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https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-05 16:48:03 +08:00
Add sqrt, exp, round, log functions
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64
fastdeploy/function/math.cc
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64
fastdeploy/function/math.cc
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// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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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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#include "fastdeploy/function/math.h"
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#include "fastdeploy/function/eigen.h"
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#include "fastdeploy/function/math_functor.h"
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namespace fastdeploy {
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namespace function {
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#define DEFINE_ACTIVATION_KERNEL(name, functor_class) \
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template <typename T> void name##Kernel(const FDTensor& x, FDTensor* out) { \
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functor_class<T> functor; \
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ActivationImpl<T, functor_class<T>>(x, out, functor); \
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}
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template <typename T, typename Functor>
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void ActivationImpl(const FDTensor& X, FDTensor* Out, const Functor& functor) {
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FDASSERT(Out != nullptr, "Output Out should not be nullptr");
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auto x = EigenVector<T>::Flatten(X);
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Out->Allocate(X.Shape(), X.Dtype());
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auto out = EigenVector<T>::Flatten(*Out);
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const auto& dev = *EigenDeviceWrapper::GetInstance()->GetDevice();
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functor(dev, x, out);
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}
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DEFINE_ACTIVATION_KERNEL(Sqrt, SqrtFunctor)
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DEFINE_ACTIVATION_KERNEL(Log, LogFunctor)
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DEFINE_ACTIVATION_KERNEL(Round, RoundFunctor)
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DEFINE_ACTIVATION_KERNEL(Exp, ExpFunctor)
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void Sqrt(const FDTensor& x, FDTensor* out) {
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FD_VISIT_FLOAT_TYPES(x.dtype, "SqrtKernel",
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([&] { SqrtKernel<data_t>(x, out); }));
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}
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void Log(const FDTensor& x, FDTensor* out) {
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FD_VISIT_FLOAT_TYPES(x.dtype, "LogKernel",
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([&] { LogKernel<data_t>(x, out); }));
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}
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void Round(const FDTensor& x, FDTensor* out) {
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FD_VISIT_FLOAT_TYPES(x.dtype, "RoundKernel",
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([&] { RoundKernel<data_t>(x, out); }));
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}
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void Exp(const FDTensor& x, FDTensor* out) {
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FD_VISIT_FLOAT_TYPES(x.dtype, "ExpKernel",
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([&] { ExpKernel<data_t>(x, out); }));
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}
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} // namespace function
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} // namespace fastdeploy
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47
fastdeploy/function/math.h
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47
fastdeploy/function/math.h
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// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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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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#pragma once
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#include "fastdeploy/core/fd_tensor.h"
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namespace fastdeploy {
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namespace function {
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/** Calculates the sqrt of the given input Tensor, element-wise. Only for float type FDTensor
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@param x The input tensor.
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@param out The output tensor which stores the result.
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*/
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FASTDEPLOY_DECL void Sqrt(const FDTensor& x, FDTensor* out);
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/** Calculates the natural log of the given input Tensor, element-wise. Only for float type FDTensor
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@param x The input tensor.
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@param out The output tensor which stores the result.
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*/
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FASTDEPLOY_DECL void Log(const FDTensor& x, FDTensor* out);
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/** Rounds the values in the input to the nearest integer value, element-wise. Only for float type FDTensor
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@param x The input tensor.
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@param out The output tensor which stores the result.
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*/
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FASTDEPLOY_DECL void Round(const FDTensor& x, FDTensor* out);
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/** Computes exp of x element-wise with a natural number e as the base, element-wise. Only for float type FDTensor
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@param x The input tensor.
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@param out The output tensor which stores the result.
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*/
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FASTDEPLOY_DECL void Exp(const FDTensor& x, FDTensor* out);
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} // namespace function
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} // namespace fastdeploy
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56
fastdeploy/function/math_functor.h
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56
fastdeploy/function/math_functor.h
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// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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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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#pragma once
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#include "fastdeploy/function/eigen.h"
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namespace fastdeploy {
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namespace function {
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// log(x) = natural logarithm of x
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template <typename T> struct LogFunctor {
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template <typename Device, typename X, typename Out>
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void operator()(Device d, X x, Out out) const {
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out.device(d) = x.log();
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}
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};
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// exp functor
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// exp(x) = e^x
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template <typename T> struct ExpFunctor {
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template <typename Device, typename X, typename Out>
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void operator()(Device d, X x, Out out) const {
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out.device(d) = x.exp();
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}
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};
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// round(x) = [x]
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template <typename T> struct RoundFunctor {
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template <typename Device, typename X, typename Out>
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void operator()(Device d, X x, Out out) const {
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out.device(d) = x.round();
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}
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};
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// sqrt(x) = x^(1/2)
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template <typename T> struct SqrtFunctor {
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template <typename Device, typename X, typename Out>
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void operator()(Device d, X x, Out out) const {
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out.device(d) = x.sqrt();
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}
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};
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} // namespace function
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} // namespace fastdeploy
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87
tests/function/test_math.cc
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87
tests/function/test_math.cc
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// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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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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#include "fastdeploy/core/fd_tensor.h"
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#include "fastdeploy/function/math.h"
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#include "glog/logging.h"
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#include "gtest_utils.h"
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#include "gtest/gtest.h"
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#include <array>
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#include <vector>
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namespace fastdeploy {
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namespace function {
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std::vector<float> CreateTestData() {
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// Shape: [2, 3, 4]
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std::vector<float> x_data = {
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0.8428625, 0.6461913, 0.13740455, 0.11430702, 0.659926, 0.535816,
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0.7429162, 0.8456049, 0.21228176, 0.29970083, 0.8621713, 0.40894133,
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0.12684688, 0.1566195, 0.42884097, 0.8476526, 0.2458633, 0.669046,
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0.87888306, 0.6762589, 0.666453, 0.32523027, 0.4139388, 0.8341406};
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return x_data;
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}
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TEST(fastdeploy, exp_sqrt_round_log) {
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CheckShape check_shape;
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CheckData check_data;
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FDTensor x, y;
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auto test_data = CreateTestData();
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x.SetExternalData({2, 3, 4}, FDDataType::FP32, test_data.data());
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// Test Sqrt function
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Sqrt(x, &y);
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std::vector<float> sqrt_result = {
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0.918075, 0.80386, 0.370681, 0.338093, 0.812358, 0.731995,
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0.861926, 0.919568, 0.46074, 0.547449, 0.928532, 0.639485,
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0.356156, 0.395752, 0.654859, 0.920681, 0.495846, 0.817952,
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0.937488, 0.82235, 0.816366, 0.57029, 0.643381, 0.913313};
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check_shape(y.shape, {2, 3, 4});
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check_data(reinterpret_cast<const float*>(y.Data()), sqrt_result.data(),
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sqrt_result.size());
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// Test Exp function
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Exp(x, &y);
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std::vector<float> exp_result = {
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2.323007, 1.908259, 1.147292, 1.121096, 1.934649, 1.708842,
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2.102057, 2.329386, 1.236496, 1.349455, 2.368297, 1.505223,
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1.135243, 1.169551, 1.535477, 2.334161, 1.278725, 1.952374,
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2.408208, 1.966507, 1.947318, 1.384349, 1.512764, 2.302834};
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check_shape(y.shape, {2, 3, 4});
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check_data(reinterpret_cast<const float*>(y.Data()), exp_result.data(),
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exp_result.size());
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// Test Round function
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Round(x, &y);
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std::vector<float> round_result = {1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 1.0, 1.0,
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0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0,
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0.0, 1.0, 1.0, 1.0, 1.0, 0.0, 0.0, 1.0};
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check_shape(y.shape, {2, 3, 4});
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check_data(reinterpret_cast<const float*>(y.Data()), round_result.data(),
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round_result.size());
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// Test Log function
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Log(x, &y);
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std::vector<float> log_result = {
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-0.170951, -0.43666, -1.984826, -2.168867, -0.415628, -0.623964,
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-0.297172, -0.167703, -1.549841, -1.204971, -0.148301, -0.894184,
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-2.064775, -1.853936, -0.846669, -0.165284, -1.40298, -0.401902,
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-0.129103, -0.391179, -0.405786, -1.123222, -0.882037, -0.181353};
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check_shape(y.shape, {2, 3, 4});
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check_data(reinterpret_cast<const float*>(y.Data()), log_result.data(),
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log_result.size());
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}
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} // namespace function
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} // namespace fastdeploy
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