code: def _make_random_tensor(dtype, shape):
      """Create a random test tensor with given shape and dtype."""
      global RAND_SEED
      if RANDOM_TENSOR_START is not None:
          to_return = np.arange(
              RANDOM_TENSOR_START,
              RANDOM_TENSOR_START + np.prod(shape),
              dtype=dtype,
          ).reshape(shape)
          RAND_SEED += np.prod(shape)
          return to_return
  
      dinfo = dtype_info(dtype)
      if "int" in dtype:
          return np.random.randint(
              dinfo.min, dinfo.max, shape, dtype=dtype
          )
      else:
          to_return = np.random.uniform(0, dinfo.max, shape).astype(
              dtype
          )
          np.reshape(to_return, np.prod(shape))[::2] *= -1
          return to_return
  
imports: import collections
  import ctypes
  import json
  import os
  import re
  from contextlib import redirect_stderr
  from io import StringIO
  import numpy
  import tvm
  import tvm.relay
  import tvm.testing
  from tvm import meta_schedule
  from tvm import relay
  from tvm.contrib import utils
  from tvm.relay.backend import Executor, Runtime
label_desc: Use image node_id 2 for calling a global function with example usage: _make_random_tensor(dtype, shape) and returns: to_return, np, to_return