code: def valatt_attention_tensor(cfg):
      qkv = cfg["queries_keys_values"]
      batch, seq_len, _ = qkv.shape
      heads = cfg["heads"]
      att_shape = (batch, heads, seq_len, seq_len)
      return mx.nd.random.randint(0, 2, att_shape).astype(qkv.dtype)
  
file_path: mxnet/tests/python/dnnl/op_cfg.py
imports: from collections import namedtuple
  from itertools import product
  from functools import partial
  import mxnet
  from mxnet.base import _is_np_op, _NP_OP_PREFIX, _NP_EXT_OP_PREFIX, _NP_INTERNAL_OP_PREFIX, _OP_NAME_PREFIX_LIST
label_desc: Use image node_id 4 for calling a global function with example usage: valatt_attention_tensor(cfg) and returns: mx