AssertionError: Cannot call env.step() before calling reset()

[frenzytejask98]

I don't know why this error shows up. Please help me out here.

[] GPU : 1.0000
2019-05-23 23:34:52.437286: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
{'_save_step': 500000,
'_test_step': 50000,
'action_repeat': 4,
'backend': 'tf',
'batch_size': 32,
'cnn_format': 'NHWC',
'discount': 0.99,
'display': True,
'double_q': False,
'dueling': False,
'env_name': 'Breakout-v0',
'env_type': 'detail',
'ep_end': 0.1,
'ep_end_t': 100000,
'ep_start': 1.0,
'history_length': 4,
'learn_start': 50000.0,
'learning_rate': 0.00025,
'learning_rate_decay': 0.96,
'learning_rate_decay_step': 50000,
'learning_rate_minimum': 0.00025,
'max_delta': 1,
'max_reward': 1.0,
'max_step': 50000000,
'memory_size': 100000,
'min_delta': -1,
'min_reward': -1.0,
'model': 'm1',
'random_start': 30,
'scale': 10000,
'screen_height': 84,
'screen_width': 84,
'target_q_update_step': 10000,
'train_frequency': 4}
WARNING:tensorflow:From /home/tejask98/Desktop/DQN-tensorflow/dqn/agent.py:225: calling argmax (from tensorflow.python.ops.math_ops) with dimension is deprecated and will be removed in a future version.
Instructions for updating:
Use the axis argument instead
WARNING:tensorflow:From /usr/local/lib/python2.7/dist-packages/tensorflow/python/util/tf_should_use.py:189: initialize_all_variables (from tensorflow.python.ops.variables) is deprecated and will be removed after 2017-03-02.
Instructions for updating:
Use tf.global_variables_initializer instead.
[] Loading checkpoints...
[!] Load FAILED: checkpoints/Breakout-v0/min_delta--1/max_delta-1/history_length-4/train_frequency-4/target_q_update_step-10000/double_q-False/memory_size-100000/action_repeat-4/ep_end_t-100000/dueling-False/min_reward--1.0/backend-tf/random_start-30/scale-10000/env_type-detail/learning_rate_decay_step-50000/ep_start-1.0/screen_width-84/learn_start-50000.0/cnn_format-NHWC/learning_rate-0.00025/batch_size-32/discount-0.99/max_step-50000000/max_reward-1.0/learning_rate_decay-0.96/learning_rate_minimum-0.00025/env_name-Breakout-v0/ep_end-0.1/model-m1/screen_height-84/
Traceback (most recent call last):
File "main.py", line 70, in
tf.app.run()
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/platform/app.py", line 125, in run
_sys.exit(main(argv))
File "main.py", line 65, in main
agent.train()
File "/home/tejask98/Desktop/DQN-tensorflow/dqn/agent.py", line 43, in train
screen, reward, action, terminal = self.env.new_random_game()
File "/home/tejask98/Desktop/DQN-tensorflow/dqn/environment.py", line 28, in new_random_game
self.new_game(True)
File "/home/tejask98/Desktop/DQN-tensorflow/dqn/environment.py", line 23, in new_game
self._step(0)
File "/home/tejask98/Desktop/DQN-tensorflow/dqn/environment.py", line 35, in _step
self._screen, self.reward, self.terminal, _ = self.env.step(action)
File "/usr/local/lib/python2.7/dist-packages/gym/wrappers/time_limit.py", line 30, in step
assert self._episode_started_at is not None, "Cannot call env.step() before calling reset()"
AssertionError: Cannot call env.step() before calling reset()

[KingCoCos]

I think this might work, change self._screen = None to self._screen = self.env.reset() in def init in the environment.py file