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https://github.com/vale981/ray
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127 lines
4 KiB
Python
127 lines
4 KiB
Python
import gym
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import numpy as np
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import unittest
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from ray.rllib.connectors.action.clip import ClipActionsConnector
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from ray.rllib.connectors.action.lambdas import (
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ConvertToNumpyConnector,
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UnbatchActionsConnector,
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)
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from ray.rllib.connectors.action.normalize import NormalizeActionsConnector
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from ray.rllib.connectors.action.pipeline import ActionConnectorPipeline
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from ray.rllib.connectors.connector import (
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ConnectorContext,
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get_connector,
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)
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from ray.rllib.utils.framework import try_import_torch
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from ray.rllib.utils.typing import ActionConnectorDataType
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torch, _ = try_import_torch()
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class TestActionConnector(unittest.TestCase):
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def test_connector_pipeline(self):
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ctx = ConnectorContext()
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connectors = [ConvertToNumpyConnector(ctx)]
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pipeline = ActionConnectorPipeline(ctx, connectors)
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name, params = pipeline.to_config()
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restored = get_connector(ctx, name, params)
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self.assertTrue(isinstance(restored, ActionConnectorPipeline))
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self.assertTrue(isinstance(restored.connectors[0], ConvertToNumpyConnector))
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def test_convert_to_numpy_connector(self):
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ctx = ConnectorContext()
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c = ConvertToNumpyConnector(ctx)
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name, params = c.to_config()
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self.assertEqual(name, "ConvertToNumpyConnector")
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restored = get_connector(ctx, name, params)
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self.assertTrue(isinstance(restored, ConvertToNumpyConnector))
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action = torch.Tensor([8, 9])
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states = torch.Tensor([[1, 1, 1], [2, 2, 2]])
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ac_data = ActionConnectorDataType(0, 1, (action, states, {}))
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converted = c(ac_data)
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self.assertTrue(isinstance(converted.output[0], np.ndarray))
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self.assertTrue(isinstance(converted.output[1], np.ndarray))
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def test_unbatch_action_connector(self):
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ctx = ConnectorContext()
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c = UnbatchActionsConnector(ctx)
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name, params = c.to_config()
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self.assertEqual(name, "UnbatchActionsConnector")
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restored = get_connector(ctx, name, params)
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self.assertTrue(isinstance(restored, UnbatchActionsConnector))
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ac_data = ActionConnectorDataType(
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0,
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1,
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(
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{
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"a": np.array([1, 2, 3]),
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"b": (np.array([4, 5, 6]), np.array([7, 8, 9])),
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},
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[],
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{},
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),
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)
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unbatched = c(ac_data)
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actions, _, _ = unbatched.output
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self.assertEqual(len(actions), 3)
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self.assertEqual(actions[0]["a"], 1)
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self.assertTrue((actions[0]["b"] == np.array((4, 7))).all())
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self.assertEqual(actions[1]["a"], 2)
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self.assertTrue((actions[1]["b"] == np.array((5, 8))).all())
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self.assertEqual(actions[2]["a"], 3)
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self.assertTrue((actions[2]["b"] == np.array((6, 9))).all())
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def test_normalize_action_connector(self):
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ctx = ConnectorContext(
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action_space=gym.spaces.Box(low=0.0, high=6.0, shape=[1])
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)
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c = NormalizeActionsConnector(ctx)
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name, params = c.to_config()
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self.assertEqual(name, "NormalizeActionsConnector")
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restored = get_connector(ctx, name, params)
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self.assertTrue(isinstance(restored, NormalizeActionsConnector))
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ac_data = ActionConnectorDataType(0, 1, (0.5, [], {}))
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normalized = c(ac_data)
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self.assertEqual(normalized.output[0], 4.5)
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def test_clip_action_connector(self):
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ctx = ConnectorContext(
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action_space=gym.spaces.Box(low=0.0, high=6.0, shape=[1])
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)
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c = ClipActionsConnector(ctx)
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name, params = c.to_config()
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self.assertEqual(name, "ClipActionsConnector")
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restored = get_connector(ctx, name, params)
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self.assertTrue(isinstance(restored, ClipActionsConnector))
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ac_data = ActionConnectorDataType(0, 1, (8.8, [], {}))
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clipped = c(ac_data)
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self.assertEqual(clipped.output[0], 6.0)
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if __name__ == "__main__":
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import pytest
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import sys
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sys.exit(pytest.main(["-v", __file__]))
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