code: def tensors_allclose(a_tensors, b_tensors, rtol=0, atol=1e-7):
      """
      For each backends, calls f with its tensors, and returns the results to
      allclose.
  
      Arguments:
          a_tensors: list of tensors, or a tensor
          b_tensors: (another) list of tensors, or a tensor
          rtol (float, optional): Relative tolerance.
          atol (float, optional): Absolute tolerance.
      Returns:
          bool: If the tensors of fs is all close
      """
      # deal with individual tensor
      if type(a_tensors) is not list and type(b_tensors) is not list:
          a_tensors = [a_tensors]
          b_tensors = [b_tensors]
      results = []
      for a_tensor, b_tensor in zip(a_tensors, b_tensors):
          if isinstance(a_tensor, Tensor):
              a_tensor = a_tensor.get()
          if isinstance(b_tensor, Tensor):
              b_tensor = b_tensor.get()
          results.append(
              allclose_with_out(
                  a_tensor.astype(b_tensor.dtype),
                  b_tensor,
                  rtol=rtol,
                  atol=atol,
              )
          )
  
      return all(results)
  
file_path: neon/tests/utils.py
imports: from builtins import zip
  import numpy
  import numpy.random
  from neon import logger
  from neon.backends.backend import Tensor
label_desc: Use image node_id 5 for calling a global function with example usage: tensors_allclose(a_tensors, b_tensors, rtol, atol) and returns: all