code: def flatten_batch_and_time_dim(t):
      if not isinstance(t, tf.Tensor):
          t = tf.convert_to_tensor(t, dtype=tf.float32)
      new_shape = [-1] + t.shape[2:].as_list()
      return tf.reshape(t, new_shape)
  
file_path: ray/python/ray/rllib/algorithms/impala/tests/test_vtrace_v2.py
imports: import unittest
  import numpy
  from gymnasium.spaces import Box, Discrete
  from ray.rllib.algorithms.impala.tf.vtrace_tf_v2 import vtrace_tf2, make_time_major
  from ray.rllib.algorithms.impala.torch.vtrace_torch_v2 import vtrace_torch
  from ray.rllib.algorithms.impala.tests.test_vtrace import _ground_truth_vtrace_calculation
  from ray.rllib.utils.torch_utils import convert_to_torch_tensor
  from ray.rllib.models.tf.tf_action_dist import Categorical
  from ray.rllib.utils.framework import try_import_tf
  from ray.rllib.utils.test_utils import check
label_desc: Use image node_id 1 for calling a global function with example usage: flatten_batch_and_time_dim(t) and returns: tf