forked from 626_privacy/tensorflow_privacy
73 lines
2.6 KiB
Python
73 lines
2.6 KiB
Python
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# Copyright 2019 The TensorFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Tests for tensor_buffer in graph mode."""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import tensorflow as tf
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from privacy.analysis import tensor_buffer
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class TensorBufferTest(tf.test.TestCase):
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"""Tests for TensorBuffer in graph mode."""
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def test_noresize(self):
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"""Test buffer does not resize if capacity is not exceeded."""
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with self.cached_session() as sess:
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size, shape = 2, [2, 3]
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my_buffer = tensor_buffer.TensorBuffer(size, shape, name='my_buffer')
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value1 = [[1, 2, 3], [4, 5, 6]]
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with tf.control_dependencies([my_buffer.append(value1)]):
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value2 = [[7, 8, 9], [10, 11, 12]]
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with tf.control_dependencies([my_buffer.append(value2)]):
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values = my_buffer.values
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current_size = my_buffer.current_size
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capacity = my_buffer.capacity
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self.evaluate(tf.global_variables_initializer())
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v, cs, cap = sess.run([values, current_size, capacity])
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self.assertAllEqual(v, [value1, value2])
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self.assertEqual(cs, 2)
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self.assertEqual(cap, 2)
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def test_resize(self):
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"""Test buffer resizes if capacity is exceeded."""
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with self.cached_session() as sess:
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size, shape = 2, [2, 3]
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my_buffer = tensor_buffer.TensorBuffer(size, shape, name='my_buffer')
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value1 = [[1, 2, 3], [4, 5, 6]]
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with tf.control_dependencies([my_buffer.append(value1)]):
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value2 = [[7, 8, 9], [10, 11, 12]]
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with tf.control_dependencies([my_buffer.append(value2)]):
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value3 = [[13, 14, 15], [16, 17, 18]]
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with tf.control_dependencies([my_buffer.append(value3)]):
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values = my_buffer.values
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current_size = my_buffer.current_size
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capacity = my_buffer.capacity
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self.evaluate(tf.global_variables_initializer())
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v, cs, cap = sess.run([values, current_size, capacity])
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self.assertAllEqual(v, [value1, value2, value3])
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self.assertEqual(cs, 3)
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self.assertEqual(cap, 4)
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if __name__ == '__main__':
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tf.test.main()
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