forked from mindspore-Ecosystem/mindspore
35 lines
1011 B
Python
35 lines
1011 B
Python
import numpy as np
|
|
import pytest
|
|
import mindspore.common.dtype as mstype
|
|
import mindspore.nn as nn
|
|
from mindspore import Tensor
|
|
from mindspore import context
|
|
|
|
|
|
class Net(nn.Cell):
|
|
def construct(self, x, other):
|
|
return x.true_divide(other)
|
|
|
|
|
|
@pytest.mark.level0
|
|
@pytest.mark.platform_x86_cpu
|
|
@pytest.mark.platform_arm_cpu
|
|
@pytest.mark.platform_x86_gpu_training
|
|
@pytest.mark.platform_arm_ascend_training
|
|
@pytest.mark.platform_x86_ascend_training
|
|
@pytest.mark.env_onecard
|
|
@pytest.mark.parametrize('mode', [context.GRAPH_MODE, context.PYNATIVE_MODE])
|
|
def test_subtract(mode):
|
|
"""
|
|
Feature: tensor.subtract()
|
|
Description: Verify the result of tensor.subtract
|
|
Expectation: success
|
|
"""
|
|
context.set_context(mode=mode)
|
|
net = Net()
|
|
x = Tensor(np.array([1.0, 2.0, 3.0]), mstype.float32)
|
|
y = Tensor(np.array([4.0, 5.0, 6.0]), mstype.float32)
|
|
output = net(x, y)
|
|
expected = np.array([0.25, 0.4, 0.5], dtype=np.float32)
|
|
assert np.allclose(output.asnumpy(), expected)
|