mindspore/tests/st/fusion/test_tbe_eltwise_fusion_2.py

55 lines
1.6 KiB
Python

# 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
from mindspore.ops import operations as P
context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
class Net(nn.Cell):
def __init__(self):
super(Net, self).__init__()
self.softmax = P.Softmax(axis=1)
self.cast = P.Cast()
self.relu = P.ReLU()
self.biasadd = P.BiasAdd()
def construct(self, x, y):
x = self.relu(x)
x = self.relu(x)
x = self.relu(x)
x = self.biasadd(x, y)
x = self.relu(x)
x = self.relu(x)
x = self.relu(x)
return x
@pytest.mark.level0
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_onecard
def test_net():
x = np.random.randn(32, 10).astype(np.float32)
y = np.random.randn(10).astype(np.float32)
net = Net()
output = net(Tensor(x), Tensor(y))
print(output.asnumpy())