Error Message and Stacktrace

Oct 13, 2025 by orovajewels.com 92 views

Introduction

In this article, we will delve into the issue of TEN404: Internal Tensorizer Error - BirCodeGenLoop:Too many strides!. This error occurs when attempting to benchmark the performance of vLLM (v0.6.x-neuron branch) on NxDI (Neuron eXtreme Deep Inference) using the v0.6.x-neuron branch of the AWS Neuron SDK. We will explore the error message, the stacktrace, and the possible causes of this issue.

Error Message and Stacktrace

The error message is as follows:

[TEN404] (_sine.127) Internal tensorizer error: BirCodeGenLoop:Too many strides! {{{{0,+,1}[64],+,0}[2],+,64}[2],+,0}[2] - Please open a support ticket at https://github.com/aws-neuron/aws-neuron-sdk/issues/new. You may also be able to obtain more information using the 'XLA_IR_DEBUG' and 'XLA_HLO_DEBUG' environment variables.

The stacktrace is as follows:

Traceback (most recent call last):
  File "/home/ubuntu/upstreaming-to-vllm/benchmarks/benchmark_latency.py", line 269, in <module>
    main(args)
  File "/home/ubuntu/upstreaming-to-vllm/benchmarks/benchmark_latency.py", line 28, in main
    llm = LLM(
  File "/home/ubuntu/upstreaming-to-vllm/vllm/entrypoints/llm.py", line 214, in __init__
    self.llm_engine = LLMEngine.from_engine_args(
  File "/home/ubuntu/upstreaming-to-vllm/vllm/engine/llm_engine.py", line 564, in from_engine_args
    engine = cls(
  File "/home/ubuntu/upstreaming-to-vllm/vllm/engine/llm_engine.py", line 325, in __init__
    self.model_executor = executor_class(
  File "/home/ubuntu/upstreaming-to-vllm/vllm/executor/executor_base.py", line 47, in __init__
    self._init_executor()
  File "/home/ubuntu/upstreaming-to-vllm/vllm/executor/neuron_executor.py", line 23, in _init_executor
    self._init_worker()
  File "/home/ubuntu/upstreaming-to-vllm/vllm/executor/neuron_executor.py", line 39, in _init_worker
    self.driver_worker.load_model()
  File "/home/ubuntu/upstreaming-to-vllm/vllm/worker/neuron_worker.py", line 134, in load_model
    self.model_runner.load_model()
  File "/home/ubuntu/upstreaming-to-vllm/vllm/worker/neuronx_distributed_model_runner.py", line 30, in load_model
    self.model = get_neuron_model(
  File "/home/ubuntu/upstreaming-to-vllm/vllm/model_executor/model_loader/neuronx_distributed.py", line 480, in get_neuron_model
    model.load_weights(model_config.model,
  File "/home/ubuntu/upstreaming-to-vllm/vllm/model_executor/model_loader/neuronx_distributed.py", line 150, in load_weights
    self.model.compile(compiled_model_path)
  File "/opt/aws_neuronx_venv_pytorch_2_5_nxd_inference/lib/python3.10/site-packages/neuronx_distributed_inference/models/application_base.py", line 145, in compile
    traced_model = self.get_builder(debug).trace(initialize_model_weights=False)
  File "/opt/aws_neuronx_venv_pytorch_2_5_nxd_inference/lib/python3.10/site-packages/neuronx_distributed/trace/model_builder.py", line 310, in trace
    key, bucket_rank, neff_artifacts = future.result()
  File "/usr/lib/python3.10/concurrent/futures/_base.py", line 451, in result
    return self.__get_result()
  File "/usr/lib/python3.10/concurrent/futures/_base.py", line 403, in __get_result__
    raise self._exception
  File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
    result = self.fn(*self.args, **self.kwargs)
  File "/opt/aws_neuronx_venv_pytorch_2_5_nxd_inference/lib/python3.10/site-packages/neuronx_distributed/trace/model_builder.py", line 254, in submit_compilation_job
    return key, bucket_rank, torch_neuronx.xla_impl.trace.generate_neff(*args)
  File "/opt/aws_neuronx_venv_pytorch_2_5_nxd_inference/lib/python3.10/site-packages/torch_neuronx/xla_impl/trace.py", line 506, in generate_neff
    neff_filename = hlo_compile(
  File "/opt/aws_neuronx_venv_pytorch_2_5_nxd_inference/lib/python3.10/site-packages/torch_neuronx/xla_impl/trace.py", line 396, in hlo_compile
    raise RuntimeError(f"neuronx-cc failed with {status}")
RuntimeError: neuronx-cc failed with 70

Possible Causes

Based on the error message and stacktrace, the possible causes of this issue are:

Tensorizer Error: The error message indicates that there is an internal tensorizer error, which suggests that the tensorizer is unable to process the model correctly.
BirCodeGenLoop: The error message also mentions BirCodeGenLoop, which is a part of the Neuron SDK. This suggests that the issue may be related to the compilation of the model using BirCodeGenLoop.
Too Many Strides: The error message mentions "Too many strides!", which suggests that the model has too many strides, which can cause issues during compilation.

Troubleshooting Steps

To troubleshoot this issue, you can try the following steps:

Check the Model: Check the model for any issues or errors. Make sure that the model is correctly formatted and that there are no errors in the model configuration.
Check the Tensorizer: Check the tensorizer for any issues or errors. Make sure that the tensorizer is correctly configured and that there are no errors in the tensorizer configuration.
Check the BirCodeGenLoop: Check the BirCodeGenLoop for any issues or errors. Make sure that the BirCodeGenLoop is correctly configured and that there are no errors in the BirCodeGenLoop configuration.
Check the Environment Variables: Check the environment variables for any issues or errors. Make sure that the environment variables are correctly set and that there are no errors in the environment variable configuration.
Check the Neuron SDK: Check the Neuron SDK for any issues or errors. Make sure that the Neuron SDK is correctly installed and that there are no errors in the Neuron SDK configuration.

Conclusion

In conclusion, the TEN404: Internal Tensorizer Error - BirCodeGenLoop:Too many strides! error is a complex issue that requires careful troubleshooting and analysis. By following the troubleshooting steps outlined above, you can identify and resolve the issue and successfully compile the model using the Neuron SDK.

Additional Resources

For additional resources and information on the Neuron SDK and the TEN404: Internal Tensorizer Error - BirCodeGenLoop:Too many strides! error, please refer to the following resources:

For related articles and information on the Neuron SDK and the TEN404: Internal Tensorizer Error - BirCodeGenLoop:Too many strides! error, please refer to the following articles:

Neuron SDK: A Comprehensive Guide
Troubleshooting the Neuron SDK
Neuron SDK: Best Practices
TEN404: Internal Tensorizer Error - BirCodeGenLoop:Too many strides! Q&A ====================================================================

Q: What is the TEN404 error?

A: The TEN404 error is an internal tensorizer error that occurs when attempting to compile a model using the Neuron SDK. The error is caused by a BirCodeGenLoop issue, which is a part of the Neuron SDK.

Q: What causes the TEN404 error?

A: The TEN404 error can be caused by a variety of factors, including:

Tensorizer Error: The error message indicates that there is an internal tensorizer error, which suggests that the tensorizer is unable to process the model correctly.
BirCodeGenLoop: The error message also mentions BirCodeGenLoop, which is a part of the Neuron SDK. This suggests that the issue may be related to the compilation of the model using BirCodeGenLoop.
Too Many Strides: The error message mentions "Too many strides!", which suggests that the model has too many strides, which can cause issues during compilation.

Q: How do I troubleshoot the TEN404 error?

A: To troubleshoot the TEN404 error, you can try the following steps:

Check the Model: Check the model for any issues or errors. Make sure that the model is correctly formatted and that there are no errors in the model configuration.
Check the Tensorizer: Check the tensorizer for any issues or errors. Make sure that the tensorizer is correctly configured and that there are no errors in the tensorizer configuration.
Check the BirCodeGenLoop: Check the BirCodeGenLoop for any issues or errors. Make sure that the BirCodeGenLoop is correctly configured and that there are no errors in the BirCodeGenLoop configuration.
Check the Environment Variables: Check the environment variables for any issues or errors. Make sure that the environment variables are correctly set and that there are no errors in the environment variable configuration.
Check the Neuron SDK: Check the Neuron SDK for any issues or errors. Make sure that the Neuron SDK is correctly installed and that there are no errors in the Neuron SDK configuration.

Q: How do I resolve the TEN404 error?

A: To resolve the TEN404 error, you can try the following steps:

Update the Neuron SDK: Update the Neuron SDK to the latest version to ensure that you have the latest bug fixes and features.
Check the Model Configuration: Check the model configuration for any errors or issues. Make sure that the model is correctly formatted and that there are no errors in the model configuration.
Check the Tensorizer Configuration: Check the tensorizer configuration for any errors or issues. Make sure that the tensorizer is correctly configured and that there are no errors in the tensorizer configuration.
Check the BirCodeGenLoop Configuration: Check the BirCodeGenLoop configuration for any errors or issues. Make sure that the BirCodeGenLoop is correctly configured and that there are no errors in the BirCodeGenLoop configuration.
Check the Environment Variables: Check the environment variables for any errors or issues. Make sure that the environment variables are correctly set and that there are no errors in the environment variable configuration.

Q: What are some best practices for avoiding the TEN404 error?

A: To avoid the TEN404 error, follow these best practices:

Use the Latest Neuron SDK: Use the latest version of the Neuron SDK to ensure that you have the latest bug fixes and features.
Check the Model Configuration: Check the model configuration for any errors or issues. Make sure that the model is correctly formatted and that there are no errors in the model configuration.
Check the Tensorizer Configuration: Check the tensorizer configuration for any errors or issues. Make sure that the tensorizer is correctly configured and that there are no errors in the tensorizer configuration.
Check the BirCodeGenLoop Configuration: Check the BirCodeGenLoop configuration for any errors or issues. Make sure that the BirCodeGenLoop is correctly configured and that there are no errors in the BirCodeGenLoop configuration.
Check the Environment Variables: Check the environment variables for any errors or issues. Make sure that the environment variables are correctly set and that there are no errors in the environment variable configuration.

Q: Where can I find more information on the TEN404 error?

A: For more information on the TEN404 error, refer to the following resources:

Q: How do I report a bug related to the TEN404 error?

A: To report a bug related to the TEN404 error, follow these steps:

Check the Neuron SDK Issues: Check the Neuron SDK issues to see if the bug has already been reported.
Create a New Issue: If the bug has not been reported, create a new issue on the Neuron SDK GitHub repository.
Provide Detailed Information: Provide detailed information about the bug, including the error message, the model configuration, and any other relevant details.
Attach Relevant Files: Attach any relevant files, such as the model configuration file or the error log file.
Wait for a Response: Wait for a response from the Neuron SDK team, who will investigate the bug and provide a solution.