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New protobuf #33

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Sep 5, 2022
Merged

New protobuf #33

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3f6fb42
Updated with new protobuf interface
alexpalms Sep 5, 2022
e34d0f0
Updating imitation learning tests
alexpalms Sep 5, 2022
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49 changes: 25 additions & 24 deletions diambra/arena/arena_gym.py
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Original file line number Diff line number Diff line change
Expand Up @@ -67,7 +67,7 @@ def env_info_process(self, env_info_dict):
self.max_stage = env_info_dict["max_stage"]

# Min-Max reward
self.minmax_reward = env_info_dict["min_max_rew"]
self.cumulative_reward_bounds = env_info_dict["cumulative_reward_bounds"]

# Characters names list
self.char_names = env_info_dict["char_list"]
Expand All @@ -78,11 +78,12 @@ def env_info_process(self, env_info_dict):
# Action dict
self.print_actions_dict = env_info_dict["actions_dict"]

# Additional Obs map
self.add_obs = {}
for idx in range(len(env_info_dict["additional_obs"])):
elem = env_info_dict["additional_obs"][idx]
self.add_obs[elem["name"]] = [elem["type"], elem["min"], elem["max"]]
# Ram states map
self.ram_states = {}
for k in sorted(env_info_dict["ram_states"].keys()):
self.ram_states[k] = [env_info_dict["ram_states"][k].type,
env_info_dict["ram_states"][k].min,
env_info_dict["ram_states"][k].max]

# Return env action list
def action_list(self):
Expand All @@ -98,10 +99,10 @@ def print_actions(self):
for k, v in self.print_actions_dict[1].items():
print(" {}: {}".format(k, v))

# Return min max rewards for the environment
def get_min_max_reward(self):
return [self.minmax_reward[0] / (self.reward_normalization_value),
self.minmax_reward[1] / (self.reward_normalization_value)]
# Return cumulative reward bounds for the environment
def get_cumulative_reward_bounds(self):
return [self.cumulative_reward_bounds[0] / (self.reward_normalization_value),
self.cumulative_reward_bounds[1] / (self.reward_normalization_value)]

# Step method to be implemented in derived classes
def step(self, action):
Expand Down Expand Up @@ -295,7 +296,7 @@ def __init__(self, env_settings):
player_spec_dict = {}

# Adding env additional observations (side-specific)
for k, v in self.add_obs.items():
for k, v in self.ram_states.items():

if k == "stage":
continue
Expand Down Expand Up @@ -323,13 +324,13 @@ def __init__(self, env_settings):

player_spec_dict["actions"] = spaces.Dict(actions_dict)
observation_space_dict["P1"] = spaces.Dict(player_spec_dict)
observation_space_dict["stage"] = spaces.Box(low=self.add_obs["stage"][1],
high=self.add_obs["stage"][2],
observation_space_dict["stage"] = spaces.Box(low=self.ram_states["stage"][1],
high=self.ram_states["stage"][2],
shape=(1,), dtype=np.int8)

self.observation_space = spaces.Dict(observation_space_dict)

def add_obs_integration(self, frame, data):
def ram_states_integration(self, frame, data):

observation = {}
observation["frame"] = frame
Expand All @@ -338,7 +339,7 @@ def add_obs_integration(self, frame, data):
player_spec_dict = {}

# Adding env additional observations (side-specific)
for k, v in self.add_obs.items():
for k, v in self.ram_states.items():

if k == "stage":
continue
Expand All @@ -364,7 +365,7 @@ def step(self, action):

self.frame, reward, done, data = self.step_complete(action)

observation = self.add_obs_integration(self.frame, data)
observation = self.ram_states_integration(self.frame, data)

return observation, reward, done,\
{"round_done": data["round_done"], "stage_done": data["stage_done"],
Expand All @@ -373,7 +374,7 @@ def step(self, action):
# Reset the environment
def reset(self):
self.frame, data, self.player_side = self.arena_engine.reset()
observation = self.add_obs_integration(self.frame, data)
observation = self.ram_states_integration(self.frame, data)
return observation

# DIAMBRA Gym base class providing frame and additional info as observations
Expand All @@ -393,7 +394,7 @@ def __init__(self, env_settings):
player_spec_dict = {}

# Adding env additional observations (side-specific)
for k, v in self.add_obs.items():
for k, v in self.ram_states.items():

if k == "stage":
continue
Expand Down Expand Up @@ -430,13 +431,13 @@ def __init__(self, env_settings):
player_dict_p2 = player_spec_dict.copy()
observation_space_dict["P2"] = spaces.Dict(player_dict_p2)

observation_space_dict["stage"] = spaces.Box(low=self.add_obs["stage"][1],
high=self.add_obs["stage"][2],
observation_space_dict["stage"] = spaces.Box(low=self.ram_states["stage"][1],
high=self.ram_states["stage"][2],
shape=(1,), dtype=np.int8)

self.observation_space = spaces.Dict(observation_space_dict)

def add_obs_integration(self, frame, data):
def ram_states_integration(self, frame, data):

observation = {}
observation["frame"] = frame
Expand All @@ -447,7 +448,7 @@ def add_obs_integration(self, frame, data):
player_spec_dict = {}

# Adding env additional observations (side-specific)
for k, v in self.add_obs.items():
for k, v in self.ram_states.items():

if k == "stage":
continue
Expand All @@ -474,7 +475,7 @@ def step(self, action):

self.frame, reward, done, data = self.step_complete(action)

observation = self.add_obs_integration(self.frame, data)
observation = self.ram_states_integration(self.frame, data)

return observation, reward, done,\
{"round_done": data["round_done"], "stage_done": data["stage_done"],
Expand All @@ -483,5 +484,5 @@ def step(self, action):
# Reset the environment
def reset(self):
self.frame, data, self.player_side = self.arena_engine.reset()
observation = self.add_obs_integration(self.frame, data)
observation = self.ram_states_integration(self.frame, data)
return observation
23 changes: 11 additions & 12 deletions diambra/arena/arena_imitation_learning_gym.py
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Original file line number Diff line number Diff line change
Expand Up @@ -116,7 +116,7 @@ def step(self, dummy_action):
done_flags = self.rl_traj_dict["done_flags"][self.step_idx]

if (done_flags[0] or done_flags[1] or done_flags[2]) and not done:
self.shift_counter += self.frame_n_channels-1
self.shift_counter += self.frame_n_channels - 1

# Observation retrieval
observation = self.obs_retrieval()
Expand Down Expand Up @@ -306,7 +306,7 @@ def obs_retrieval(self, reset_shift=0):
observation[:, :, iframe] = self.rl_traj_dict["frames"][self.step_idx +
self.shift_counter + iframe - reset_shift]
# Storing last observation for rendering
self.last_obs = observation[:, :, self.frame_n_channels-1]
self.last_obs = observation[:, :, self.frame_n_channels - 1]

return observation

Expand Down Expand Up @@ -338,8 +338,7 @@ def __init__(self, traj_files_list, rank=0, total_cpus=1):
# Specific observation retrieval
def obs_retrieval(self, reset_shift=0):
# Observation retrieval
observation = self.rl_traj_dict["add_obs"][self.step_idx +
1 - reset_shift].copy()
observation = self.rl_traj_dict["ram_states"][self.step_idx + 1 - reset_shift].copy()

# Frame
observation["frame"] = np.zeros(
Expand All @@ -348,7 +347,7 @@ def obs_retrieval(self, reset_shift=0):
observation["frame"][:, :, iframe] = self.rl_traj_dict["frames"][self.step_idx +
self.shift_counter + iframe - reset_shift]
# Storing last observation for rendering
self.last_obs = observation["frame"][:, :, self.frame_n_channels-1]
self.last_obs = observation["frame"][:, :, self.frame_n_channels - 1]

return observation

Expand All @@ -366,12 +365,12 @@ def generate_p2_experience_from_p1(self):
super().generate_p2_experience_from_p1()

# Process Additiona Obs for P2 (copy them in P1 position)
for add_obs in self.rl_traj_dict_p2["add_obs"]:
add_obs.pop("P1")
add_obs["P1"] = add_obs.pop("P2")
add_obs["stage"] = 0
for ram_states in self.rl_traj_dict_p2["ram_states"]:
ram_states.pop("P1")
ram_states["P1"] = ram_states.pop("P2")
ram_states["stage"] = 0

# Remove P2 info from P1 Observation
for add_obs in self.rl_traj_dict["add_obs"]:
add_obs.pop("P2")
add_obs["stage"] = 0
for ram_states in self.rl_traj_dict["ram_states"]:
ram_states.pop("P2")
ram_states["stage"] = 0
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