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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.common.dtype as mstype
- import mindspore.nn as nn
- from mindspore import Tensor, context
- from mindspore.ops import operations as P
-
- context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
-
- class TensorAdd(nn.Cell):
- def __init__(self):
- super(TensorAdd, self).__init__()
- self.add = P.Add()
-
- def construct(self, x, y):
- res = self.add(x, y)
- return res
-
-
- @pytest.mark.level0
- @pytest.mark.platform_x86_cpu
- @pytest.mark.env_onecard
- def test_tensor_add():
- x0 = Tensor(np.random.uniform(-2, 2, (2, 3, 4, 4)).astype(np.float32))
- y0 = Tensor(np.random.uniform(-2, 2, (1, 1, 1, 1)).astype(np.float32))
- x1 = Tensor(np.random.uniform(-2, 2, (1, 3, 1, 4)).astype(np.float32))
- y1 = Tensor(np.random.uniform(-2, 2, (2, 3, 4, 4)).astype(np.float32))
- x2 = Tensor(np.random.uniform(-2, 2, (2, 3, 4, 4)).astype(np.float32))
- y2 = Tensor(2, mstype.float32)
- x3 = Tensor(2, mstype.float32)
- y3 = Tensor(2, mstype.float32)
- x4 = Tensor(np.random.uniform(-2, 2, (4)).astype(np.float32))
- y4 = Tensor(np.random.uniform(-2, 2, (4, 4)).astype(np.float32))
- add = TensorAdd()
- out = add(x0, y0).asnumpy()
- exp = x0.asnumpy() + y0.asnumpy()
- diff = np.abs(out - exp)
- err = np.ones(shape=exp.shape) * 1.0e-5
- assert np.all(diff < err)
- assert out.shape == exp.shape
-
- out = add(x1, y1).asnumpy()
- exp = x1.asnumpy() + y1.asnumpy()
- diff = np.abs(out - exp)
- err = np.ones(shape=exp.shape) * 1.0e-5
- assert np.all(diff < err)
- assert out.shape == exp.shape
-
- out = add(x2, y2).asnumpy()
- exp = x2.asnumpy() + y2.asnumpy()
- diff = np.abs(out - exp)
- err = np.ones(shape=exp.shape) * 1.0e-5
- assert np.all(diff < err)
- assert out.shape == exp.shape
-
- out = add(x3, y3).asnumpy()
- exp = x3.asnumpy() + y3.asnumpy()
- diff = np.abs(out - exp)
- err = np.ones(shape=exp.shape) * 1.0e-5
- assert np.all(diff < err)
- assert out.shape == exp.shape
-
- out = add(x4, y4).asnumpy()
- exp = x4.asnumpy() + y4.asnumpy()
- diff = np.abs(out - exp)
- err = np.ones(shape=exp.shape) * 1.0e-5
- assert np.all(diff < err)
- assert out.shape == exp.shape
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