mindspore-ci-bot
4 years ago
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Gitee
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# Copyright 2020 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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""" test lazy adam """
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import numpy as np
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from mindspore.nn.optim import LazyAdam, FTRL, Adam, ProximalAdagrad
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import mindspore.nn as nn
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from mindspore import Tensor, Parameter, context
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from mindspore.ops import operations as P
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context.set_context(enable_sparse=True)
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class NetWithSparseGatherV2(nn.Cell):
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""" NetWithSparseGatherV2 definition """
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def __init__(self):
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super(NetWithSparseGatherV2, self).__init__()
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self.weight1 = Parameter(Tensor(np.ones([3, 1, 2]).astype(np.float32)), name="weight1")
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self.weight2 = Parameter(Tensor(np.ones([2, 1, 2]).astype((np.float32))), name="weight2")
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self.axis = 0
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self.gather = P.SparseGatherV2()
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def construct(self, indices, label):
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return self.gather(self.weight1, indices, self.axis) + self.weight2
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def test_ftrl_target():
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""" test_ftrl_target """
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net = NetWithSparseGatherV2()
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net.set_train()
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optimizer = FTRL(net.trainable_params(), weight_decay=0.9, loss_scale=2.0)
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if optimizer.target not in ('CPU', 'Ascend'):
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raise ValueError("The value must be 'CPU' or 'Ascend', but got value {}".format(optimizer.target))
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def test_lazyadam_target():
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""" test_lazyadam_target """
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net = NetWithSparseGatherV2()
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net.set_train()
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optimizer = LazyAdam(net.trainable_params(), learning_rate=0.1, weight_decay=0.9, loss_scale=2.0)
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if optimizer.target not in ('CPU', 'Ascend'):
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raise ValueError("The value must be 'CPU' or 'Ascend', but got value {}".format(optimizer.target))
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def test_adam_target():
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""" test_adam_target """
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net = NetWithSparseGatherV2()
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net.set_train()
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optimizer = Adam(net.trainable_params(), learning_rate=0.1, loss_scale=1024.0, weight_decay=0.9)
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if optimizer.target not in ('CPU', 'Ascend'):
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raise ValueError("The value must be 'CPU' or 'Ascend', but got value {}".format(optimizer.target))
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def test_proximal_target():
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""" test_proximal_target """
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net = NetWithSparseGatherV2()
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net.set_train()
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optimizer = ProximalAdagrad(net.trainable_params(), weight_decay=0.9, loss_scale=1024.0)
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if optimizer.target not in ('CPU', 'Ascend'):
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raise ValueError("The value must be 'CPU' or 'Ascend', but got value {}".format(optimizer.target))
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