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107 行
4.5 KiB
107 行
4.5 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.bc.models import BehavioralCloningModel
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from unityagents import UnityEnvironment
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from .mock_communicator import MockCommunicator
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@mock.patch('unityagents.UnityEnvironment.executable_launcher')
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@mock.patch('unityagents.UnityEnvironment.get_communicator')
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def test_cc_bc_model(mock_communicator, mock_launcher):
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tf.reset_default_graph()
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with tf.Session() as sess:
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with tf.variable_scope("FakeGraphScope"):
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mock_communicator.return_value = MockCommunicator(
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discrete_action=False, visual_inputs=0)
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env = UnityEnvironment(' ')
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model = BehavioralCloningModel(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.sample_action, model.policy]
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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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@mock.patch('unityagents.UnityEnvironment.executable_launcher')
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@mock.patch('unityagents.UnityEnvironment.get_communicator')
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def test_dc_bc_model(mock_communicator, mock_launcher):
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tf.reset_default_graph()
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with tf.Session() as sess:
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with tf.variable_scope("FakeGraphScope"):
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mock_communicator.return_value = MockCommunicator(
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discrete_action=True, visual_inputs=0)
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env = UnityEnvironment(' ')
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model = BehavioralCloningModel(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.sample_action, model.policy]
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feed_dict = {model.batch_size: 2,
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model.dropout_rate: 1.0,
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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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@mock.patch('unityagents.UnityEnvironment.executable_launcher')
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@mock.patch('unityagents.UnityEnvironment.get_communicator')
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def test_visual_dc_bc_model(mock_communicator, mock_launcher):
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tf.reset_default_graph()
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with tf.Session() as sess:
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with tf.variable_scope("FakeGraphScope"):
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mock_communicator.return_value = MockCommunicator(
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discrete_action=True, visual_inputs=2)
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env = UnityEnvironment(' ')
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model = BehavioralCloningModel(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.sample_action, model.policy]
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feed_dict = {model.batch_size: 2,
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model.dropout_rate: 1.0,
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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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model.visual_in[1]: np.ones([2, 40, 30, 3])}
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sess.run(run_list, feed_dict=feed_dict)
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env.close()
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@mock.patch('unityagents.UnityEnvironment.executable_launcher')
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@mock.patch('unityagents.UnityEnvironment.get_communicator')
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def test_visual_cc_bc_model(mock_communicator, mock_launcher):
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tf.reset_default_graph()
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with tf.Session() as sess:
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with tf.variable_scope("FakeGraphScope"):
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mock_communicator.return_value = MockCommunicator(
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discrete_action=False, visual_inputs=2)
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env = UnityEnvironment(' ')
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model = BehavioralCloningModel(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.sample_action, model.policy]
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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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model.visual_in[1]: np.ones([2, 40, 30, 3])}
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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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