code: def _np_log_sum_exp(x, axis, keepdims=False):
      max_x = np.max(x, axis=axis, keepdims=True)
      x = np.log(np.sum(np.exp(x - max_x), axis=axis, keepdims=True))
      x = x + max_x
      if not keepdims:
          x = np.squeeze(x, axis=axis)
      return x
  
imports: import sys
  import numpy
  import numpy.random
  import pytest
  import tvm
  import tvm.testing
  import tvm.topi.testing
  from tvm import relay, te
  from tvm.relay import transform
  from tvm.relay.testing import run_infer_type
label_desc: Use image node_id 7 for calling a global function with example usage: _np_log_sum_exp(x, axis, keepdims) and returns: x