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