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- # Copyright 2020 Huawei Technologies Co., Ltd
- #
- # Licensed under the Apache License, Version 2.0 (the "License");
- # you may not use this file except in compliance with the License.
- # You may obtain a copy of the License at
- #
- # http://www.apache.org/licenses/LICENSE-2.0
- #
- # Unless required by applicable law or agreed to in writing, software
- # distributed under the License is distributed on an "AS IS" BASIS,
- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- # See the License for the specific language governing permissions and
- # limitations under the License.
- # ============================================================================
-
- import numpy as np
- import pytest
-
- import mindspore.context as context
- import mindspore.nn as nn
- from mindspore import Tensor, Parameter
- from mindspore.ops import operations as P
- import mindspore.common.dtype as mstype
-
- context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
-
- var_np = np.random.rand(3, 3).astype(np.float32)
- accum_np = np.random.rand(3, 3).astype(np.float32)
-
-
- class Net(nn.Cell):
- def __init__(self):
- super(Net, self).__init__()
- self.apply_adagrad = P.ApplyAdagrad()
- self.var = Parameter(Tensor(var_np), name="var")
- self.accum = Parameter(Tensor(accum_np), name="accum")
-
- def construct(self, lr, grad):
- self.apply_adagrad(self.var, self.accum, lr, grad)
- return self.var, self.accum
-
-
- @pytest.mark.level0
- @pytest.mark.platform_x86_gpu_training
- @pytest.mark.env_onecard
- def test_apply_adagrad():
- # numpy op
- grident_np = np.random.rand(3, 3).astype(np.float32)
- expect_accum_np = accum_np + grident_np * grident_np
- expect_var_np = var_np - (0.001 * grident_np * (1 / np.sqrt(expect_accum_np + 1e-6)))
-
- net = Net()
- lr = Tensor(0.001, mstype.float32)
- grad = Tensor(grident_np)
- out = net(lr, grad)
- res_var_mindspore = out[0].asnumpy()
- res_accum_mindspore = out[1].asnumpy()
- eps = np.array([1e-6 for i in range(9)]).reshape(3, 3)
-
- assert np.all(expect_var_np - res_var_mindspore < eps)
- assert np.all(expect_accum_np - res_accum_mindspore < eps)
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