Troubleshooting your Model

This section provides troubleshooting instructions that can be referred to for common issues when training PyTorch models. The following are common functional issues that may occur when running on HPU and not on CPU/GPU.

Runtime Errors

Please ensure that both model and inputs are moved to the device in the script before the training loop begins. The most common symptoms of these could manifest as runtime errors from the python stack which will result in a backtrace:

model_inputs = model_inputs.to("hpu")
model = model.to("hpu")

The following table outlines possible runtime errors:

Error

Workaround

RuntimeError: FATAL ERROR :: MODULE:BRIDGE syn compile encountered : Graph compile failed. 26 compile time 5076188974 ns

  • Make sure Eager/Lazy mode flags were set correctly

  • Or, run the following:

    • export PT_HPU_LOG_MOD_MASK=0x604

    • export PT_HPU_LOG_TYPE_MASK=0x5

    • export ENABLE_CONSOLE=true

    • export LOG_LEVEL_ALL=4

File “/usr/local/lib/python 3.8/dist-packages/habana_framewo rks/torch/core/step_closure.py”, line 45, in mark_step

htcore._mark_step(device_str)

RuntimeError: FATAL ERROR :: MODULE:BRIDGE syn launch encountered : synLaunch failed. 26

Run the following:

  • export PT_HPU_LOG_MOD_MASK=0x604

  • export PT_HPU_LOG_TYPE_MASK=0x5

  • export ENABLE_CONSOLE=true

  • export LOG_LEVEL_ALL=4

RuntimeError: Unaccounted output %t925__1 at index 21. Cached recipe execution might break

Run the following:

  • export PT_HPU_LOG_MOD_MASK=0x604

  • export PT_HPU_LOG_TYPE_MASK=0x5

  • export ENABLE_CONSOLE=true

  • export LOG_LEVEL_ALL=4

RuntimeError: Sizes of tensors along one of the non-cat dimensions don’t match

Check cat operation. User may not be able to do this unless maybe written from scratch.

RuntimeError: tensor does not have a device

Run the following:

  • export PT_HPU_LOG_MOD_MASK=0x604

  • export PT_HPU_LOG_TYPE_MASK=0x5

  • export ENABLE_CONSOLE=true

  • export LOG_LEVEL_ALL=4

Performance Issues

For details on how to get best performance on HPU, refer to Model Performance Optimization Guide for PyTorch