Add sqrt, exp, round, log functions

fastdeploy/function/math.cc

@@ -0,0 +1,64 @@
+// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+//
+// 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.
+
+#include "fastdeploy/function/math.h"
+#include "fastdeploy/function/eigen.h"
+#include "fastdeploy/function/math_functor.h"
+
+namespace fastdeploy {
+namespace function {
+
+#define DEFINE_ACTIVATION_KERNEL(name, functor_class)                          \
+  template <typename T> void name##Kernel(const FDTensor& x, FDTensor* out) {  \
+    functor_class<T> functor;                                                  \
+    ActivationImpl<T, functor_class<T>>(x, out, functor);                      \
+  }
+
+template <typename T, typename Functor>
+void ActivationImpl(const FDTensor& X, FDTensor* Out, const Functor& functor) {
+  FDASSERT(Out != nullptr, "Output Out should not be nullptr");
+  auto x = EigenVector<T>::Flatten(X);
+  Out->Allocate(X.Shape(), X.Dtype());
+  auto out = EigenVector<T>::Flatten(*Out);
+  const auto& dev = *EigenDeviceWrapper::GetInstance()->GetDevice();
+  functor(dev, x, out);
+}
+
+DEFINE_ACTIVATION_KERNEL(Sqrt, SqrtFunctor)
+DEFINE_ACTIVATION_KERNEL(Log, LogFunctor)
+DEFINE_ACTIVATION_KERNEL(Round, RoundFunctor)
+DEFINE_ACTIVATION_KERNEL(Exp, ExpFunctor)
+
+void Sqrt(const FDTensor& x, FDTensor* out) {
+  FD_VISIT_FLOAT_TYPES(x.dtype, "SqrtKernel",
+                       ([&] { SqrtKernel<data_t>(x, out); }));
+}
+
+void Log(const FDTensor& x, FDTensor* out) {
+  FD_VISIT_FLOAT_TYPES(x.dtype, "LogKernel",
+                       ([&] { LogKernel<data_t>(x, out); }));
+}
+
+void Round(const FDTensor& x, FDTensor* out) {
+  FD_VISIT_FLOAT_TYPES(x.dtype, "RoundKernel",
+                       ([&] { RoundKernel<data_t>(x, out); }));
+}
+
+void Exp(const FDTensor& x, FDTensor* out) {
+  FD_VISIT_FLOAT_TYPES(x.dtype, "ExpKernel",
+                       ([&] { ExpKernel<data_t>(x, out); }));
+}
+
+}  // namespace function
+}  // namespace fastdeploy

fastdeploy/function/math.h

@@ -0,0 +1,47 @@
+// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+//
+// 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.
+
+#pragma once
+
+#include "fastdeploy/core/fd_tensor.h"
+
+namespace fastdeploy {
+namespace function {
+
+/** Calculates the sqrt of the given input Tensor, element-wise. Only for float type FDTensor
+    @param x The input tensor.
+    @param out The output tensor which stores the result.
+*/
+FASTDEPLOY_DECL void Sqrt(const FDTensor& x, FDTensor* out);
+
+/** Calculates the natural log of the given input Tensor, element-wise. Only for float type FDTensor
+    @param x The input tensor.
+    @param out The output tensor which stores the result.
+*/
+FASTDEPLOY_DECL void Log(const FDTensor& x, FDTensor* out);
+
+/** Rounds the values in the input to the nearest integer value, element-wise. Only for float type FDTensor
+    @param x The input tensor.
+    @param out The output tensor which stores the result.
+*/
+FASTDEPLOY_DECL void Round(const FDTensor& x, FDTensor* out);
+
+/** Computes exp of x element-wise with a natural number e as the base, element-wise. Only for float type FDTensor
+    @param x The input tensor.
+    @param out The output tensor which stores the result.
+*/
+FASTDEPLOY_DECL void Exp(const FDTensor& x, FDTensor* out);
+
+}  // namespace function
+}  // namespace fastdeploy

fastdeploy/function/math_functor.h

@@ -0,0 +1,56 @@
+// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+//
+// 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.
+
+#pragma once
+
+#include "fastdeploy/function/eigen.h"
+
+namespace fastdeploy {
+namespace function {
+
+// log(x) = natural logarithm of x
+template <typename T> struct LogFunctor {
+  template <typename Device, typename X, typename Out>
+  void operator()(Device d, X x, Out out) const {
+    out.device(d) = x.log();
+  }
+};
+
+// exp functor
+// exp(x) = e^x
+template <typename T> struct ExpFunctor {
+  template <typename Device, typename X, typename Out>
+  void operator()(Device d, X x, Out out) const {
+    out.device(d) = x.exp();
+  }
+};
+
+// round(x) = [x]
+template <typename T> struct RoundFunctor {
+  template <typename Device, typename X, typename Out>
+  void operator()(Device d, X x, Out out) const {
+    out.device(d) = x.round();
+  }
+};
+
+// sqrt(x) = x^(1/2)
+template <typename T> struct SqrtFunctor {
+  template <typename Device, typename X, typename Out>
+  void operator()(Device d, X x, Out out) const {
+    out.device(d) = x.sqrt();
+  }
+};
+
+}  // namespace function
+}  // namespace fastdeploy