forked from huawei/mindspore2022
91 lines
3.9 KiB
Python
91 lines
3.9 KiB
Python
# Copyright 2021 Huawei Technologies Co., Ltd
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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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import numpy as np
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import mindspore.context as context
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from .optimizer_utils import build_network, loss_default_rprop, loss_group_rprop, loss_not_default_rprop
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def test_default_rprop_pynative():
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"""
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Feature: Test Rprop optimizer
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Description: Test Rprop in Pynative mode with default parameter
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Expectation: Loss values and parameters conform to preset values.
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"""
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context.set_context(mode=context.PYNATIVE_MODE, device_target='GPU')
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config = {'name': 'Rprop', 'lr': 0.01, 'etas': (0.5, 1.2), 'step_sizes': (1e-6, 50.), 'weight_decay': 0.0}
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loss = build_network(config)
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assert np.allclose(loss_default_rprop, loss, atol=1.e-5)
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def test_default_rprop_graph():
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"""
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Feature: Test Rprop optimizer
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Description: Test Rprop in Graph mode with default parameter
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Expectation: Loss values and parameters conform to preset values.
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"""
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context.set_context(mode=context.GRAPH_MODE, device_target='GPU')
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config = {'name': 'Rprop', 'lr': 0.01, 'etas': (0.5, 1.2), 'step_sizes': (1e-6, 50.), 'weight_decay': 0.0}
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loss = build_network(config)
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assert np.allclose(loss_default_rprop, loss, atol=1.e-5)
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def test_no_default_rprop_pynative():
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"""
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Feature: Test Rprop optimizer
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Description: Test Rprop in Pynative mode with another set of parameter
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Expectation: Loss values and parameters conform to preset values.
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"""
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context.set_context(mode=context.PYNATIVE_MODE, device_target='GPU')
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config = {'name': 'Rprop', 'lr': 0.001, 'etas': (0.6, 1.9), 'step_sizes': (1e-3, 20.), 'weight_decay': 0.0}
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loss = build_network(config)
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assert np.allclose(loss_not_default_rprop, loss, atol=1.e-5)
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def test_no_default_rprop_graph():
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"""
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Feature: Test Rprop optimizer
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Description: Test Rprop in Graph mode with another set of parameter
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Expectation: Loss values and parameters conform to preset values.
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"""
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context.set_context(mode=context.GRAPH_MODE, device_target='GPU')
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config = {'name': 'Rprop', 'lr': 0.001, 'etas': (0.6, 1.9), 'step_sizes': (1e-3, 20.), 'weight_decay': 0.0}
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loss = build_network(config)
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assert np.allclose(loss_not_default_rprop, loss, atol=1.e-5)
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def test_default_rprop_group_pynative():
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"""
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Feature: Test Rprop optimizer
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Description: Test Rprop in Pynative mode with parameter grouping
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Expectation: Loss values and parameters conform to preset values.
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"""
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context.set_context(mode=context.PYNATIVE_MODE, device_target='GPU')
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config = {'name': 'Rprop', 'lr': 0.001, 'etas': (0.6, 1.9), 'step_sizes': (1e-2, 10.), 'weight_decay': 0.0}
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loss = build_network(config, is_group=True)
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assert np.allclose(loss_group_rprop, loss, atol=1.e-5)
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def test_default_rprop_group_graph():
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"""
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Feature: Test Rprop optimizer
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Description: Test Rprop in Graph mode with parameter grouping
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Expectation: Loss values and parameters conform to preset values.
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"""
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context.set_context(mode=context.GRAPH_MODE, device_target='GPU')
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config = {'name': 'Rprop', 'lr': 0.001, 'etas': (0.6, 1.9), 'step_sizes': (1e-2, 10.), 'weight_decay': 0.0}
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loss = build_network(config, is_group=True)
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assert np.allclose(loss_group_rprop, loss, atol=1.e-5)
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