How to fix AttributeError: 'tuple' object has no attribute 'rank' creating a DqnAgent with Tensorflow?

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I'm trying to create a DqnAgent using an own environment. But i'm receiving the following error

AttributeError: 'tuple' object has no attribute 'rank' In call to configurable 'DqnAgent' (<class 'tf_agents.agents.dqn.dqn_agent.DqnAgent'>)

Below is the code for my environment myEnv

import numpy as np
import tensorflow as tf

from tf_agents.environments import py_environment
from tf_agents.specs import array_spec
from tf_agents.utils import common
from tf_agents.networks import q_network
from tf_agents.agents.dqn import dqn_agent

class myEnv(py_environment.PyEnvironment):
    def __init__(self):
        self._action_spec = array_spec.BoundedArraySpec(
            shape=(), dtype=np.int32, minimum=0, maximum=2, name='action')
        self._observation_spec = array_spec.BoundedArraySpec(
            shape=(2,), dtype=np.int32, minimum=0, name='observation')
        self._state = np.zeros(shape=(2,),dtype=np.int32)


    def action_spec(self):
        return self._action_spec


    def observation_spec(self):
        return self._observation_spec

    def _reset(self):
        self._state = np.zeros(shape=(8,),dtype=np.int32)
        self._c_reward = 0
        return ts.restart(self._state)


    def _step(self, action):
      self._state[action] = self._state[action] + 1
      return ts.transition(self._state, reward=0.0, discount=1.0)

I can create an instance of myEnv without any errors.

train_env = myEnv()

But if i try to create the agent with the following code

q_net = q_network.QNetwork(
    train_env.observation_spec(),
    train_env.action_spec(),
    fc_layer_params=(10,))

optimizer = tf.keras.optimizers.Adam(learning_rate=1e-3)
train_step_counter = tf.Variable(0)

agent = dqn_agent.DqnAgent(
    train_env.time_step_spec(),
    train_env.action_spec(),
    q_network=q_net,
    optimizer=optimizer,
    td_errors_loss_fn=common.element_wise_squared_loss,
    train_step_counter=train_step_counter)

I'm receiving this Traceback

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-3-a730748f947f> in <module>()
     15     optimizer=optimizer,
     16     td_errors_loss_fn=common.element_wise_squared_loss,
---> 17     train_step_counter=train_step_counter)

4 frames
/usr/local/lib/python3.7/dist-packages/tf_agents/agents/dqn/dqn_agent.py in _check_action_spec(self, action_spec)
    293 
    294     # TODO(oars): Get DQN working with more than one dim in the actions.
--> 295     if len(flat_action_spec) > 1 or flat_action_spec[0].shape.rank > 0:
    296       raise ValueError(
    297           'Only scalar actions are supported now, but action spec is: {}'

AttributeError: 'tuple' object has no attribute 'rank'
  In call to configurable 'DqnAgent' (<class 'tf_agents.agents.dqn.dqn_agent.DqnAgent'>)

How to fix this error?

tensorflow2.0
1 Answers

The DqnAgent expects a TFPyEnvironment but you're implementing the environment as an PyEnvironment.

To fix this error you should convert the environment into the TensorFlow implementation before you are creating the agent.

You can do it this way:

from tf_agents.environments import tf_py_environment

train_env = myEnv()

train_env_tf = tf_py_environment.TFPyEnvironment(train_envt)

q_net = q_network.QNetwork(
    train_env_tf.observation_spec(),
    train_env_tf.action_spec(),
    fc_layer_params=(10,))

optimizer = tf.keras.optimizers.Adam(learning_rate=1e-3)
train_step_counter = tf.Variable(0)

agent = dqn_agent.DqnAgent(
    train_env_tf.time_step_spec(),
    train_env_tf.action_spec(),
    q_network=q_net,
    optimizer=optimizer,
    td_errors_loss_fn=common.element_wise_squared_loss,
    train_step_counter=train_step_counter)
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