From cc04d63ff36bb36e07b9b5ac966c6e691518f854 Mon Sep 17 00:00:00 2001
From: Dipam Chakraborty <dipam@aicrowd.com>
Date: Tue, 14 Sep 2021 00:36:16 +0530
Subject: [PATCH] malfunction fix: can save actions during malfunction
---
flatland/envs/malfunction_generators.py | 11 +++++-----
flatland/envs/rail_env.py | 2 +-
flatland/envs/step_utils/action_saver.py | 10 +++------
tests/test_flatland_malfunction.py | 27 ++++++++++++------------
tests/test_utils.py | 1 -
5 files changed, 23 insertions(+), 28 deletions(-)
diff --git a/flatland/envs/malfunction_generators.py b/flatland/envs/malfunction_generators.py
index 0dfafb36..086fd9ce 100644
--- a/flatland/envs/malfunction_generators.py
+++ b/flatland/envs/malfunction_generators.py
@@ -253,7 +253,7 @@ def malfunction_from_params(parameters: MalfunctionParameters) -> Tuple[Malfunct
min_number_of_steps_broken = parameters.min_duration
max_number_of_steps_broken = parameters.max_duration
- def generator(agent: EnvAgent = None, np_random: RandomState = None, reset=False) -> Optional[Malfunction]:
+ def generator(np_random: RandomState = None, reset=False) -> Optional[Malfunction]:
"""
Generate malfunctions for agents
Parameters
@@ -270,11 +270,10 @@ def malfunction_from_params(parameters: MalfunctionParameters) -> Tuple[Malfunct
if reset:
return Malfunction(0)
- if agent.malfunction_data['malfunction'] < 1:
- if np_random.rand() < _malfunction_prob(mean_malfunction_rate):
- num_broken_steps = np_random.randint(min_number_of_steps_broken,
- max_number_of_steps_broken + 1) + 1
- return Malfunction(num_broken_steps)
+ if np_random.rand() < _malfunction_prob(mean_malfunction_rate):
+ num_broken_steps = np_random.randint(min_number_of_steps_broken,
+ max_number_of_steps_broken + 1)
+ return Malfunction(num_broken_steps)
return Malfunction(0)
return generator, MalfunctionProcessData(mean_malfunction_rate, min_number_of_steps_broken,
diff --git a/flatland/envs/rail_env.py b/flatland/envs/rail_env.py
index a6a15531..f3456485 100644
--- a/flatland/envs/rail_env.py
+++ b/flatland/envs/rail_env.py
@@ -549,7 +549,7 @@ class RailEnv(Environment):
if agent.malfunction_handler.in_malfunction:
movement_allowed = False
else:
- movement_allowed = self.motionCheck.check_motion(i_agent, agent.position) # TODO: Remove final_new_postion from motioncheck
+ movement_allowed = self.motionCheck.check_motion(i_agent, agent.position)
# Position can be changed only if other cell is empty
# And either the speed counter completes or agent is being added to map
diff --git a/flatland/envs/step_utils/action_saver.py b/flatland/envs/step_utils/action_saver.py
index bf61076e..913e9576 100644
--- a/flatland/envs/step_utils/action_saver.py
+++ b/flatland/envs/step_utils/action_saver.py
@@ -17,14 +17,10 @@ class ActionSaver:
"""
Save the action if all conditions are met
1. It is a movement based action -> Forward, Left, Right
- 2. Action is not already saved
- 3. Not in a malfunction state
- 4. Agent is not already done
+ 2. Action is not already saved
+ 3. Agent is not already done
"""
- if action.is_moving_action() and \
- not self.is_action_saved and \
- not state.is_malfunction_state() and \
- not state == TrainState.DONE:
+ if action.is_moving_action() and not self.is_action_saved and not state == TrainState.DONE:
self.saved_action = action
def clear_saved_action(self):
diff --git a/tests/test_flatland_malfunction.py b/tests/test_flatland_malfunction.py
index d633351e..b4632f3e 100644
--- a/tests/test_flatland_malfunction.py
+++ b/tests/test_flatland_malfunction.py
@@ -190,8 +190,9 @@ def test_malfunction_before_entry():
# Test initial malfunction values for all agents
# we want some agents to be malfuncitoning already and some to be working
# we want different next_malfunction values for the agents
- assert env.agents[0].malfunction_data['malfunction'] == 0
- assert env.agents[1].malfunction_data['malfunction'] == 10
+ malfunction_values = [env.malfunction_generator(env.np_random).num_broken_steps for _ in range(1000)]
+ expected_value = (1 - np.exp(-0.5)) * 10
+ assert np.allclose(np.mean(malfunction_values), expected_value, rtol=0.1), "Mean values of malfunction don't match rate"
def test_malfunction_values_and_behavior():
@@ -257,7 +258,7 @@ def test_initial_malfunction():
set_penalties_for_replay(env)
replay_config = ReplayConfig(
replay=[
- Replay(
+ Replay( # 0
position=(3, 2),
direction=Grid4TransitionsEnum.EAST,
action=RailEnvActions.MOVE_FORWARD,
@@ -265,7 +266,7 @@ def test_initial_malfunction():
malfunction=3,
reward=env.step_penalty # full step penalty when malfunctioning
),
- Replay(
+ Replay( # 1
position=(3, 2),
direction=Grid4TransitionsEnum.EAST,
action=RailEnvActions.MOVE_FORWARD,
@@ -274,7 +275,7 @@ def test_initial_malfunction():
),
# malfunction stops in the next step and we're still at the beginning of the cell
# --> if we take action MOVE_FORWARD, agent should restart and move to the next cell
- Replay(
+ Replay( # 2
position=(3, 2),
direction=Grid4TransitionsEnum.EAST,
action=RailEnvActions.MOVE_FORWARD,
@@ -282,14 +283,14 @@ def test_initial_malfunction():
reward=env.step_penalty
), # malfunctioning ends: starting and running at speed 1.0
- Replay(
+ Replay( # 3
position=(3, 2),
direction=Grid4TransitionsEnum.EAST,
action=RailEnvActions.MOVE_FORWARD,
malfunction=0,
reward=env.start_penalty + env.step_penalty * 1.0 # running at speed 1.0
),
- Replay(
+ Replay( # 4
position=(3, 3),
direction=Grid4TransitionsEnum.EAST,
action=RailEnvActions.MOVE_FORWARD,
@@ -420,7 +421,7 @@ def test_initial_malfunction_do_nothing():
action=RailEnvActions.DO_NOTHING,
malfunction=2,
reward=env.step_penalty, # full step penalty while malfunctioning
- state=TrainState.ACTIVE
+ state=TrainState.MOVING
),
# malfunction stops in the next step and we're still at the beginning of the cell
# --> if we take action DO_NOTHING, agent should restart without moving
@@ -431,7 +432,7 @@ def test_initial_malfunction_do_nothing():
action=RailEnvActions.DO_NOTHING,
malfunction=1,
reward=env.step_penalty, # full step penalty while stopped
- state=TrainState.ACTIVE
+ state=TrainState.MOVING
),
# we haven't started moving yet --> stay here
Replay(
@@ -440,7 +441,7 @@ def test_initial_malfunction_do_nothing():
action=RailEnvActions.DO_NOTHING,
malfunction=0,
reward=env.step_penalty, # full step penalty while stopped
- state=TrainState.ACTIVE
+ state=TrainState.MOVING
),
Replay(
@@ -449,7 +450,7 @@ def test_initial_malfunction_do_nothing():
action=RailEnvActions.MOVE_FORWARD,
malfunction=0,
reward=env.start_penalty + env.step_penalty * 1.0, # start penalty + step penalty for speed 1.0
- state=TrainState.ACTIVE
+ state=TrainState.MOVING
), # we start to move forward --> should go to next cell now
Replay(
position=(3, 3),
@@ -457,7 +458,7 @@ def test_initial_malfunction_do_nothing():
action=RailEnvActions.MOVE_FORWARD,
malfunction=0,
reward=env.step_penalty * 1.0, # step penalty for speed 1.0
- state=TrainState.ACTIVE
+ state=TrainState.MOVING
)
],
speed=env.agents[0].speed_counter.speed,
@@ -546,7 +547,7 @@ def test_last_malfunction_step():
env.reset(False, False)
for a_idx in range(len(env.agents)):
env.agents[a_idx].position = env.agents[a_idx].initial_position
- env.agents[a_idx].state = TrainState.ACTIVE
+ env.agents[a_idx].state = TrainState.MOVING
# Force malfunction to be off at beginning and next malfunction to happen in 2 steps
env.agents[0].malfunction_data['next_malfunction'] = 2
env.agents[0].malfunction_data['malfunction'] = 0
diff --git a/tests/test_utils.py b/tests/test_utils.py
index 3469c9c8..391ba535 100644
--- a/tests/test_utils.py
+++ b/tests/test_utils.py
@@ -107,7 +107,6 @@ def run_replay_config(env: RailEnv, test_configs: List[ReplayConfig], rendering:
for a, test_config in enumerate(test_configs):
agent: EnvAgent = env.agents[a]
replay = test_config.replay[step]
- print(agent.position, replay.position, agent.state, agent.speed_counter)
_assert(a, agent.position, replay.position, 'position')
_assert(a, agent.direction, replay.direction, 'direction')
if replay.state is not None:
--
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