code: def log_softmax(x, axis=-1):
      x = torch.from_numpy(x)  # zero-copy
      x = x.float()
      x = torch.log_softmax(x, dim=axis)
      x = x.numpy()
      return x
  
imports: import numpy
  import pytest
  import torch
  from numba import cuda
  from nemo.collections.asr.losses.rnnt_pytorch import MultiblankRNNTLossPytorch, TDTLossPytorch
  from nemo.collections.asr.parts.numba.rnnt_loss import rnnt_numpy
  from nemo.collections.asr.parts.numba.rnnt_loss.rnnt_pytorch import certify_inputs
  from nemo.collections.asr.parts.numba.rnnt_loss.utils.cuda_utils import gpu_rnnt_kernel, reduce
  from nemo.core.utils import numba_utils
  from nemo.core.utils.numba_utils import __NUMBA_MINIMUM_VERSION__
label_desc: Use image node_id 1 for calling a global function with example usage: log_softmax(x, axis) and returns: x