# Simple NLP Example not working

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**Category:** 🤗Accelerate\
**Created:** [September 12, 2021, 2:41pm UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fsimple-nlp-example-not-working%2F9913 "2021-09-12T14:41:58Z")\
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**Showing post:** 7

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**Author:** ![drscotthawley](https://sea2.discourse-cdn.com/hellohellohello/user_avatar/discuss.huggingface.co/drscotthawley/32/62161_2.png) [@drscotthawley](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2Fdrscotthawley)%5C
**Post date:** [June 2, 2022, 8:53pm UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fsimple-nlp-example-not-working%2F9913%2F7 "2022-06-02T20:53:22Z")

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I too am seeing the SIGSEV error when I run the Simple NLP example on an A100 pod:

```auto
---------------------------------------------------------------------------
ProcessExitedException Traceback (most recent call last)
Input In [25], in <cell line: 3>()
      1 from accelerate import notebook_launcher
----> 3 notebook_launcher(training_function, num_processes=4)

File ~/envs/wav2vec/lib/python3.9/site-packages/accelerate/launchers.py:129, in notebook_launcher(function, args, num_processes, use_fp16, mixed_precision, use_port)
    126 launcher = PrepareForLaunch(function, distributed_type="MULTI_GPU")
    128 print(f"Launching training on {num_processes} GPUs.")
--> 129 start_processes(launcher, args=args, nprocs=num_processes, start_method="fork")
    131 else:
    132 # No need for a distributed launch otherwise as it's either CPU or one GPU.
    133 if torch.cuda.is_available():

File ~/envs/wav2vec/lib/python3.9/site-packages/torch/multiprocessing/spawn.py:198, in start_processes(fn, args, nprocs, join, daemon, start_method)
    195 return context
    197 # Loop on join until it returns True or raises an exception.
--> 198 while not context.join():
    199 pass

File ~/envs/wav2vec/lib/python3.9/site-packages/torch/multiprocessing/spawn.py:140, in ProcessContext.join(self, timeout)
    138 if exitcode < 0:
    139 name = signal.Signals(-exitcode).name
--> 140 raise ProcessExitedException(
    141 "process %d terminated with signal %s" %
    142 (error_index, name),
    143 error_index=error_index,
    144 error_pid=failed_process.pid,
    145 exit_code=exitcode,
    146 signal_name=name
    147 )
    148 else:
    149 raise ProcessExitedException(
    150 "process %d terminated with exit code %d" %
    151 (error_index, exitcode),
   (...)
    154 exit_code=exitcode
    155 )

ProcessExitedException: process 0 terminated with signal SIGSEGV

```

That error was also preceded by a bunch of warnings BTW:

```auto
Launching training on 4 GPUs.
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
	- Avoid using `tokenizers` before the fork if possible
	- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
	- Avoid using `tokenizers` before the fork if possible
	- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
	- Avoid using `tokenizers` before the fork if possible
	- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
	- Avoid using `tokenizers` before the fork if possible
	- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)

```

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