Some trouble about installing vllm in MARIO-Math-Reasoning

Thanks for publishing this customized version of vllm.
According to the readme.md, I tried to install it and found some problems.
The error message is as follows:
Building wheels for collected packages: vllm
  Building wheel for vllm (pyproject.toml) ... error
  error: subprocess-exited-with-error

  × Building wheel for vllm (pyproject.toml) did not run successfully.
  │ exit code: 1
  ╰─> [242 lines of output]
      /tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/torch/nn/modules/transformer.py:20: UserWarning: Failed to initialize NumPy: No module named 'numpy' (Triggered internally at ../torch/csrc/utils/tensor_numpy.cpp:84.)
        device: torch.device = torch.device(torch._C._get_default_device()),  # torch.device('cpu'),
      No CUDA runtime is found, using CUDA_HOME='/home/hanc/miniconda3/envs/mario'
      running bdist_wheel
      running build
      running build_py
      copying vllm/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm
      copying vllm/block.py -> build/lib.linux-x86_64-cpython-310/vllm
      copying vllm/utils.py -> build/lib.linux-x86_64-cpython-310/vllm
      copying vllm/test_utils.py -> build/lib.linux-x86_64-cpython-310/vllm
      copying vllm/outputs.py -> build/lib.linux-x86_64-cpython-310/vllm
      copying vllm/sequence.py -> build/lib.linux-x86_64-cpython-310/vllm
      copying vllm/sampling_params.py -> build/lib.linux-x86_64-cpython-310/vllm
      copying vllm/config.py -> build/lib.linux-x86_64-cpython-310/vllm
      copying vllm/logger.py -> build/lib.linux-x86_64-cpython-310/vllm
      copying tests/core/test_block_manager.py -> build/lib.linux-x86_64-cpython-310/tests/core
      copying tests/core/__init__.py -> build/lib.linux-x86_64-cpython-310/tests/core
      copying tests/core/utils.py -> build/lib.linux-x86_64-cpython-310/tests/core
      copying tests/core/test_scheduler.py -> build/lib.linux-x86_64-cpython-310/tests/core
      copying tests/lora/test_layers.py -> build/lib.linux-x86_64-cpython-310/tests/lora
      copying tests/lora/test_llama.py -> build/lib.linux-x86_64-cpython-310/tests/lora
      copying tests/lora/test_punica.py -> build/lib.linux-x86_64-cpython-310/tests/lora
      copying tests/lora/__init__.py -> build/lib.linux-x86_64-cpython-310/tests/lora
      copying tests/lora/conftest.py -> build/lib.linux-x86_64-cpython-310/tests/lora
      copying tests/lora/utils.py -> build/lib.linux-x86_64-cpython-310/tests/lora
      copying tests/lora/test_layer_variation.py -> build/lib.linux-x86_64-cpython-310/tests/lora
      copying tests/lora/test_utils.py -> build/lib.linux-x86_64-cpython-310/tests/lora
      copying tests/lora/test_gemma.py -> build/lib.linux-x86_64-cpython-310/tests/lora
      copying tests/lora/test_tokenizer_group.py -> build/lib.linux-x86_64-cpython-310/tests/lora
      copying tests/lora/test_lora.py -> build/lib.linux-x86_64-cpython-310/tests/lora
      copying tests/lora/test_lora_manager.py -> build/lib.linux-x86_64-cpython-310/tests/lora
      copying tests/lora/test_worker.py -> build/lib.linux-x86_64-cpython-310/tests/lora
      copying tests/lora/test_mixtral.py -> build/lib.linux-x86_64-cpython-310/tests/lora
      copying tests/worker/test_model_runner.py -> build/lib.linux-x86_64-cpython-310/tests/worker
      copying tests/worker/__init__.py -> build/lib.linux-x86_64-cpython-310/tests/worker
      copying tests/worker/test_swap.py -> build/lib.linux-x86_64-cpython-310/tests/worker
      copying tests/tokenization/__init__.py -> build/lib.linux-x86_64-cpython-310/tests/tokenization
      copying tests/tokenization/test_tokenizer_group.py -> build/lib.linux-x86_64-cpython-310/tests/tokenization
      copying tests/tokenization/test_detokenize.py -> build/lib.linux-x86_64-cpython-310/tests/tokenization
      copying tests/tokenization/test_cached_tokenizer.py -> build/lib.linux-x86_64-cpython-310/tests/tokenization
      copying tests/spec_decode/test_metrics.py -> build/lib.linux-x86_64-cpython-310/tests/spec_decode
      copying tests/spec_decode/test_spec_decode_worker.py -> build/lib.linux-x86_64-cpython-310/tests/spec_decode
      copying tests/spec_decode/test_multi_step_worker.py -> build/lib.linux-x86_64-cpython-310/tests/spec_decode
      copying tests/spec_decode/__init__.py -> build/lib.linux-x86_64-cpython-310/tests/spec_decode
      copying tests/spec_decode/utils.py -> build/lib.linux-x86_64-cpython-310/tests/spec_decode
      copying tests/spec_decode/test_utils.py -> build/lib.linux-x86_64-cpython-310/tests/spec_decode
      copying tests/spec_decode/test_batch_expansion.py -> build/lib.linux-x86_64-cpython-310/tests/spec_decode
      copying vllm/core/evictor.py -> build/lib.linux-x86_64-cpython-310/vllm/core
      copying vllm/core/block_manager.py -> build/lib.linux-x86_64-cpython-310/vllm/core
      copying vllm/core/scheduler.py -> build/lib.linux-x86_64-cpython-310/vllm/core
      copying vllm/core/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/core
      copying vllm/core/policy.py -> build/lib.linux-x86_64-cpython-310/vllm/core
      copying vllm/lora/request.py -> build/lib.linux-x86_64-cpython-310/vllm/lora
      copying vllm/lora/lora.py -> build/lib.linux-x86_64-cpython-310/vllm/lora
      copying vllm/lora/models.py -> build/lib.linux-x86_64-cpython-310/vllm/lora
      copying vllm/lora/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/lora
      copying vllm/lora/punica.py -> build/lib.linux-x86_64-cpython-310/vllm/lora
      copying vllm/lora/utils.py -> build/lib.linux-x86_64-cpython-310/vllm/lora
      copying vllm/lora/layers.py -> build/lib.linux-x86_64-cpython-310/vllm/lora
      copying vllm/lora/worker_manager.py -> build/lib.linux-x86_64-cpython-310/vllm/lora
      copying vllm/engine/llm_engine.py -> build/lib.linux-x86_64-cpython-310/vllm/engine
      copying vllm/engine/ray_utils.py -> build/lib.linux-x86_64-cpython-310/vllm/engine
      copying vllm/engine/async_llm_engine.py -> build/lib.linux-x86_64-cpython-310/vllm/engine
      copying vllm/engine/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/engine
      copying vllm/engine/metrics.py -> build/lib.linux-x86_64-cpython-310/vllm/engine
      copying vllm/engine/arg_utils.py -> build/lib.linux-x86_64-cpython-310/vllm/engine
      copying vllm/worker/cache_engine.py -> build/lib.linux-x86_64-cpython-310/vllm/worker
      copying vllm/worker/worker.py -> build/lib.linux-x86_64-cpython-310/vllm/worker
      copying vllm/worker/neuron_worker.py -> build/lib.linux-x86_64-cpython-310/vllm/worker
      copying vllm/worker/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/worker
      copying vllm/worker/neuron_model_runner.py -> build/lib.linux-x86_64-cpython-310/vllm/worker
      copying vllm/worker/model_runner.py -> build/lib.linux-x86_64-cpython-310/vllm/worker
      copying vllm/model_executor/neuron_model_loader.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor
      copying vllm/model_executor/model_loader.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor
      copying vllm/model_executor/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor
      copying vllm/model_executor/guided_decoding.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor
      copying vllm/model_executor/utils.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor
      copying vllm/model_executor/guided_logits_processors.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor
      copying vllm/model_executor/input_metadata.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor
      copying vllm/model_executor/weight_utils.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor
      copying vllm/model_executor/sampling_metadata.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor
      copying vllm/executor/gpu_executor.py -> build/lib.linux-x86_64-cpython-310/vllm/executor
      copying vllm/executor/neuron_executor.py -> build/lib.linux-x86_64-cpython-310/vllm/executor
      copying vllm/executor/executor_base.py -> build/lib.linux-x86_64-cpython-310/vllm/executor
      copying vllm/executor/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/executor
      copying vllm/executor/utils.py -> build/lib.linux-x86_64-cpython-310/vllm/executor
      copying vllm/executor/ray_gpu_executor.py -> build/lib.linux-x86_64-cpython-310/vllm/executor
      copying vllm/transformers_utils/tokenizer.py -> build/lib.linux-x86_64-cpython-310/vllm/transformers_utils
      copying vllm/transformers_utils/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/transformers_utils
      copying vllm/transformers_utils/config.py -> build/lib.linux-x86_64-cpython-310/vllm/transformers_utils
      copying vllm/entrypoints/api_server.py -> build/lib.linux-x86_64-cpython-310/vllm/entrypoints
      copying vllm/entrypoints/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/entrypoints
      copying vllm/entrypoints/llm.py -> build/lib.linux-x86_64-cpython-310/vllm/entrypoints
      copying vllm/model_executor/parallel_utils/communication_op.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/parallel_utils
      copying vllm/model_executor/parallel_utils/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/parallel_utils
      copying vllm/model_executor/parallel_utils/parallel_state.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/parallel_utils
      copying vllm/model_executor/parallel_utils/utils.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/parallel_utils
      copying vllm/model_executor/parallel_utils/custom_all_reduce.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/parallel_utils
      copying vllm/model_executor/parallel_utils/cupy_utils.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/parallel_utils
      copying vllm/model_executor/models/gpt_neox.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/decilm.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/jais.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/qwen.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/stablelm.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/llama.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/qwen2.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/baichuan.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/deepseek.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/mixtral_quant.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/starcoder2.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/phi.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/gemma.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/orion.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/chatglm.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/gpt_j.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/internlm2.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/gpt_bigcode.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/modeling_value_head.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/olmo.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/gpt2.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/falcon.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/mpt.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/opt.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/bloom.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/mixtral.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/layers/activation.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers
      copying vllm/model_executor/layers/logits_processor.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers
      copying vllm/model_executor/layers/vocab_parallel_embedding.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers
      copying vllm/model_executor/layers/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers
      copying vllm/model_executor/layers/linear.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers
      copying vllm/model_executor/layers/rotary_embedding.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers
      copying vllm/model_executor/layers/layernorm.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers
      copying vllm/model_executor/layers/sampler.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers
      copying vllm/model_executor/layers/rejection_sampler.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers
      copying vllm/model_executor/layers/fused_moe/fused_moe.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/fused_moe
      copying vllm/model_executor/layers/fused_moe/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/fused_moe
      copying vllm/model_executor/layers/ops/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/ops
      copying vllm/model_executor/layers/ops/rand.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/ops
      copying vllm/model_executor/layers/ops/sample.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/ops
      copying vllm/model_executor/layers/quantization/gptq.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/quantization
      copying vllm/model_executor/layers/quantization/awq.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/quantization
      copying vllm/model_executor/layers/quantization/marlin.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/quantization
      copying vllm/model_executor/layers/quantization/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/quantization
      copying vllm/model_executor/layers/quantization/squeezellm.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/quantization
      copying vllm/model_executor/layers/quantization/base_config.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/quantization
      copying vllm/model_executor/layers/attention/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/attention
      copying vllm/model_executor/layers/attention/attention.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/attention
      copying vllm/model_executor/layers/attention/ops/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/attention/ops
      copying vllm/model_executor/layers/attention/ops/paged_attn.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/attention/ops
      copying vllm/model_executor/layers/attention/ops/prefix_prefill.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/attention/ops
      copying vllm/model_executor/layers/attention/backends/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/attention/backends
      copying vllm/model_executor/layers/attention/backends/xformers.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/attention/backends
      copying vllm/model_executor/layers/attention/backends/flash_attn.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/attention/backends
      copying vllm/transformers_utils/tokenizer_group/base_tokenizer_group.py -> build/lib.linux-x86_64-cpython-310/vllm/transformers_utils/tokenizer_group
      copying vllm/transformers_utils/tokenizer_group/ray_tokenizer_group.py -> build/lib.linux-x86_64-cpython-310/vllm/transformers_utils/tokenizer_group
      copying vllm/transformers_utils/tokenizer_group/tokenizer_group.py -> build/lib.linux-x86_64-cpython-310/vllm/transformers_utils/tokenizer_group
      copying vllm/transformers_utils/tokenizer_group/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/transformers_utils/tokenizer_group
      copying vllm/transformers_utils/configs/jais.py -> build/lib.linux-x86_64-cpython-310/vllm/transformers_utils/configs
      copying vllm/transformers_utils/configs/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/transformers_utils/configs
      copying vllm/transformers_utils/configs/chatglm.py -> build/lib.linux-x86_64-cpython-310/vllm/transformers_utils/configs
      copying vllm/transformers_utils/configs/falcon.py -> build/lib.linux-x86_64-cpython-310/vllm/transformers_utils/configs
      copying vllm/transformers_utils/configs/mpt.py -> build/lib.linux-x86_64-cpython-310/vllm/transformers_utils/configs
      copying vllm/transformers_utils/tokenizers/baichuan.py -> build/lib.linux-x86_64-cpython-310/vllm/transformers_utils/tokenizers
      copying vllm/transformers_utils/tokenizers/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/transformers_utils/tokenizers
      copying vllm/entrypoints/openai/serving_engine.py -> build/lib.linux-x86_64-cpython-310/vllm/entrypoints/openai
      copying vllm/entrypoints/openai/serving_chat.py -> build/lib.linux-x86_64-cpython-310/vllm/entrypoints/openai
      copying vllm/entrypoints/openai/api_server.py -> build/lib.linux-x86_64-cpython-310/vllm/entrypoints/openai
      copying vllm/entrypoints/openai/serving_completion.py -> build/lib.linux-x86_64-cpython-310/vllm/entrypoints/openai
      copying vllm/entrypoints/openai/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/entrypoints/openai
      copying vllm/entrypoints/openai/protocol.py -> build/lib.linux-x86_64-cpython-310/vllm/entrypoints/openai
      copying vllm/entrypoints/openai/cli_args.py -> build/lib.linux-x86_64-cpython-310/vllm/entrypoints/openai
      copying vllm/py.typed -> build/lib.linux-x86_64-cpython-310/vllm
      copying vllm/model_executor/layers/fused_moe/configs/E=8,N=3584,device_name=NVIDIA_H100_80GB_HBM3.json -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/fused_moe/configs
      copying vllm/model_executor/layers/fused_moe/configs/E=8,N=7168,device_name=NVIDIA_A100-SXM4-80GB.json -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/fused_moe/configs
      copying vllm/model_executor/layers/fused_moe/configs/E=8,N=1792,device_name=NVIDIA_H100_80GB_HBM3.json -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/fused_moe/configs
      copying vllm/model_executor/layers/fused_moe/configs/E=8,N=7168,device_name=NVIDIA_H100_80GB_HBM3.json -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/fused_moe/configs
      copying vllm/model_executor/layers/fused_moe/configs/E=8,N=3584,device_name=NVIDIA_A100-SXM4-80GB.json -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/fused_moe/configs
      copying vllm/model_executor/layers/fused_moe/configs/E=8,N=1792,device_name=NVIDIA_A100-SXM4-80GB.json -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/fused_moe/configs
      running build_ext
      CMake Error at CMakeLists.txt:3 (project):
        Running

         '/tmp/pip-build-env-nbudjmwn/overlay/bin/ninja' '--version'

        failed with:

         no such file or directory

      -- Configuring incomplete, errors occurred!
      Traceback (most recent call last):
        File "/home/hanc/miniconda3/envs/mario/lib/python3.10/site-packages/pip/_vendor/pyproject_hooks/_in_process/_in_process.py", line 353, in <module>
          main()
        File "/home/hanc/miniconda3/envs/mario/lib/python3.10/site-packages/pip/_vendor/pyproject_hooks/_in_process/_in_process.py", line 335, in main
          json_out['return_val'] = hook(**hook_input['kwargs'])
        File "/home/hanc/miniconda3/envs/mario/lib/python3.10/site-packages/pip/_vendor/pyproject_hooks/_in_process/_in_process.py", line 251, in build_wheel
          return _build_backend().build_wheel(wheel_directory, config_settings,
        File "/tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/setuptools/build_meta.py", line 410, in build_wheel
          return self._build_with_temp_dir(
        File "/tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/setuptools/build_meta.py", line 395, in _build_with_temp_dir
          self.run_setup()
        File "/tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/setuptools/build_meta.py", line 311, in run_setup
          exec(code, locals())
        File "<string>", line 338, in <module>
        File "/tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/setuptools/__init__.py", line 104, in setup
          return distutils.core.setup(**attrs)
        File "/tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/setuptools/_distutils/core.py", line 184, in setup
          return run_commands(dist)
        File "/tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/setuptools/_distutils/core.py", line 200, in run_commands
          dist.run_commands()
        File "/tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/setuptools/_distutils/dist.py", line 969, in run_commands
          self.run_command(cmd)
        File "/tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/setuptools/dist.py", line 967, in run_command
          super().run_command(command)
        File "/tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/setuptools/_distutils/dist.py", line 988, in run_command
          cmd_obj.run()
        File "/tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/wheel/bdist_wheel.py", line 368, in run
          self.run_command("build")
        File "/tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/setuptools/_distutils/cmd.py", line 316, in run_command
          self.distribution.run_command(command)
        File "/tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/setuptools/dist.py", line 967, in run_command
          super().run_command(command)
        File "/tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/setuptools/_distutils/dist.py", line 988, in run_command
          cmd_obj.run()
        File "/tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/setuptools/_distutils/command/build.py", line 132, in run
          self.run_command(cmd_name)
        File "/tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/setuptools/_distutils/cmd.py", line 316, in run_command
          self.distribution.run_command(command)
        File "/tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/setuptools/dist.py", line 967, in run_command
          super().run_command(command)
        File "/tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/setuptools/_distutils/dist.py", line 988, in run_command
          cmd_obj.run()
        File "/tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/setuptools/command/build_ext.py", line 91, in run
          _build_ext.run(self)
        File "/tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/setuptools/_distutils/command/build_ext.py", line 359, in run
          self.build_extensions()
        File "<string>", line 157, in build_extensions
        File "<string>", line 140, in configure
        File "/home/hanc/miniconda3/envs/mario/lib/python3.10/subprocess.py", line 369, in check_call
          raise CalledProcessError(retcode, cmd)
      subprocess.CalledProcessError: Command '['cmake', '/home/hanc/workspace/Super_MARIO/vllm', '-G', 'Ninja', '-DCMAKE_BUILD_TYPE=RelWithDebInfo', '-DCMAKE_LIBRARY_OUTPUT_DIRECTORY=/home/hanc/workspace/Super_MARIO/vllm/build/lib.linux-x86_64-cpython-310/vllm', '-DCMAKE_ARCHIVE_OUTPUT_DIRECTORY=build/temp.linux-x86_64-cpython-310', '-DVLLM_PYTHON_EXECUTABLE=/home/hanc/miniconda3/envs/mario/bin/python', '-DNVCC_THREADS=8', '-DCMAKE_JOB_POOL_COMPILE:STRING=compile', '-DCMAKE_JOB_POOLS:STRING=compile=24']' returned non-zero exit status 1.
      [end of output]

  note: This error originates from a subprocess, and is likely not a problem with pip.
  ERROR: Failed building wheel for vllm
Failed to build vllm
ERROR: Could not build wheels for vllm, which is required to install pyproject.toml-based projects

In addition, when I tried to modify it manually according to the instructions in readme.md, I found that the current vllm version is different from the one in this library. Which release version of vllm should I modify based on?

In readme, I indicated that the version of vllm we modified is from vllm@f721096.

Thanks for publishing this customized version of vllm. According to the readme.md, I tried to install it and found some problems. The error message is as follows:
Building wheels for collected packages: vllm
  Building wheel for vllm (pyproject.toml) ... error
  error: subprocess-exited-with-error

  × Building wheel for vllm (pyproject.toml) did not run successfully.
  │ exit code: 1
  ╰─> [242 lines of output]
      /tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/torch/nn/modules/transformer.py:20: UserWarning: Failed to initialize NumPy: No module named 'numpy' (Triggered internally at ../torch/csrc/utils/tensor_numpy.cpp:84.)
        device: torch.device = torch.device(torch._C._get_default_device()),  # torch.device('cpu'),
      No CUDA runtime is found, using CUDA_HOME='/home/hanc/miniconda3/envs/mario'
      running bdist_wheel
      running build
      running build_py
      copying vllm/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm
      copying vllm/block.py -> build/lib.linux-x86_64-cpython-310/vllm
      copying vllm/utils.py -> build/lib.linux-x86_64-cpython-310/vllm
      copying vllm/test_utils.py -> build/lib.linux-x86_64-cpython-310/vllm
      copying vllm/outputs.py -> build/lib.linux-x86_64-cpython-310/vllm
      copying vllm/sequence.py -> build/lib.linux-x86_64-cpython-310/vllm
      copying vllm/sampling_params.py -> build/lib.linux-x86_64-cpython-310/vllm
      copying vllm/config.py -> build/lib.linux-x86_64-cpython-310/vllm
      copying vllm/logger.py -> build/lib.linux-x86_64-cpython-310/vllm
      copying tests/core/test_block_manager.py -> build/lib.linux-x86_64-cpython-310/tests/core
      copying tests/core/__init__.py -> build/lib.linux-x86_64-cpython-310/tests/core
      copying tests/core/utils.py -> build/lib.linux-x86_64-cpython-310/tests/core
      copying tests/core/test_scheduler.py -> build/lib.linux-x86_64-cpython-310/tests/core
      copying tests/lora/test_layers.py -> build/lib.linux-x86_64-cpython-310/tests/lora
      copying tests/lora/test_llama.py -> build/lib.linux-x86_64-cpython-310/tests/lora
      copying tests/lora/test_punica.py -> build/lib.linux-x86_64-cpython-310/tests/lora
      copying tests/lora/__init__.py -> build/lib.linux-x86_64-cpython-310/tests/lora
      copying tests/lora/conftest.py -> build/lib.linux-x86_64-cpython-310/tests/lora
      copying tests/lora/utils.py -> build/lib.linux-x86_64-cpython-310/tests/lora
      copying tests/lora/test_layer_variation.py -> build/lib.linux-x86_64-cpython-310/tests/lora
      copying tests/lora/test_utils.py -> build/lib.linux-x86_64-cpython-310/tests/lora
      copying tests/lora/test_gemma.py -> build/lib.linux-x86_64-cpython-310/tests/lora
      copying tests/lora/test_tokenizer_group.py -> build/lib.linux-x86_64-cpython-310/tests/lora
      copying tests/lora/test_lora.py -> build/lib.linux-x86_64-cpython-310/tests/lora
      copying tests/lora/test_lora_manager.py -> build/lib.linux-x86_64-cpython-310/tests/lora
      copying tests/lora/test_worker.py -> build/lib.linux-x86_64-cpython-310/tests/lora
      copying tests/lora/test_mixtral.py -> build/lib.linux-x86_64-cpython-310/tests/lora
      copying tests/worker/test_model_runner.py -> build/lib.linux-x86_64-cpython-310/tests/worker
      copying tests/worker/__init__.py -> build/lib.linux-x86_64-cpython-310/tests/worker
      copying tests/worker/test_swap.py -> build/lib.linux-x86_64-cpython-310/tests/worker
      copying tests/tokenization/__init__.py -> build/lib.linux-x86_64-cpython-310/tests/tokenization
      copying tests/tokenization/test_tokenizer_group.py -> build/lib.linux-x86_64-cpython-310/tests/tokenization
      copying tests/tokenization/test_detokenize.py -> build/lib.linux-x86_64-cpython-310/tests/tokenization
      copying tests/tokenization/test_cached_tokenizer.py -> build/lib.linux-x86_64-cpython-310/tests/tokenization
      copying tests/spec_decode/test_metrics.py -> build/lib.linux-x86_64-cpython-310/tests/spec_decode
      copying tests/spec_decode/test_spec_decode_worker.py -> build/lib.linux-x86_64-cpython-310/tests/spec_decode
      copying tests/spec_decode/test_multi_step_worker.py -> build/lib.linux-x86_64-cpython-310/tests/spec_decode
      copying tests/spec_decode/__init__.py -> build/lib.linux-x86_64-cpython-310/tests/spec_decode
      copying tests/spec_decode/utils.py -> build/lib.linux-x86_64-cpython-310/tests/spec_decode
      copying tests/spec_decode/test_utils.py -> build/lib.linux-x86_64-cpython-310/tests/spec_decode
      copying tests/spec_decode/test_batch_expansion.py -> build/lib.linux-x86_64-cpython-310/tests/spec_decode
      copying vllm/core/evictor.py -> build/lib.linux-x86_64-cpython-310/vllm/core
      copying vllm/core/block_manager.py -> build/lib.linux-x86_64-cpython-310/vllm/core
      copying vllm/core/scheduler.py -> build/lib.linux-x86_64-cpython-310/vllm/core
      copying vllm/core/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/core
      copying vllm/core/policy.py -> build/lib.linux-x86_64-cpython-310/vllm/core
      copying vllm/lora/request.py -> build/lib.linux-x86_64-cpython-310/vllm/lora
      copying vllm/lora/lora.py -> build/lib.linux-x86_64-cpython-310/vllm/lora
      copying vllm/lora/models.py -> build/lib.linux-x86_64-cpython-310/vllm/lora
      copying vllm/lora/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/lora
      copying vllm/lora/punica.py -> build/lib.linux-x86_64-cpython-310/vllm/lora
      copying vllm/lora/utils.py -> build/lib.linux-x86_64-cpython-310/vllm/lora
      copying vllm/lora/layers.py -> build/lib.linux-x86_64-cpython-310/vllm/lora
      copying vllm/lora/worker_manager.py -> build/lib.linux-x86_64-cpython-310/vllm/lora
      copying vllm/engine/llm_engine.py -> build/lib.linux-x86_64-cpython-310/vllm/engine
      copying vllm/engine/ray_utils.py -> build/lib.linux-x86_64-cpython-310/vllm/engine
      copying vllm/engine/async_llm_engine.py -> build/lib.linux-x86_64-cpython-310/vllm/engine
      copying vllm/engine/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/engine
      copying vllm/engine/metrics.py -> build/lib.linux-x86_64-cpython-310/vllm/engine
      copying vllm/engine/arg_utils.py -> build/lib.linux-x86_64-cpython-310/vllm/engine
      copying vllm/worker/cache_engine.py -> build/lib.linux-x86_64-cpython-310/vllm/worker
      copying vllm/worker/worker.py -> build/lib.linux-x86_64-cpython-310/vllm/worker
      copying vllm/worker/neuron_worker.py -> build/lib.linux-x86_64-cpython-310/vllm/worker
      copying vllm/worker/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/worker
      copying vllm/worker/neuron_model_runner.py -> build/lib.linux-x86_64-cpython-310/vllm/worker
      copying vllm/worker/model_runner.py -> build/lib.linux-x86_64-cpython-310/vllm/worker
      copying vllm/model_executor/neuron_model_loader.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor
      copying vllm/model_executor/model_loader.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor
      copying vllm/model_executor/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor
      copying vllm/model_executor/guided_decoding.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor
      copying vllm/model_executor/utils.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor
      copying vllm/model_executor/guided_logits_processors.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor
      copying vllm/model_executor/input_metadata.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor
      copying vllm/model_executor/weight_utils.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor
      copying vllm/model_executor/sampling_metadata.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor
      copying vllm/executor/gpu_executor.py -> build/lib.linux-x86_64-cpython-310/vllm/executor
      copying vllm/executor/neuron_executor.py -> build/lib.linux-x86_64-cpython-310/vllm/executor
      copying vllm/executor/executor_base.py -> build/lib.linux-x86_64-cpython-310/vllm/executor
      copying vllm/executor/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/executor
      copying vllm/executor/utils.py -> build/lib.linux-x86_64-cpython-310/vllm/executor
      copying vllm/executor/ray_gpu_executor.py -> build/lib.linux-x86_64-cpython-310/vllm/executor
      copying vllm/transformers_utils/tokenizer.py -> build/lib.linux-x86_64-cpython-310/vllm/transformers_utils
      copying vllm/transformers_utils/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/transformers_utils
      copying vllm/transformers_utils/config.py -> build/lib.linux-x86_64-cpython-310/vllm/transformers_utils
      copying vllm/entrypoints/api_server.py -> build/lib.linux-x86_64-cpython-310/vllm/entrypoints
      copying vllm/entrypoints/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/entrypoints
      copying vllm/entrypoints/llm.py -> build/lib.linux-x86_64-cpython-310/vllm/entrypoints
      copying vllm/model_executor/parallel_utils/communication_op.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/parallel_utils
      copying vllm/model_executor/parallel_utils/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/parallel_utils
      copying vllm/model_executor/parallel_utils/parallel_state.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/parallel_utils
      copying vllm/model_executor/parallel_utils/utils.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/parallel_utils
      copying vllm/model_executor/parallel_utils/custom_all_reduce.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/parallel_utils
      copying vllm/model_executor/parallel_utils/cupy_utils.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/parallel_utils
      copying vllm/model_executor/models/gpt_neox.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/decilm.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/jais.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/qwen.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/stablelm.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/llama.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/qwen2.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/baichuan.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/deepseek.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/mixtral_quant.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/starcoder2.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/phi.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/gemma.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/orion.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/chatglm.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/gpt_j.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/internlm2.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/gpt_bigcode.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/modeling_value_head.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/olmo.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/gpt2.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/falcon.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/mpt.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/opt.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/bloom.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/models/mixtral.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/models
      copying vllm/model_executor/layers/activation.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers
      copying vllm/model_executor/layers/logits_processor.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers
      copying vllm/model_executor/layers/vocab_parallel_embedding.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers
      copying vllm/model_executor/layers/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers
      copying vllm/model_executor/layers/linear.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers
      copying vllm/model_executor/layers/rotary_embedding.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers
      copying vllm/model_executor/layers/layernorm.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers
      copying vllm/model_executor/layers/sampler.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers
      copying vllm/model_executor/layers/rejection_sampler.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers
      copying vllm/model_executor/layers/fused_moe/fused_moe.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/fused_moe
      copying vllm/model_executor/layers/fused_moe/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/fused_moe
      copying vllm/model_executor/layers/ops/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/ops
      copying vllm/model_executor/layers/ops/rand.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/ops
      copying vllm/model_executor/layers/ops/sample.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/ops
      copying vllm/model_executor/layers/quantization/gptq.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/quantization
      copying vllm/model_executor/layers/quantization/awq.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/quantization
      copying vllm/model_executor/layers/quantization/marlin.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/quantization
      copying vllm/model_executor/layers/quantization/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/quantization
      copying vllm/model_executor/layers/quantization/squeezellm.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/quantization
      copying vllm/model_executor/layers/quantization/base_config.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/quantization
      copying vllm/model_executor/layers/attention/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/attention
      copying vllm/model_executor/layers/attention/attention.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/attention
      copying vllm/model_executor/layers/attention/ops/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/attention/ops
      copying vllm/model_executor/layers/attention/ops/paged_attn.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/attention/ops
      copying vllm/model_executor/layers/attention/ops/prefix_prefill.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/attention/ops
      copying vllm/model_executor/layers/attention/backends/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/attention/backends
      copying vllm/model_executor/layers/attention/backends/xformers.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/attention/backends
      copying vllm/model_executor/layers/attention/backends/flash_attn.py -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/attention/backends
      copying vllm/transformers_utils/tokenizer_group/base_tokenizer_group.py -> build/lib.linux-x86_64-cpython-310/vllm/transformers_utils/tokenizer_group
      copying vllm/transformers_utils/tokenizer_group/ray_tokenizer_group.py -> build/lib.linux-x86_64-cpython-310/vllm/transformers_utils/tokenizer_group
      copying vllm/transformers_utils/tokenizer_group/tokenizer_group.py -> build/lib.linux-x86_64-cpython-310/vllm/transformers_utils/tokenizer_group
      copying vllm/transformers_utils/tokenizer_group/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/transformers_utils/tokenizer_group
      copying vllm/transformers_utils/configs/jais.py -> build/lib.linux-x86_64-cpython-310/vllm/transformers_utils/configs
      copying vllm/transformers_utils/configs/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/transformers_utils/configs
      copying vllm/transformers_utils/configs/chatglm.py -> build/lib.linux-x86_64-cpython-310/vllm/transformers_utils/configs
      copying vllm/transformers_utils/configs/falcon.py -> build/lib.linux-x86_64-cpython-310/vllm/transformers_utils/configs
      copying vllm/transformers_utils/configs/mpt.py -> build/lib.linux-x86_64-cpython-310/vllm/transformers_utils/configs
      copying vllm/transformers_utils/tokenizers/baichuan.py -> build/lib.linux-x86_64-cpython-310/vllm/transformers_utils/tokenizers
      copying vllm/transformers_utils/tokenizers/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/transformers_utils/tokenizers
      copying vllm/entrypoints/openai/serving_engine.py -> build/lib.linux-x86_64-cpython-310/vllm/entrypoints/openai
      copying vllm/entrypoints/openai/serving_chat.py -> build/lib.linux-x86_64-cpython-310/vllm/entrypoints/openai
      copying vllm/entrypoints/openai/api_server.py -> build/lib.linux-x86_64-cpython-310/vllm/entrypoints/openai
      copying vllm/entrypoints/openai/serving_completion.py -> build/lib.linux-x86_64-cpython-310/vllm/entrypoints/openai
      copying vllm/entrypoints/openai/__init__.py -> build/lib.linux-x86_64-cpython-310/vllm/entrypoints/openai
      copying vllm/entrypoints/openai/protocol.py -> build/lib.linux-x86_64-cpython-310/vllm/entrypoints/openai
      copying vllm/entrypoints/openai/cli_args.py -> build/lib.linux-x86_64-cpython-310/vllm/entrypoints/openai
      copying vllm/py.typed -> build/lib.linux-x86_64-cpython-310/vllm
      copying vllm/model_executor/layers/fused_moe/configs/E=8,N=3584,device_name=NVIDIA_H100_80GB_HBM3.json -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/fused_moe/configs
      copying vllm/model_executor/layers/fused_moe/configs/E=8,N=7168,device_name=NVIDIA_A100-SXM4-80GB.json -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/fused_moe/configs
      copying vllm/model_executor/layers/fused_moe/configs/E=8,N=1792,device_name=NVIDIA_H100_80GB_HBM3.json -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/fused_moe/configs
      copying vllm/model_executor/layers/fused_moe/configs/E=8,N=7168,device_name=NVIDIA_H100_80GB_HBM3.json -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/fused_moe/configs
      copying vllm/model_executor/layers/fused_moe/configs/E=8,N=3584,device_name=NVIDIA_A100-SXM4-80GB.json -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/fused_moe/configs
      copying vllm/model_executor/layers/fused_moe/configs/E=8,N=1792,device_name=NVIDIA_A100-SXM4-80GB.json -> build/lib.linux-x86_64-cpython-310/vllm/model_executor/layers/fused_moe/configs
      running build_ext
      CMake Error at CMakeLists.txt:3 (project):
        Running

         '/tmp/pip-build-env-nbudjmwn/overlay/bin/ninja' '--version'

        failed with:

         no such file or directory

      -- Configuring incomplete, errors occurred!
      Traceback (most recent call last):
        File "/home/hanc/miniconda3/envs/mario/lib/python3.10/site-packages/pip/_vendor/pyproject_hooks/_in_process/_in_process.py", line 353, in <module>
          main()
        File "/home/hanc/miniconda3/envs/mario/lib/python3.10/site-packages/pip/_vendor/pyproject_hooks/_in_process/_in_process.py", line 335, in main
          json_out['return_val'] = hook(**hook_input['kwargs'])
        File "/home/hanc/miniconda3/envs/mario/lib/python3.10/site-packages/pip/_vendor/pyproject_hooks/_in_process/_in_process.py", line 251, in build_wheel
          return _build_backend().build_wheel(wheel_directory, config_settings,
        File "/tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/setuptools/build_meta.py", line 410, in build_wheel
          return self._build_with_temp_dir(
        File "/tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/setuptools/build_meta.py", line 395, in _build_with_temp_dir
          self.run_setup()
        File "/tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/setuptools/build_meta.py", line 311, in run_setup
          exec(code, locals())
        File "<string>", line 338, in <module>
        File "/tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/setuptools/__init__.py", line 104, in setup
          return distutils.core.setup(**attrs)
        File "/tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/setuptools/_distutils/core.py", line 184, in setup
          return run_commands(dist)
        File "/tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/setuptools/_distutils/core.py", line 200, in run_commands
          dist.run_commands()
        File "/tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/setuptools/_distutils/dist.py", line 969, in run_commands
          self.run_command(cmd)
        File "/tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/setuptools/dist.py", line 967, in run_command
          super().run_command(command)
        File "/tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/setuptools/_distutils/dist.py", line 988, in run_command
          cmd_obj.run()
        File "/tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/wheel/bdist_wheel.py", line 368, in run
          self.run_command("build")
        File "/tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/setuptools/_distutils/cmd.py", line 316, in run_command
          self.distribution.run_command(command)
        File "/tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/setuptools/dist.py", line 967, in run_command
          super().run_command(command)
        File "/tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/setuptools/_distutils/dist.py", line 988, in run_command
          cmd_obj.run()
        File "/tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/setuptools/_distutils/command/build.py", line 132, in run
          self.run_command(cmd_name)
        File "/tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/setuptools/_distutils/cmd.py", line 316, in run_command
          self.distribution.run_command(command)
        File "/tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/setuptools/dist.py", line 967, in run_command
          super().run_command(command)
        File "/tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/setuptools/_distutils/dist.py", line 988, in run_command
          cmd_obj.run()
        File "/tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/setuptools/command/build_ext.py", line 91, in run
          _build_ext.run(self)
        File "/tmp/pip-build-env-wcxbdxnq/overlay/lib/python3.10/site-packages/setuptools/_distutils/command/build_ext.py", line 359, in run
          self.build_extensions()
        File "<string>", line 157, in build_extensions
        File "<string>", line 140, in configure
        File "/home/hanc/miniconda3/envs/mario/lib/python3.10/subprocess.py", line 369, in check_call
          raise CalledProcessError(retcode, cmd)
      subprocess.CalledProcessError: Command '['cmake', '/home/hanc/workspace/Super_MARIO/vllm', '-G', 'Ninja', '-DCMAKE_BUILD_TYPE=RelWithDebInfo', '-DCMAKE_LIBRARY_OUTPUT_DIRECTORY=/home/hanc/workspace/Super_MARIO/vllm/build/lib.linux-x86_64-cpython-310/vllm', '-DCMAKE_ARCHIVE_OUTPUT_DIRECTORY=build/temp.linux-x86_64-cpython-310', '-DVLLM_PYTHON_EXECUTABLE=/home/hanc/miniconda3/envs/mario/bin/python', '-DNVCC_THREADS=8', '-DCMAKE_JOB_POOL_COMPILE:STRING=compile', '-DCMAKE_JOB_POOLS:STRING=compile=24']' returned non-zero exit status 1.
      [end of output]

  note: This error originates from a subprocess, and is likely not a problem with pip.
  ERROR: Failed building wheel for vllm
Failed to build vllm
ERROR: Could not build wheels for vllm, which is required to install pyproject.toml-based projects

In addition, when I tried to modify it manually according to the instructions in readme.md, I found that the current vllm version is different from the one in this library. Which release version of vllm should I modify based on?

Did you pin the version of setuptools? setuptools is recently updated to 70.0.0, which is not compatible with vllm.
https://github.com/MARIO-Math-Reasoning/vllm/blob/main/pyproject.toml#L7
https://github.com/MARIO-Math-Reasoning/vllm/blob/main/requirements-build.txt#L5

I think I've got the right version of setuptools(69.5.1), but I didn't install this lib properly.
Besides, I've cloned the repo of vllm@f721096, and run pip install . in it. It reported the same traceback. So I think it might be the issue from the original vllm but not your repo?

I think I've got the right version of setuptools(69.5.1), but I didn't install this lib properly.
Besides, I've cloned the repo of vllm@f721096, and run pip install . in it. It reported the same traceback. So I think it might be the issue from the original vllm but not your repo?

Even if you cloned the original vllm, you still need to pin the version of setuptools in pyproject.toml and requirements-build.txt .

I also encounter this problem, have you solved it?

I change an another machine, and install vllm successfully. What we can be sure of now is that the problem lies in the local environment, or the adaptation of the environment to that version of vllm, and it should not be a problem with this library.

I also encounter this problem, have you solved it?

I change an another machine, and install vllm successfully. What we can be sure of now is that the problem lies in the local environment, or the adaptation of the environment to that version of vllm, and it should not be a problem with this library.

OK, thanks for your reply, I will try it

I also encountered the same problem.

I also encounter this problem, have you solved it?

I change an another machine, and install vllm successfully. What we can be sure of now is that the problem lies in the local environment, or the adaptation of the environment to that version of vllm, and it should not be a problem with this library.

OK, thanks for your reply, I will try it

I solved the issue by cleaning up the old builds: rm -rf build. Reference: https://github.com/vllm-project/vllm/issues/4913

Still having this problem... I double-checked that the setuptools version was correct (69.5.1). Not sure what to do about it.
`Processing /scratch/bc3194/Super_MARIO/vllm
Installing build dependencies ... done
Getting requirements to build wheel ... error
error: subprocess-exited-with-error
× Getting requirements to build wheel did not run successfully.
│ exit code: 1
╰─> [19 lines of output]
/tmpdata/pip-build-env-ml44wjni/overlay/lib/python3.10/site-packages/torch/nn/modules/transformer.py:20: UserWarning: Failed to initialize NumPy: No module named 'numpy' (Triggered internally at ../torch/csrc/utils/tensor_numpy.cpp:84.)
device: torch.device = torch.device(torch._C._get_default_device()),  # torch.device('cpu'),
Traceback (most recent call last):
File "/scratch/bc3194/conda-envs/mario/lib/python3.10/site-packages/pip/_vendor/pyproject_hooks/_in_process/_in_process.py", line 353, in
main()
File "/scratch/bc3194/conda-envs/mario/lib/python3.10/site-packages/pip/_vendor/pyproject_hooks/_in_process/_in_process.py", line 335, in main
json_out['return_val'] = hook(**hook_input['kwargs'])
File "/scratch/bc3194/conda-envs/mario/lib/python3.10/site-packages/pip/_vendor/pyproject_hooks/_in_process/_in_process.py", line 118, in get_requires_for_build_wheel
return hook(config_settings)
File "/tmpdata/pip-build-env-ml44wjni/overlay/lib/python3.10/site-packages/setuptools/build_meta.py", line 325, in get_requires_for_build_wheel
return self._get_build_requires(config_settings, requirements=['wheel'])
File "/tmpdata/pip-build-env-ml44wjni/overlay/lib/python3.10/site-packages/setuptools/build_meta.py", line 295, in _get_build_requires
self.run_setup()
File "/tmpdata/pip-build-env-ml44wjni/overlay/lib/python3.10/site-packages/setuptools/build_meta.py", line 311, in run_setup
exec(code, locals())
File "", line 340, in
File "", line 266, in get_vllm_version
File "", line 237, in get_nvcc_cuda_version
TypeError: unsupported operand type(s) for +: 'NoneType' and 'str'
[end of output]
note: This error originates from a subprocess, and is likely not a problem with pip.
error: subprocess-exited-with-error
× Getting requirements to build wheel did not run successfully.
│ exit code: 1
╰─> See above for output.
note: This error originates from a subprocess, and is likely not a problem with pip.
`

Still having this problem. I double-checked that the setuptools version was correct (69.5.1). For some reason it can't find numpy, but I actually have it in pip. Not sure what to do about it. Any ideas?
Processing /scratch/bc/Super_MARIO/vllm
  Installing build dependencies ... done
  Getting requirements to build wheel ... error
  error: subprocess-exited-with-error

  × Getting requirements to build wheel did not run successfully.
  │ exit code: 1
  ╰─> [19 lines of output]
      /tmpdata/pip-build-env-ml44wjni/overlay/lib/python3.10/site-packages/torch/nn/modules/transformer.py:20: UserWarning: Failed to initialize NumPy: No module named 'numpy' (Triggered internally at ../torch/csrc/utils/tensor_numpy.cpp:84.)
        device: torch.device = torch.device(torch._C._get_default_device()),  # torch.device('cpu'),
      Traceback (most recent call last):
        File "/scratch/bc3194/conda-envs/mario/lib/python3.10/site-packages/pip/_vendor/pyproject_hooks/_in_process/_in_process.py", line 353, in <module>
          main()
        File "/scratch/bc3194/conda-envs/mario/lib/python3.10/site-packages/pip/_vendor/pyproject_hooks/_in_process/_in_process.py", line 335, in main
          json_out['return_val'] = hook(**hook_input['kwargs'])
        File "/scratch/bc3194/conda-envs/mario/lib/python3.10/site-packages/pip/_vendor/pyproject_hooks/_in_process/_in_process.py", line 118, in get_requires_for_build_wheel
          return hook(config_settings)
        File "/tmpdata/pip-build-env-ml44wjni/overlay/lib/python3.10/site-packages/setuptools/build_meta.py", line 325, in get_requires_for_build_wheel
          return self._get_build_requires(config_settings, requirements=['wheel'])
        File "/tmpdata/pip-build-env-ml44wjni/overlay/lib/python3.10/site-packages/setuptools/build_meta.py", line 295, in _get_build_requires
          self.run_setup()
        File "/tmpdata/pip-build-env-ml44wjni/overlay/lib/python3.10/site-packages/setuptools/build_meta.py", line 311, in run_setup
          exec(code, locals())
        File "<string>", line 340, in <module>
        File "<string>", line 266, in get_vllm_version
        File "<string>", line 237, in get_nvcc_cuda_version
      TypeError: unsupported operand type(s) for +: 'NoneType' and 'str'
      [end of output]

  note: This error originates from a subprocess, and is likely not a problem with pip.
error: subprocess-exited-with-error

× Getting requirements to build wheel did not run successfully.
│ exit code: 1
╰─> See above for output.

note: This error originates from a subprocess, and is likely not a problem with pip.

I've met this issue before. I fixed it by installing it on a machine with GPU and cuda. (But some other issues came out.)

I encountered the same issue on two different machines using the specified PyTorch 2.1.2, CUDA 12.1, and setuptools. I hope the project maintainers can clean up the code or provide clearer installation instructions.

The dependencies of this project are very fragile; I successfully installed it in a strict CUDA 12.1 environment.

Basically, the installation of vllm in this repo is identical to the original vllm v0.3.3. As readme mentioned, the exact commit we used is vllm@f721096.
If you can install the original vllm v0.3.3, you should be able to install this repo. So I recommend an alternative installation method.

Install vllm v0.3.3 first

git clone https://github.com/vllm-project/vllm.git
cd vllm
git checkout f721096
pip install -e .

Just copy these modified files from our repo to your installed vllm in step 1.


upgrade redis-parser to remove DeprecationWarning: Buffer() is deprecated due to security and usability issues

Hello,
In node 10:
[DEP0005] DeprecationWarning: Buffer() is deprecated due to security and usability issues. Please use the Buffer.alloc(), Buffer.allocUnsafe(), or Buffer.from() methods instead.
at showFlaggedDeprecation (buffer.js:159:11)
at new Buffer (buffer.js:174:3)
at bufferAlloc (/app/node_modules/redis/node_modules/redis-parser/lib/parser.js:21:47)
at Object. (/app/node_modules/redis/node_modules/redis-parser/lib/parser.js:7:18)
at Module._compile (internal/modules/cjs/loader.js:689:30)
at Object.Module._extensions..js (internal/modules/cjs/loader.js:700:10)
at Module.load (internal/modules/cjs/loader.js:599:32)
at tryModuleLoad (internal/modules/cjs/loader.js:538:12)
at Function.Module._load (internal/modules/cjs/loader.js:530:3)
at Module.require (internal/modules/cjs/loader.js:637:17)
at require (internal/modules/cjs/helpers.js:20:18)
at Object. (/app/node_modules/redis/node_modules/redis-parser/index.js:3:18)
at Module._compile (internal/modules/cjs/loader.js:689:30)
at Object.Module._extensions..js (internal/modules/cjs/loader.js:700:10)
at Module.load (internal/modules/cjs/loader.js:599:32)
at tryModuleLoad (internal/modules/cjs/loader.js:538:12)
see also https://nodejs.org/en/docs/guides/buffer-constructor-deprecation/
upgrade redis-parser will solve the problem
Thanks.

Is node_redis a dead project?

@bigman73 Nope.

OK, thanks for clarifying that.
Could you please release an updated version that has the latest redis-parser module?

The latest parser is live on master and will be in the next release, thanks

Hey everyone, I've taken over as lead maintainer and have all the required access now 🎉 (thanks @BridgeAR)
I've spent the last few days getting master ready for a release, and as of a few minutes ago I've just published v3.0.0 to NPM; https://github.com/NodeRedis/node-redis/releases/tag/v3.0.0 - which includes this change.


chore: release main

:robot: I have created a release beep boop
create: 1.0.7
1.0.7 (2024-03-31)
Bug Fixes

publish attempt - 4 (2e20704)

This PR was generated with Release Please. See documentation.

:robot: Release is at https://github.com/templ-project/create/releases/tag/create-v1.0.7 :sunflower:


 via NBI/Webservice

Hi @jarlah , I'm sorry, I do not know which way to contact you, so I do it over here ...
I was able to start working with the STUN Server module, I configured a new parameter from the Web page, I pressed the "Provision" button and the FreeACS does the rest of the wonder.
This same I would like to do it via NBI, to be able to set the parameter and send the "Provision" that is sent via Web but by webservice.
When checking the LOG the command of  is observed, there is a way to do this without waiting for the PeriodicInformInterval to be fulfilled and the CPE come to read everything from the Server (FreeACS)
2018-09-04 18:41:03 [qtp1479100519-22] INFO  Conversation - =============== FROM ACS TO ( 434v3test ) ============
<soapenv:Envelope xmlns:soapenv="http://schemas.xmlsoap.org/soap/envelope/" xmlns:soapenc="http://schemas.xmlsoap.org/soap/encoding/" xmlns:xsd="http://www.w3.org/2001/XMLSchema" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:cwmp="urn:dslforum-org:cwmp-1-0">
	<soapenv:Header>
		<cwmp:ID soapenv:mustUnderstand="1">FREEACS-1536104463012</cwmp:ID>
	</soapenv:Header>
	<soapenv:Body>
		<cwmp:SetParameterValues>	<!--How send this command via NBI-->
			<ParameterList soapenc:arrayType="cwmp:ParameterValueStruct[4]">
				<ParameterValueStruct>
					<Name>InternetGatewayDevice.ManagementServer.PeriodicInformInterval</Name>
					<Value xsi:type="xsd:unsignedInt">73389</Value>
				</ParameterValueStruct>
				<ParameterValueStruct>
					<Name>InternetGatewayDevice.ManagementServer.ConnectionRequestPassword</Name>
					<Value xsi:type="xsd:string">admin</Value>
				</ParameterValueStruct>
				<ParameterValueStruct>
					<Name>InternetGatewayDevice.LANDevice.1.WLANConfiguration.2.PreSharedKey.1.KeyPassphrase</Name>
					<Value xsi:type="xsd:string">Clave5G</Value>
				</ParameterValueStruct>
				<ParameterValueStruct>
					<Name>InternetGatewayDevice.LANDevice.1.WLANConfiguration.1.PreSharedKey.1.KeyPassphrase</Name>
					<Value xsi:type="xsd:string">Clave24G</Value>
				</ParameterValueStruct>
			</ParameterList>
			<ParameterKey>af84b11484cad2507682f05738bc75d0</ParameterKey>
		</cwmp:SetParameterValues>
	</soapenv:Body>
</soapenv:Envelope>

What about POST http://localhost:8088/webservice/ws/AddOrChangeUnitRequest
You send in the same as with GetUnits, but it wil update the unit and its parameters.

POST http://localhost:8088/webservice/ws/AddOrChangeUnitRequest (the latter part of the url could be anything. its the method in the payload that counts)
<soapenv:Envelope xmlns:soapenv="http://schemas.xmlsoap.org/soap/envelope/" xmlns:x.="http://xml.ws.freeacs.github.com/">
   <soapenv:Header/>
   <soapenv:Body>
      <x.:AddOrChangeUnitRequest>
         <x.:login>
            <x.:username>admin</x.:username>
            <!--Optional:-->
            <x.:password>freeacs</x.:password>
         </x.:login>
         <x.:unit>
            <x.:unitId>sddsdddd</x.:unitId>
            <x.:profile>
            	<x.:name>Default</x.:name>
            </x.:profile>
            <x.:unittype>
            	<x.:name>sddd</x.:name>
            </x.:unittype>
            <x.:parameters>
	    		<x.:parameterArray>
	    			<x.:item>
	    				<x.:name>System.X_FREEACS-COM.Comment</x.:name>
	    				<x.:value>Hello world</x.:value>
	    			</x.:item>
	    		</x.:parameterArray>
            </x.:parameters>
         </x.:unit>
      </x.:AddOrChangeUnitRequest>
   </soapenv:Body>
</soapenv:Envelope>

gives
<SOAP-ENV:Envelope xmlns:SOAP-ENV="http://schemas.xmlsoap.org/soap/envelope/">
    <SOAP-ENV:Header/>
    <SOAP-ENV:Body>
        <ns2:AddOrChangeUnitResponse xmlns:ns2="http://xml.ws.freeacs.github.com/">
            <ns2:unit>
                <ns2:unitId>sddsdddd</ns2:unitId>
                <ns2:profile>
                    <ns2:name>Default</ns2:name>
                </ns2:profile>
                <ns2:unittype>
                    <ns2:name>sddd</ns2:name>
                </ns2:unittype>
                <ns2:parameters>
                    <ns2:parameterArray>
                        <ns2:item>
                            <ns2:name>System.X_FREEACS-COM.Comment</ns2:name>
                            <ns2:value>Hello world</ns2:value>
                        </ns2:item>
                    </ns2:parameterArray>
                </ns2:parameters>
            </ns2:unit>
        </ns2:AddOrChangeUnitResponse>
    </SOAP-ENV:Body>
</SOAP-ENV:Envelope>

the response is actually stupid, because it just echoes the unit info. But it does magic on the backend, updating parameters

This just showcase that you can set params. I need to think about the webservice module.  I need to assess how it can be fixed in short and long term.

Its very simple to add a KickUnit method in the soap interface. But i need to think about authentication and security first. First thought is that a default setup is too insecure. I need to generate a random password on each startup of each module, so that each module has it owns admin password when no admin password is set. This is how spring security works by default when no security is setup.
Next, I need to find out why there is a Login object in the request. I havent seen this very insecure method of authentication anywhere else before. Its actually a bit nice, because the user/pass is hidden by ssl/tls, instead of readable as in digest or basic (because they are in headers). But i am not sure about this. Maybe the automatic admin password generation is enough to make sure that new installations is not easily breakable. But we should think about requiring checksummed passwords in the Login object, and not the cleartext password.

Its very simple to add a KickUnit method in the soap interface. But i need to think about authentication and security first. First thought is that a default setup is too insecure. I need to generate a random password on each startup of each module, so that each module has it owns admin password when no admin password is set. This is how spring security works by default when no security is setup.
Next, I need to find out why there is a Login object in the request. I havent seen this very insecure method of authentication anywhere else before. Its actually a bit nice, because the user/pass is hidden by ssl/tls, instead of readable as in digest or basic (because they are in headers). But i am not sure about this. Maybe the automatic admin password generation is enough to make sure that new installations is not easily breakable. But we should think about requiring checksummed passwords in the Login object, and not the cleartext password.

Hello @jarlah , good day ... !!
I was testing the webservice http://localhost:8088/webservice/ws/AddOrChangeUnitRequest
There is some way to push the provisioning or some change directly to the CPE and not wait for the time when the UnitID is reported again.
And to be able to give a kick through the SOAP to the CPE.
¿?

https://github.com/freeacs/freeacs/pull/205

I have added a KickUnitRequest/KickUnitResponse request/response to webservice.

<soapenv:Envelope xmlns:soapenv="http://schemas.xmlsoap.org/soap/envelope/" xmlns:x.="http://xml.ws.freeacs.github.com/">
   <soapenv:Header/>
   <soapenv:Body>
      <x.:KickUnitRequest>
         <x.:login>
            <x.:username>admin</x.:username>
            <!--Optional:-->
            <x.:password>freeacs</x.:password>
         </x.:login>
         <x.:unitId>easycwmp</x.:unitId>
      </x.:KickUnitRequest>
   </soapenv:Body>
</soapenv:Envelope>

@penaivanalejandro please verify and we will close this issue. It will come in next ordinary release or you can use it in docker.

I started update when finish i start to test again..!
Give 20 minutes

Sorry I misunderstood, I thought that the change was already in place (in the webservice), the XML that you send would be excellent as a complement to the "AddOrChangeUnitRequest" command.

I Will release a minor minor version with this change today so it can be used on Ubuntu and centos

Aware,
I'm ready to test when he's released.
Greetings.

@penaivanalejandro ready to test on ubuntu now.

and now also rpm files. Its a veeery tedious process to create rpm files, so i really should consider making a docker based script that can build them for me.

Sir (@jarlah ) I want to congratulate you, it works correctly through the webservice ...
When sending the kick it shows the following message in the webservice log:
2018-10-17 16:00:19 [qtp181326224-24] DEBUG c.g.f.dbi.UnitQueryCrossUnittype - [      0.38 ms] SELECT u.unit_id, u.profile_id, u.unit_type_id, up.unit_type_param_id, u
p.value FROM unit u LEFT JOIN unit_param up ON u.unit_id = up.unit_id WHERE u.unit_id = 'IPHO00510BCF'
2018-10-17 16:00:20 [DBI for WebService] DEBUG com.github.freeacs.dbi.DBI - Message: [MTYPE: PUBLISH-IM, OTYPE: UNIT, FROM: WebService, TO: STUN, OBJECTID: 533660:IPHO
00510BCF] sent/inserted

In the CPE the change was immediately applied, thank you very much for this new module (kick).
If something comes out he reported it to you


Change AutostopServlet into AutostopHelper, and test properly

AutostopServlet is no longer in its own process because it's easier to just run
python commands in SkyPilot's venv through subprocess than start an actor inside
that interpreter. Here we're changing the AutostopServlet to AutostopHelper (a regular class,
not an Actor), fleshing out the available autostop commands it can make,  and testing it thoroughly.
Previously keep_warm or the cluster.autostop_mins setter wouldn't work if called on the cluster,
now they do.

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This pull request is not mergeable via GitHub because a downstack PR is open. Once all requirements are satisfied, merge this PR as a stack on Graphite.
Learn more

#897  👈
#896
#895
#894
main

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Merge activity

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Dask Dataframe does not support Pandas dtype 'Float32'

pd_df = pd.DataFrame({
		'float32': pd.Series([None, 1,<PHONE_NUMBER>], dtype="Float32"),
		'float64': pd.Series([None, 1,<PHONE_NUMBER>3709551615], dtype="Float64")}
)

dd_df = dd.from_pandas(pd_df, npartitions=10)
print(dd_df['float32'].values)
# This last line caused the crash

What happened:
Traceback (most recent call last):
  File "dask_test.py", line 17, in <module>
    print(dd_df['float32'].values)
  File "/opt/homebrew/lib/python3.9/site-packages/dask/dataframe/core.py", line 3324, in values
    return self.map_partitions(methods.values)
  File "/opt/homebrew/lib/python3.9/site-packages/dask/dataframe/core.py", line 867, in map_partitions
    return map_partitions(func, self, *args, **kwargs)
  File "/opt/homebrew/lib/python3.9/site-packages/dask/dataframe/core.py", line 6578, in map_partitions
    return new_dd_object(graph, name, meta, divisions)
  File "/opt/homebrew/lib/python3.9/site-packages/dask/dataframe/core.py", line 7706, in new_dd_object
    return da.Array(dsk, name=name, chunks=chunks, dtype=meta.dtype)
  File "/opt/homebrew/lib/python3.9/site-packages/dask/array/core.py", line 1329, in __new__
    meta = meta_from_array(meta, dtype=dtype)
  File "/opt/homebrew/lib/python3.9/site-packages/dask/array/utils.py", line 57, in meta_from_array
    x = x(shape=(0,) * (ndim or 0), dtype=dtype)
TypeError: Cannot interpret 'Float32Dtype()' as a data type

What you expected to happen:
I would expect the either from_pandas to fail instantly, or for it to be able to work with the dtype
Anything else we need to know?:
Environment:

Dask version: installed through python3 -m pip install dask

>>> dask._version.version_json
'\n{\n "dirty": false,\n "error": null,\n "full-revisionid": "a77ce9513745d64cb47033d5f8026b3acc5424bf",\n "version": "2022.8.0"\n}\n'

Python version: 3.9.13
Operating System: MacOS
Install method (conda, pip, source): pip

Thanks for raising @Tishj
It looks like the problem here is in the creation of a dask.array.Array with a Float32Dtype() (and probably not in dask.dataframe). As far as I can tell, dask.dataframe works with these dtypes just fine, but dask.array gets tripped up at creation time (i.e. when ddf.values is used). Here is another reproducer:
import dask.array as da
import dask.dataframe as dd
import pandas as pd

s_f32 = pd.Series([None, 1,<PHONE_NUMBER>], dtype="float32")
s_F32 = pd.Series([None, 1,<PHONE_NUMBER>], dtype="Float32")

dd.from_pandas(s_f32, npartitions=2).compute()  # Works fine
dd.from_pandas(s_F32, npartitions=2).compute()  # Works fine

da.from_array(s_f32)  # Works fine
da.from_array(s_F32)  # Fails with `TypeError: Cannot interpret 'Float32Dtype()' as a data type`

This is an ongoing issue. Dask doesn't support extension types altogether. Not just this one, but all of them, see #5720


[TA] only run tests where features supported

Looked at the wrong pipeline and assumed we were good. Missed a few more tests where these features are not supported yet in non-public cloud.
https://dev.azure.com/azure-sdk/internal/_build/results?buildId=1987607&view=results

API change check
API changes are not detected in this pull request.


questions about UIAD setting

Hi, great work!
I was wondering, in the UIAD setting which Table 2 used, the model are trained on all categories in the dataset and tested on each category (the setting UniAD proposed)? or the model are trained on one specific category and tested on the corresponding category (one model for one category)?
Thanks in advance!

The latter, that is, the single-class setting where one model corresponds to one class, which is not the unified setting as discussed in UniAD and ViTAD.

Thanks, I got it!


SplitText operation seems not using UTF-8 encoding

Maybe I am not consuming the API as it is expected.

Insert a single text 👨👩👧 into a new Automerge.Document is expected to have a length equal to 👨👩👧.utf8.count. But it is retrieving a non-expected length.
After doing some checks I can confirm the next:

Swift.UTF-8 👨👩👧 = 18 bytes; received: 5
Swift.UTF-8 👩👩👧👦 = 25 bytes; received: 7
Swift.UTF-8 🕰 = 7 bytes; received: 2

./cc @alexjg

Thank you for this example setup - I've incorporated it into #99, and with it found a number of issues elsewhere in the higher level apis that were using the incorrect assumptions about UTF-8 code points, which are also resolved with #99. I'm closing this PR, with the relevant code sample illustrating what's working in #99 - and with multiple verifications there.

@heckj Thanks for all the work around it, and the new version - it is really helpful


what does the "Pair" means in the status bar when enabling "showDebug" on demo page?

hi there,  I modified the "sensor" example, made 1500 random static polygons, each with 30 sides. then added a circle sensor, keep setPosition of it and keep it NOT sleep.
When everything not sleep, the "Pair" value is always around 90-95 (collided polygons normally is about 50, plus extra polygons on the way to fall sleep equals about 90-95 in total)
When enable sleeping in "engine" menu, all polygons went to sleep except those ones collided with the moving circle, the "Pair" then becomes the total number of circles HAS collided with circle on the moving path from left to right, and finally stay at 349.
Is this number bigger means optimised better or should be smaller.  If smaller is better then making things sleep should not make it becomes larger number, right? I am little confused about the value.

The Pair number refers to the number of collision pairs currently in the engine's internal collision pair manager, which is roughly the number of colliding pairs of bodies in the last few seconds (it should drop when collisions end).
The number just relates to how many collisions are happening, so I wouldn't worry about this number unless you're familiar with the internal collision system and know there is a problem?

thanks for feedback~ :)


Changes made on first feedback

Add project milestone
delete the pypkgknnclassifier since it is empty

completed during meeting
completed at #57


Incorrect date display with the parameter weekStart = 1

When the "weekStart" parameter is set to 1 in November 2020, the calendar is displayed incorrectly. It is stated that November 1 is Monday. All other months are working correctly:
TDatepicker: {
    weekStart: 1,
    dateFormat: 'Y-m-d',
    userFormat: 'd.m.Y',
},

Hey just to ley you know that I already saw your issue, was especially busy the last week but ill take care of this tomorrow

@gerasimovs problem solved please update to the latest version of the package ^1.3.1


Leaflet map coordinate issue

From Jay's email: 9/27/2021

Another thought on the -180to 180 cycle problem in mapping:
I simple and helpful interim solution could be to put a button in a corner of the map labeled “whole earth”, and the response to a click would be to display the map from lon -180 to 180, lat -80 to  80 or -90 to 90. This would support users who want to plot global information, and also as a handy intermediate step before zooming into to a particular location.

A related development would add a related selection option (check box?) to the various mapping tabs (GNSS, UAVSAR, Seismicity, etc).  This could be a “whole earth” selection box adjacent to the “Draw an area on map.”  This would fill the lon, lat span entries with -180 to 180, -90 to 90.

These proposed modifications would be particularly helpful for educational applications: it is easy and interesting to display earthquakes > M6 over any 20 year period, to highlight the ring of fire and the mid-atlantic ridge.  It is also interesting to plot the global set of GNSS (JPL) velocities, which together with the >M6 seismicity tells much of the story of plate tectonics for students.
Attempting this with the current system requires considerable risk (the view of the map needs to be centered at 0, 0, which is not simple to select), and risks embarrassing results when views are selected that span the -180 180 longitude cycle jump: only part of the display data is displayed on the map in those cases, similar to the troubles documented in the earlier message (below).
In summary, adding a whole-earth standard map view together with a whole-earth option for data selection, GeoGateway will be more useful for educators and students, and easier to demonstrate live with  much-reduced risk of missing data. A complete solution to the problems for selections boxes crossing the longitude 180 line would also be helpful, but could be implemented later with more care.

https://leafletjs.com/reference-1.7.1.html#map-option  maxBounds  worldCopyJump  wrapLatLng


Error in sample code

There's an error in the code that you add to Function1.cs.
In the Run method you have this:
await ConfigurationRefresher.Refresh();
when it should be this:
await ConfigurationRefresher.RefreshAsync();

Document Details
⚠ Do not edit this section. It is required for docs.microsoft.com ➟ GitHub issue linking.

ID: 22237330-6826-5a33-80b9-73c9beb5417a
Version Independent ID: 5aadf141-63c8-9f12-e010-939ef4b9958c
Content: Tutorial for using Azure App Configuration dynamic configuration in an Azure Functions app
Content Source: articles/azure-app-configuration/enable-dynamic-configuration-azure-functions-csharp.md
Service: azure-app-configuration
GitHub Login: @zhenlan
Microsoft Alias: zhenlwa

@probertdaniel , Thanks for brining this to our attention. We will investigate it further and update you shortly.


Adds Sine Wave Pascal implementation

Compiled with FreePascal:
fpc sinewave.pas

I've moved Pascal to the "alternate implementations" folder since we can't guarantee memory safety with it:
https://github.com/coding-horror/basic-computer-games/tree/main/00_Alternate_Languages/78_Sine_Wave

Moved the pascal implementation to 00_Alternate_Languages/78_Sine_Wave

Thank you! 🙏


Add init option description to the example

Add a simple description of 'init' option to the example.
Close #63

Thanks, much appreciated


createSymbolicLink: already exists (File exists) - this time with docker in the path

With cache-s3 v0.1.2, this is still happening:
cache-s3: /home/xxxxxxxx/xxxxxxxxxxx/.stack-work/docker/_home/.ssh: createSymbolicLink: already exists (File exists)

The build is using Stack's Docker support.

Under normal condition It should remove any existing symlink with the same name before creating a new one. I don't have any project currently setup with docker to test it myself, so could you please check the ownership and permissions of that link and check if current user has enough privileges to remove it?

At the same time, symlinks' permissions are always 0o777, so this unlikely to be the cause of the problem.
Here is the code that is responsible for this error: https://github.com/snoyberg/tar-conduit/blob/master/src/Data/Conduit/Tar/Unix.hs#L78-L79
So, the only way to debug this problem is to try to remove that link manually from ghci and see what error will it throw:
λ> import System.Posix.Files as Posix
λ> Posix.removeLink "/home/xxxxxxxx/xxxxxxxxxxx/.stack-work/docker/_home/.ssh"

I suspect you're right and there were some permissions issues on that runner. The runner is gone so I can't investigate the exact conditions. However, the error message in case of a permissions error should be different.

I've worked with docker many times and I am more than sure this issue is caused by permissions. More specifically ownership and permissions on this folder /home/xxxxxxxx/xxxxxxxxxxx/.stack-work/docker/_home/. The error message, although maybe a bit misleading, is exactly what expected: Link is already there and cannot be replaced. Here is the reason why, consider a folder bar and a file bar/foo owned by root:
λ> Posix.removeLink "bar/foo"
*** Exception: bar/foo: removeLink: permission denied (Permission denied)
λ> _ <- tryAny $ Posix.removeLink "bar/foo"
λ> Posix.createSymbolicLink "baz" "bar/foo"
*** Exception: baz: createSymbolicLink: already exists (File exists)

Point is, currently we ignore any errors when trying to remove the link, because we define restore operation as best effort.
Regardless of the error message, I don't think there is a workaround that can be implemented in cache-s3 or tar-conduit. The only thing I can think of is adding an extra command: cache-s3 rm, which would remove all files/folders that would be cached, so it can be executed separately with sudo. I'll add a separate ticket for that.


Fix: Incorrect LHN subtitle when last message is flagged as assault

Details

The LHN subtitle should display the correct subtitle when the last message is flagged as assault
Fixed Issues

$ https://github.com/Expensify/App/issues/30575
PROPOSAL: https://github.com/Expensify/App/issues/30575#issuecomment-1788560074
Tests

User A’s App

Add a task to a Chat Report with User B.
Add a task message to the Task Report.
Cancel the task using 3dots menu in Task Report.
Navigate back to Chat Report. The canceled task will be shown as [Deleted task] in report screen.
Add a new message to the chat report (say Message to be flagged as assault)

User B’s App

Now, move to the app where User B is signed-in and navigate to chat report with User A.
Flag the message (i.e. Message to be flagged as assault) with User A as assault.
Verify that the LHN subtitle displayed ’[Deleted task]’

[x] Verify that no errors appear in the JS console

Offline tests

QA Steps

User A’s App

Add a task to a Chat Report with User B.
Add a task message to the Task Report.
Cancel the task using 3dots menu in Task Report.
Navigate back to Chat Report. The canceled task will be shown as [Deleted task] in report screen.
Add a new message to the chat report (say Message to be flagged as assault)

User B’s App

Now, move to the app where User B is signed-in and navigate to chat report with User A.
Flag the message (i.e. Message to be flagged as assault) with User A as assault.
Verify that the LHN subtitle displayed ’[Deleted task]’

[x] Verify that no errors appear in the JS console

PR Author Checklist

[x] I linked the correct issue in the ### Fixed Issues section above
[x] I wrote clear testing steps that cover the changes made in this PR

[x] I added steps for local testing in the Tests section
[x] I added steps for the expected offline behavior in the Offline steps section
[x] I added steps for Staging and/or Production testing in the QA steps section
[x] I added steps to cover failure scenarios (i.e. verify an input displays the correct error message if the entered data is not correct)
[x] I turned off my network connection and tested it while offline to ensure it matches the expected behavior (i.e. verify the default avatar icon is displayed if app is offline)
[x] I tested this PR with a High Traffic account against the staging or production API to ensure there are no regressions (e.g. long loading states that impact usability).

[x] I included screenshots or videos for tests on all platforms
[x] I ran the tests on all platforms & verified they passed on:

[x] Android: Native
[x] Android: mWeb Chrome
[x] iOS: Native
[x] iOS: mWeb Safari
[x] MacOS: Chrome / Safari
[x] MacOS: Desktop

[x] I verified there are no console errors (if there's a console error not related to the PR, report it or open an issue for it to be fixed)
[x] I followed proper code patterns (see Reviewing the code)

[x] I verified that any callback methods that were added or modified are named for what the method does and never what callback they handle (i.e. toggleReport and not onIconClick)
[x] I verified that the left part of a conditional rendering a React component is a boolean and NOT a string, e.g. myBool && <MyComponent />.
[x] I verified that comments were added to code that is not self explanatory
[x] I verified that any new or modified comments were clear, correct English, and explained "why" the code was doing something instead of only explaining "what" the code was doing.
[x] I verified any copy / text shown in the product is localized by adding it to src/languages/* files and using the translation method

[x] If any non-english text was added/modified, I verified the translation was requested/reviewed in #expensify-open-source and it was approved by an internal Expensify engineer. Link to Slack message:

[x] I verified all numbers, amounts, dates and phone numbers shown in the product are using the localization methods
[x] I verified any copy / text that was added to the app is grammatically correct in English. It adheres to proper capitalization guidelines (note: only the first word of header/labels should be capitalized), and is approved by marketing by adding the Waiting for Copy label for a copy review on the original GH to get the correct copy.
[x] I verified proper file naming conventions were followed for any new files or renamed files. All non-platform specific files are named after what they export and are not named "index.js". All platform-specific files are named for the platform the code supports as outlined in the README.
[x] I verified the JSDocs style guidelines (in STYLE.md) were followed

[x] If a new code pattern is added I verified it was agreed to be used by multiple Expensify engineers
[x] I followed the guidelines as stated in the Review Guidelines
[x] I tested other components that can be impacted by my changes (i.e. if the PR modifies a shared library or component like Avatar, I verified the components using Avatar are working as expected)
[x] I verified all code is DRY (the PR doesn't include any logic written more than once, with the exception of tests)
[x] I verified any variables that can be defined as constants (ie. in CONST.js or at the top of the file that uses the constant) are defined as such
[x] I verified that if a function's arguments changed that all usages have also been updated correctly
[x] If a new component is created I verified that:

[x] A similar component doesn't exist in the codebase
[x] All props are defined accurately and each prop has a /** comment above it */
[x] The file is named correctly
[x] The component has a clear name that is non-ambiguous and the purpose of the component can be inferred from the name alone
[x] The only data being stored in the state is data necessary for rendering and nothing else
[x] If we are not using the full Onyx data that we loaded, I've added the proper selector in order to ensure the component only re-renders when the data it is using changes
[x] For Class Components, any internal methods passed to components event handlers are bound to this properly so there are no scoping issues (i.e. for onClick={this.submit} the method this.submit should be bound to this in the constructor)
[x] Any internal methods bound to this are necessary to be bound (i.e. avoid this.submit = this.submit.bind(this); if this.submit is never passed to a component event handler like onClick)
[x] All JSX used for rendering exists in the render method
[x] The component has the minimum amount of code necessary for its purpose, and it is broken down into smaller components in order to separate concerns and functions

[x] If any new file was added I verified that:

[x] The file has a description of what it does and/or why is needed at the top of the file if the code is not self explanatory

[x] If a new CSS style is added I verified that:

[x] A similar style doesn't already exist
[x] The style can't be created with an existing StyleUtils function (i.e. StyleUtils.getBackgroundAndBorderStyle(themeColors.componentBG))

[x] If the PR modifies code that runs when editing or sending messages, I tested and verified there is no unexpected behavior for all supported markdown - URLs, single line code, code blocks, quotes, headings, bold, strikethrough, and italic.
[x] If the PR modifies a generic component, I tested and verified that those changes do not break usages of that component in the rest of the App (i.e. if a shared library or component like Avatar is modified, I verified that Avatar is working as expected in all cases)
[x] If the PR modifies a component related to any of the existing Storybook stories, I tested and verified all stories for that component are still working as expected.
[x] If the PR modifies a component or page that can be accessed by a direct deeplink, I verified that the code functions as expected when the deeplink is used - from a logged in and logged out account.
[x] If a new page is added, I verified it's using the ScrollView component to make it scrollable when more elements are added to the page.
[x] If the main branch was merged into this PR after a review, I tested again and verified the outcome was still expected according to the Test steps.
[x] I have checked off every checkbox in the PR author checklist, including those that don't apply to this PR.

Screenshots/Videos

Android: Native
https://github.com/Expensify/App/assets/129500732/f9153706-7f09-4e8d-826e-44e7aa8dccd8

Android: mWeb Chrome
https://github.com/Expensify/App/assets/129500732/00e4ffb5-0159-443a-bb71-21d09c4e4639

iOS: Native
https://github.com/Expensify/App/assets/129500732/cb704d69-8d04-425c-bf4a-d365967f89c0

iOS: mWeb Safari
https://github.com/Expensify/App/assets/129500732/0ebbd967-8b09-45ff-9a98-bcb31a3bc297

MacOS: Chrome / Safari
https://github.com/Expensify/App/assets/129500732/8e3a528d-ba92-4d7a-9285-5f421bfe7b0f

MacOS: Desktop

https://github.com/Expensify/App/assets/129500732/595dff8c-0647-4ce5-8ab8-85e88197aae9

:hand: This PR was not deployed to staging yet because QA is ongoing. It will be automatically deployed to staging after the next production release.

🚀 Deployed to staging by https://github.com/tylerkaraszewski in version: 1.3.99-0 🚀

platform
result

🤖 android 🤖
success ✅

🖥 desktop 🖥
success ✅

🍎 iOS 🍎
success ✅

🕸 web 🕸
success ✅

🚀 Deployed to production by https://github.com/roryabraham in version: 1.3.99-0 🚀

platform
result

🤖 android 🤖
success ✅

🖥 desktop 🖥
success ✅

🍎 iOS 🍎
success ✅

🕸 web 🕸
success ✅


OP_REVERSEBYTES / BCH_2020_05

This PR adds a new OP_REVERSEBYTES opcode to a new BCH_2020_05_STRICT_SPEC. It also updates the script_tests.json with Bitcoin-ABC's OP_REVERSEBYTES tests. To make the script_tests work without to many changes, I also added a non-strict BCH_2020_05_SPEC, which uses the same standardness checks as BCH_2019_05 (which is not strictly correct for 2020_05, since most of those stanardness checks have been incorporated into the consensus rules.

@rkalis this is fantastic, thanks for the PR! Well done on updating the "addendum" too, I'm sure that was a pain. 😅
Should have a release out shortly 👍


THE BROWN STAINS OF DARKEESE LATIFAH PART 6-12 (REMIX) (feat. ScHoolboy Q) by Tyler, The Creator unsupported.

Check if issue with swaglyrics or whether song lyrics unavailable on Genius.

stripper -> Tyler-The-Creator-THE-BROWN-STAINS-OF-DARKEESE-LATIFAH-PART-6-12

added


[bug]modify TaskMainInfo class field's type

modify TaskMainInfo class field's type
#12673

Codecov Report

Merging #12674 (5f1c07c) into dev (f889d85) will decrease coverage by 0.02%.
The diff coverage is n/a.

@@             Coverage Diff              @@
##                dev   #12674      +/-   ##
============================================
- Coverage     39.03%   39.01%   -0.03%
- Complexity     4182     4183       +1
============================================
  Files          1043     1043
  Lines         39514    39469      -45
  Branches       4545     4527      -18
============================================
- Hits          15423    15397      -26
+ Misses        22332    22314      -18
+ Partials       1759     1758       -1

Impacted Files
Coverage Δ

...eduler/api/dto/schedule/ScheduleCreateRequest.java
83.33% <0.00%> (-2.39%)
:arrow_down:

...e/dolphinscheduler/service/queue/TaskPriority.java
51.31% <0.00%> (-1.25%)
:arrow_down:

...r/plugin/task/sqoop/parameter/SqoopParameters.java
51.19% <0.00%> (-1.20%)
:arrow_down:

...cheduler/plugin/alert/dingtalk/DingTalkSender.java
34.13% <0.00%> (-0.78%)
:arrow_down:

...inscheduler/plugin/registry/etcd/EtcdRegistry.java
50.34% <0.00%> (-0.69%)
:arrow_down:

...he/dolphinscheduler/plugin/task/java/JavaTask.java
58.50% <0.00%> (-0.69%)
:arrow_down:

...lphinscheduler/api/dto/task/TaskCreateRequest.java
83.33% <0.00%> (-0.54%)
:arrow_down:

...hinscheduler/service/storage/impl/HadoopUtils.java
10.59% <0.00%> (-0.49%)
:arrow_down:

.../apache/dolphinscheduler/common/utils/OSUtils.java
33.33% <0.00%> (-0.40%)
:arrow_down:

...olphinscheduler/plugin/alert/email/ExcelUtils.java
81.25% <0.00%> (-0.39%)
:arrow_down:

... and 22 more

:mega: We’re building smart automated test selection to slash your CI/CD build times. Learn more


not work in "react-native": "0.61.5", and crashing

"react": "16.9.0",
"react-native": "0.61.5",
"react-native-background-job": "^2.3.1",
BackgroundJob.register({
jobKey: JobKeyStr,
job: () => {
this.uploadvideoBackTask(formdata, JobKeyStr, data.source);
}
});
                BackgroundJob.schedule({
                    jobKey: JobKeyStr,
                    notificationTitle: "Notification title",
                    notificationText: "Notification text",
                    allowWhileIdle: true,
                    allowExecutionInForeground: true,
                    period: 1000
                });

Same problem...

+1

It seems to me helped

in AndroidManifest.xml


fix map equality

Fix map equality when keys are added to the second map.
Fixes #304

 Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.You have signed the CLA already but the status is still pending? Let us recheck it.

@timostamm thanks. I simplified the code and added a few more tests.


Project admin interface gives a 500 server error

As of now:
https://alyx.internationalbrainlab.org/admin/subjects/project/

Fixed in d3300f77538461bc4c1f6d5b2cca88a47ebe9e72