class_docstr: A collection of functions to be tested
code: def func_reduction_mix_axis_1(be, x0, x1, x2, x3):
      f1 = be.mean(x0, axis=1, keepdims=True)
      f2 = be.max(x1, axis=1, keepdims=True) + be.min(
          x1, axis=1, keepdims=True
      )
      f3 = be.std(x2, axis=1, keepdims=True)
      if be is np:
          f4 = be.argmax(x3, axis=1).reshape(x3.shape[0], -1)
      else:
          f4 = be.argmax(x3, axis=1, keepdims=True)
  
      if be is np:
          x4 = np.hstack([f1, f2, f3, f4])
      else:
          x4 = be.empty((x0.shape[0], 4))
          x4[:, 0] = f1
          x4[:, 1] = f2
          x4[:, 2] = f3
          x4[:, 3] = f4
      return x4
  
file_path: neon/tests/test_backend_reduction.py
imports: import itertools
  import numpy
  import pytest
  from neon import NervanaObject
  from utils import call_func, gen_backend_tensors, tensors_allclose
label_desc: Use image node_id 2 for calling the TestFuncs obj's underlying member method code with example usage: obj.func_reduction_mix_axis_1(be, x0, x1, x2, x3) and returns: x4