mindspore/tests/st/ops/graph_kernel/test_slice.py

56 lines
1.8 KiB
Python

# Copyright 2021 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
class Net(nn.Cell):
def __init__(self):
super(Net, self).__init__()
self.slice = P.Slice()
def construct(self, x, begin, size):
return self.slice(x, begin, size)
def get_output(x, begin, size, enable_graph_kernel=False):
context.set_context(enable_graph_kernel=enable_graph_kernel)
net = Net()
output = net(x, begin, size)
return output
def test_slice():
in1 = np.array([[[1, -1, 1], [2, -2, 2]], [[3, -3, 3], [4, -4, 4]], [[5, -5, 5], [6, -6, 6]]]).astype(np.float32)
x1 = Tensor(in1)
begin1 = (0, 1, 0)
size1 = (2, 1, 3)
expect = get_output(x1, begin1, size1, False)
output = get_output(x1, begin1, size1, True)
assert np.allclose(expect.asnumpy(), output.asnumpy(), 0.0001, 0.0001)
@pytest.mark.level0
@pytest.mark.platform_x86_gpu_training
@pytest.mark.env_onecard
def test_slice_gpu():
context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
test_slice()