Added test script

celeste/celeste_ai/paths.py

@@ -0,0 +1,119 @@
+from pathlib import Path
+import torch
+import json
+
+from celeste_ai import Celeste
+from celeste_ai import DQN
+
+
+
+model_data_root = Path("model_data/solved_1")
+
+compute_device = torch.device(
+	"cuda" if torch.cuda.is_available() else "cpu"
+)
+
+
+# Celeste env properties
+n_observations = len(Celeste.state_number_map)
+n_actions = len(Celeste.action_space)
+
+policy_net = DQN(
+	n_observations,
+	n_actions
+).to(compute_device)
+
+k = (model_data_root / "model_archive").iterdir()
+i = 0
+
+state_history = []
+current_path = None
+
+def next_image():
+	global policy_net
+	global current_path
+	global i
+	i += 1
+
+	try:
+		current_path = k.__next__()
+	except StopIteration:
+		return False
+
+	print(f"Pathing {current_path} ({i})")
+
+	# Load model if one exists
+	checkpoint = torch.load(
+		current_path,
+		map_location = compute_device
+	)
+	policy_net.load_state_dict(checkpoint["policy_state_dict"])
+
+
+next_image()
+
+def on_state_before(celeste):
+	global steps_done
+
+	state = celeste.state
+
+	pt_state = torch.tensor(
+		[getattr(state, x) for x in Celeste.state_number_map],
+		dtype = torch.float32,
+		device = compute_device
+	).unsqueeze(0)
+
+
+	action = policy_net(pt_state).max(1)[1].view(1, 1).item()
+	str_action = Celeste.action_space[action]
+
+	celeste.act(str_action)
+
+	return state, action
+
+
+def on_state_after(celeste, before_out):
+	global episode_number
+	global state_history
+
+	state, action = before_out
+	next_state = celeste.state
+	finished_stage = next_state.stage >= 1
+
+	state_history.append({
+		"xpos": state.xpos,
+		"ypos": state.ypos,
+		"action": Celeste.action_space[action]
+	})
+
+	# Move on to the next episode once we reach
+	# a terminal state.
+	if (next_state.deaths != 0 or finished_stage):
+
+		with (model_data_root / "paths.json").open("a") as f:
+			f.write(json.dumps(
+				{
+					"hist": state_history,
+					"current_image": str(current_path)
+				}
+			) + "\n")
+
+		state_history = []
+		k = next_image()
+
+		if k is False:
+			raise Exception("Done.")
+
+		print("Game over. Resetting.")
+		celeste.reset()
+
+
+
+c = Celeste(
+	"resources/pico-8/linux/pico8"
+)
+
+c.update_loop(
+	on_state_before,
+	on_state_after
+)

celeste/celeste_ai/test.py

@@ -0,0 +1,100 @@
+from pathlib import Path
+import torch
+
+from celeste_ai import Celeste
+from celeste_ai import DQN
+from celeste_ai.util.screenshots import ScreenshotManager
+
+
+if __name__ == "__main__":
+	# Where to read/write model data.
+	model_data_root = Path("model_data/current")
+
+	model_save_path		= model_data_root / "model.torch"
+	model_data_root.mkdir(parents = True, exist_ok = True)
+
+
+	sm = ScreenshotManager(
+		# Where PICO-8 saves screenshots.
+		# Probably your desktop.
+		source = Path("/home/mark/Desktop"),
+		pattern = "hackcel_*.png",
+		target = model_data_root / "screenshots_test"
+	).clean() # Remove old screenshots
+
+
+	compute_device = torch.device(
+		"cuda" if torch.cuda.is_available() else "cpu"
+	)
+
+	episode_number = 0
+
+	# Celeste env properties
+	n_observations = len(Celeste.state_number_map)
+	n_actions = len(Celeste.action_space)
+
+	policy_net = DQN(
+		n_observations,
+		n_actions
+	).to(compute_device)
+
+
+	# Load model if one exists
+	checkpoint = torch.load(
+		model_save_path,
+		map_location = compute_device
+	)
+	policy_net.load_state_dict(checkpoint["policy_state_dict"])
+
+
+def on_state_before(celeste):
+	global steps_done
+
+	state = celeste.state
+
+	pt_state = torch.tensor(
+		[getattr(state, x) for x in Celeste.state_number_map],
+		dtype = torch.float32,
+		device = compute_device
+	).unsqueeze(0)
+
+
+	action = policy_net(pt_state).max(1)[1].view(1, 1).item()
+	str_action = Celeste.action_space[action]
+
+	print(str_action)
+	celeste.act(str_action)
+
+	return state, action
+
+
+def on_state_after(celeste, before_out):
+	global episode_number
+
+	state, action = before_out
+	next_state = celeste.state
+	finished_stage = next_state.stage >= 1
+
+
+	# Move on to the next episode once we reach
+	# a terminal state.
+	if (next_state.deaths != 0 or finished_stage):
+		s = celeste.state
+
+		sm.move()
+
+
+		print("Game over. Resetting.")
+		celeste.reset()
+		episode_number += 1
+
+
+if __name__ == "__main__":
+	c = Celeste(
+		"resources/pico-8/linux/pico8"
+	)
+
+	c.update_loop(
+		on_state_before,
+		on_state_after
+	)