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// Tencent is pleased to support the open source community by making ncnn available.
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// Copyright (C) 2020 THL A29 Limited, a Tencent company. All rights reserved.
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// Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
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// in compliance with the License. You may obtain a copy of the License at
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// https://opensource.org/licenses/BSD-3-Clause
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// Unless required by applicable law or agreed to in writing, software distributed
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// under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
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// CONDITIONS OF ANY KIND, either express or implied. See the License for the
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// specific language governing permissions and limitations under the License.
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static int test_instancenorm(const ncnn::Mat& a, float eps, int affine)
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pd.set(0, affine ? channels : 0);
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std::vector<ncnn::Mat> weights(2);
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weights[0] = RandomMat(channels);
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weights[1] = RandomMat(channels);
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int ret = test_layer("InstanceNorm", pd, weights, a);
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fprintf(stderr, "test_instancenorm failed a.dims=%d a=(%d %d %d) eps=%f affine=%d\n", a.dims, a.w, a.h, a.c, eps, affine);
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static int test_instancenorm_0()
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|| test_instancenorm(RandomMat(6, 4, 2), 0.01f, 0)
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|| test_instancenorm(RandomMat(3, 3, 12), 0.002f, 0)
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|| test_instancenorm(RandomMat(5, 7, 16), 0.02f, 0)
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|| test_instancenorm(RandomMat(6, 4, 2), 0.01f, 1)
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|| test_instancenorm(RandomMat(3, 3, 12), 0.002f, 1)
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|| test_instancenorm(RandomMat(5, 7, 16), 0.02f, 1);
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|| test_instancenorm_0();