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64 lines
2.2 KiB
64 lines
2.2 KiB
# Copyright 2019 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ============================================================================
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import numpy as np
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import pytest
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import mindspore.context as context
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import mindspore.nn as nn
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from mindspore import Tensor
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from mindspore.ops import operations as P
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class NetConv2d(nn.Cell):
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def __init__(self):
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super(NetConv2d, self).__init__()
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out_channel = 2
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kernel_size = 1
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self.conv = P.Conv2D(out_channel,
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kernel_size,
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mode=1,
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pad_mode="valid",
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pad=0,
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stride=1,
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dilation=1,
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group=1)
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def construct(self, x, w):
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return self.conv(x, w)
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@pytest.mark.level0
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_conv2d():
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x = Tensor(np.arange(1 * 3 * 3 * 3).reshape(1, 3, 3, 3).astype(np.float32))
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w = Tensor(np.arange(2 * 3 * 1 * 1).reshape(2, 3, 1, 1).astype(np.float32))
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expect = np.array([[[[45, 48, 51],
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[54, 57, 60],
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[63, 66, 69]],
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[[126, 138, 150],
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[162, 174, 186],
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[198, 210, 222]]]]).astype(np.float32)
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context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU", max_device_memory="0.2GB")
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conv2d = NetConv2d()
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output = conv2d(x, w)
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assert (output.asnumpy() == expect).all()
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context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
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conv2d = NetConv2d()
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output = conv2d(x, w)
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assert (output.asnumpy() == expect).all()
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