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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,114 @@ | ||
| # coding=utf-8 | ||
| # Copyright 2019 Google LLC | ||
| # Licensed under the Apache License, Version 2.0 (the "License"); | ||
| # you may not use this file except in compliance with the License. | ||
| # You may obtain a copy of the License at | ||
| # | ||
| # http://www.apache.org/licenses/LICENSE-2.0 | ||
| # | ||
| # Unless required by applicable law or agreed to in writing, software | ||
| # distributed under the License is distributed on an "AS IS" BASIS, | ||
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| # See the License for the specific language governing permissions and | ||
| # limitations under the License. | ||
|
|
||
| r"""Player from PPO2 cnn checkpoint. | ||
| Example usage with play_game script: | ||
| python3 -m gfootball.play_game \ | ||
| --players "ppo2_cnn:left_players=1,checkpoint=$YOUR_PATH,policy=$POLICY" | ||
| $POLICY should be one of: cnn, impala_cnn, gfootball_impala_cnn. | ||
| """ | ||
|
|
||
| from baselines.common.policies import build_policy | ||
| from gfootball.env import football_action_set | ||
| from gfootball.env import observation_preprocessing | ||
| from gfootball.env import player_base | ||
| from gfootball.examples import models | ||
| import gym | ||
| import joblib | ||
| import numpy as np | ||
| import tensorflow as tf | ||
|
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|
|
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| class Player(player_base.PlayerBase): | ||
| """An agent loaded from PPO2 cnn model checkpoint.""" | ||
|
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| def __init__(self, player_config, env_config): | ||
| player_base.PlayerBase.__init__(self, player_config) | ||
|
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| self._action_set = 'default' | ||
| self._sess = tf.Session() | ||
| self._player_prefix = 'player_{}'.format(player_config['index']) | ||
| stacking = 4 if player_config.get('stacked', True) else 1 | ||
| policy = player_config.get('policy', 'cnn') | ||
| self._stacker = ObservationStacker(stacking) | ||
| with tf.variable_scope(self._player_prefix): | ||
| with tf.variable_scope('ppo2_model'): | ||
| policy_fn = build_policy(DummyEnv(self._action_set, stacking), policy) | ||
| self._policy = policy_fn(nbatch=1, sess=self._sess) | ||
| _load_variables(player_config['checkpoint'], self._sess, | ||
| prefix=self._player_prefix + '/') | ||
|
|
||
| def __del__(self): | ||
| self._sess.close() | ||
|
|
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| def take_action(self, observation): | ||
| assert len(observation) == 1, 'Multiple players control is not supported' | ||
|
|
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| observation = observation_preprocessing.generate_smm(observation) | ||
| observation = self._stacker.get(observation) | ||
| action = self._policy.step(observation)[0][0] | ||
| actions = [football_action_set.action_set_dict[self._action_set][action]] | ||
| return actions | ||
|
|
||
| def reset(self): | ||
| self._stacker.reset() | ||
|
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|
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| def _load_variables(load_path, sess, prefix='', remove_prefix=True): | ||
| """Loads variables from checkpoint of policy trained by baselines.""" | ||
|
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| # Forked from address below since we needed loading from different var names: | ||
| # https://github.com/openai/baselines/blob/master/baselines/common/tf_util.py | ||
| variables = [v for v in tf.get_collection(tf.GraphKeys.GLOBAL_VARIABLES) | ||
| if v.name.startswith(prefix)] | ||
|
|
||
| loaded_params = joblib.load(load_path) | ||
| restores = [] | ||
| for v in variables: | ||
| v_name = v.name[len(prefix):] if remove_prefix else v.name | ||
| restores.append(v.assign(loaded_params[v_name])) | ||
|
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| sess.run(restores) | ||
|
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||
|
|
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| class ObservationStacker(object): | ||
| """Utility class that produces stacked observations.""" | ||
|
|
||
| def __init__(self, stacking): | ||
| self._stacking = stacking | ||
| self._data = [] | ||
|
|
||
| def get(self, observation): | ||
| if self._data: | ||
| self._data.append(observation) | ||
| self._data = self._data[-self._stacking:] | ||
| else: | ||
| self._data = [observation] * self._stacking | ||
| return np.concatenate(self._data, axis=-1) | ||
|
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||
| def reset(self): | ||
| self._data = [] | ||
|
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|
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| class DummyEnv(object): | ||
| # We need env object to pass to build_policy, however real environment | ||
| # is not there yet. | ||
|
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| def __init__(self, action_set, stacking): | ||
| self.action_space = gym.spaces.Discrete( | ||
| len(football_action_set.action_set_dict[action_set])) | ||
| self.observation_space = gym.spaces.Box( | ||
| 0, 255, shape=[72, 96, 4 * stacking], dtype=np.uint8) |
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