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71 lines
3.0 KiB
71 lines
3.0 KiB
# Copyright (c) 2018 PaddlePaddle 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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from __future__ import print_function
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import unittest
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from paddle.fluid.framework import default_main_program
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from paddle.fluid.incubate.fleet.parameter_server.ir.pserver_pass import _get_optimizer_input_shape
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main_program = default_main_program()
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class TestFleetPS(unittest.TestCase):
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def test_version(self):
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from paddle.fluid.incubate.fleet.parameter_server import version
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transpiler = version.is_transpiler()
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self.assertEqual(transpiler, True)
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def test_optimizer_shape(self):
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optimizers = []
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optimizers.append(("adam", "Moment1", [100, 1], [50, 1]))
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optimizers.append(("adam", "Moment2", [100, 1], [50, 1]))
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optimizers.append(("adagrad", "Moment", [100, 1], [50, 1]))
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optimizers.append(("adamax", "Moment", [100, 1], [50, 1]))
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optimizers.append(("adamax", "InfNorm", [100, 1], [50, 1]))
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optimizers.append(("momentum", "Velocity", [100, 1], [50, 1]))
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optimizers.append(("lars_momentum", "Velocity", [100, 1], [50, 1]))
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optimizers.append(("decayed_adagrad", "Moment", [100, 1], [50, 1]))
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optimizers.append(("rmsprop", "Moment", [100, 1], [50, 1]))
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optimizers.append(("rmsprop", "MeanSquare", [100, 1], [50, 1]))
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optimizers.append(("ftrl", "SquaredAccumulator", [100, 1], [50, 1]))
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optimizers.append(("ftrl", "LinearAccumulator", [100, 1], [50, 1]))
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for attrs in optimizers:
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op_type, varkey, orig_shape, param_shape = attrs
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new_shape = _get_optimizer_input_shape(op_type, varkey, orig_shape,
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param_shape)
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self.assertListEqual(new_shape, param_shape)
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optimizers = []
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optimizers.append(("sgd", "", [100, 1], [50, 1]))
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for attrs in optimizers:
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op_type, varkey, orig_shape, param_shape = attrs
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new_shape = _get_optimizer_input_shape(op_type, varkey, orig_shape,
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param_shape)
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self.assertListEqual(new_shape, orig_shape)
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with self.assertRaises(ValueError):
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optimizers = []
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optimizers.append(("new_opti", "", [100, 1], [50, 1]))
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for attrs in optimizers:
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op_type, varkey, orig_shape, param_shape = attrs
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_get_optimizer_input_shape(op_type, varkey, orig_shape,
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param_shape)
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if __name__ == '__main__':
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unittest.main()
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