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105 行
4.3 KiB
105 行
4.3 KiB
import unittest.mock as mock
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import pytest
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import numpy as np
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import tensorflow as tf
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from unitytrainers.ppo.models import PPOModel
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from unityagents import UnityEnvironment
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def test_ppo_model_continuous():
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c_action_c_state_start = '''{
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"AcademyName": "RealFakeAcademy",
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"resetParameters": {},
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"brainNames": ["RealFakeBrain"],
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"externalBrainNames": ["RealFakeBrain"],
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"logPath":"RealFakePath",
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"apiNumber":"API-3",
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"brainParameters": [{
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"vectorObservationSize": 3,
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"numStackedVectorObservations": 2,
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"vectorActionSize": 2,
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"memorySize": 0,
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"cameraResolutions": [],
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"vectorActionDescriptions": ["",""],
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"vectorActionSpaceType": 1,
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"vectorObservationSpaceType": 1
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}]
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}'''.encode()
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tf.reset_default_graph()
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with mock.patch('subprocess.Popen'):
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with mock.patch('socket.socket') as mock_socket:
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with mock.patch('glob.glob') as mock_glob:
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# End of mock
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with tf.Session() as sess:
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with tf.variable_scope("FakeGraphScope"):
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mock_glob.return_value = ['FakeLaunchPath']
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mock_socket.return_value.accept.return_value = (mock_socket, 0)
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mock_socket.recv.return_value.decode.return_value = c_action_c_state_start
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env = UnityEnvironment(' ')
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model = PPOModel(env.brains["RealFakeBrain"])
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init = tf.global_variables_initializer()
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sess.run(init)
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run_list = [model.output, model.probs, model.value, model.entropy,
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model.learning_rate]
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feed_dict = {model.batch_size: 2,
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model.sequence_length: 1,
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model.vector_in: np.array([[1, 2, 3, 1, 2, 3],
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[3, 4, 5, 3, 4, 5]])}
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sess.run(run_list, feed_dict=feed_dict)
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env.close()
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def test_ppo_model_discrete():
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d_action_c_state_start = '''{
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"AcademyName": "RealFakeAcademy",
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"resetParameters": {},
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"brainNames": ["RealFakeBrain"],
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"externalBrainNames": ["RealFakeBrain"],
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"logPath":"RealFakePath",
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"apiNumber":"API-3",
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"brainParameters": [{
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"vectorObservationSize": 3,
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"numStackedVectorObservations": 2,
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"vectorActionSize": 2,
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"memorySize": 0,
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"cameraResolutions": [{"width":30,"height":40,"blackAndWhite":false}],
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"vectorActionDescriptions": ["",""],
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"vectorActionSpaceType": 0,
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"vectorObservationSpaceType": 1
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}]
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}'''.encode()
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tf.reset_default_graph()
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with mock.patch('subprocess.Popen'):
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with mock.patch('socket.socket') as mock_socket:
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with mock.patch('glob.glob') as mock_glob:
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# End of mock
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with tf.Session() as sess:
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with tf.variable_scope("FakeGraphScope"):
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mock_glob.return_value = ['FakeLaunchPath']
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mock_socket.return_value.accept.return_value = (mock_socket, 0)
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mock_socket.recv.return_value.decode.return_value = d_action_c_state_start
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env = UnityEnvironment(' ')
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model = PPOModel(env.brains["RealFakeBrain"])
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init = tf.global_variables_initializer()
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sess.run(init)
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run_list = [model.output, model.all_probs, model.value, model.entropy,
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model.learning_rate]
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feed_dict = {model.batch_size: 2,
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model.sequence_length: 1,
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model.vector_in: np.array([[1, 2, 3, 1, 2, 3],
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[3, 4, 5, 3, 4, 5]]),
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model.visual_in[0]: np.ones([2, 40, 30, 3])
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}
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sess.run(run_list, feed_dict=feed_dict)
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env.close()
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if __name__ == '__main__':
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pytest.main()
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