class_docstr: A conv. + recurrent keras net example using a pre-trained MobileNet.
class_docstr_tok: ["A","conv",".","+","recurrent","keras","net","example","using","a","pre-trained","MobileNet","."]
code: def forward_rnn(self, inputs, state, seq_lens):
      model_out, self._value_out, h, c = self.rnn_model(
          [inputs, seq_lens] + state
      )
      return model_out, [h, c]
  
file_path: ray/python/ray/rllib/examples/models/mobilenet_v2_with_lstm_models.py
imports: import numpy
  from ray.rllib.models.modelv2 import ModelV2
  from ray.rllib.models.tf.recurrent_net import RecurrentNetwork
  from ray.rllib.models.torch.misc import SlimFC
  from ray.rllib.models.torch.recurrent_net import RecurrentNetwork
  from ray.rllib.utils.annotations import override
  from ray.rllib.utils.framework import try_import_tf, try_import_torch
label_desc: Use image node_id 2 for calling the MobileV2PlusRNNModel obj's underlying member method code with example usage: obj.forward_rnn(inputs, state, seq_lens) and returns: model_out,  list