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mindspore/tests/st/ops/cpu/test_tensoradd.py

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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.TensorAdd()
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)
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