Move keras related memory_checker_test to keras/tests.
PiperOrigin-RevId: 306081516 Change-Id: I759c0b0283ac02324637e6be71499036e5ed48de
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@ -18,11 +18,9 @@ from __future__ import division
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from __future__ import print_function
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from tensorflow.python import _memory_checker_test_helper
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from tensorflow.python import keras
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from tensorflow.python.framework import constant_op
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from tensorflow.python.framework import ops
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from tensorflow.python.framework.memory_checker import MemoryChecker
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from tensorflow.python.ops import array_ops
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from tensorflow.python.platform import test
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@ -153,55 +151,6 @@ class MemoryCheckerTest(test.TestCase):
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'builtins.function': 1,
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})
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def testKerasBasic(self):
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# TODO(kkb): Fix the the slowness on Forge.
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self.skipTest('This test is too slow on Forge so disabled for now.')
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x = array_ops.zeros([1, 1])
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y = constant_op.constant([[3]])
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model = keras.models.Sequential()
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model.add(keras.layers.Dense(1, input_dim=1))
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model.compile(loss='mean_squared_error')
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with MemoryChecker() as memory_checker:
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for _ in range(10):
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model.fit(x, y)
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model.evaluate(x, y)
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memory_checker.record_snapshot()
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memory_checker.report()
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memory_checker.assert_no_leak_if_all_possibly_except_one()
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def testKerasAdvanced(self):
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# TODO(kkb): Fix the the slowness on Forge.
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self.skipTest('This test is too slow on Forge so disabled for now.')
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# A real world example taken from the following.
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# https://github.com/tensorflow/tensorflow/issues/32500
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# b/142150794
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with MemoryChecker() as memory_checker:
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rows = 6
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columns = 7
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model = keras.Sequential([
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keras.layers.Flatten(input_shape=[rows * columns, 3]),
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keras.layers.Dense(7, input_shape=[rows * columns * 3]),
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])
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model.compile(
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optimizer=keras.optimizer_v2.gradient_descent.SGD(lr=0.01),
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loss='mean_squared_error',
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metrics=['accuracy'])
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states = [[1] * rows * columns for _ in range(20)]
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f = array_ops.one_hot(states, dtype='float32', depth=3)
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for _ in range(20):
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model.predict(f, steps=10)
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memory_checker.record_snapshot()
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memory_checker.report()
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memory_checker.assert_no_leak_if_all_possibly_except_one()
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if __name__ == '__main__':
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ops.enable_eager_execution()
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@ -190,6 +190,30 @@ cuda_py_test(
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],
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)
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tf_py_test(
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name = "memory_checker_test",
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size = "medium",
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srcs = ["memory_checker_test.py"],
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python_version = "PY3",
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shard_count = 8,
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tags = [
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"no_oss",
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"no_pip",
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"no_windows",
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"noasan", # TODO(b/149948895): Re-enable.
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"nomsan", # TODO(b/149948895): Re-enable.
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"notsan", # TODO(b/149948895): Re-enable.
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],
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deps = [
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"//tensorflow/python:array_ops",
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"//tensorflow/python:client_testlib",
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"//tensorflow/python:constant_op",
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"//tensorflow/python:extra_py_tests_deps",
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"//tensorflow/python:framework_ops",
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"//tensorflow/python:memory_checker",
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],
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)
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tf_py_test(
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name = "temporal_sample_weights_correctness_test",
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srcs = ["temporal_sample_weights_correctness_test.py"],
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82
tensorflow/python/keras/tests/memory_checker_test.py
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82
tensorflow/python/keras/tests/memory_checker_test.py
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@ -0,0 +1,82 @@
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# Copyright 2020 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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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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from tensorflow.python import keras
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from tensorflow.python.framework import constant_op
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from tensorflow.python.framework import ops
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from tensorflow.python.framework.memory_checker import MemoryChecker
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from tensorflow.python.ops import array_ops
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from tensorflow.python.platform import test
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class MemoryCheckerTest(test.TestCase):
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def testKerasBasic(self):
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# TODO(kkb): Fix the the slowness on Forge.
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self.skipTest('This test is too slow on Forge so disabled for now.')
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x = array_ops.zeros([1, 1])
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y = constant_op.constant([[3]])
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model = keras.models.Sequential()
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model.add(keras.layers.Dense(1, input_dim=1))
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model.compile(loss='mean_squared_error')
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with MemoryChecker() as memory_checker:
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for _ in range(10):
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model.fit(x, y)
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model.evaluate(x, y)
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memory_checker.record_snapshot()
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memory_checker.report()
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memory_checker.assert_no_leak_if_all_possibly_except_one()
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def testKerasAdvanced(self):
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# TODO(kkb): Fix the the slowness on Forge.
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self.skipTest('This test is too slow on Forge so disabled for now.')
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# A real world example taken from the following.
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# https://github.com/tensorflow/tensorflow/issues/32500
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# b/142150794
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with MemoryChecker() as memory_checker:
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rows = 6
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columns = 7
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model = keras.Sequential([
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keras.layers.Flatten(input_shape=[rows * columns, 3]),
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keras.layers.Dense(7, input_shape=[rows * columns * 3]),
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])
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model.compile(
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optimizer=keras.optimizer_v2.gradient_descent.SGD(lr=0.01),
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loss='mean_squared_error',
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metrics=['accuracy'])
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states = [[1] * rows * columns for _ in range(20)]
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f = array_ops.one_hot(states, dtype='float32', depth=3)
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for _ in range(20):
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model.predict(f, steps=10)
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memory_checker.record_snapshot()
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memory_checker.report()
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memory_checker.assert_no_leak_if_all_possibly_except_one()
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if __name__ == '__main__':
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ops.enable_eager_execution()
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test.main()
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