error while converting to TensorRT-LLM

Hi I am following the steps here https://kipok.github.io/NeMo-Skills/openmathinstruct2/evaluation/
The convert step
ns convert \     --cluster=local \     --input_model=/workspace/OpenMath2-Llama3.1-8B \     --output_model=/workspace/openmath2-llama3.1-8b-trtllm \     --convert_from=hf \     --convert_to=trtllm \     --model_type=llama \     --num_gpus=1 \     --hf_model_name=nvidia/OpenMath2-Llama3.1-8B
is failing on nemo-run/0 FileNotFoundError: [Errno 2] No such file or directory: '/workspace/openmath2-llama3.1-8b-trtllm-tmp/config.json'
the script has created the /workspace/openmath2-llama3.1-8b-trtllm-tmp/ folder but there is nothing inside

Can you please share the full output of that command? It's likely that there is another error message before this one that will make it easier to understand what is wrong

`/workspace$ ns convert
--cluster=local
--input_model=/workspace/OpenMath2-Llama3.1-8B
--output_model=/workspace/openmath2-llama3.1-8b-trtllm
--convert_from=hf
--convert_to=trtllm
--model_type=llama
--num_gpus=1
--hf_model_name=nvidia/OpenMath2-Llama3.1-8B
2024-11-10 16:12:29 INFO  Starting conversion job
2024-11-10 16:12:29 INFO  Extra arguments that will be passed to the underlying script:
────────────────────────────────────────────────────────────────────────────────────────────── Entering Experiment conversion with id: conversion_1731255149 ───────────────────────────────────────────────────────────────────────────────────────────────
[16:12:29] INFO     Launching task with command export PYTHONPATH=$PYTHONPATH:/nemo_run/code && export HF_TOKEN=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 && cd /nemo_run/code && if [ ! -d /workspace/openmath2-llama3.1-8b-trtllm-tmp ]; then   convert.py:238
python -m nemo_skills.conversion.hf_to_trtllm_llama     --model_dir /workspace/OpenMath2-Llama3.1-8B     --output_dir /workspace/openmath2-llama3.1-8b-trtllm-tmp     --dtype bfloat16     --tp_size 1     --pp_size 1
; fi && trtllm-build     --checkpoint_dir /workspace/openmath2-llama3.1-8b-trtllm-tmp     --output_dir /workspace/openmath2-llama3.1-8b-trtllm     --gpt_attention_plugin bfloat16     --use_paged_context_fmha enable
--max_input_len 4096     --max_seq_len 8192     --max_num_tokens 8192     --max_batch_size 128      && cp /workspace/OpenMath2-Llama3.1-8B/tokenizer* /workspace/openmath2-llama3.1-8b-trtllm
WARNING  Not running from a git repo, trying to upload installed package. Make sure there are no extra files in /home/ubuntu/NeMo-Skills/nemo_skills/*                                                                               utils.py:392
[16:12:29] Launching job nemo-run for experiment conversion                                                                                experiment.py:693
[16:12:37] INFO     Pulling container image: igitman/nemo-skills-trtllm:0.4.1 (this may take a while)                                                                                docker.py:113
[16:12:40] INFO     Launched app: docker_persistent://nemo_run/nemo-run-cddz7mdj7klqdc                                                                                launcher.py:111
INFO     AppStatus:                                                                                launcher.py:114
State: RUNNING
Num Restarts: -1
Roles:
*nemo-run[0]:RUNNING
Msg:
Structured Error Msg:
UI URL: None
────────────────────────────────────────────────────────────────────────────────────────────────── Waiting for Experiment conversion_1731255149 to finish ──────────────────────────────────────────────────────────────────────────────────────────────────
Experiment Status for conversion_1731255149
Task 0: nemo-run

Status: RUNNING

Executor: DockerExecutor

Job id: nemo-run-cddz7mdj7klqdc

Local Directory: /home/ubuntu/.nemo_run/experiments/conversion/conversion_1731255149/nemo-run
     INFO     Waiting for job nemo-run-cddz7mdj7klqdc to finish [log=True]...                                                                                launcher.py:132

nemo-run/0
nemo-run/0 ==========
nemo-run/0 == CUDA ==
nemo-run/0 ==========
nemo-run/0
nemo-run/0 CUDA Version 12.5.1
nemo-run/0
nemo-run/0 Container image Copyright (c) 2016-2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
nemo-run/0
nemo-run/0 This container image and its contents are governed by the NVIDIA Deep Learning Container License.
nemo-run/0 By pulling and using the container, you accept the terms and conditions of this license:
nemo-run/0 https://developer.nvidia.com/ngc/nvidia-deep-learning-container-license
nemo-run/0
nemo-run/0 A copy of this license is made available in this container at /NGC-DL-CONTAINER-LICENSE for your convenience.
nemo-run/0
nemo-run/0 [TensorRT-LLM] TensorRT-LLM version: 0.12.0
nemo-run/0 [11/10/2024-16:12:50] [TRT-LLM] [I] Set bert_attention_plugin to auto.
nemo-run/0 [11/10/2024-16:12:50] [TRT-LLM] [I] Set gpt_attention_plugin to bfloat16.
nemo-run/0 [11/10/2024-16:12:50] [TRT-LLM] [I] Set gemm_plugin to None.
nemo-run/0 [11/10/2024-16:12:50] [TRT-LLM] [I] Set gemm_swiglu_plugin to None.
nemo-run/0 [11/10/2024-16:12:50] [TRT-LLM] [I] Set fp8_rowwise_gemm_plugin to None.
nemo-run/0 [11/10/2024-16:12:50] [TRT-LLM] [I] Set nccl_plugin to auto.
nemo-run/0 [11/10/2024-16:12:50] [TRT-LLM] [I] Set lookup_plugin to None.
nemo-run/0 [11/10/2024-16:12:50] [TRT-LLM] [I] Set lora_plugin to None.
nemo-run/0 [11/10/2024-16:12:50] [TRT-LLM] [I] Set moe_plugin to auto.
nemo-run/0 [11/10/2024-16:12:50] [TRT-LLM] [I] Set mamba_conv1d_plugin to auto.
nemo-run/0 [11/10/2024-16:12:50] [TRT-LLM] [I] Set context_fmha to True.
nemo-run/0 [11/10/2024-16:12:50] [TRT-LLM] [I] Set bert_context_fmha_fp32_acc to False.
nemo-run/0 [11/10/2024-16:12:50] [TRT-LLM] [I] Set paged_kv_cache to True.
nemo-run/0 [11/10/2024-16:12:50] [TRT-LLM] [I] Set remove_input_padding to True.
nemo-run/0 [11/10/2024-16:12:50] [TRT-LLM] [I] Set reduce_fusion to False.
nemo-run/0 [11/10/2024-16:12:50] [TRT-LLM] [I] Set enable_xqa to True.
nemo-run/0 [11/10/2024-16:12:50] [TRT-LLM] [I] Set tokens_per_block to 64.
nemo-run/0 [11/10/2024-16:12:50] [TRT-LLM] [I] Set use_paged_context_fmha to True.
nemo-run/0 [11/10/2024-16:12:50] [TRT-LLM] [I] Set use_fp8_context_fmha to False.
nemo-run/0 [11/10/2024-16:12:50] [TRT-LLM] [I] Set multiple_profiles to False.
nemo-run/0 [11/10/2024-16:12:50] [TRT-LLM] [I] Set paged_state to True.
nemo-run/0 [11/10/2024-16:12:50] [TRT-LLM] [I] Set streamingllm to False.
nemo-run/0 Traceback (most recent call last):
nemo-run/0   File "/usr/local/bin/trtllm-build", line 8, in
nemo-run/0     sys.exit(main())
nemo-run/0   File "/usr/local/lib/python3.10/dist-packages/tensorrt_llm/commands/build.py", line 442, in main
nemo-run/0     model_config = PretrainedConfig.from_json_file(config_path)
nemo-run/0   File "/usr/local/lib/python3.10/dist-packages/tensorrt_llm/models/modeling_utils.py", line 301, in from_json_file
nemo-run/0     with open(config_file) as f:
nemo-run/0 FileNotFoundError: [Errno 2] No such file or directory: '/workspace/openmath2-llama3.1-8b-trtllm-tmp/config.json'
[16:12:54] INFO     Job nemo-run-cddz7mdj7klqdc finished: SUCCEEDED                                                                                launcher.py:162
The experiment was run with the following tasks: ['nemo-run']
You can inspect and reconstruct this experiment at a later point in time using:
experiment = run.Experiment.from_id("conversion_1731255149")
experiment.status() # Gets the overall status
experiment.logs("nemo-run") # Gets the log for the provided task
experiment.cancel("nemo-run") # Cancels the provided task if still running
You can inspect this experiment at a later point in time using the CLI as well:
nemo experiment status conversion_1731255149
nemo experiment logs conversion_1731255149 0
nemo experiment cancel conversion_1731255149 0  `

Sorry, can you please add --no-trt_reuse_tmp_engine and share logs after that? Otherwise it's trying to reuse that tmp engine which has not been built properly for you

ah the VM seems to crash after this conversion step. I tried increasing to 32 GB of RAM but crashed again
/workspace$ ns convert
--cluster=local
--input_model=/workspace/OpenMath2-Llama3.1-8B
--output_model=/workspace/openmath2-llama3.1-8b-trtllm
--convert_from=hf
--convert_to=trtllm
--model_type=llama
--num_gpus=1
--hf_model_name=nvidia/OpenMath2-Llama3.1-8B
--no-trt_reuse_tmp_engine
2024-11-10 16:59:27 INFO  Starting conversion job
2024-11-10 16:59:27 INFO  Extra arguments that will be passed to the underlying script:
────────────────────────────────────────────────────────────────────────────────────────────── Entering Experiment conversion with id: conversion_1731257967 ───────────────────────────────────────────────────────────────────────────────────────────────
[16:59:27] INFO     Launching task with command export PYTHONPATH=$PYTHONPATH:/nemo_run/code && export HF_TOKEN=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 && cd /nemo_run/code && python -m nemo_skills.conversion.hf_to_trtllm_llama             convert.py:238
--model_dir /workspace/OpenMath2-Llama3.1-8B     --output_dir /workspace/openmath2-llama3.1-8b-trtllm-tmp     --dtype bfloat16     --tp_size 1     --pp_size 1       && trtllm-build     --checkpoint_dir
/workspace/openmath2-llama3.1-8b-trtllm-tmp     --output_dir /workspace/openmath2-llama3.1-8b-trtllm     --gpt_attention_plugin bfloat16     --use_paged_context_fmha enable     --max_input_len 4096     --max_seq_len
8192     --max_num_tokens 8192     --max_batch_size 128      && cp /workspace/OpenMath2-Llama3.1-8B/tokenizer* /workspace/openmath2-llama3.1-8b-trtllm
WARNING  Not running from a git repo, trying to upload installed package. Make sure there are no extra files in /home/ubuntu/NeMo-Skills/nemo_skills/*                                                                               utils.py:392
[16:59:27] Launching job nemo-run for experiment conversion                                                                                experiment.py:693
[16:59:35] INFO     Pulling container image: igitman/nemo-skills-trtllm:0.4.1 (this may take a while)                                                                                docker.py:113
[16:59:38] INFO     Launched app: docker_persistent://nemo_run/nemo-run-jn31tdtptndfz                                                                                launcher.py:111
INFO     AppStatus:                                                                                launcher.py:114
State: RUNNING
Num Restarts: -1
Roles:
*nemo-run[0]:RUNNING
Msg:
Structured Error Msg:
UI URL: None
────────────────────────────────────────────────────────────────────────────────────────────────── Waiting for Experiment conversion_1731257967 to finish ──────────────────────────────────────────────────────────────────────────────────────────────────
Experiment Status for conversion_1731257967
Task 0: nemo-run

Status: RUNNING

Executor: DockerExecutor

Job id: nemo-run-jn31tdtptndfz

Local Directory: /home/ubuntu/.nemo_run/experiments/conversion/conversion_1731257967/nemo-run
     INFO     Waiting for job nemo-run-jn31tdtptndfz to finish [log=True]...                                                                                launcher.py:132

nemo-run/0
nemo-run/0 ==========
nemo-run/0 == CUDA ==
nemo-run/0 ==========
nemo-run/0
nemo-run/0 CUDA Version 12.5.1
nemo-run/0
nemo-run/0 Container image Copyright (c) 2016-2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
nemo-run/0
nemo-run/0 This container image and its contents are governed by the NVIDIA Deep Learning Container License.
nemo-run/0 By pulling and using the container, you accept the terms and conditions of this license:
nemo-run/0 https://developer.nvidia.com/ngc/nvidia-deep-learning-container-license
nemo-run/0
nemo-run/0 A copy of this license is made available in this container at /NGC-DL-CONTAINER-LICENSE for your convenience.
nemo-run/0
nemo-run/0 [TensorRT-LLM] TensorRT-LLM version: 0.12.0
nemo-run/0 0.12.0
nemo-run/0 230it [00:19, 11.62it/s]
nemo-run/0 Total time of reading and converting 19.9861741065979 s

the conversion succeeded! having an issue in the eval step now, trying to run on just GSM8K
ns eval     --cluster=local     --model=/workspace/openmath2-llama3.1-8b-trtllm     --server_type=trtllm     --output_dir=/workspace/openmath2-llama3.1-8b-eval     --benchmarks=gsm8k:0     --server_gpus=1     --num_jobs=1     ++prompt_template=llama3-instruct     ++batch_size=512     ++inference.tokens_to_generate=4096
Sun Nov 10 17:11:13 2024
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 550.90.07              Driver Version: 550.90.07      CUDA Version: 12.5     |
|-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA A10G                    On  |   00000000:00:1E.0 Off |                    0 |
|  0%   23C    P8             15W /  300W |       1MiB /  23028MiB |      0%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+
+-----------------------------------------------------------------------------------------+
| Processes:                                                                              |
|  GPU   GI   CI        PID   Type   Process name                              GPU Memory |
|        ID   ID                                                               Usage      |
|=========================================================================================|
|  No running processes found                                                             |
+-----------------------------------------------------------------------------------------+
[TensorRT-LLM] TensorRT-LLM version: 0.12.0
[TensorRT-LLM][INFO] Engine version 0.12.0 found in the config file, assuming engine(s) built by new builder API.
[TensorRT-LLM][INFO] MPI size: 1, MPI local size: 1, rank: 0
[TensorRT-LLM][INFO] Engine version 0.12.0 found in the config file, assuming engine(s) built by new builder API.
[TensorRT-LLM][INFO] Refreshed the MPI local session
[TensorRT-LLM][INFO] MPI size: 1, MPI local size: 1, rank: 0
[TensorRT-LLM][INFO] Rank 0 is using GPU 0
[TensorRT-LLM][INFO] TRTGptModel maxNumSequences: 128
[TensorRT-LLM][INFO] TRTGptModel maxBatchSize: 128
[TensorRT-LLM][INFO] TRTGptModel maxBeamWidth: 1
[TensorRT-LLM][INFO] TRTGptModel maxSequenceLen: 8192
[TensorRT-LLM][INFO] TRTGptModel maxDraftLen: 0
[TensorRT-LLM][INFO] TRTGptModel mMaxAttentionWindowSize: 8192
[TensorRT-LLM][INFO] TRTGptModel enableTrtOverlap: 0
[TensorRT-LLM][INFO] TRTGptModel normalizeLogProbs: 1
[TensorRT-LLM][INFO] TRTGptModel maxNumTokens: 8192
[TensorRT-LLM][INFO] TRTGptModel maxInputLen: 8191  = maxSequenceLen - 1 since chunked context is enabled
[TensorRT-LLM][INFO] TRTGptModel If model type is encoder, maxInputLen would be reset in trtEncoderModel to maxInputLen: 8192 = maxSequenceLen.
[TensorRT-LLM][INFO] Capacity Scheduler Policy: GUARANTEED_NO_EVICT
[TensorRT-LLM][INFO] Context Chunking Scheduler Policy: None
[TensorRT-LLM][INFO] Loaded engine size: 15403 MiB
[TensorRT-LLM][INFO] [MemUsageChange] Allocated 928.01 MiB for execution context memory.
[TensorRT-LLM][INFO] [MemUsageChange] TensorRT-managed allocation in IExecutionContext creation: CPU +0, GPU +0, now: CPU 0, GPU 15380 (MiB)
[TensorRT-LLM][INFO] [MemUsageChange] Allocated 86.66 MB GPU memory for runtime buffers.
[TensorRT-LLM][INFO] [MemUsageChange] Allocated 337.15 MB GPU memory for decoder.
[TensorRT-LLM][INFO] Memory usage when calculating max tokens in paged kv cache: total: 21.98 GiB, available: 5.31 GiB
[TensorRT-LLM][INFO] Number of blocks in KV cache primary pool: 612
[TensorRT-LLM][INFO] Number of blocks in KV cache secondary pool: 0, onboard blocks to primary memory before reuse: true
[TensorRT-LLM][INFO] Max KV cache pages per sequence: 128
[TensorRT-LLM][INFO] Number of tokens per block: 64.
[TensorRT-LLM][INFO] [MemUsageChange] Allocated 4.78 GiB for max tokens in paged KV cache (39168).

Serving Flask app '/nemo_run/code/nemo_skills/inference/server/serve_trt.py'
Debug mode: off
[11/10/2024-17:13:17] WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead.
Running on all addresses (<IP_ADDRESS>)
Running on http://<IP_ADDRESS>:5000
Running on http://<IP_ADDRESS>:5000
WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead.
Running on all addresses (<IP_ADDRESS>)
Running on http://<IP_ADDRESS>:5000
Running on http://<IP_ADDRESS>:5000
[11/10/2024-17:13:17] Press CTRL+C to quit
Press CTRL+C to quit
[11/10/2024-17:13:17] <IP_ADDRESS> - - [10/Nov/2024 17:13:17] "PUT / HTTP/1.1" 404 -
<IP_ADDRESS> - - [10/Nov/2024 17:13:17] "PUT / HTTP/1.1" 404 -
[11/10/2024-17:13:21] Exception on /get_result [PUT]
Traceback (most recent call last):
File "/usr/local/lib/python3.10/dist-packages/flask/app.py", line 880, in full_dispatch_request
rv = self.dispatch_request()
File "/usr/local/lib/python3.10/dist-packages/flask/app.py", line 865, in dispatch_request
return self.ensure_sync(self.view_functions[rule.endpoint])(**view_args)  # type: ignore[no-any-return]
File "/usr/local/lib/python3.10/dist-packages/flask_restful/init.py", line 489, in wrapper
resp = resource(*args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/flask/views.py", line 110, in view
return current_app.ensure_sync(self.dispatch_request)(**kwargs)  # type: ignore[no-any-return]
File "/usr/local/lib/python3.10/dist-packages/flask_restful/init.py", line 604, in dispatch_request
resp = meth(*args, **kwargs)
File "/nemo_run/code/nemo_skills/inference/server/serve_trt.py", line 137, in put
return jsonify(self.get_result(input_request['generation_id']))
File "/nemo_run/code/nemo_skills/inference/server/serve_trt.py", line 130, in get_result
return self.model.get_result(idx)
File "/nemo_run/code/nemo_skills/inference/server/serve_trt.py", line 524, in get_result
result = self.requests.pop(idx).result()
File "/usr/lib/python3.10/concurrent/futures/_base.py", line 451, in result
return self.__get_result()
File "/usr/lib/python3.10/concurrent/futures/_base.py", line 403, in __get_result
raise self._exception
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
result = self.fn(*self.args, **self.kwargs)
File "/nemo_run/code/nemo_skills/inference/server/serve_trt.py", line 494, in get_output
output = generate(
File "/nemo_run/code/nemo_skills/inference/server/serve_trt.py", line 311, in generate
sampling_config = trtllm.SamplingConfig(**sampling_params)
TypeError: init(): incompatible constructor arguments. The following argument types are supported:

tensorrt_llm.bindings.executor.SamplingConfig(beam_width: int = 1, top_k: Optional[int] = None, top_p: Optional[float] = None, top_p_min: Optional[float] = None, top_p_reset_ids: Optional[int] = None, top_p_decay: Optional[float] = None, random_seed: Optional[int] = None, temperature: Optional[float] = None, min_length: Optional[int] = None, beam_search_diversity_rate: Optional[float] = None, repetition_penalty: Optional[float] = None, presence_penalty: Optional[float] = None, frequency_penalty: Optional[float] = None, length_penalty: Optional[float] = None, early_stopping: Optional[int] = None, no_repeat_ngram_size: Optional[int] = None)

another log also has
Waiting for the server to start at localhost:5000
Evaluating benchmark gsm8k
2024-11-10 17:13:19 INFO  Config used: GenerateSolutionsConfig(output_file='/workspace/openmath2-llama3.1-8b-eval/eval-results/gsm8k/output-greedy.jsonl', server={'server_type': 'trtllm'}, sandbox={}, prompt_template='llama3-instruct', prompt_config=None, examples_type=None, inference=InferenceConfig(temperature=0.0, top_k=0, top_p=0.95, random_seed=0, tokens_to_generate=4096, repetition_penalty=1.0), dataset='gsm8k', split='test', input_file=PosixPath('/nemo_run/code/nemo_skills/dataset/gsm8k/test.jsonl'), batch_size=512, max_samples=-1, skip_filled=False, offset=0, generation_key='generation', multi_turn_key=None, dry_run=False, code_execution=False)
2024-11-10 17:13:19 INFO  Prompt used: PromptConfig(user='Solve the following math problem. Make sure to put the answer (and only answer) inside \boxed{{}}.\n\n{examples}{problem}', system='', template=PromptTemplate(text_begin='<|begin_of_text|>', system_begin='<|start_header_id|>system<|end_header_id|>\n\n', system_end='<|eot_id|>', user_begin='<|start_header_id|>user<|end_header_id|>\n\n', user_end='<|eot_id|>', assistant_begin='<|start_header_id|>assistant<|end_header_id|>\n\n', assistant_end='<|eot_id|>', stop_phrases=['<|eot_id|>'], code_begin='<|python_tag|>', code_end='<|eom_id|>', code_output_begin='<|start_header_id|>ipython<|end_header_id|>', code_output_end='<|eot_id|><|start_header_id|>assistant<|end_header_id|>', code_output_format='llama'), few_shot_examples=FewShotExamplesConfig(prefix='Here are some examples of problems and solutions you can refer to.\n\n', template='Problem:\n{problem}\n\nSolution:\n{solution}\n\n\n\n\n\n', suffix='Here is the problem you need to solve:\n', examples_type=None, retrieval_field=None, retrieval_file=None, retrieved_entries=10, retrieved_few_shots=5, randomize_retrieved_entries=False, max_retrieved_chars=100000000, max_retrieved_chars_field='reference_solution', retriever=None))
2024-11-10 17:13:19 INFO  Example prompt:
Data dictionary: {'problem': "Janet’s ducks lay 16 eggs per day. She eats three for breakfast every morning and bakes muffins for her friends every day with four. She sells the remainder at the farmers' market daily for $2 per fresh duck egg. How much in dollars does she make every day at the farmers' market?", 'expected_answer': 18, 'reference_solution': 'Janet sells 16 - 3 - 4 = 9 duck eggs a day.\nShe makes 9 * 2 = $18 every day at the farmer’s market.\n'}
Prompt: <|begin_of_text|><|start_header_id|>system<|end_header_id|>
<|eot_id|><|start_header_id|>user<|end_header_id|>
Solve the following math problem. Make sure to put the answer (and only answer) inside \boxed{}.
Janet’s ducks lay 16 eggs per day. She eats three for breakfast every morning and bakes muffins for her friends every day with four. She sells the remainder at the farmers' market daily for $2 per fresh duck egg. How much in dollars does she make every day at the farmers' market?<|eot_id|><|start_header_id|>assistant<|end_header_id|>
0%|          | 0/1319 [00:00<?, ?it/s]
39%|███▊      | 511/1319 [00:02<00:03, 212.83it/s]
Error executing job with overrides: ['++dataset=gsm8k', '++split=test', '++output_file=/workspace/openmath2-llama3.1-8b-eval/eval-results/gsm8k/output-greedy.jsonl', '++prompt_template=llama3-instruct', '++batch_size=512', '++inference.tokens_to_generate=4096', '++server.server_type=trtllm']
Traceback (most recent call last):
File "/nemo_run/code/nemo_skills/inference/generate.py", line 226, in generate
outputs = llm.generate(
File "/nemo_run/code/nemo_skills/inference/server/model.py", line 182, in generate
postprocess_output(outputs, stop_phrases)
File "/nemo_run/code/nemo_skills/inference/server/model.py", line 53, in postprocess_output
output['generation'] = trim_after_stop_phrases(output['generation'], stop_phrases)
File "/nemo_run/code/nemo_skills/inference/server/model.py", line 37, in trim_after_stop_phrases
return re.split("|".join(escaped_stop_phrases), text, maxsplit=1)[0]
File "/usr/local/lib/python3.10/re.py", line 230, in split
return _compile(pattern, flags).split(string, maxsplit)
TypeError: expected string or bytes-like object
Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.

That's strange.. Can you please try to run with ++batch_size=1 and see if anything changes?

similar with batch_size=1
workspace$ ns eval     --cluster=local     --model=/workspace/openmath2-llama3.1-8b-trtllm     --server_type=trtllm     --output_dir=/workspace/openmath2-llama3.1-8b-eval     --benchmarks=gsm8k:0     --server_gpus=1     --num_jobs=1     ++prompt_template=llama3-instruct     ++batch_size=1     ++inference.tokens_to_generate=4096
2024-11-10 17:44:49 INFO  Starting evaluation job
2024-11-10 17:44:49 INFO  Extra arguments that will be passed to the underlying script: ++prompt_template=llama3-instruct ++batch_size=1 ++inference.tokens_to_generate=4096
──────────────────────────────────────────────────────────────────────────────────────────────────── Entering Experiment eval with id: eval_1731260689 ─────────────────────────────────────────────────────────────────────────────────────────────────────
[17:44:49] INFO     Launching task with command echo "Evaluating benchmark gsm8k" && python -m nemo_skills.inference.generate     ++dataset=gsm8k     ++split=test                                                                               eval.py:179
++output_file=/workspace/openmath2-llama3.1-8b-eval/eval-results/gsm8k/output-greedy.jsonl      ++prompt_template=llama3-instruct ++batch_size=1 ++inference.tokens_to_generate=4096 ++server.server_type=trtllm  && python
-m nemo_skills.evaluation.evaluate_results     ++input_files=/workspace/openmath2-llama3.1-8b-eval/eval-results/gsm8k/output-greedy.jsonl ++eval_type=math
WARNING  Not running from a git repo, trying to upload installed package. Make sure there are no extra files in /home/ubuntu/NeMo-Skills/nemo_skills/*                                                                               utils.py:392
WARNING  Not running from a git repo, trying to upload installed package. Make sure there are no extra files in /home/ubuntu/NeMo-Skills/nemo_skills/*                                                                               utils.py:392
WARNING  Not running from a git repo, trying to upload installed package. Make sure there are no extra files in /home/ubuntu/NeMo-Skills/nemo_skills/*                                                                               utils.py:392
[17:44:49] Launching job nemo-run for experiment eval                                                                                experiment.py:693
[17:44:57] INFO     Pulling container image: igitman/nemo-skills-sandbox:0.4.1 (this may take a while)                                                                                docker.py:113
INFO     Pulling container image: igitman/nemo-skills:0.4.1 (this may take a while)                                                                                docker.py:113
INFO     Pulling container image: igitman/nemo-skills-trtllm:0.4.1 (this may take a while)                                                                                docker.py:113
[17:45:00] INFO     Launched app: docker_persistent://nemo_run/nemo-run-xvjln436j2sms                                                                                launcher.py:111
INFO     AppStatus:                                                                                launcher.py:114
State: RUNNING
Num Restarts: -1
Roles:
*nemo-run-0[0]:RUNNING
*nemo-run-1[0]:RUNNING
*nemo-run-2[0]:RUNNING
Msg:
Structured Error Msg:
UI URL: None
───────────────────────────────────────────────────────────────────────────────────────────────────── Waiting for Experiment eval_1731260689 to finish ─────────────────────────────────────────────────────────────────────────────────────────────────────
Experiment Status for eval_1731260689
Task 0: nemo-run

Status: RUNNING

Executor: DockerExecutor

Job id: nemo-run-xvjln436j2sms

Local Directory: /home/ubuntu/.nemo_run/experiments/eval/eval_1731260689/nemo-run
     INFO     Waiting for job nemo-run-xvjln436j2sms to finish [log=True]...                                                                                launcher.py:132

nemo-run-0/0
nemo-run-0/0 ==========
nemo-run-0/0 == CUDA ==
nemo-run-0/0 ==========
nemo-run-0/0
nemo-run-0/0 CUDA Version 12.5.1
nemo-run-0/0
nemo-run-0/0 Container image Copyright (c) 2016-2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
nemo-run-0/0
nemo-run-0/0 This container image and its contents are governed by the NVIDIA Deep Learning Container License.
nemo-run-0/0 By pulling and using the container, you accept the terms and conditions of this license:
nemo-run-0/0 https://developer.nvidia.com/ngc/nvidia-deep-learning-container-license
nemo-run-0/0
nemo-run-0/0 A copy of this license is made available in this container at /NGC-DL-CONTAINER-LICENSE for your convenience.
nemo-run-0/0
nemo-run-0/0 Sun Nov 10 17:44:59 2024
nemo-run-0/0 +-----------------------------------------------------------------------------------------+
nemo-run-0/0 | NVIDIA-SMI 550.90.07              Driver Version: 550.90.07      CUDA Version: 12.5     |
nemo-run-2/0 Checking for script in /app/prestart.sh
nemo-run-0/0 |-----------------------------------------+------------------------+----------------------+
nemo-run-1/0 Waiting for the server to start at localhost:5000
nemo-run-0/0 | GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
nemo-run-2/0 Running script /app/prestart.sh
nemo-run-0/0 | Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
nemo-run-0/0 |                                         |                        |               MIG M. |
nemo-run-2/0 Running inside /app/prestart.sh, you could add migrations to this file, e.g.:
nemo-run-0/0 |=========================================+========================+======================|
nemo-run-2/0
nemo-run-0/0 |   0  NVIDIA A10G                    On  |   00000000:00:1E.0 Off |                    0 |
nemo-run-2/0 #! /usr/bin/env sh
nemo-run-0/0 |  0%   22C    P8             15W /  300W |       1MiB /  23028MiB |      0%      Default |
nemo-run-2/0
nemo-run-0/0 |                                         |                        |                  N/A |
nemo-run-2/0 # Let the DB start
nemo-run-0/0 +-----------------------------------------+------------------------+----------------------+
nemo-run-2/0 sleep 10;
nemo-run-0/0
nemo-run-2/0 # Run migrations
nemo-run-0/0 +-----------------------------------------------------------------------------------------+
nemo-run-2/0 alembic upgrade head
nemo-run-0/0 | Processes:                                                                              |
nemo-run-2/0
nemo-run-0/0 |  GPU   GI   CI        PID   Type   Process name                              GPU Memory |
nemo-run-0/0 |        ID   ID                                                               Usage      |
nemo-run-0/0 |=========================================================================================|
nemo-run-0/0 |  No running processes found                                                             |
nemo-run-0/0 +-----------------------------------------------------------------------------------------+
nemo-run-2/0 /usr/lib/python3/dist-packages/supervisor/options.py:474: UserWarning: Supervisord is running as root and it is searching for its configuration file in default locations (including its current working directory); you probably want to specify a "-c" argument specifying an absolute path to a configuration file for improved security.
nemo-run-2/0   self.warnings.warn(
nemo-run-2/0 2024-11-10 17:45:00,577 CRIT Supervisor is running as root.  Privileges were not dropped because no user is specified in the config file.  If you intend to run as root, you can set user=root in the config file to avoid this message.
nemo-run-2/0 2024-11-10 17:45:00,577 INFO Included extra file "/etc/supervisor/conf.d/supervisord.conf" during parsing
nemo-run-2/0 2024-11-10 17:45:00,584 INFO RPC interface 'supervisor' initialized
nemo-run-2/0 2024-11-10 17:45:00,584 CRIT Server 'unix_http_server' running without any HTTP authentication checking
nemo-run-2/0 2024-11-10 17:45:00,584 INFO supervisord started with pid 12
nemo-run-2/0 2024-11-10 17:45:01,587 INFO spawned: 'quit_on_failure' with pid 13
nemo-run-2/0 2024-11-10 17:45:01,588 INFO spawned: 'nginx' with pid 14
nemo-run-2/0 2024-11-10 17:45:01,590 INFO spawned: 'uwsgi' with pid 15
nemo-run-2/0 2024-11-10 17:45:01,592 INFO success: nginx entered RUNNING state, process has stayed up for > than 0 seconds (startsecs)
nemo-run-2/0 2024-11-10 17:45:01,592 INFO success: uwsgi entered RUNNING state, process has stayed up for > than 0 seconds (startsecs)
nemo-run-2/0 [uWSGI] getting INI configuration from /app/uwsgi.ini
nemo-run-2/0 [uWSGI] getting INI configuration from /etc/uwsgi/uwsgi.ini
nemo-run-2/0
nemo-run-2/0 ;uWSGI instance configuration
nemo-run-2/0 [uwsgi]
nemo-run-2/0 ini = /app/uwsgi.ini
nemo-run-2/0 module = main
nemo-run-2/0 callable = app
nemo-run-2/0 processes = 240
nemo-run-2/0 cheaper = 24
nemo-run-2/0 ini = /etc/uwsgi/uwsgi.ini
nemo-run-2/0 socket = /tmp/uwsgi.sock
nemo-run-2/0 chown-socket = nginx:nginx
nemo-run-2/0 chmod-socket = 664
nemo-run-2/0 hook-master-start = unix_signal:15 gracefully_kill_them_all
nemo-run-2/0 need-app = true
nemo-run-2/0 die-on-term = true
nemo-run-2/0 show-config = true
nemo-run-2/0 ;end of configuration
nemo-run-2/0
nemo-run-2/0 *** Starting uWSGI 2.0.26 (64bit) on [Sun Nov 10 17:45:01 2024] ***
nemo-run-2/0 compiled with version: 10.2.1 20210110 on 23 September 2024 00:25:14
nemo-run-2/0 os: Linux-6.8.0-1015-aws #16~22.04.1-Ubuntu SMP Mon Aug 19 19:38:17 UTC 2024
nemo-run-2/0 nodename: nemo-run-2
nemo-run-2/0 machine: x86_64
nemo-run-2/0 clock source: unix
nemo-run-2/0 pcre jit disabled
nemo-run-2/0 detected number of CPU cores: 8
nemo-run-2/0 current working directory: /nemo_run/code
nemo-run-2/0 detected binary path: /usr/local/bin/uwsgi
nemo-run-2/0 your memory page size is 4096 bytes
nemo-run-2/0 detected max file descriptor number: 1048576
nemo-run-2/0 lock engine: pthread robust mutexes
nemo-run-2/0 thunder lock: disabled (you can enable it with --thunder-lock)
nemo-run-2/0 uwsgi socket 0 bound to UNIX address /tmp/uwsgi.sock fd 3
nemo-run-2/0 uWSGI running as root, you can use --uid/--gid/--chroot options
nemo-run-2/0 *** WARNING: you are running uWSGI as root !!! (use the --uid flag) ***
nemo-run-2/0 Python version: 3.10.15 (main, Sep 12 2024, 21:08:59) [GCC 10.2.1 20210110]
nemo-run-2/0 *** Python threads support is disabled. You can enable it with --enable-threads ***
nemo-run-2/0 Python main interpreter initialized at 0x5b30aea13c50
nemo-run-2/0 uWSGI running as root, you can use --uid/--gid/--chroot options
nemo-run-2/0 *** WARNING: you are running uWSGI as root !!! (use the --uid flag) ***
nemo-run-2/0 your server socket listen backlog is limited to 100 connections
nemo-run-2/0 your mercy for graceful operations on workers is 60 seconds
nemo-run-2/0 mapped 17573720 bytes (17161 KB) for 240 cores
nemo-run-2/0 *** Operational MODE: preforking ***
nemo-run-2/0 WSGI app 0 (mountpoint='') ready in 1 seconds on interpreter 0x5b30aea13c50 pid: 15 (default app)
nemo-run-2/0 uWSGI running as root, you can use --uid/--gid/--chroot options
nemo-run-2/0 *** WARNING: you are running uWSGI as root !!! (use the --uid flag) ***
nemo-run-2/0 *** uWSGI is running in multiple interpreter mode ***
nemo-run-2/0 spawned uWSGI master process (pid: 15)
nemo-run-2/0 spawned uWSGI worker 1 (pid: 17, cores: 1)
nemo-run-2/0 spawned uWSGI worker 2 (pid: 18, cores: 1)
nemo-run-2/0 spawned uWSGI worker 3 (pid: 19, cores: 1)
nemo-run-2/0 spawned uWSGI worker 4 (pid: 20, cores: 1)
nemo-run-2/0 spawned uWSGI worker 5 (pid: 21, cores: 1)
nemo-run-2/0 spawned uWSGI worker 6 (pid: 22, cores: 1)
nemo-run-2/0 spawned uWSGI worker 7 (pid: 23, cores: 1)
nemo-run-2/0 spawned uWSGI worker 8 (pid: 24, cores: 1)
nemo-run-2/0 spawned uWSGI worker 9 (pid: 25, cores: 1)
nemo-run-2/0 spawned uWSGI worker 10 (pid: 26, cores: 1)
nemo-run-2/0 spawned uWSGI worker 11 (pid: 27, cores: 1)
nemo-run-2/0 spawned uWSGI worker 12 (pid: 28, cores: 1)
nemo-run-2/0 spawned uWSGI worker 13 (pid: 29, cores: 1)
nemo-run-2/0 spawned uWSGI worker 14 (pid: 30, cores: 1)
nemo-run-2/0 spawned uWSGI worker 15 (pid: 31, cores: 1)
nemo-run-2/0 spawned uWSGI worker 16 (pid: 32, cores: 1)
nemo-run-2/0 spawned uWSGI worker 17 (pid: 33, cores: 1)
nemo-run-2/0 spawned uWSGI worker 18 (pid: 34, cores: 1)
nemo-run-2/0 spawned uWSGI worker 19 (pid: 35, cores: 1)
nemo-run-2/0 spawned uWSGI worker 20 (pid: 36, cores: 1)
nemo-run-2/0 spawned uWSGI worker 21 (pid: 37, cores: 1)
nemo-run-2/0 spawned uWSGI worker 22 (pid: 38, cores: 1)
nemo-run-2/0 spawned uWSGI worker 23 (pid: 39, cores: 1)
nemo-run-2/0 spawned uWSGI worker 24 (pid: 40, cores: 1)
nemo-run-2/0 running "unix_signal:15 gracefully_kill_them_all" (master-start)...
nemo-run-2/0 2024-11-10 17:45:03,375 INFO success: quit_on_failure entered RUNNING state, process has stayed up for > than 1 seconds (startsecs)
nemo-run-2/0 <IP_ADDRESS> - - [10/Nov/2024:17:45:05 +0000] "l\x00\x0B\x00\x00\x00\x00\x00\x00\x00\x00\x00" 400 157 "-" "-" "-"
nemo-run-2/0 <IP_ADDRESS> - - [10/Nov/2024:17:45:05 +0000] "l\x00\x0B\x00\x00\x00\x00\x00\x00\x00\x00\x00" 400 157 "-" "-" "-"
nemo-run-2/0 <IP_ADDRESS> - - [10/Nov/2024:17:45:05 +0000] "l\x00\x0B\x00\x00\x00\x00\x00\x00\x00\x00\x00" 400 157 "-" "-" "-"
nemo-run-0/0 [TensorRT-LLM] TensorRT-LLM version: 0.12.0
nemo-run-0/0 [TensorRT-LLM][INFO] Engine version 0.12.0 found in the config file, assuming engine(s) built by new builder API.
nemo-run-0/0 [TensorRT-LLM][INFO] MPI size: 1, MPI local size: 1, rank: 0
nemo-run-0/0 [TensorRT-LLM][INFO] Engine version 0.12.0 found in the config file, assuming engine(s) built by new builder API.
nemo-run-0/0 [TensorRT-LLM][INFO] Refreshed the MPI local session
nemo-run-0/0 [TensorRT-LLM][INFO] MPI size: 1, MPI local size: 1, rank: 0
nemo-run-0/0 [TensorRT-LLM][INFO] Rank 0 is using GPU 0
nemo-run-0/0 [TensorRT-LLM][INFO] TRTGptModel maxNumSequences: 128
nemo-run-0/0 [TensorRT-LLM][INFO] TRTGptModel maxBatchSize: 128
nemo-run-0/0 [TensorRT-LLM][INFO] TRTGptModel maxBeamWidth: 1
nemo-run-0/0 [TensorRT-LLM][INFO] TRTGptModel maxSequenceLen: 8192
nemo-run-0/0 [TensorRT-LLM][INFO] TRTGptModel maxDraftLen: 0
nemo-run-0/0 [TensorRT-LLM][INFO] TRTGptModel mMaxAttentionWindowSize: 8192
nemo-run-0/0 [TensorRT-LLM][INFO] TRTGptModel enableTrtOverlap: 0
nemo-run-0/0 [TensorRT-LLM][INFO] TRTGptModel normalizeLogProbs: 1
nemo-run-0/0 [TensorRT-LLM][INFO] TRTGptModel maxNumTokens: 8192
nemo-run-0/0 [TensorRT-LLM][INFO] TRTGptModel maxInputLen: 8191  = maxSequenceLen - 1 since chunked context is enabled
nemo-run-0/0 [TensorRT-LLM][INFO] TRTGptModel If model type is encoder, maxInputLen would be reset in trtEncoderModel to maxInputLen: 8192 = maxSequenceLen.
nemo-run-0/0 [TensorRT-LLM][INFO] Capacity Scheduler Policy: GUARANTEED_NO_EVICT
nemo-run-0/0 [TensorRT-LLM][INFO] Context Chunking Scheduler Policy: None
nemo-run-0/0 [TensorRT-LLM][INFO] Loaded engine size: 15403 MiB
nemo-run-0/0 [TensorRT-LLM][INFO] [MemUsageChange] Allocated 928.01 MiB for execution context memory.
nemo-run-0/0 [TensorRT-LLM][INFO] [MemUsageChange] TensorRT-managed allocation in IExecutionContext creation: CPU +0, GPU +0, now: CPU 0, GPU 15380 (MiB)
nemo-run-0/0 [TensorRT-LLM][INFO] [MemUsageChange] Allocated 86.66 MB GPU memory for runtime buffers.
nemo-run-0/0 [TensorRT-LLM][INFO] [MemUsageChange] Allocated 337.15 MB GPU memory for decoder.
nemo-run-0/0 [TensorRT-LLM][INFO] Memory usage when calculating max tokens in paged kv cache: total: 21.98 GiB, available: 5.31 GiB
nemo-run-0/0 [TensorRT-LLM][INFO] Number of blocks in KV cache primary pool: 612
nemo-run-0/0 [TensorRT-LLM][INFO] Number of blocks in KV cache secondary pool: 0, onboard blocks to primary memory before reuse: true
nemo-run-0/0 [TensorRT-LLM][INFO] Max KV cache pages per sequence: 128
nemo-run-0/0 [TensorRT-LLM][INFO] Number of tokens per block: 64.
nemo-run-0/0 [TensorRT-LLM][INFO] [MemUsageChange] Allocated 4.78 GiB for max tokens in paged KV cache (39168).
nemo-run-0/0  * Serving Flask app '/nemo_run/code/nemo_skills/inference/server/serve_trt.py'
nemo-run-0/0  * Debug mode: off
nemo-run-0/0 [11/10/2024-17:47:21] WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead.
nemo-run-0/0  * Running on all addresses (<IP_ADDRESS>)
nemo-run-0/0  * Running on http://<IP_ADDRESS>:5000
nemo-run-0/0  * Running on http://<IP_ADDRESS>:5000
nemo-run-0/0 WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead.
nemo-run-0/0  * Running on all addresses (<IP_ADDRESS>)
nemo-run-0/0  * Running on http://<IP_ADDRESS>:5000
nemo-run-0/0  * Running on http://<IP_ADDRESS>:5000
nemo-run-0/0 [11/10/2024-17:47:21] Press CTRL+C to quit
nemo-run-0/0 Press CTRL+C to quit
nemo-run-0/0 [11/10/2024-17:47:21] <IP_ADDRESS> - - [10/Nov/2024 17:47:21] "PUT / HTTP/1.1" 404 -
nemo-run-0/0 <IP_ADDRESS> - - [10/Nov/2024 17:47:21] "PUT / HTTP/1.1" 404 -
nemo-run-1/0 Evaluating benchmark gsm8k
nemo-run-1/0 2024-11-10 17:47:23 INFO  Config used: GenerateSolutionsConfig(output_file='/workspace/openmath2-llama3.1-8b-eval/eval-results/gsm8k/output-greedy.jsonl', server={'server_type': 'trtllm'}, sandbox={}, prompt_template='llama3-instruct', prompt_config=None, examples_type=None, inference=InferenceConfig(temperature=0.0, top_k=0, top_p=0.95, random_seed=0, tokens_to_generate=4096, repetition_penalty=1.0), dataset='gsm8k', split='test', input_file=PosixPath('/nemo_run/code/nemo_skills/dataset/gsm8k/test.jsonl'), batch_size=1, max_samples=-1, skip_filled=False, offset=0, generation_key='generation', multi_turn_key=None, dry_run=False, code_execution=False)
nemo-run-1/0 2024-11-10 17:47:23 INFO  Prompt used: PromptConfig(user='Solve the following math problem. Make sure to put the answer (and only answer) inside \boxed{{}}.\n\n{examples}{problem}', system='', template=PromptTemplate(text_begin='<|begin_of_text|>', system_begin='<|start_header_id|>system<|end_header_id|>\n\n', system_end='<|eot_id|>', user_begin='<|start_header_id|>user<|end_header_id|>\n\n', user_end='<|eot_id|>', assistant_begin='<|start_header_id|>assistant<|end_header_id|>\n\n', assistant_end='<|eot_id|>', stop_phrases=['<|eot_id|>'], code_begin='<|python_tag|>', code_end='<|eom_id|>', code_output_begin='<|start_header_id|>ipython<|end_header_id|>', code_output_end='<|eot_id|><|start_header_id|>assistant<|end_header_id|>', code_output_format='llama'), few_shot_examples=FewShotExamplesConfig(prefix='Here are some examples of problems and solutions you can refer to.\n\n', template='Problem:\n{problem}\n\nSolution:\n{solution}\n\n\n\n\n\n', suffix='Here is the problem you need to solve:\n', examples_type=None, retrieval_field=None, retrieval_file=None, retrieved_entries=10, retrieved_few_shots=5, randomize_retrieved_entries=False, max_retrieved_chars=100000000, max_retrieved_chars_field='reference_solution', retriever=None))
nemo-run-1/0 2024-11-10 17:47:23 INFO  Example prompt:
nemo-run-1/0 Data dictionary: {'problem': "Janet’s ducks lay 16 eggs per day. She eats three for breakfast every morning and bakes muffins for her friends every day with four. She sells the remainder at the farmers' market daily for $2 per fresh duck egg. How much in dollars does she make every day at the farmers' market?", 'expected_answer': 18, 'reference_solution': 'Janet sells 16 - 3 - 4 = 9 duck eggs a day.\nShe makes 9 * 2 = $18 every day at the farmer’s market.\n'}
nemo-run-1/0 Prompt: <|begin_of_text|><|start_header_id|>system<|end_header_id|>
nemo-run-1/0
nemo-run-1/0 <|eot_id|><|start_header_id|>user<|end_header_id|>
nemo-run-1/0
nemo-run-1/0 Solve the following math problem. Make sure to put the answer (and only answer) inside \boxed{}.
nemo-run-1/0
nemo-run-1/0 Janet’s ducks lay 16 eggs per day. She eats three for breakfast every morning and bakes muffins for her friends every day with four. She sells the remainder at the farmers' market daily for $2 per fresh duck egg. How much in dollars does she make every day at the farmers' market?<|eot_id|><|start_header_id|>assistant<|end_header_id|>
nemo-run-1/0
nemo-run-1/0
nemo-run-0/0 [11/10/2024-17:47:23] Exception on /get_result [PUT]
nemo-run-0/0 Traceback (most recent call last):
nemo-run-0/0   File "/usr/local/lib/python3.10/dist-packages/flask/app.py", line 880, in full_dispatch_request
nemo-run-0/0     rv = self.dispatch_request()
nemo-run-0/0   File "/usr/local/lib/python3.10/dist-packages/flask/app.py", line 865, in dispatch_request
nemo-run-0/0     return self.ensure_sync(self.view_functions[rule.endpoint])(**view_args)  # type: ignore[no-any-return]
nemo-run-0/0   File "/usr/local/lib/python3.10/dist-packages/flask_restful/init.py", line 489, in wrapper
nemo-run-0/0     resp = resource(*args, **kwargs)
nemo-run-0/0   File "/usr/local/lib/python3.10/dist-packages/flask/views.py", line 110, in view
nemo-run-0/0     return current_app.ensure_sync(self.dispatch_request)(**kwargs)  # type: ignore[no-any-return]
nemo-run-0/0   File "/usr/local/lib/python3.10/dist-packages/flask_restful/init.py", line 604, in dispatch_request
nemo-run-0/0     resp = meth(*args, **kwargs)
nemo-run-0/0   File "/nemo_run/code/nemo_skills/inference/server/serve_trt.py", line 137, in put
nemo-run-0/0     return jsonify(self.get_result(input_request['generation_id']))
nemo-run-0/0   File "/nemo_run/code/nemo_skills/inference/server/serve_trt.py", line 130, in get_result
nemo-run-0/0     return self.model.get_result(idx)
nemo-run-0/0   File "/nemo_run/code/nemo_skills/inference/server/serve_trt.py", line 524, in get_result
nemo-run-0/0     result = self.requests.pop(idx).result()
nemo-run-0/0   File "/usr/lib/python3.10/concurrent/futures/_base.py", line 451, in result
nemo-run-0/0     return self.__get_result()
nemo-run-0/0   File "/usr/lib/python3.10/concurrent/futures/_base.py", line 403, in __get_result
nemo-run-0/0     raise self._exception
nemo-run-0/0   File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
nemo-run-0/0     result = self.fn(*self.args, **self.kwargs)
nemo-run-0/0   File "/nemo_run/code/nemo_skills/inference/server/serve_trt.py", line 494, in get_output
nemo-run-1/0   0%|          | 0/1319 [00:00<?, ?it/s]
nemo-run-0/0     output = generate(
nemo-run-1/0 Error executing job with overrides: ['++dataset=gsm8k', '++split=test', '++output_file=/workspace/openmath2-llama3.1-8b-eval/eval-results/gsm8k/output-greedy.jsonl', '++prompt_template=llama3-instruct', '++batch_size=1', '++inference.tokens_to_generate=4096', '++server.server_type=trtllm']
nemo-run-0/0   File "/nemo_run/code/nemo_skills/inference/server/serve_trt.py", line 311, in generate
nemo-run-0/0     sampling_config = trtllm.SamplingConfig(**sampling_params)
nemo-run-0/0 TypeError: init(): incompatible constructor arguments. The following argument types are supported:
nemo-run-0/0     1. tensorrt_llm.bindings.executor.SamplingConfig(beam_width: int = 1, top_k: Optional[int] = None, top_p: Optional[float] = None, top_p_min: Optional[float] = None, top_p_reset_ids: Optional[int] = None, top_p_decay: Optional[float] = None, random_seed: Optional[int] = None, temperature: Optional[float] = None, min_length: Optional[int] = None, beam_search_diversity_rate: Optional[float] = None, repetition_penalty: Optional[float] = None, presence_penalty: Optional[float] = None, frequency_penalty: Optional[float] = None, length_penalty: Optional[float] = None, early_stopping: Optional[int] = None, no_repeat_ngram_size: Optional[int] = None)
nemo-run-0/0
nemo-run-0/0 Invoked with: kwargs: temperature=1.0, top_k=1, top_p=1.0, repetition_penalty=1.0, seed=0
nemo-run-0/0 Exception on /get_result [PUT]
nemo-run-0/0 Traceback (most recent call last):
nemo-run-0/0   File "/usr/local/lib/python3.10/dist-packages/flask/app.py", line 880, in full_dispatch_request
nemo-run-0/0     rv = self.dispatch_request()
nemo-run-0/0   File "/usr/local/lib/python3.10/dist-packages/flask/app.py", line 865, in dispatch_request
nemo-run-0/0     return self.ensure_sync(self.view_functions[rule.endpoint])(**view_args)  # type: ignore[no-any-return]
nemo-run-0/0   File "/usr/local/lib/python3.10/dist-packages/flask_restful/init.py", line 489, in wrapper
nemo-run-0/0     resp = resource(*args, **kwargs)
nemo-run-0/0   File "/usr/local/lib/python3.10/dist-packages/flask/views.py", line 110, in view
nemo-run-0/0     return current_app.ensure_sync(self.dispatch_request)(**kwargs)  # type: ignore[no-any-return]
nemo-run-0/0   File "/usr/local/lib/python3.10/dist-packages/flask_restful/init.py", line 604, in dispatch_request
nemo-run-0/0     resp = meth(*args, **kwargs)
nemo-run-0/0   File "/nemo_run/code/nemo_skills/inference/server/serve_trt.py", line 137, in put
nemo-run-0/0     return jsonify(self.get_result(input_request['generation_id']))
nemo-run-0/0   File "/nemo_run/code/nemo_skills/inference/server/serve_trt.py", line 130, in get_result
nemo-run-0/0     return self.model.get_result(idx)
nemo-run-0/0   File "/nemo_run/code/nemo_skills/inference/server/serve_trt.py", line 524, in get_result
nemo-run-0/0     result = self.requests.pop(idx).result()
nemo-run-0/0   File "/usr/lib/python3.10/concurrent/futures/_base.py", line 451, in result
nemo-run-0/0     return self.__get_result()
nemo-run-0/0   File "/usr/lib/python3.10/concurrent/futures/_base.py", line 403, in __get_result
nemo-run-0/0     raise self._exception
nemo-run-0/0   File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
nemo-run-0/0     result = self.fn(*self.args, **self.kwargs)
nemo-run-0/0   File "/nemo_run/code/nemo_skills/inference/server/serve_trt.py", line 494, in get_output
nemo-run-0/0     output = generate(
nemo-run-0/0   File "/nemo_run/code/nemo_skills/inference/server/serve_trt.py", line 311, in generate
nemo-run-0/0     sampling_config = trtllm.SamplingConfig(**sampling_params)
nemo-run-0/0 TypeError: init(): incompatible constructor arguments. The following argument types are supported:
nemo-run-0/0     1. tensorrt_llm.bindings.executor.SamplingConfig(beam_width: int = 1, top_k: Optional[int] = None, top_p: Optional[float] = None, top_p_min: Optional[float] = None, top_p_reset_ids: Optional[int] = None, top_p_decay: Optional[float] = None, random_seed: Optional[int] = None, temperature: Optional[float] = None, min_length: Optional[int] = None, beam_search_diversity_rate: Optional[float] = None, repetition_penalty: Optional[float] = None, presence_penalty: Optional[float] = None, frequency_penalty: Optional[float] = None, length_penalty: Optional[float] = None, early_stopping: Optional[int] = None, no_repeat_ngram_size: Optional[int] = None)
nemo-run-0/0
nemo-run-0/0 Invoked with: kwargs: temperature=1.0, top_k=1, top_p=1.0, repetition_penalty=1.0, seed=0
nemo-run-0/0 [11/10/2024-17:47:23] <IP_ADDRESS> - - [10/Nov/2024 17:47:23] "PUT /get_result HTTP/1.1" 500 -
nemo-run-0/0 <IP_ADDRESS> - - [10/Nov/2024 17:47:23] "PUT /get_result HTTP/1.1" 500 -
nemo-run-1/0 Traceback (most recent call last):
nemo-run-1/0   File "/nemo_run/code/nemo_skills/inference/generate.py", line 226, in generate
nemo-run-1/0     outputs = llm.generate(
nemo-run-1/0   File "/nemo_run/code/nemo_skills/inference/server/model.py", line 182, in generate
nemo-run-1/0     postprocess_output(outputs, stop_phrases)
nemo-run-1/0   File "/nemo_run/code/nemo_skills/inference/server/model.py", line 53, in postprocess_output
nemo-run-1/0     output['generation'] = trim_after_stop_phrases(output['generation'], stop_phrases)
nemo-run-1/0   File "/nemo_run/code/nemo_skills/inference/server/model.py", line 37, in trim_after_stop_phrases
nemo-run-1/0     return re.split("|".join(escaped_stop_phrases), text, maxsplit=1)[0]
nemo-run-1/0   File "/usr/local/lib/python3.10/re.py", line 230, in split
nemo-run-1/0     return _compile(pattern, flags).split(string, maxsplit)
nemo-run-1/0 TypeError: expected string or bytes-like object
nemo-run-1/0
nemo-run-1/0 Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.

Actually, from the trtllm version it looks like your config file doesn't match the current code version. Can you please try to change all containers to what's in here https://github.com/Kipok/NeMo-Skills/blob/main/cluster_configs/example-local.yaml#L17 and redo the conversion/evaluation after that? Alternatively, you can go back to this commit and hopefully it will work as well 0f3e4c29ae7f063d5ab1c96cd37ee9d2f100c6c4

that worked! updated local.yaml versions to 0.4.2, successfully ran over the gsm8k 1319 test examples
thank you!!!


Another pass on Owners

Save before we edit an owner. If you were to unselect or add owners to a parcel then Click Edit and Save, since the Parcel was never saved it would undo all of this upon reloading.
Upon adding a new owner we do not want to reload the whole application as the owner has only been soft linked to the parcel, meaning reloading right away prevents the link from being done in the front end. So reload only owners when this happens.
Fix typo
Clear selected owner on NOIs when changing between Fee Simple -> Crown

lgtm


Variant Title issue - AJAX Cart

Hi there,
This might be an issue, or it might just be me...
The variant title at the moment current also puts in the some of the product title because my titles have hyphens in them. All I'm looking for is the item.variant.title. The issue seems to be this line:
var prodVariation = cartItem.title.replace(/^[^-]*/, "");
Is there a way to do this without using some strange replace technique on the full title?
Cheers
Sam

Aha... "You can use item.product_title and item.variant_title - a semi-recent and undocumented addition" - Gavin from TalkShopify
Also just realised this is available in the most recent version. My bad!


TS- DataDog errors - AWAF messages defined as metrics as opposed to logs

Environment
Telemetry Streaming Version: 1.28
BIG-IP Version: 16.1
AS3 Version: 3.35
Summary
Telemetry streaming is misclassifying ASM data as metrics when sending to DataDog.  No ASM data show up as DataDog logs instead data shows up as DataDog metrics.  Looking at live tail logs in DataDog shows no data.  Could the data being misclassified as metrics and send to DataDog metrics API vs DataDog log API?
Steps To Reproduce
Steps to reproduce the behavior:

Submit the following declaration:

{
    "class": "Telemetry",
    "My_System": {
        "class": "Telemetry_System",
        "systemPoller": {
            "interval": 60
        }
    },
    "My_Listener": {
        "class": "Telemetry_Listener",
        "port": 6514
    },
    "My_Consumer": {
        "class": "Telemetry_Consumer",
        "type": "Splunk",
        "host": "X.X.X.X",
        "protocol": "https",
        "port": 8088,
        "allowSelfSignedCert": true,
        "passphrase": {
            "cipherText": "*****key******"
        }
    },
    "My_Second_Consumer": {
        "class": "Telemetry_Consumer",
        "trace": true,
        "type": "DataDog",
        "apiKey": "******api_key******",
        "compressionType": "gzip",
        "region": "US1",
        "service": "f5-telemetry",
        "metricPrefix": ["f5", "bigip"],
        "convertBooleansToMetrics": true
    }
}

Observe the following messages in /var/temp/ response:

                    {
                        "host": "xxxx.bigip.xxxx.com",
                        "metric": "f5.bigip.violation_rating",
                        "points": [
                            [
<PHONE_NUMBER>.162,
                                0
                            ]
                        ],
                        "tags": [
                            "hostname:xxxx.bigip.xxxx.com",
                            "management_ip_address:X.X.X.X",
                            "management_ip_address_2:N/A",
                            "http_class_name:/Common/templates-default",
                            "web_application_name:/Common/templates-default",
                            "policy_name:/Common/templates-default",
                            "policy_apply_date:2021-08-10 12:12:05",
                            "violations:N/A",
                            "request_status:passed",
                            "ip_client:X.X.X.X",
                            "method:GET",
                            "protocol:HTTPS",
                            "query_string:id=72",
                            "x_forwarded_for_header_value:X.X.X.X",
                            "sig_ids:N/A",
                            "sig_names:N/A",
                            "severity:Informational",
                            "attack_type:N/A",
                            "geo_location:N/A",
                            "ip_address_intelligence:N/A",
                            "username:N/A",
                            "session_id:d57cf5e412d369b5",
                            "dest_ip:X.X.X.X",
                            "sub_violations:N/A",
                            "virus_name:N/A",
                            "websocket_direction:N/A",
                            "websocket_message_type:N/A",
                            "device_id:N/A",
                            "threat_campaign_names:N/A",
                            "staged_threat_campaign_names:N/A",
                            "blocking_exception_reason:N/A",
                            "captcha_result:not_received",
                            "microservice:site36.example.com/*",
                            "tap_event_id:N/A",
                            "tap_vid:N/A",
                            "vs_name:/Common/site36.example.com/default_vs_443",
                            "sig_cves:N/A",
                            "staged_sig_cves:N/A",
                            "uri:/product/view",
                            "request:GET /product/view?id=72 HTTP/1.1\\r\\nHost: site36.example.com\\r\\nUser-Agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/62.0.3202.89 Safari/537.36\\r\\nAccept: */*\\r\\nAccept-Encoding: deflate, gzip\\r\\nX-Forwarded-For: <IP_ADDRESS>\\r\\n\\r\\n",
                            "response:Response logging disabled",
                            "telemetryEventCategory:ASM",
                            "tenant:Common"
                        ],
                        "type": "gauge"
                    }
                ]
            }
        },
        "timestamp": "2022-04-26T18:45:01.164Z"

Expected Behavior
telemetryeventcatagory:ASM data should land in DataDog Logs.
Actual Behavior
Data is landing as metrics with type gauge.

ASM events contain log and metrics data. Would sending each ASM to metrics and logs work for your use case?


Build failed in AppIcon.swift

in AppIcon.swift line 94
var jsonFile = ContentsJSON(forType: AssetType.AppIcon, andPlatforms: self.images.keys.array)
I get the following error
'array' is unavailable: please construct an Array from your lazy sequence: Array(...)
OS X: El Capitan
Xcode: 7.0.1

Oops! Forgot to push this change.
Thanks! It should work now. ;-)

Yup it works. Thanks.


Use firebase realtime database instead of PubbNub.

Hello. this chat is amazing and i was thinking if there are means to connect this chat app to Firebase realtime database or Firestore? if so how can i do that?
Thanks

Hi @Steco17 yes indeed!  There are many ways to go about this.  I think the best way would be to replace the publish and subscribe functions found in this file here: https://github.com/stephenlb/angularjs-chat/blob/master/angular-chat.js and replace them with Firebase read/write methods.


No way to unselect in student search

I have to refresh the page in order to unselect

Solved by #26


[HOLD for payment 2024-01-26] [HOLD for payment 2024-01-25] [$500] Create new command for Payment cancelling in "Paid Elsewhere" reports

Problem
Currently, we have no way to revert an existing payment in NewDot. This is part of our core functionality and something we should be able to do.
Solution
Let's add that functionality as discussed here. We'll start by adding it for "Paid Elsewhere" reports, as it is simpler and will give us the core structure of the command and the UI, and move to "Paid in Expensify" reports in a follow-up issue.
Upwork Automation - Do Not Edit

Upwork Job URL: https://www.upwork.com/jobs/~01c0fd3da0a160792d
Upwork Job ID:<PHONE_NUMBER>582071296
Last Price Increase: 2024-01-05

The PR has caused numerous deploy blockers in App:

https://github.com/Expensify/App/issues/33507
https://github.com/Expensify/App/issues/33513
https://github.com/Expensify/App/issues/33540
https://github.com/Expensify/App/issues/33508
https://github.com/Expensify/App/issues/33509

Some might be considered as not a blockers but I think given the number of these and that the author is ooo I will revert the PR and we can just fix this in the second attempt

Seems we just need to pay $500 flat fee for PR review(s) to @narefyev91.

Using automation to create the new upwork job to pay Nicolay

Can we close this GH?

@michaelhaxhiu We had to revert the PR so I am not sure if we put it back in place, I would wait for @Gonals to confirm
@narefyev91 is agency worker nothing to pay there

Roger that, I'll wait on Alberto's confirmation.
And totally makes sense re: agency worker, I spaced out 🛸 🤦

It is in review! https://github.com/Expensify/App/pull/33836

Man, this is being more of a pain than expected. Bringing some discussions to Slack

@michaelhaxhiu please handle the payment when you get a chance!

There is no payment here! And no need for regression steps IMO (it's not a regression from a bug, it's a new feature).

@Ollyws sorry about that, glad you caught it!
can you please accept the job and reply here once you have?
https://www.upwork.com/jobs/~01f578768b7177142d

@Ollyws you were asked to review in January so we need to pay via Upwork
https://github.com/Expensify/App/pull/33836#event-11370487527
Please rescind your NewDot request.  It's best practice to wait for the BZ payment summary before requesting funds via NewDot. Thx

Contributor: @Ollyws  paid $500 via Upwork
Apologies again for the lonnnnng delay here @Ollyws


current version is not compate the ebean version 7.2.1

in DelegateEbeanServer class is not implement method docStore method define in  EbeanServer interface.
other quest: this project is step by step follow ebean with newest version?

> class is not implement method docStore method
Yes, I'll fix and release shortly.
>  this project is step by step follow ebean with newest version?
No, it just needs to support public API changes.
On 21 March 2016 at 14:39, tom.wen<EMAIL_ADDRESS>wrote:

in DelegateEbeanServer class is not implement method docStore method
define in EbeanServer interface.
other quest: this project is step by step follow ebean with newest version?
—
You are receiving this because you are subscribed to this thread.
Reply to this email directly or view it on GitHub
https://github.com/ebean-orm/avaje-ebeanorm-mocker/issues/5

:+1:


Mobile website

Fixing #139

Looks like jquery.terminal-src.js is missing?

Anyway looks much better than the current 😄

This is very old. Sorry I didn't notice your comment, I'm playing with GraphQL GitHub API and found that I have PR that is not merged, will fix the issue when I find some free time.

fixed filenames also renamed them to .min.css and .min.js to it will be easier to change version.
I'm not sure about doc/r7rs.html why it have diff I didn't modified source file but generated file differ a bit.

Thank you!

I'm not sure about doc/r7rs.html why it have diff I didn't modified source file but generated file differ a bit.

Maybe due to the version of marked (markdown converter)? Looks like no problem.


what scenario will be happened in tracker.py

In traker.py code
def accept_slaves(self, nslave):
# set of nodes that finishs the job
shutdown = {}
# set of nodes that is waiting for connections
wait_conn = {}
# maps job id to rank
job_map = {}
# list of workers that is pending to be assigned rank
pending = []
# lazy initialize tree_map
tree_map = None
    while len(shutdown) != nslave:
       logging.info("do while")
        fd, s_addr = self.sock.accept()
         logging.info("do while_accept")
        s = SlaveEntry(fd, s_addr)

when launch multiple-machines,it can't print do do while_accept. What scenario will be printed?What is used for accept_slaves function?

it's used by the dmlc/rabbit project

got it now,thanks.


Issue 880 testing mpi on travis

Submission Checklist

[X] Run unit tests: ./runTests.py test/unit
[ ] Run cpplint: make cpplint
[X] Declare copyright holder and open-source license: see below

Summary:
This PR adds testing of MPI under linux using g++-4.9 and clang++-3.8 on Travis.
Intended Effect:
Improve test coverage of MPI. Note that only the folders which contain mpi tests are actually being tested with the Travis MPI environment.
For reviewer: If deemed desireable, it should be possible to get this to work as well under macOS. This is not as straightforward, but if this is seen valuable we can do so. Note that we concentrate primarily on Linux for the MPI feature at the moment, but macOS is claimed to be supported as well. With testing under macOS on Travis, we may consider to turn off MPI testing on Jenkins.
How to Verify:
Check the .travis.xml file which now has two more test environments and two more test cases.
Side Effects:
None.
Documentation:
Copyright and Licensing
Please list the copyright holder for the work you are submitting (this will be you or your assignee, such as a university or company): Sebastian Weber
By submitting this pull request, the copyright holder is agreeing to license the submitted work under the following licenses:

Code: BSD 3-clause (https://opensource.org/licenses/BSD-3-Clause)
Documentation: CC-BY 4.0 (https://creativecommons.org/licenses/by/4.0/)

Good catch, Sean---this is why code review's so useful.  To pull out non-idiomatic code (hey, have you heard of lock_guard?) and to catch typo-driven mistakes (hey, did you drop those other tests on purpose?).

Oh, NO! Let me double check this (this PR is to increase test-converage).

@seantalts all good now? I would feel better if this MPI stuff gets regularly tested in Travis as well.

thanks!


Sprintly Dev Community of Practice

Describe the issue
Create a recurring developers community of practice focused on Cloud Pathfinder technical work
Which Sprint Goal is this issue related to?

Note: 'Milestone' is a ZenHub term that we use synonymously with 'Sprint'.

Additional context
Definition of done

Warren to be point of contact for this meeting and to book an hour with all the developers on the CPF client teams
Necessary Teams or Rocket channels/groups created
Meeting focused on Developer patterns, new services available and solutions to problems/painpoints that the developers may have
Needs to be aligned with our sprint cycle after the regular sprint review
Figure out reoccurrence

Sid to ask Warren to be point of contact for this meeting and to book an hour with all the developers on the CPF client teams.

Set meeting for May 17 to finalize.


gRPC in Python fails on StatusCode.RESOURCE_EXHAUSTED

Background
Looks like increasing complexity of Lightning network triggers message size limits in gRPC Python implementation while calling DescribeGraph RPC:
Traceback (most recent call last):
  File "lndtools.py", line 89, in <module>
    main()
  File "lndtools.py", line 62, in main
    collect.collect(args, db, rpc)
  File "/home/bitcoin/lndstats/collect.py", line 288, in collect
    describegraph = rpc.DescribeGraph(ln.ChannelGraphRequest())
  File "/home/bitcoin/.local/lib/python3.5/site-packages/grpc/_channel.py", line 514, in __call__
    return _end_unary_response_blocking(state, call, False, None)
  File "/home/bitcoin/.local/lib/python3.5/site-packages/grpc/_channel.py", line 448, in _end_unary_response_blocking
    raise _Rendezvous(state, None, None, deadline)
grpc._channel._Rendezvous: <_Rendezvous of RPC that terminated with:
	status = StatusCode.RESOURCE_EXHAUSTED
	details = "Received message larger than max (4746533 vs. 4194304)"
	debug_error_string = "{"created":"@1546533588.666415375","description":"Error received from peer","file":"src/core/lib/surface/call.cc","file_line":1083,"grpc_message":"Received message larger than max (4746533 vs. 4194304)","grpc_status":8}"

Your environment

lncli version 0.5.1-beta commit=v0.5.1-beta-rc3-4-g8924d8fb20eb2abfd9cc93c6cc7eb6951184cb88-dirty
Linux server01 4.9.0-8-amd64 #1 SMP Debian 4.9.110-3+deb9u6 (2018-10-08) x86_64 GNU/Linux

Steps to reproduce
describegraph = rpc.DescribeGraph(ln.ChannelGraphRequest())

Expected behaviour
RPC call should return network graph of Lightning network.
Actual behaviour
Exception about message limit raised.
I've actually found a workaround and the primary reason to open this issue is to tell others about the workaround. While default limit of gRPC message is 4MB, there's a way how to overload it:
channel = grpc.secure_channel(grpc_url, combined_creds, options=[
        ('grpc.max_send_message_length', 50 * 1024 * 1024),
        ('grpc.max_receive_message_length', 50 * 1024 * 1024)
        ])

However it is supposed as dirty hack as grpc developers mentions the message size should be rather in kilobytes than in megabytes: https://github.com/grpc/grpc/issues/7927#issuecomment-244845823
Considering the data structure in DescribeGraph will tend to expand in time, I propose to change DescribeGraph message to avoid such issue.

See #2374.

Considering the data structure in DescribeGraph will tend to expand in time, I propose to change DescribeGraph message to avoid such issue.

Change it how?

Hm, I tried to search it before posting, but missed that issue. My bad and sorry for duplicate.

Change it how?

Introduce paging / streaming.


The HELM for structures with groups is calculated differently if it is collapsed or expanded

See below for an example. The collapsed HELM is the correct one.

The problem itself is fixed, but there some other related issues are not completely fixed.

Fixed 2017-11-06 update

The two HELM notations are equal now:
Expanded:
BLOB1{}|RNA1{R(U)P.R(G)P.R(G)}|RNA2{R(A)P.R(C)P.R(T)P}$RNA2,RNA1,9:R2-1:R1|RNA2,BLOB1,R:-:*$$$V2.0
Collapsed:
BLOB1{}|RNA1{R(A)P.R(C)P.R(T)P}|RNA2{R(U)P.R(G)P.R(G)}$RNA1,RNA2,9:R2-1:R1|RNA1,BLOB1,R:-:*$$$V2.0

This particular example works now, but in the example below the naming of the simple polymers changes when collapsing the group.

I think this may be OK, but will check with the team at tomorrow's meeting.


the cursor is stucking when i use the phone

the cursor is stucking when i use the phone

Can you post this as a video?

the cursor is stucking when i use the phone

Can you post this as a video?

https://user-images.githubusercontent.com/71113131/140771027-f64b62ba-8416-49a0-8c82-f684cfa2d277.mp4


Inconsistent application of RequestAuthentication

Using master gcr.io/istio-testing:latest , Kubernetes 1.19
To set this up, I first create sleep and httpbin pods:
kubectl apply -f samples/sleep/sleep.yaml
kubectl apply -f samples/httpbin/httpbin.yaml

Next I apply security.  I expect to get an RBAC error, but it works:
$ kubectl get RequestAuthentication,AuthorizationPolicy
No resources found in default namespace.
$ kubectl apply -f https://raw.githubusercontent.com/dgn/oidc-filter/master/example/istio-auth.yaml
requestauthentication.security.istio.io/jwt-example created
authorizationpolicy.security.istio.io/frontend-ingress created
$ kubectl exec -it deployment/sleep -- curl http://httpbin:8000/ip
{
  "origin": "<IP_ADDRESS>"
}

That shouldn't have worked....
Deleting and recreating the RequestAuthentication gets the security started.
$ kubectl delete requestauthentication.security.istio.io jwt-example
requestauthentication.security.istio.io "jwt-example" deleted
$ kubectl apply -f https://raw.githubusercontent.com/dgn/oidc-filter/master/example/istio-auth.yaml
requestauthentication.security.istio.io/jwt-example created
authorizationpolicy.security.istio.io/frontend-ingress unchanged
$ kubectl exec -it deployment/sleep -- curl http://httpbin:8000/ip
RBAC: access denied

I'm running into the same issue when applying to my own pod, however any requests returns a 503


Stabilize storage and event handling tests

Add a general libvirt reconnect strategy, fixes #194
Make sure that  storage tests don't start before previous connections were dropped

LGTM


make confbot_laser a component

This seem to work so far.
I loaded the component into it's own container to keep it semantically separated from the driver ones.
How I tested it:
# Shell 1
ros2 launch confbot_bringup confbot_bringup.launch.py
# Shell 2
ros2 run rviz2 rviz2 -d `ros2 pkg prefix confbot_bringup --share`/config/confbot.rviz
# Shell 3
ros2 lifecycle set /confbot_laser 1
ros2 lifecycle set /confbot_laser 3
ros2 component list
ros2 component unload /confbot_sensors_container 1
ros2 component types
ros2 component load /confbot_sensors_container confbot_sensors confbot_sensors::nodes::ConfbotLaser
ros2 lifecycle set /confbot_laser 1
ros2 lifecycle set /confbot_laser 3

Note: the terminal with the launch file will not print anything for the component once it's been unloader -> reloaded

looks like we've had the same idea here


chore: csharp-template to 0.0.8

chore: Promote csharp-template to version 0.0.8

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Serialization of DictField of ReferenceField

It appears that DictFields of ReferenceFields are not supported for serialization nor deserialization.
I have implemented the method for serialization and am currently working on the deserialization. I would be glad to propose a PR once I am done if you are interested ?

Well, do you mind if I ask you more information (Doc Structure to reproduce bug / to improve the behavior)? e.g. I suppose that the document named First has a DictField named emb and the another document named Second references First then to_json doesn't serialize emb. i.e.
import mongoengine as db
import mongoengine_goodjson as gj

class First(gj.Document):
    emb = db.DictField()

class Second(gj.Document):
    ref = db.ReferenceFIeld(First)

Sure, sorry for the lack of precision. Here is a snippet:
class First(gj.Document):
    name = me.StringField()
    random= me.ReferenceField(SomeDocument, default=None)

class Second(gj.Document):
    name= me.StringField()
    firsts= me.DictField(me.ReferenceField(First))

    meta = {'allow_inheritance': True}
    meta = {'collection': 'second'}

The document._follow_reference method has a special case for db.ListField as the is_list variable, but does not seem to support db.DictField. I managed to make it work by adding a is_dict variable and implementing the following method, using the example of _follow_reference_list:
def __follow_reference_dict(self, fld, fldname, *args, **kwargs):
        """Follow reference with dict."""
        value = {}
        for (key, doc) in getattr(self, fldname).items():
            tdoc = fld.document_type.objects(
                id=doc.id
            ).get() if isinstance(doc, DBRef) else doc
            dct = self.__serialize_doc_to_dict(fld, tdoc, *args, **kwargs)
            value[key] = id_first(dct)
        return value

I hope it is clearer now :)

Ok, this seems to be a bug.
I'll appreciate PR, but don't forget writing test 👍

I created a PR for serialization, deserialization seems much harder to do and I'm not sure I will have time to do it so that's already something.

Ok, thank you for the code. I'll merge it and push some fixes 👍

Hello again !
Do you think you could merge this fix ? I am working with a team and I would love this improvement to be available in the pip release instead of having to use a local fix.
Thanks !

Hi,
Yes, your commit is already merged on fix/185-dictfield branch, but unfortunately I have no idea for de-serialization part....
I think you can pull https://github.com/hiroaki-yamamoto/mongoengine-goodjson/commit/57a056a78994b203f17a19006796a88ce96dd6a1 to use.

I think I have managed to pull something off for the deserialization. However, the problem happens when saving the document. If the referenced documents are not saved, the DBRefs will just lead to an empty document. But we probably don't want to save the referenced documents on creation without asking the user.
The only solution that comes to my mind is to override the default save method in the objects created by the deserialization, so that saving the top-level document recursively saves all referenced documents.
What do you think of this solution? If you are ok, I could try to implement it and propose a PR.

Sorry for my response is delayed, because I move into Tokyo for my work.
As you can see this, you might know this package overrides to_json and from_json, and I don't mind overriding any default behavior. However, my stance is use what is useful that means you can leave the default behavior as-is, afap.
However, your (and any) PR will be appreciated though I don't accept it as you might know 😄

Hello again,
I have opened a PR here: #207
It is a work in progress but I would like you to review it and tell me what you think about it, and if it is worth continuing.
Thanks

Merging & releasing done :+1:


Mine bug during replay

Describe the bug
If during a replay a mine is hit, the number of NPS (notes per second) goes through the roof (in some cases thousands of NPS) and the score is affected negativly (for example if your score was 98 after you hit a mine it goes at for example 67).
To Reproduce
Play a chart and hit a mine. Watch the replay.
Desktop (please complete the following information):

OS: Windows
Version 2004
64bit

could not reproduce but ive had this happen and seen it happen and manifest in a lot of different ways
i reproduced a form of it where a mine hit was basically expecting to be judged twice and then was not judged twice (because this is impossible) so blah blah blah
basically i think i fixed it
3f5ce78ecb0b971dc72d40a6481c900c7761d339


http://scratch.mit.edu/projects/128273669/

Will not show questions and lists
http://scratch.mit.edu/projects/128273669/
http://phosphorus.github.io/#128273669
Mozilla/5.0 (Windows NT 6.3; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/54.0.2840.71 Safari/537.36

Phosphorous does not display lists

#2


Cannot bring up the In-App Developer Menu on iOS simulator or on device after upgrading to 0.43.4

Description
Steps

upgrade react-native to 0.43.4
restart the packager
rebuild debug version of the app for simulator or device

Observations

Shake the device cannot bring up the developer menu

In simulator, Command + R works for reload, but, Command + D doesn't work, Hardware -> Shake gesture doesn't work.

Revert to version 0.42.3, the Develper Menu works as expected again.

Developer Menu in Android app works as expected in version 0.43.4.

Environment

React Native version: 0.43.4
Platform: iOS
Development Operating System: MacOS
Dev tools: Xcode

Are you using cocoapods ? If so you need to add DevSupport as a subspec of React like so
  pod 'React', :path => react_path, :subspecs => [
    'Core',
    'DevSupport', # Devmenu
    'RCTWebSocket', # needed for debugging
   # everything else you need...
   Thank you very much. It is working now :)

I've found it very hardly, THANKS FOR U!

React native 0.48.1
Platform - IOS
Development Operating System: MacOS
Dev tools: Xcode

it doesn't work for me. DevSupport in subspecs in podfile.


error adding the ios platform

When I add the iOS platform to the project, I get an error (about 10 times, same error) that it cannot find the icon file:
sbroders-2015:ShapesCon-dev.1446731874255 sbroders$ cordova platform add ios
Adding ios project...
iOS project created with<EMAIL_ADDRESS>cp: no such file or directory: /Users/sbroders/Documents/6.1/Apps/ShapesCon-dev.1446731874255/icon.png
Seems like it should be looking in the www folder instead of the project folder.

icon.png is now in the expected location, so this error should no longer occur.


Add RBAC visibility to the help menu

@chalettu can you please add the RBAC you created here: https://github.com/ManageIQ/manageiq-ui-service/issues/882 for the help menu?  If they have access, please show it, otherwise, please hide it.

@chalettu per @Loicavenel comment here https://github.com/ManageIQ/manageiq-ui-service/issues/882#issuecomment-333203894 could you please investigate and use this if you can?

There is a recent PR from Classic-UI for this

@Loicavenel this item is complete :)


GitHub actions validation

AC from:
https://app.zenhub.com/workspaces/the-outlaws-6193fe815d79fc0011e741b1/issues/gh/energinet-datahub/the-outlaws/966

Codecov Report

Merging #199 (310a982) into main (df2faee) will increase coverage by 11.84%.
The diff coverage is n/a.

@@             Coverage Diff             @@
##             main     #199       +/-   ##
===========================================
+ Coverage   57.48%   69.33%   +11.84%
===========================================
  Files          51      179      +128
  Lines         741     3248     +2507
  Branches       79      412      +333
===========================================
+ Hits          426     2252     +1826
- Misses        301      863      +562
- Partials       14      133      +119

Flag
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logging
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Issue when serializing abstract classes as private members.

Hi!
I was trying to use Odin Inspector and found that one of our classes was not serializing at all the it was rendered by Odin, but it was working properly when excluded.
After some debugging, I found that Odin was crashing on MemberInfoExtensions.GetAttributes due to a private member which is an abstract class, an actual native c# class. No dependencies with Unity.
I manage to fix the issue by swapping Odin to Sources and modifying the source code as provided in the path file. (renamed to txt as requested by GitHub)
MemberInfoExtensions-patch.diff.txt
If would be great If you do not find any incompatibilities with it and could integrate the fix in the binary version.
Thanks for your time!
Jose

I've committed a fix that should take care of this.

Thanks!


Add leader election

Signed off by @jnpacker

Add support for leader election
Increase replica's to two
Update self build process

/cc @Randy424 @hanqiuzh


CreateEvent returns NULL, not INVALID_HANDLE_VALUE on failure.

In CommandListManager.cpp, line 84-85, the code is:
    m_FenceEventHandle = CreateEvent(nullptr, false, false, nullptr);     ASSERT(m_FenceEventHandle != INVALID_HANDLE_VALUE);
However, according to MSDN, the return value of CreateEvent is

If the function succeeds, the return value is a handle to the event object. If the named event object existed before the function call, the function returns a handle to the existing object and GetLastError returns ERROR_ALREADY_EXISTS.
If the function fails, the return value is NULL. To get extended error information, call GetLastError.

So it should be
ASSERT(m_FenceEventHandle != NULL);

Thanks for pointing that out.  I'll make the change in the various places I've propagated the mistake and try to push a fix soon, though I'd also accept a pull request.

There a nice blog post on why some Win32 functions return INVALID_HANDLE_VALUE and others return NULL. See Why are HANDLE return values so inconsistent?
Personally I use these helpers when dealing with Win32 functions:
struct handle_closer { void operator()(HANDLE h) { assert(h != INVALID_HANDLE_VALUE); if (h) CloseHandle(h); } };

typedef std::unique_ptr<void, handle_closer> ScopedHandle;

inline HANDLE safe_handle(HANDLE h) { return (h == INVALID_HANDLE_VALUE) ? nullptr : h; }

and use safe_handle as a wrapper around the Win32 function call to ensure errors are always null. I've confirmed that there is no valid handle that is 0.

I've confirmed that there is no valid handle that is 0.

Its explained in the linked article, but I think its worth spelling out that the reverse is not true, i.e. the constant INVALID_HANDLE_VALUE is actually a valid handle in some contexts because it has the same numerical value as GetCurrentProcess() returns. So normalizing to INVALID_HANDLE_VALUE is not an option, you can only normalize to null/zero.


buildGoModule: remove modSha256

This is dead code but I'll wait until we're closer to 20.09 before merging.

Yes. Actually I think should be not merge before the 20.09 branch off. So people that migrate from 20.03 to 20.09 have the time to migrate - They would get one release time to migrate everything which is the smallest time unit we can give them.

They would get one release time to migrate everything which is the smallest time unit we can give them.

Why?

They would get one release time to migrate everything which is the smallest time unit we can give them.

Why?

This was not present in 20.03. If users upgrade to 20.09 all their packages needs an update. If you have a infrastructure large enough, you may not upgrade all installations at once.

This was not present in 20.03. If users upgrade to 20.09 all their packages needs an update. If you have a infrastructure large enough, you may not upgrade all installations at once.

Yes, it is a breaking change that is documented.
People will need to set vendorSha256 = null anyway to use modSha256 so I don't see why we need to keep it around for another release cycle.

Ok. Than we can merge it already.

People that needs to support both can just have both checksums defined in the package.

People that needs to support both can just have both checksums defined in the package.

With the change to throw the above won't be true anymore. I think it'll be useful for people to support both. Can we throw only if modSha256 is defined but vendorSha256 is not?

I'd rather we go back to the original which just outright removed modSha256 without throws or warnings.
IMHO the error that vendorSha256 is required is clear and it still allowed people to set modSha256 if needed.

Oh, I didn't realise it said that.
It's been in the 20.09 release notes for a couple of months now, is it okay to change it?


Fix typos in documentation and example-related code

What this PR does / why we need it?
I have gone through the documentation on the Yorkie homepage and identified several typos in the example code and documentation.

Fixed a typo in the helm command for AWS EKS setup.

I changed --set inngress.ingressClassName=alb to --set ingress.ingressClassName=alb for accurate configuration on AWS EKS.

Any background context you want to provide?

Also, 'https://github.com/yorkie-team/yorkie-ui.git' in the scripts/fetch-ui.sh file is a link that doesn't exist, so fetch:ui script is throwing an error. Is there a link to replace that one?
https://github.com/yorkie-team/yorkie-team.github.io/blob/b1a47e3963dbfacd6e6e1043f099b901402364e5/scripts/fetch-ui.sh#L3

What are the relevant tickets?

Fixes #
Checklist

[x] Added relevant tests or not required
[x] Didn't break anything

Can we roll back typos in classNames? Obvious typo, but the UI repository needs to be updated as well.

@hackerwins
Is this what you're referring to? <ol className="commnet_list">
If so, I also fixed it in the styles/style.css file as well.
I didn't know it needed to be updated in the UI repository though.
I'll revert it back

Sure! Thanks for letting me know!


[MM-12746] Migrate user update actions from user_actions.jsx to redux

Summary
Migrated to redux actions according to ticket task, updated/created tests
Ticket Link
MM-12746
Checklist

[x] Ran make check-style to check for style errors (required for all pull requests)
[x] Ran make test to ensure unit and component tests passed
[x] Added or updated unit tests (required for all new features)
[x] Touches critical sections of the codebase (password changing component)

Thanks for your PR, @MirlanMaksv!
@saturninoabril Since it was assigned to you, I didn't do the merge myself. :-)

@DSchalla Oh I missed to remove it.  Nothing special, it's only my way of not missing notification from this PR :)
@MirlanMaksv Thank you for your contribution!

It is a pleasure to contribute to such a great app, thank you for your support :)


Added size option to fileType example of Buffer

file-type package does not require to read whole file to guess mime type. We can put size option to the request, so example has better quality for readers.

also possible to solve it using range request header... just saying


Documentation urls are not working or I am trying wrong url?

I got following error after installing query-string module.
 > react-scripts build

       Creating an optimized production build...
       Failed to compile.

       Failed to minify the code from this file:

        	./node_modules/query-string/index.js:9

       Read more here: http://bit.ly/2tRViJ9

Read more url is working but the Documentation urls shown in that Readme isn't.
For example, if I click on following url, it doesn't work:

https://create-react-app.dev/docs/troubleshooting#npm-run-build-fails-to-minify

Also appreciate if anyone can share their insights on the above issue. Thanks

That full link does work for me. We just updated our docs today. Give it another try.

Thank you, works great!


Add authentication support for default registries

https://trello.com/c/TXe7uAER/36-5-back-port-1-9-x-add-authentication-support-for-default-registries
@rhatdan @miminar
Signed-off-by: Antonio Murdaca<EMAIL_ADDRESS>

@miminar taking care of https://github.com/runcom/docker/commit/52f9224edda45e1017dad3f10ec610e8dcea3d34#commitcomment-15338406

@miminar PTAL

Already commented in WIP branch. It's being addressed.

@miminar took care of your comment, now it should be good to go (except what I was talking about wrt docker push busybox failing because of auth, which the trello card doesn't cover so I guess it's ok)

@miminar added tests and deduplicate code

Few nitpicks from my side. Great work otherwise!

LGTM

@rhatdan as agreed with @miminar, I'm finishing to fix all the tests and let you know when this will be good to merge

Ok ping me when it is done, and I will do a quick scan.

@rhatdan everything's good now, you can review and merge now

LGTM Except for the nasty size of this patch.  Are we merging something like this into docker-1.10 also?

This patch should be merged into registry patches. It affects at least 3 of them.
It needs to be applied to docker-1.10 branch as well once the registry patches are rebased.

That is what I thought.  @runcom has another patch that should also be merged docker info lists the registries that were added, I believe.

@rhatdan yes PR is at https://github.com/projectatomic/docker/pull/32

I'll merge the info patch.


nixos/tests/privoxy: Verify socks support

Description of changes
As detailed in issue #265654, the recent glibc bump broke privoxy's socks4 and socks4a support, likely by exposing a bug in privoxy which has been present before. This pull request adds a corresponding test.
On current unstable, the socks5 and socks5t tests succeed and the socks4 and socks4a tests fail.
On the known good commit 6b20f99fc7b7b7b8f38989537177c4908bfef5e7, all tests succeed.
Things done

Built on platform(s)

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

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

[ ] sandbox = relaxed
[ ] sandbox = true

[x] Tested, as applicable:

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

[x] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[x] Tested basic functionality of all binary files (usually in ./result/bin/)
23.11 Release Notes (or backporting 23.05 Release notes)

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

[x] Fits CONTRIBUTING.md.

This pull request has been mentioned on NixOS Discourse. There might be relevant details there:
https://discourse.nixos.org/t/prs-ready-for-review/3032/3332

Works for me on x86_64-linux on master
@ofborg test privoxy


feat: improve open in maps button

fix: #3

Hi @adripo thanks for opening the PR, I'll take a look at this soon.


Expose API to skip CRC32 calculation at top level

CRC32 calculation causes a performance impact. Currently there is a low-level API to skip CRC3 calculation in:
https://github.com/weichsel/ZIPFoundation/blob/e1c406df93423ff867b35c743aca59632d0c1961/Sources/ZIPFoundation/Data%2BSerialization.swift#L45
However, that flag is not exposed in the higher level API, such as Archive+Reading.swift.
Describe the solution you'd like
Please consider exposing skipCRC32:Bool in methods in Archive+Reading.swift.

The skipCRC32 parameter is currently only used during entry removal.
To make CRC32 checks optional during all reads, we'd have to add an additional parameter to all high level read method and the low level method for compressed reading (consumePart is only used for uncompressed reading).

Ok, no worries. I noticed a 10x performance difference when reading uncompressed entries. For now, I’ve exposed the flag specifically in the code path I’m using. Reading an archive with about 40 image files takes 160 ms compared to 1900 ms with the checksum.
Would you be open to exposing the flag at all in the official repository? If I find the time, I could add this and send a pull-request.

On 14. May 2019, at 09:43, Thomas Zoechling<EMAIL_ADDRESS>wrote:
The skipCRC32 parameter is currently only used during entry removal.
To make CRC32 checks optional during all reads, we'd have to add an additional parameter to all high level read method and the low level method for compressed reading (consumePart is only used for uncompressed reading).
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub https://github.com/weichsel/ZIPFoundation/issues/120?email_source=notifications&email_token=AADWQSAARY77ZXJDVYGRYWTPVJUR7A5CNFSM4HMN6X2KYY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGODVKR2EQ#issuecomment-492117266, or mute the thread https://github.com/notifications/unsubscribe-auth/AADWQSEUST22WPEEBEAPVMTPVJUR7ANCNFSM4HMN6X2A.

Yes, exposing an optional skipCRC32 parameter for read operations would work for me.
A PR would be very welcome.


Update for base16 scheme colors

I had to remove table order list to make select box order themes in correctly.

Updated scheme list

fixed core.error message


Deployment error

I have compared all the tables , measures, relationships on the sql model(ssas) and made them similar to my direct lake mode to deploy the model to fabric in direct lake mode , but I’m getting an error below in the tabular editor when I try to deploy it

It looks like you haven't updated the partitions to be entity partitions which are needed for Direct Lake mode. I recommend following the Direct Lake Migration process here.

My source model doesn’t use power query but import mode and I already have all the tables in the Lakehouse