You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
53 lines
1.7 KiB
53 lines
1.7 KiB
# Copyright 2019 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 pytest
|
|
from mindspore import Tensor
|
|
from mindspore.ops import operations as P
|
|
import mindspore.nn as nn
|
|
import numpy as np
|
|
import mindspore.context as context
|
|
|
|
|
|
class NetFlatten(nn.Cell):
|
|
def __init__(self):
|
|
super(NetFlatten, self).__init__()
|
|
self.flatten = P.Flatten()
|
|
|
|
def construct(self, x):
|
|
return self.flatten(x)
|
|
|
|
|
|
@pytest.mark.level0
|
|
@pytest.mark.platform_x86_gpu_training
|
|
@pytest.mark.env_onecard
|
|
def test_flatten():
|
|
x = Tensor(np.array([[-0.1, 0.3, 3.6], [0.4, 0.5, -3.2]]).astype(np.float32))
|
|
expect = np.array([[-0.1, 0.3, 3.6], [0.4, 0.5, -3.2]]).astype(np.float32)
|
|
"""
|
|
expect output:
|
|
[[-0.1, 0.3, 3.6], [0.4, 0.5, -3.2]]
|
|
"""
|
|
|
|
context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")
|
|
flatten = NetFlatten()
|
|
output = flatten(x)
|
|
assert (output.asnumpy() == expect).all()
|
|
|
|
context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
|
|
flatten = NetFlatten()
|
|
output = flatten(x)
|
|
assert (output.asnumpy() == expect).all()
|