code: def bit_shift_generator(seq_length, shift, batch_size):
      while True:
          values = np.array([0.0, 1.0], dtype=np.float32)
          seq = np.random.choice(values, (batch_size, seq_length, 1))
          targets = np.squeeze(
              np.roll(seq, shift, axis=1).astype(np.int32)
          )
          targets[:, :shift] = 0
          yield seq, targets
  
imports: from gymnasium.spaces import Box, Discrete
  import numpy
  from rllib.models.tf.attention_net import TrXLNet
  from ray.rllib.utils.framework import try_import_tf
label_desc: Use image node_id 1 for calling a global function with example usage: bit_shift_generator(seq_length, shift, batch_size) without return types