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from functools import partial as bind |
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import embodied |
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import numpy as np |
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class TestDriver: |
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def test_episode_length(self): |
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agent = self._make_agent() |
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driver = embodied.Driver([self._make_env]) |
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driver.reset(agent.init_policy) |
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seq = [] |
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driver.on_step(lambda tran, _: seq.append(tran)) |
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driver(agent.policy, episodes=1) |
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assert len(seq) == 11 |
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def test_first_step(self): |
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agent = self._make_agent() |
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driver = embodied.Driver([self._make_env]) |
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driver.reset(agent.init_policy) |
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seq = [] |
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driver.on_step(lambda tran, _: seq.append(tran)) |
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driver(agent.policy, episodes=2) |
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for index in [0, 11]: |
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assert seq[index]['is_first'].item() is True |
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assert seq[index]['is_last'].item() is False |
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for index in [1, 10, 12]: |
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assert seq[index]['is_first'].item() is False |
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def test_last_step(self): |
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agent = self._make_agent() |
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driver = embodied.Driver([self._make_env]) |
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driver.reset(agent.init_policy) |
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seq = [] |
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driver.on_step(lambda tran, _: seq.append(tran)) |
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driver(agent.policy, episodes=2) |
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for index in [10, 21]: |
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assert seq[index]['is_last'].item() is True |
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assert seq[index]['is_first'].item() is False |
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for index in [0, 1, 9, 11, 20]: |
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assert seq[index]['is_last'].item() is False |
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def test_env_reset(self): |
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agent = self._make_agent() |
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driver = embodied.Driver([bind(self._make_env, length=5)]) |
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driver.reset(agent.init_policy) |
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seq = [] |
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driver.on_step(lambda tran, _: seq.append(tran)) |
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action = {'act_disc': np.ones(1, int), 'act_cont': np.zeros((1, 6), float)} |
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policy = lambda carry, obs: (carry, action, {}) |
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driver(policy, episodes=2) |
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assert len(seq) == 12 |
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seq = {k: np.array([seq[i][k] for i in range(len(seq))]) for k in seq[0]} |
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assert (seq['is_first'] == [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0]).all() |
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assert (seq['is_last'] == [0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1]).all() |
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assert (seq['reset'] == [0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1]).all() |
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assert (seq['act_disc'] == [1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0]).all() |
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def test_agent_inputs(self): |
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agent = self._make_agent() |
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driver = embodied.Driver([self._make_env]) |
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driver.reset(agent.init_policy) |
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inputs = [] |
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states = [] |
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def policy(carry, obs, mode='train'): |
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inputs.append(obs) |
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states.append(carry) |
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_, act, _ = agent.policy(carry, obs, mode) |
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return 'carry', act, {} |
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seq = [] |
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driver.on_step(lambda tran, _: seq.append(tran)) |
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driver(policy, episodes=2) |
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assert len(seq) == 22 |
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assert states == ([()] + ['carry'] * 21) |
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for index in [0, 11]: |
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assert inputs[index]['is_first'].item() is True |
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for index in [1, 10, 12, 21]: |
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assert inputs[index]['is_first'].item() is False |
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for index in [10, 21]: |
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assert inputs[index]['is_last'].item() is True |
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for index in [0, 1, 9, 11, 20]: |
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assert inputs[index]['is_last'].item() is False |
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def test_unexpected_reset(self): |
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class UnexpectedReset(embodied.Wrapper): |
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"""Send is_first without preceeding is_last.""" |
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def __init__(self, env, when): |
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super().__init__(env) |
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self._when = when |
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self._step = 0 |
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def step(self, action): |
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if self._step == self._when: |
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action = action.copy() |
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action['reset'] = np.ones_like(action['reset']) |
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self._step += 1 |
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return self.env.step(action) |
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env = self._make_env(length=4) |
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env = UnexpectedReset(env, when=3) |
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agent = self._make_agent() |
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driver = embodied.Driver([lambda: env]) |
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driver.reset(agent.init_policy) |
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steps = [] |
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driver.on_step(lambda tran, _: steps.append(tran)) |
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driver(agent.policy, episodes=1) |
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assert len(steps) == 8 |
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steps = {k: np.array([x[k] for x in steps]) for k in steps[0]} |
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assert (steps['reset'] == [0, 0, 0, 0, 0, 0, 0, 1]).all() |
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assert (steps['is_first'] == [1, 0, 0, 1, 0, 0, 0, 0]).all() |
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assert (steps['is_last'] == [0, 0, 0, 0, 0, 0, 0, 1]).all() |
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def _make_env(self, length=10): |
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from embodied.envs import dummy |
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return dummy.Dummy('disc', length=length) |
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def _make_agent(self): |
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env = self._make_env() |
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agent = embodied.RandomAgent(env.obs_space, env.act_space) |
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env.close() |
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return agent |
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