51 lines
1.7 KiB
GDScript
Executable file
51 lines
1.7 KiB
GDScript
Executable file
extends Resource
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class_name ONNXModel
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var inferencer_script = load("res://addons/godot_rl_agents/onnx/csharp/ONNXInference.cs")
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var inferencer = null
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## How many action values the model outputs
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var action_output_size: int
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## Used to differentiate models
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## that only output continuous action mean (e.g. sb3, cleanrl export)
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## versus models that output mean and logstd (e.g. rllib export)
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var action_means_only: bool
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## Whether action_means_value has been set already for this model
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var action_means_only_set: bool
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# Must provide the path to the model and the batch size
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func _init(model_path, batch_size):
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inferencer = inferencer_script.new()
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action_output_size = inferencer.Initialize(model_path, batch_size)
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# This function is the one that will be called from the game,
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# requires the observation as an array and the state_ins as an int
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# returns an Array containing the action the model takes.
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func run_inference(obs: Array, state_ins: int) -> Dictionary:
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if inferencer == null:
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printerr("Inferencer not initialized")
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return {}
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return inferencer.RunInference(obs, state_ins)
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func _notification(what):
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if what == NOTIFICATION_PREDELETE:
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inferencer.FreeDisposables()
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inferencer.free()
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# Check whether agent uses a continuous actions model with only action means or not
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func set_action_means_only(agent_action_space):
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action_means_only_set = true
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var continuous_only: bool = true
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var continuous_actions: int
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for action in agent_action_space:
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if not agent_action_space[action]["action_type"] == "continuous":
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continuous_only = false
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break
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else:
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continuous_actions += agent_action_space[action]["size"]
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if continuous_only:
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if continuous_actions == action_output_size:
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action_means_only = true
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