66c48046f1
This is mostly the result of an internal cleanup and formatting pass. PiperOrigin-RevId: 286318018 Change-Id: I8f9e2f7519070035da73f9f24d2fc90864abc51b
103 lines
3.8 KiB
Python
103 lines
3.8 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 warm_starting_util with Distribution Strategy.
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These tests are located here instead of as part of `WarmStartingUtilTest`
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because they need access to distribution strategies which are only present in
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contrib right now.
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TODO(priyag): Move the tests to core `WarmStartingUtilTest` when distribution
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strategy moves out of contrib.
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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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import os
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from absl.testing import parameterized
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from tensorflow.python.distribute import combinations
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from tensorflow.python.distribute import strategy_combinations
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from tensorflow.python.framework import ops
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from tensorflow.python.ops import variable_scope
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from tensorflow.python.ops import variables
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from tensorflow.python.platform import test
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from tensorflow.python.training import saver as saver_lib
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from tensorflow.python.training import warm_starting_util as ws_util
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class WarmStartingUtilWithDistributionStrategyTest(
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test.TestCase, parameterized.TestCase):
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@combinations.generate(
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combinations.combine(
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distribution=[
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strategy_combinations.default_strategy,
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strategy_combinations.one_device_strategy,
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strategy_combinations.mirrored_strategy_with_gpu_and_cpu,
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strategy_combinations.mirrored_strategy_with_two_gpus,
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],
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save_with_distribution=[True, False],
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restore_with_distribution=[True, False],
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mode=["graph"]))
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def testWarmStart(self, distribution, save_with_distribution,
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restore_with_distribution):
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var_name = "v"
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original_value = [[1., 2.], [3., 4.]]
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# Create variable and save checkpoint from which to warm-start.
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def create_var(g):
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with self.session(graph=g) as sess:
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var = variable_scope.get_variable(var_name, initializer=original_value)
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sess.run(variables.global_variables_initializer())
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saver = saver_lib.Saver()
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ckpt_prefix = os.path.join(self.get_temp_dir(), "model")
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saver.save(sess, ckpt_prefix, global_step=0)
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return var, sess.run(var)
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if save_with_distribution:
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with ops.Graph().as_default() as g, distribution.scope():
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_, prev_init_val = create_var(g)
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else:
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with ops.Graph().as_default() as g:
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_, prev_init_val = create_var(g)
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# Verify we initialized the values correctly.
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self.assertAllEqual(original_value, prev_init_val)
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def warm_start(g):
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with self.session(graph=g) as sess:
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# Initialize with zeros.
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var = variable_scope.get_variable(
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var_name, initializer=[[0., 0.], [0., 0.]])
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ws_util.warm_start(self.get_temp_dir())
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sess.run(variables.global_variables_initializer())
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# Verify weights were correctly warm-started to previous values.
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self.assertAllEqual(original_value, self.evaluate(var))
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# Warm start in a new graph.
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if restore_with_distribution:
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with ops.Graph().as_default() as g, distribution.scope():
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warm_start(g)
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else:
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with ops.Graph().as_default() as g:
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warm_start(g)
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if __name__ == "__main__":
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test.main()
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