from accelerate import notebook_launcher

def dummy_training_function():
    print("Inside training function")

notebook_launcher(dummy_training_function, num_processes=1)

---------------------------------------------------------------------------
FileNotFoundError                         Traceback (most recent call last)
/tmp/ipython-input-3351436335.py in <cell line: 0>()
      4     print("Inside training function")
      5 
----> 6 notebook_launcher(dummy_training_function, num_processes=1)

/usr/local/lib/python3.12/dist-packages/accelerate/launchers.py in notebook_launcher(function, args, num_processes, mixed_precision, use_port, master_addr, node_rank, num_nodes, rdzv_backend, rdzv_endpoint, rdzv_conf, rdzv_id, max_restarts, monitor_interval, log_line_prefix_template)
    150         print("Launching a training on TPU cores.")
    151         xmp.spawn(launcher, args=args, start_method="fork")
--> 152     elif in_colab and get_gpu_info()[1] < 2:
    153         # No need for a distributed launch otherwise as it's either CPU or one GPU.
    154         if torch.cuda.is_available():

/usr/local/lib/python3.12/dist-packages/accelerate/utils/environment.py in get_gpu_info()
    171     """
    172     # Returns as list of `n` GPUs and their names
--> 173     output = subprocess.check_output(
    174         [_nvidia_smi(), "--query-gpu=count,name", "--format=csv,noheader"], universal_newlines=True
    175     )

/usr/lib/python3.12/subprocess.py in check_output(timeout, *popenargs, **kwargs)
    464         kwargs['input'] = empty
    465 
--> 466     return run(*popenargs, stdout=PIPE, timeout=timeout, check=True,
...
-> 1955                         raise child_exception_type(errno_num, err_msg, err_filename)
   1956                     else:
   1957                         raise child_exception_type(errno_num, err_msg)

FileNotFoundError: [Errno 2] No such file or directory: 'nvidia-smi'