related Issues

Please list all the issues related to this PR. Use NA if no issues exist

Fixes #554
Ratified/Unratified Extensions

[x] Ratified
[ ] Unratified

Thanks for the quick fix.


[HOLD for payment 2023-08-28] [$1000] Profile - Entering country without a diacritic for Côte D'ivoire returns no suggestions

If you haven’t already, check out our contributing guidelines for onboarding and email<EMAIL_ADDRESS>to request to join our Slack channel!

Issue found when executing PR https://github.com/Expensify/App/pull/24140
Action Performed:

Open the app
Go to Settings > Profile > Personal details > Home address > Country
Start entering "cote" or "cote d'Ivoire" without a diacritic

Expected Result:
The suggested country name "Côte d'Ivoire" is displayed
Actual Result:
The suggested country is not displayed, and "no results found" is shown
Workaround:
Unknown
Platforms:

Which of our officially supported platforms is this issue occurring on?

[ ] Android / native
[ ] Android / Chrome
[x] iOS / native
[ ] iOS / Safari
[ ] MacOS / Chrome / Safari
[ ] MacOS / Desktop

Version Number: <IP_ADDRESS>
Reproducible in staging?: Yes
Reproducible in production?: Yes
If this was caught during regression testing, add the test name, ID and link from TestRail:
Email or phone of affected tester (no customers):
Logs: https://stackoverflow.com/c/expensify/questions/4856
Notes/Photos/Videos: Any additional supporting documentation
https://github.com/Expensify/App/assets/78819774/0308fc16-f876-4eb9-a196-c0d60487e523
Expensify/Expensify Issue URL:
Issue reported by: Applause - Internal Team
Slack conversation:
View all open jobs on GitHub
Upwork Automation - Do Not Edit

Upwork Job URL: https://www.upwork.com/jobs/~01788d0f20c53c4622
Upwork Job ID:<PHONE_NUMBER>122317312
Last Price Increase: 2023-08-10
Automatic offers:

Pluto0104 | Contributor | 26073309

Proposal
Please re-state the problem that we are trying to solve in this issue.

Without diatric characters, it is difficult to search for Côte d'Ivoire in the country field.

What is the root cause of that problem?

The root cause is that the country field does not normalize diatric characters.

What changes do you think we should make in order to solve the problem?

We can use the below code to normalize diatric characters in the country field.

function normalizeDiacritics(str) {
  return str.normalize("NFD").replace(/[\u0300-\u036f]/g, "");
}

Now we will need to update:

searchCountryOptions.js to use above function to normalize diatric characters.
We can further use above function in searching for Chats, Rooms, and Users.

By adding it to isSearchStringMatch of OptionsListUtils.js.

What alternative solutions did you explore? (Optional)

There are no alternative solutions. As this is a simple problem, the above solution should be sufficient.

Proposal
Please re-state the problem that we are trying to solve in this issue.
The country name is not displayed when you start entering "cote" or "cote d'Ivoire" without a diacritic, and instead you see "no results found".
What is the root cause of that problem?
The app does not handle diacritics or special characters properly when searching or matching country names.
What changes do you think we should make in order to solve the problem?
We can use _.deburr instead of simplifyWordFromDiacritics to remove diacritics from a string. This is a built-in function from lodash, which is a library that we already use in our app. This will make your code more concise and readable.
For example:
const trimmedSearchValue =_.chain(searchValue).deburr().toLower().value().replaceAll(CONST.REGEX.NON_ALPHABETIC_AND_NON_LATIN_CHARS, '');
/* ... */
const filteredData = _.filter(countriesData, (country) => _.deburr(country.searchValue).includes(trimmedSearchValue));
/* ... */

What alternative solutions did you explore? (Optional)
function simplifyWordFromDiacritics(country) {
    return country.normalize('NFD').replace(/[\u0300-\u036f]/g, '');
}

Thanks for the proposals folks, all the proposals have the correct RCA, but I think @Pluto0104's proposal is good. Using lodash.deburr would be more reliable.
🎀 👀 🎀  C+ reviewed.

Missed by lodash didn't knew they already had a function. Cheers to @Pluto0104 🥂 🎉

Yeah and I experience with regex NFD is it anyway supports limited characters. I've used it quite a few times, and we've always had to patch with few additional cases, until we started using lodash.

Umm, so is this proposal accepted? @mananjadhav, Can I make a proposal in Upwork?

@Pluto0104 We now wait for @aldo-expensify to review and officially assign you the job here in Github. You can then start the work on the PR, and in parallel get yourself hired on Upwork.

@mananjadhav, Thank you for your comment. I'm new to contributing Expensify app.

@aldo-expensify Could you please review my proposal?

I think this should also include that if you put a diacritic in the search when you type, you should find results with and without the diacritic, right?
Just mentioning that because I'm not 100% the proposal is handling this case. Does it?

Agree with preferring the implementation using lodash.

Contributor details
Your Expensify account email<EMAIL_ADDRESS>Upwork Profile Link: https://www.upwork.com/freelancers/~0111689310c69ddae7

I would treat this as a feature request instead of a bug fix. We never intended to consider diacritic characters when we originally created the feature.

@bfitzexpensify Can you post the payout summary here?

How can I receive a bonus? When I was new to contributing to Expensify, I submitted my work on Upwork, and then Upwork released $1000 from escrow today. It appears that the submission wasn't approved by Expensify, but due to the 14-day period since my submission, Upwork went ahead and released the funds. While I acknowledge that submitting the work was my oversight, I believe I am still eligible for a bonus related to this issue.

Waiting for the payment summary for NewDot payment.

Payout summary:
Contributor: @Pluto0104 - $1500 for contributor work and #urgency bonus. $1000 has been paid via Upwork, remaining $500 to be paid via Upwork - @Pluto0104, please apply to this job - https://www.upwork.com/jobs/~01aa7f6d4d09c3e0de
C+: $1500 to be paid to @mananjadhav for C+ work and #urgency bonus via manual request

@bfitzexpensify I have applied the job on Upwork.

Reviewed the details for @mananjadhav. $1,500 approved for payment based on BZ summary.

@JmillsExpensify I have applied the job from here.
But my proposal is not accepted and the contract for original issue is not completed. how can I do?

@mananjadhav @bfitzexpensify @JmillsExpensify could you please take a look here?

@JmillsExpensify @bfitzexpensify Can one of you help here?

@Pluto0104 offer sent - please let me know when you accept it and I will get it paid out.

OK, that's now been paid out. I agree with this reasoning, @mananjadhav:

I would treat this as a feature request instead of a bug fix. We never intended to consider diacritic characters when we originally created the feature.

I think we're all done here now — thanks for the contributions everyone!

Hi @bfitzexpensify, I wanted to let you know that I've received payment for the work, but it seems that the contract for https://github.com/Expensify/App/issues/24344 is still open. Could you please confirm the completion of this contract? Thank you!

Hey @Pluto0104 - that's now been closed, thanks for the heads up.

@bfitzexpensify, thank you for the incredibly fast response. It appears that this issue may have been reopened, but I believe we can proceed to close it now. 🙇


Fix to test.

Closes https://github.com/mne-tools/mne-python/issues/3658

merge and backport
thanks

Current coverage is 87.39% (diff: 100%)

Merging #3659 into master will not change coverage

@@             master      #3659   diff @@
==========================================
  Files           343        343
  Lines         60765      60765
  Methods           0          0
  Messages          0          0
  Branches       9300       9300
==========================================
  Hits          53108      53108
  Misses         4903       4903
  Partials       2754       2754

Powered by Codecov. Last update c6a7562...48cacdb

Backported.

thanks !


WIP: Add labels to the test framework.

Refactor the test framework top-level API, so that labels, requirements and setup functions can be
specified in a fluent-manner. This has the additional nice side effect of early bailout/skip without running the setup tasks, if the framework decides that none of the tests will execute.
Add label based selector mechanism for selecting tests. The tests can be selected from the command-line, through the new --istio.test.selector flag, which allows selection/exclusion of tests based on labels associated with tests.
Change the current makefile and Circle CI settings, so that we can select stable tests to run in CircleCI required based integration suite gates.

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Could you add some context to the description? Why are we adding labels? what are they for?

Sure. Once it is ready. :)

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This should be baked enough to start getting reviewed.

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/lgtm
/approve

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Update ref branch to 2.7 for OpenSearch-Spatial plugins

Description
Update ref branch from 2.x to 2.7 for OpenSearch-Spatial plugins (k-NN, geospatial, neural search, dashboards-maps)
By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license.
For more information on following Developer Certificate of Origin and signing off your commits, please check here.

Hey @naveentatikonda Thanks for this updates. Could you use single quote for the ref here as '2.7'?

Updated, Thank you!

Codecov Report

Merging #3369 (a4afc5e) into main (31991db) will decrease coverage by 0.29%.
The diff coverage is n/a.

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@@            Coverage Diff             @@
##             main    #3369      +/-   ##
==========================================
- Coverage   91.74%   91.46%   -0.29%
==========================================
  Files         172      172
  Lines        4991     4991
==========================================
- Hits         4579     4565      -14
- Misses        412      426      +14

see 2 files with indirect coverage changes
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Some of the checks failed because it can't find asynchronous-search plugin in 2.7 artifact
FAILURE: Build failed with an exception.

* What went wrong:
A problem occurred evaluating root project 'asynchronous-search'.
> Can't get https://ci.opensearch.org/ci/dbc/distribution-build-opensearch/2.7.0/latest/linux/x64/tar/builds/opensearch/plugins/opensearch-asynchronous-search-<IP_ADDRESS>.zip to /tmp/tmpro65vrvd/asynchronous-search/src/test/resources/org/opensearch/search/asynchronous/bwc/<IP_ADDRESS>/opensearch-asynchronous-search-<IP_ADDRESS>.zip

CI check failed on 3.0.0 isn't a blocker for this PR. Merging now.


Add ISSUE_TEMPLATE

@TeAmP0is0N   Added a pull request template and an issue template folder with bug_report_template.md and feature_request_template.md.
Closes: #49

@swapagarwal Please review it and do let me know if any changes are required.


Add files via upload

Very interesting topic Murphy!  I really like how you structured your work in a very concise and clear format. There are some comments I would suggest in enhancing your work:

Perhaps elaborate just a little bit more on the introduction, so reader would be to able to get a more thorough understanding in what your are trying to deliver
Add a table of content for clarity purposes
Perhaps add a conclusion sections or even a sentence just to summarize your work

Very interesting topic Murphy! I really like how you structured your work in a very concise and clear format. There are some comments I would suggest in enhancing your work:

Perhaps elaborate just a little bit more on the introduction, so reader would be to able to get a more thorough understanding in what your are trying to deliver
Add a table of content for clarity purposes
Perhaps add a conclusion sections or even a sentence just to summarize your work

Thanks for your review! I add a table of content in the file


Prevent nonsensical values from being passed in through plugin command.

Pushed to v0.03 development branch.


Memory leak issue

We've used a simple method that resulted in a memory leak in our application:
private bool CompareEntities<T>(T object1, T object2)
{
    var comparer = new ObjectsComparer.Comparer<T>();

    return comparer.Compare(object1, object2, out IEnumerable<Difference> _);
}

The method was used in a background job.

Can you please provide more information? Does it help if you change
return comparer.Compare(object1, object2, out IEnumerable<Difference> _);
to
return comparer.Compare(object1, object2);

Im running into the same problem but in my case the memory leak appears when trying to access the properties of IEnumerable.
Thanks to @wholroyd issue I have assumed correctly that the following property was the problem:
public CultureInfo DefaultCultureInfo { get { return CultureInfo.GetCultureInfo(DefaultCulture); } }
I won't try your approach since I don't like dynamic variables but thanks!

@Bortxop can you please provide more information about your case?


onEnter and onLeave called twice

Currently, I always get duplicate event handlers called when I scroll into and away from the Waypoint. Is there any specific requirements in the CSS?

Hi @imouto1994, and thanks for using react-waypoint! This sounds like the same problem described in https://github.com/brigade/react-waypoint/issues/28. Is there anything from that thread that could help you track this down?
We've been trying to track this bug down for a while but any attempt at recreating it has come up short. If you can provide a repro case or describe how this particular part of your app is structured, that would be really helpful.
One thing to look at is in what order the callbacks are called. Is it onEnter - onLeave - onEnter - onLeave. Or perhaps onEnter - onEnter - onLeave - onLeave?

Hi @trotzig , I think I have kinda figured out why there is duplicate call.
This happened when in onEnter or onLeave handlers, I use setState in the parent component containing the Waypoint which will trigger the componentDidUpdate in Waypoint and call _handleScroll again.

Thanks for that information, it helps a lot actually. We have a guard to protect us from firing the same callback again by looking at the difference between currentPosition and previousPosition. But we save the previousPosition after we call the onEnter/onLeave callback. Here: https://github.com/brigade/react-waypoint/blob/master/src/waypoint.jsx#L126
I think we can resolve this by moving that line above calling the callback. We can also defer calling the callback until the next execution tick by wrapping it in a setTimeout. But I'm unsure what other consequences that might have.
As a workaround, until we have this fixed and released, you can defer your setState call by wrapping it in a setTimeout.
Do you want to take a stab at creating a PR? If not, I'll get to it when I have some time over. It would be great if we can pair it with a test (spec/waypoint_spec.js).


Automated cherry pick of #2057: fix: server-list add is_prepaid_recycle field

Cherry pick of #2057 on release/2.11.
#2057: fix: server-list add is_prepaid_recycle field

Codecov Report

:exclamation: No coverage uploaded for pull request base (release/2.11@84b943a). Click here to learn what that means.
The diff coverage is n/a.

@@              Coverage Diff               @@
##             release/2.11   #2059   +/-   ##
==============================================
  Coverage                ?   7.18%
==============================================
  Files                   ?     445
  Lines                   ?   69358
  Branches                ?       0
==============================================
  Hits                    ?    4983
  Misses                  ?   63962
  Partials                ?     413

Flag
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#aFlag
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Impacted Files
Coverage Δ

pkg/compute/models/guests.go
0.68% <ø> (ø)

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/lgtm
/approve

/approve


docs: add managing pages, api references, service user page

Pull Request Test Coverage Report for Build<PHONE_NUMBER>

0 of 0   changed or added relevant lines in 0 files are covered.
No unchanged relevant lines lost coverage.
Overall coverage remained the same at 43.577%

Totals

Change from base Build<PHONE_NUMBER>:
0.0%

Covered Lines:
4281

Relevant Lines:
9824

💛  - Coveralls

@Chief-Rishab merging this.


Using autoclose html on a different extension

Would it be possible to use autoclose-html on a something.html.twig file ? I'm just talking about using the default HTML behavior, not about a full twig support.

I'm not sure what twig is, so I can't comment on that. What you need to do is add the correct grammar. To the Additional Grammars setting. The grammar name can be found in the bottom right corner of the atom window when a file is open. ("CoffeeScript" in the first picture here https://atom.io/docs/v1.4.0/using-atom-grammar)

Nice, it's working. Thank you!


How To Resolve Azure Function Stream Too Long Error (blob trigger)

Package Name: azure.functions
Package Version: 4.0.5198
Operating System: OS Name:                   Microsoft Windows 10 Pro N
OS Version:                10.0.19045 N/A Build 19045
OS Manufacturer:           Microsoft Corporation
Python Version:  3.9.16

Describe the bug
I am using a azure function blob trigger to process some json-files and got a Stream Too Long Error if the file (which triggered the function) is very big (~2.5 GiB). After talking with Microsoft Azure Community we think the file is loaded in memory (https://learn.microsoft.com/en-us/answers/questions/1433195/how-to-resolve-azure-function-stream-too-long-erro). Is there a way to only get the name of blob and not to load file in memory?
To Reproduce
Steps to reproduce the behavior:

create very large json-file
Create durable azure function blob trigger which takes blob.name and gives it to orchestrator-function
store json file in storage account (blob trigger "looks" at this file)

Expected behavior
Error: Stream too long
Screenshots
If applicable, add screenshots to help explain your problem.
Additional context
Add any other context about the problem here.

Thanks for the feedback, I've assigned some folks who may be able to provide some insight.

Hi @GeraldRupp this does not seem like an issue with any library inside the Azure SDK repo. There is a chance they use azure-storage-blob internally in the functions service but we have no way of knowing that. I think it may be better to redirect your issue to https://github.com/Azure/azure-functions-python-library? The owners of this repo are not familiar with the inner workings of Azure Functions or that SDK. Thanks!

Closing this one and please feel free to open an issue in azure-functions repo.


[flake8-implicit-str-concat] Normalize octals before concatenating strings in single-line-implicit-string-concatenation (ISC001)

This PR pads the last octal (if there is one) to three digits before concatenating strings in the fix for ISC001.
For example: "\12""0" is fixed to "\0120".
Closes #12936.

Re putting the Cows to pasture:
The borrow checker complained when I tried to implement the fix you suggested (assuming I did it correctly), because I borrow text here:
let mut rev_bytes = text.bytes().rev();

and then try to modify it with *text = Cow::Owned(...). I can try to mess around, but it's not immediately obvious how to avoid a clone/copy/some other memory allocation.
More fundamentally, I'm hoping you could help with a Rust confusion here. I would've thought that the .to_string wouldn't be much added cost because we eventually convert everything to a String (even on the happy path) here:
let concatenation = format!("{a_leading_quote}{a_body}{b_body}{a_trailing_quote}");

Maybe a more minimal version of my question is: Do you gain much in terms or memory/performance by doing
let a = &"xyz";
let s = format!("{a}")
// then a drops out of scope

vs
let a = "xyz".to_string();
let s = format!("{a}")
// then a drops out of scope

?
Or does the compiler end up making those roughly the same?
(Obviously the first code is better in this contrived example, but the question remains.)
Sorry for the long-ish question, and thanks for the very helpful review!

The borrow checker complained when I tried to implement the fix you suggested (assuming I did it correctly), because I borrow text here:

I pushed the change I was suggesting to your PR branch in https://github.com/astral-sh/ruff/pull/13118/commits/25805a2992889918b3b5626c5e60139ca756037d :-) the key to avoiding the borrow-checker complaints is to have normalize_ending_octal() mutate the existing value in-place rather than returning a new value.

Makes sense, and thank you that was very helpful!


MotionAssistant password is '123'

Could you include this information on the page?
I took so long to find that haha

Updated, sorry about that, didn't know the new file was password protected.


Output CSS sourcemaps in separate file

Fixes https://github.com/facebook/create-react-app/issues/5120

Added comments


Padrino Generate - log per project [request]

Sometimes I want to start afresh with quite similar components - just change one or two - or very similar constraints on a project, and just change some field names or something.
It might be useful if the padrino generator output a log of commands called on it per project.. just word for word so you could copy and paste them & tweak to your liking.
padrino g project ...
padrino g model..
etc etc
in a plain text file in the app's root eg. .padrino-gen

I suggest to use:

history | grep padrino
padrino templates $ padrino.dev g project foo --template=https://github.com/padrino/padrino-recipes/raw/master/templates/lipsiasoft_template.rb

Thanks man!

Ended up adding a flag to my local version but grep works too haha
Thanks


GitHub Sync

This is an automatically generated pull request.

LGTM assuming green travis (you can ignore AppVeyor for now I think?)


Create new androapp  Movies

Please describe about your Androapp

A Flutter app that has list of movies and its details along with its trailer and posters.
Dart

Describe alternatives you've considered
No alternatives
Additional context
https://user-images.githubusercontent.com/72657303/193506848-c4e69751-1d46-4011-a8b6-3e03762c3b79.mp4

Okay, Go ahead!
Please Note:

Please go through README.md and CONTRIBUTING.md
Already existing apps on github will be considered as spam, try to make your own UI
Please use appropriate comments to self describe your code
Add necessary readme.md - references of your learnings and dependencies, images (screenshots); refer latest added apps for this task.

Assigning to you!

Hey @Simran1604 if you're still working on this issue, please update here or it'll be assigned to someone else

If anyone wants to take this issue, please comment below!

Closing this issue!


Remove mentions of deb.haskell.org from German and Italian guide

as this service has been discontinued.

Thank you @nomeata :) :+1:


Fix SyncReturn<RustOpaque<T>>

New SyncReturn system ignores SyncReturn<RustOpaque<T>>
learn more - frb_sync_generator_test function
This PR fixes it
Checklist

[x] An issue to be fixed by this PR is listed above.
[x] New tests are added to ensure new features are working. End-to-end tests are usually in the ./frb_example/pure_dart example, more specifically, rust/src/api.rs and dart/lib/main.dart.
[x] The code generator is run and the code is formatted (e.g. via just refresh_all).
[x] If this PR adds/changes features, documentations (in the ./book folder) are updated.
[x] CI is passing.

@fzyzcjy  ping just in case

Nice fix :) will probably review today

@fzyzcjy  CI ready

Good job!


Add isPnpm helper in utils

Some packages may have additional requirements in pnpm or yarn berry, so a helper like this is helpful.


Allow to add and edit Metadata of Software

It would be very nice if we could add a description for the software that we can change later.
Additionally, we should probably add the possibility to link one or multiple papers, maybe via a link to dblp entries?
This way, TIRA could link back to the ACL Anthology or also to the IR Anthology.

Renaming Software
Free-Form field to add a deep link to DBLP, e.g.: https://dblp.org/rec/conf/naacl/SanthanamKSPZ22.html
Free-Form field to add a description with markdown support (use  a markdown to HTML renderer). People can write whatever they want, like "if you like this, please cite x and y")

Thanks @theelstner for the work.
I made a small change and placed this "Edit Software Metadata" Formular behind a "Edit-Button" toggle, so that the actual change in the frontend is rather minimal.
It works in the local deployment (i.e., without disraptor/discourse), but not in the deployed version.
Can you maybe look into the logs what is the problem? And/or test if it works in your local setup?
We do not need to fix this too urgently, as the form is hidden behind the toggle.
But as soon as it is working in the live version, I would imagine the following "final test":

Start on https://www.tira.io/task/ir-convention-test/user/test-1-on-17-2022
Look if you can see some Evaluation and Run outputs
Rename the software and edit the metadata, reload the page
Can you still see the runs? Are the Evaluation and run outputs still visible?
Run the software
Is the new Software execution still added to the frontend?
Rename the software
Run the software again
Are during all the renamings etc. the Evaluations/runs still visible? can you change the name of the software back to the original?

ToDo: insert DOI

@theelstner I now have deployed the changes that we made in the meeting today.
It now works (I only tested it in a small example), could you please test the things from above and see if this also works?
And if this works, we can close the issue.
Thanks!

I have tested it like mentioned in the comment above. Everything works, except for a minor bug (#345 Docker software runs don't show unless page is reloaded).  The bug is noted in a separate issue.


Throw error instead exit on fail to read wav in java

I think it's better to throw a error instead of exit to let the developer handle it in the app

Thank you for your contribution!


Fill nc and ncctapp gaps

Part of #929
On giving this a second look, I notice that we are missing records from the end of the year because of the way the scraper creates the url
self.url = "http://appellate.nccourts.org/opinions/?c=sc&year=%s" % date.today().year
which will miss opinions near the change of year, which seem to be posted in early january, but put under the previous year link
For example, for year 2021 we are missing all nc records under the Mandate: 6 January 2022 section

This gap could be filled by simply running the current backscraper which will try to download everything again
nc
Between September 25, 2020 and February 05, 2021 we have 0 documents. We are missing around 50 published opinions from late 2020.
ncctapp
From November 4, 2020 to January 1st, 2022 we have 0 documents. There is data in the source for this time period

docker exec -it cl-django python /opt/courtlistener/manage.py cl_back_scrape_opinions --courts juriscraper.opinions.united_states.state.nc --backscrape-start=2020 --backscrape-end=2021

docker exec -it cl-django python /opt/courtlistener/manage.py cl_back_scrape_opinions --courts juriscraper.opinions.united_states.state.ncctapp --backscrape-start=2020 --backscrape-end=2022

nc
For the identified gap, we now have 67 documents, up from 0
However, the backscrape has created some duplicates. For each year, it saved ALL records available.
For 2020

DEBUG juriscraper.opinions.united_states.state.nc: Successfully crawled 179/179 opinions.

For 2021

DEBUG juriscraper.opinions.united_states.state.nc: Successfully crawled 167/167 opinions.`

Duplicate example: old, new
The hash of the documents is indeed different, but the metadata of the document fresh off the website seems to suggest it hasn't been modified?
 'Creator': 'Microsoft® Word 2013',
 'CreationDate': "D:20200124110425-05'00'",
 'ModDate': "D:20200124110425-05'00'"}

ncctapp
From 0, we got 345 opinions now
Some duplicates have been introduced via the same logic described above


Use #!/usr/bin/env to support virtualenv

Instead of hard-coding the path to python, use the current environment path to find the appropriate python3 binary. This allows scripts to work in virtualenv type environments.

ok sure :) lets see how the tests look

wonderful, thanks!


.NET 3.5 to be re-enabled later when CLI supports it

https://github.com/Microsoft/msbuild/issues/1333

If I use msbuild directly on appveyor, it works.  However doing a nuget pack is worse :(

Using msbuild for building and packing


Add support for ternary expressions

What is wrong?
We do not yet support ternary expressions (even though they are already recognized by the parser)
Example that should be working but currently doesn't:
contract Foo:

    pub def bar(input: u256) -> u256:
       return 1 if input > 5 else 0

How can it be fixed

Take the above snippet, create a fixture file from it and invoke it here:

https://github.com/ethereum/fe/blob/90ca889637a487f943ac3924dada538b0d475e0f/compiler/tests/evm_contracts.rs#L256-L259

Run cargo test --workspace --features solc-backend test_method_return and notice the failing tests

As the errors should hint, we need to add type checking in the semantic pass

https://github.com/ethereum/fe/blob/90ca889637a487f943ac3924dada538b0d475e0f/semantics/src/traversal/expressions.rs#L40

We then need to map the expression to its YUL equivalent in the mapper pass

https://github.com/ethereum/fe/blob/90ca889637a487f943ac3924dada538b0d475e0f/compiler/src/yul/mappers/expressions.rs#L27

This landed with #132


Number of dimensions of repeat dims can not be smaller than number of dimensions of tensor

Hi, I got the following error when run the example colab:
RuntimeError                              Traceback (most recent call last)

[<ipython-input-7-8f3d1d1ad737>](https://localhost:8080/#) in <cell line: 3>()
      1 # this is very slow right now since our inference code is not very optimized
      2 # but even without this crucial optimization it is still better than real-time on an RTX 4090
----> 3 pipe.generate_to_notebook("""
      4 This is the first demo of Whisper Speech, a fully open source text-to-speech model trained by Collabora and Lion on the Juwels supercomputer.
      5 """)

4 frames

[/usr/local/lib/python3.10/dist-packages/whisperspeech/s2a_delar_mup_wds_mlang.py](https://localhost:8080/#) in <listcomp>(.0)
    514         if show_progress_bar: it = progress_bar(it)
    515         with record_function("encode"):
--> 516             stoks, speakers = [x.repeat(bs, 1) for x in (stoks, speakers)]
    517             xenc, xenc_positions, _ = self.run_encoder(stoks, speakers)
    518             toks_positions = torch.arange(N, device=dev)

RuntimeError: Number of dimensions of repeat dims can not be smaller than number of dimensions of tensor

Hey, sorry about that. I pushed a new version today that solves this issue.

---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
[<ipython-input-44-de81f3a88132>](https://localhost:8080/#) in <cell line: 3>()
      1 # We can also mix different languages (e.g. for borrowed words) in a single sentence
      2 stoks = pipe.t2s.generate(["To jest pierwszy test wielojęzycznego ", " Whisper Speech ", ", modelu zamieniającego tekst na mowę, który Collabora i Laion nauczyli na superkomputerze", " Jewels."], lang=['pl', 'en', 'pl', 'en'])
----> 3 pipe.vocoder.decode_to_notebook(pipe.s2a.generate(stoks, pipe.default_speaker.unsqueeze(0)))

2 frames
[/usr/local/lib/python3.10/dist-packages/whisperspeech/s2a_delar_mup_wds_mlang.py](https://localhost:8080/#) in <listcomp>(.0)
    493         if show_progress_bar: it = progress_bar(it)
    494         with record_function("encode"):
--> 495             stoks = stoks.unsqueeze(1)
    496             speakers = speakers.unsqueeze(1)
    497             stoks, speakers = [x.repeat(bs, 1) for x in (stoks, speakers)]

RuntimeError: Number of dimensions of repeat dims can not be smaller than number of dimensions of tensor

This error still occurs.

Good point, thanks. I forgot to update the examples in the notebook.
It should be fixed now but if you have a notebook with local changes the fix is to add [0] after: stoks like this:
pipe.vocoder.decode_to_notebook(pipe.s2a.generate(stoks[0], pipe.default_speaker.unsqueeze(0)))