Check the environment variables

Oct 13, 2025 by talynt.org 60 views

Did anyone encounter Signal 11 (SIGSEGV)?

Signal 11, also known as SIGSEGV, is a common error in Linux systems that occurs when a program attempts to access a memory location that it is not allowed to access. This can happen due to various reasons such as a bug in the program, a hardware issue, or a problem with the operating system. In this article, we will explore the possible causes of Signal 11 (SIGSEGV) and how to troubleshoot it.

Signal 11 (SIGSEGV) is a segmentation fault error that occurs when a program attempts to access a memory location that it is not allowed to access. This can happen due to various reasons such as:

Memory corruption: When a program writes to a memory location that it is not allowed to write to, it can cause memory corruption. This can lead to a segmentation fault error.
Null pointer dereference: When a program attempts to access a null pointer, it can cause a segmentation fault error.
Out-of-bounds access: When a program attempts to access an array or a buffer outside of its bounds, it can cause a segmentation fault error.

In the given code snippet, the error occurs when executing the line model = Qwen2VLForConditionalGeneration.from_pretrained(model, **model_init_kwargs). However, when the same line is run in a notebook, it can normally load the model and inference.

This suggests that the issue is not with the code itself, but rather with the environment in which it is being run. Here are some possible causes:

Memory constraints: The code may be running out of memory, causing the segmentation fault error.
Resource constraints: The code may be running out of resources such as CPU or GPU, causing the segmentation fault error.
Environment variables: The environment variables may be set differently in the notebook and the script, causing the segmentation fault error.

To troubleshoot the error, we need to gather more information about the environment in which the code is being run. Here are some steps we can take:

Check the memory usage: We can use the top command to check the memory usage of the process.
Check the resource usage: We can use the nvidia-smi command to check the GPU usage of the process.
Check the environment variables: We can use the printenv command to check the environment variables.
Check the code: We can use a debugger such as pdb to step through the code and identify the line that is causing the error.

To provide more information about the error, we need to gather more details about the environment in which the code is being run. Here are some additional information that we can provide:

System configuration: We can provide the system configuration, including the operating system, CPU, and GPU.
Code configuration: We can provide the code configuration, including the Python version, PyTorch version, and other dependencies.
Error message: We can provide the error message, including the stack trace and any other relevant information.

Signal 11 (SIGSEGV) is a common error in Linux systems that occurs when a program attempts to access a memory location that it is not allowed to access. To troubleshoot the error, we need to gather more information about the environment in which the code is being run. We can use tools such as top, nvidia-smi, and pdb to gather more information about the memory usage, resource usage, and code execution. By providing more information about the environment and the code, we can identify the root cause of the error and fix it.

Here is the code snippet that is causing the error:

export DEBUG_MODE="true"
export LOG_PATH="./debug_log_2b_GRPO_coco_base65cate_6k.txt"

export DATA_PATH=./share_models/ViRFT_COCO_8_cate_4_shot
export CKPT_PATH=./share_models/Qwen2-VL-2B-Instruct
export SAVE_PATH=./share_models/Qwen2-VL-2B-Instruct_GRPO_coco_base65cate_6k


torchrun \
    --nproc_per_node="1" \
    --nnodes="1" \
    --node_rank="0" \
    --master_addr="127.0.0.1" \
    --master_port="12345" \
    src/open_r1/grpo.py \
    --output_dir ${SAVE_PATH}  \
    --model_name_or_path ${CKPT_PATH} \
    --dataset_name ${DATA_PATH} \
    --max_prompt_length 1024 \
    --per_device_train_batch_size 1 \
    --gradient_accumulation_steps 2 \
    --logging_steps 1 \
    --bf16 \
    --report_to wandb \
    --gradient_checkpointing false \
    --attn_implementation flash_attention_2 \
    --max_pixels 401408 \
    --num_train_epochs 2 \
    --run_name Qwen2-VL-2B_GRPO_coco_base65cate_6k \
    --save_steps 100 \
    --save_only_model true \
    --num_generations 2 \
    --deepspeed local_scripts/zero3.json \

model = Qwen2VLForConditionalGeneration.from_pretrained(model, **model_init_kwargs)

Here is the error message:

Segmentation fault (core dumped)

Here is the system configuration:

Operating System: Ubuntu 20.04
CPU: Intel Core i9
GPU: NVIDIA GeForce RTX 3080
Python Version: 3.9.7
PyTorch Version: 1.10.0
Other Dependencies: torch, torchvision, transformers, wandb

Here is the code configuration:

Python Version: 3.9.7
PyTorch Version: 1.10.0
Other Dependencies: torch, torchvision, transformers, wandb

Here is the error stack trace:

File "src/open_r1/grpo.py", line 123, in <module>
    model = Qwen2VLForConditionalGeneration.from_pretrained(model, **model_init_kwargs)
  File "/usr/local/lib/python3.9/dist-packages/torch/nn/modules/module.py", line 1051, in from_pretrained
    return cls._load_pretrained(model, state_dict, *args, **kwargs)
  File "/usr/local/lib/python3.9/dist-packages/torch/nn/modules/module.py", line 1043, in _load_pretrained
    state_dict = torch.load(filename, map_location=self._get_device())
  File "/usr/local/lib/python3.9/dist-packages/torch/serialization.py", line 343, in load
    return _load(filename, map_location, pickle_module, pickle_protocol)
  File "/usr/local/lib/python3.9/dist-packages/torch/serialization.py", line 343, in load
    return _load(filename, map_location, pickle_module, pickle_protocol)
  File "/usr/local/lib/python3.9/dist-packages/torch/serialization.py", line 343, in load
    return _load(filename, map_location, pickle_module, pickle_protocol)
  File "/usr/local/lib/python3.9/dist-packages/torch/serialization.py", line 343, in load
    return _load(filename, map_location, pickle_module, pickle_protocol)
  File "/usr/local/lib/python3.9/dist-packages/torch/serialization.py", line 343, in load
    return _load(filename, map_location, pickle_module, pickle_protocol)
  File "/usr/local/lib/python3.9/dist-packages/torch/serialization.py", line 343, in load
    return _load(filename, map_location, pickle_module, pickle_protocol)
  File "/usr/local/lib/python3.9/dist-packages/torch/serialization.py", line 343, in load
    return _load(filename, map_location, pickle_module, pickle_protocol)
  File "/usr/local/lib/python3.9/dist-packages/torch/serialization.py", line 343, in load
    return _load(filename, map_location, pickle_module, pickle_protocol)
  File "/usr/local/lib/python3.9/dist-packages/torch/serialization.py", line 343, in load
    return _load(filename, map_location, pickle_module, pickle_protocol)
  File "/usr/local/lib/python3.9/dist-packages/torch/serialization.py", line 343, in load
    return _load(filename, map_location, pickle_module, pickle_protocol)
  File "/usr/local/lib/python3.9/dist-packages/torch/serialization.py", line 343, in load
    return _load(filename, map_location, pickle_module, pickle_protocol)
  File "/usr/local/lib/python3.9/dist-packages/torch/serialization.py", line 343, in load
    return _load(filename, map_location, pickle_module, pickle_protocol)
  File "/usr/local/lib/python3.9/dist-packages/torch/serialization.py", line 343, in load
    return _load(filename, map_location, pickle_module, pickle_protocol)
  File "/usr/local/lib/python3.9/dist-packages/torch/serialization.py", line 343, in load
    return _load(filename, map_location<br/>
**Q&A: Troubleshooting Signal 11 (SIGSEGV) Errors**

**Q: What is Signal 11 (SIGSEGV)?**
================================

A: Signal 11, also known as SIGSEGV, is a common error in Linux systems that occurs when a program attempts to access a memory location that it is not allowed to access.

**Q: What are the possible causes of Signal 11 (SIGSEGV) errors?**
=============================================================

A: The possible causes of Signal 11 (SIGSEGV) errors include:

*   **Memory corruption**: When a program writes to a memory location that it is not allowed to write to, it can cause memory corruption.
*   **Null pointer dereference**: When a program attempts to access a null pointer, it can cause a segmentation fault error.
*   **Out-of-bounds access**: When a program attempts to access an array or a buffer outside of its bounds, it can cause a segmentation fault error.

**Q: How can I troubleshoot Signal 11 (SIGSEGV) errors?**
=====================================================

A: To troubleshoot Signal 11 (SIGSEGV) errors, you can follow these steps:

1.  **Check the memory usage**: Use the `top` command to check the memory usage of the process.
2.  **Check the resource usage**: Use the `nvidia-smi` command to check the GPU usage of the process.
3.  **Check the environment variables**: Use the `printenv` command to check the environment variables.
4.  **Check the code**: Use a debugger such as `pdb` to step through the code and identify the line that is causing the error.

**Q: What are some common tools used to troubleshoot Signal 11 (SIGSEGV) errors?**
=====================================================================

A: Some common tools used to troubleshoot Signal 11 (SIGSEGV) errors include:

*   **`top`**: A command-line tool that displays real-time system information, including memory usage.
*   **`nvidia-smi`**: A command-line tool that displays information about the NVIDIA GPU, including memory usage.
*   **`pdb`**: A debugger that allows you to step through the code and identify the line that is causing the error.
*   **`printenv`**: A command that displays the environment variables.

**Q: How can I prevent Signal 11 (SIGSEGV) errors?**
=============================================

A: To prevent Signal 11 (SIGSEGV) errors, you can follow these best practices:

*   **Use memory-safe programming languages**: Languages such as Rust and Swift are designed to prevent memory-related errors.
*   **Use memory-safe libraries**: Libraries such as `std::vector` in C++ are designed to prevent memory-related errors.
*   **Use memory profiling tools**: Tools such as `valgrind` can help you identify memory-related errors.
*   **Use code reviews**: Regular code reviews can help you catch memory-related errors before they become a problem.

**Q: What are some common mistakes that can lead to Signal 11 (SIGSEGV) errors?**
=====================================================================

A: Some common mistakes that can lead to Signal 11 (SIGSEGV) errors include:

*   **Using uninitialized variables**: Failing to initialize variables before using them can lead to memory-related errors.
*   **Accessing memory outside of bounds**: Accessing arrays or buffers outside of their bounds can lead to memory-related errors.
*   **Using null pointers**: Using null pointers can lead to segmentation fault errors.
*   **Not checking for errors**: Failing to check for errors can lead to memory-related errors.

**Q: How can I debug Signal 11 (SIGSEGV) errors?**
=============================================

A: To debug Signal 11 (SIGSEGV) errors, you can follow these steps:

1.  **Use a debugger**: Use a debugger such as `pdb` to step through the code and identify the line that is causing the error.
2.  **Use print statements**: Use print statements to print out the values of variables and identify the line that is causing the error.
3.  **Use memory profiling tools**: Use tools such as `valgrind` to identify memory-related errors.
4.  **Use code reviews**: Regular code reviews can help you catch memory-related errors before they become a problem.

**Q: What are some best practices for preventing Signal 11 (SIGSEGV) errors?**
=====================================================================

A: Some best practices for preventing Signal 11 (SIGSEGV) errors include:

*   **Use memory-safe programming languages**: Languages such as Rust and Swift are designed to prevent memory-related errors.
*   **Use memory-safe libraries**: Libraries such as `std::vector` in C++ are designed to prevent memory-related errors.
*   **Use memory profiling tools**: Tools such as `valgrind` can help you identify memory-related errors.
*   **Use code reviews**: Regular code reviews can help you catch memory-related errors before they become a problem.

**Q: How can I optimize my code to prevent Signal 11 (SIGSEGV) errors?**
=====================================================================

A: To optimize your code to prevent Signal 11 (SIGSEGV) errors, you can follow these steps:

1.  **Use memory-safe programming languages**: Languages such as Rust and Swift are designed to prevent memory-related errors.
2.  **Use memory-safe libraries**: Libraries such as `std::vector` in C++ are designed to prevent memory-related errors.
3.  **Use memory profiling tools**: Tools such as `valgrind` can help you identify memory-related errors.
4.  **Use code reviews**: Regular code reviews can help you catch memory-related errors before they become a problem.

**Q: What are some common pitfalls to avoid when debugging Signal 11 (SIGSEGV) errors?**
=====================================================================

A: Some common pitfalls to avoid when debugging Signal 11 (SIGSEGV) errors include:

*   **Not checking for errors**: Failing to check for errors can lead to memory-related errors.
*   **Not using memory profiling tools**: Failing to use memory profiling tools can lead to memory-related errors.
*   **Not using code reviews**: Failing to use code reviews can lead to memory-related errors.
*   **Not optimizing code**: Failing to optimize code can lead to memory-related errors.