f2306d9f25
The memory test couldn't be convert to integration test since the anntation for eager garbage collection is not publicly visible. PiperOrigin-RevId: 315702765 Change-Id: I4c8d54b074364d3884af64a2b4d00ad615ef319d
81 lines
3.0 KiB
Python
81 lines
3.0 KiB
Python
# Copyright 2018 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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# ==============================================================================
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"""Tests for trackable object SavedModel save."""
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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 os
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import sys
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from tensorflow.python.eager import backprop
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from tensorflow.python.eager import function
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from tensorflow.python.framework import constant_op
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from tensorflow.python.framework import dtypes
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from tensorflow.python.framework import tensor_spec
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from tensorflow.python.framework import test_util
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from tensorflow.python.keras.layers import core
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from tensorflow.python.keras.optimizer_v2 import adam
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from tensorflow.python.ops import math_ops
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from tensorflow.python.platform import test
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from tensorflow.python.saved_model import save
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from tensorflow.python.training.tracking import util
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class _ModelWithOptimizerUsingDefun(util.Checkpoint):
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def __init__(self):
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self.dense = core.Dense(1)
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self.optimizer = adam.Adam(0.01)
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# Using defun due to control flow v2 cycles, b/121159261. def_function uses
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# conds to gate variable initialization and so triggers cond reference cycles,
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# but the thing being wrapped here does not use cond itself.
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@function.defun(
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input_signature=(tensor_spec.TensorSpec([None, 2], dtypes.float32),
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tensor_spec.TensorSpec([None], dtypes.float32)),
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)
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def call(self, x, y):
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with backprop.GradientTape() as tape:
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loss = math_ops.reduce_mean((self.dense(x) - y) ** 2.)
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trainable_variables = self.dense.trainable_variables
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gradients = tape.gradient(loss, trainable_variables)
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self.optimizer.apply_gradients(zip(gradients, trainable_variables))
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return {"loss": loss}
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class MemoryTests(test.TestCase):
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def setUp(self):
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super(MemoryTests, self).setUp()
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self._model = _ModelWithOptimizerUsingDefun()
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@test_util.assert_no_garbage_created
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def test_no_reference_cycles(self):
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x = constant_op.constant([[3., 4.]])
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y = constant_op.constant([2.])
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self._model.call(x, y)
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if sys.version_info[0] < 3:
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# TODO(allenl): debug reference cycles in Python 2.x
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self.skipTest("This test only works in Python 3+. Reference cycles are "
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"created in older Python versions.")
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save_dir = os.path.join(self.get_temp_dir(), "saved_model")
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save.save(self._model, save_dir, self._model.call)
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if __name__ == "__main__":
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test.main()
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