| /** |
| * Copyright (c) 2016-present, Facebook, Inc. |
| * |
| * 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 "caffe2/operators/math_ops.h" |
| #include "caffe2/utils/math.h" |
| |
| namespace caffe2 { |
| |
| struct SqrCPUFunctor { |
| template <typename T> |
| inline void |
| operator()(const int n, const T* x, T* y, CPUContext* device_context) { |
| math::Sqr<T, CPUContext>(n, x, y, device_context); |
| } |
| }; |
| |
| REGISTER_CPU_OPERATOR( |
| Sqr, |
| UnaryElementwiseOp<TensorTypes<float>, CPUContext, SqrCPUFunctor>); |
| |
| OPERATOR_SCHEMA(Sqr) |
| .NumInputs(1) |
| .NumOutputs(1) |
| .AllowInplace({{0, 0}}) |
| .IdenticalTypeAndShape() |
| .SetDoc("Square (x^2) the elements of the input") |
| .Input(0, "input", "Input tensor") |
| .Output(0, "output", "Squared elements of the input"); |
| |
| class GetSqrGradient : public GradientMakerBase { |
| using GradientMakerBase::GradientMakerBase; |
| vector<OperatorDef> GetGradientDefs() override { |
| Argument scale_arg; |
| scale_arg.set_name("scale"); |
| scale_arg.set_f(2.0); |
| return vector<OperatorDef>{CreateOperatorDef( |
| "Scale", |
| "", |
| std::vector<string>{GO(0)}, |
| std::vector<string>{GO(0)}, |
| std::vector<Argument>{scale_arg}), |
| CreateOperatorDef( |
| "Mul", |
| "", |
| std::vector<string>{GO(0), I(0)}, |
| std::vector<string>{GI(0)})}; |
| } |
| }; |
| REGISTER_GRADIENT(Sqr, GetSqrGradient); |
| |
| struct SignCPUFunctor { |
| template <typename T> |
| inline void |
| operator()(const int n, const T* x, T* y, CPUContext* device_context) { |
| for (int i = 0; i < n; ++i) { |
| y[i] = (-T(1) * (x[i] < 0)) + (x[i] > 0); |
| } |
| } |
| }; |
| |
| REGISTER_CPU_OPERATOR( |
| Sign, |
| UnaryElementwiseOp<TensorTypes<float>, CPUContext, SignCPUFunctor>); |
| |
| OPERATOR_SCHEMA(Sign) |
| .NumInputs(1) |
| .NumOutputs(1) |
| .SetDoc("Computes sign for each element of the input: -1, 0 or 1.") |
| .IdenticalTypeAndShape(); |
| SHOULD_NOT_DO_GRADIENT(Sign); |
| |
| REGISTER_CPU_OPERATOR( |
| Pow, |
| UnaryElementwiseWithArgsOp<TensorTypes<float>, CPUContext, PowFunctor>); |
| |
| OPERATOR_SCHEMA(Pow) |
| .NumInputs(1) |
| .NumOutputs(1) |
| .Arg("exponent", "The exponent of the power function.") |
| .AllowInplace({{0, 0}}) |
| .IdenticalTypeAndShape() |
| .SetDoc(R"DOC( |
| Pow takes input data (Tensor<T>) and an argument exponent, and |
| produces one output data (Tensor<T>) where the function `f(x) = x^exponent`, |
| is applied to the data tensor elementwise. |
| )DOC") |
| .Input(0, "X", "Input tensor of any shape") |
| .Output(0, "Y", "Output tensor (same size as X)"); |
| |
| class GetPowGradient : public GradientMakerBase { |
| using GradientMakerBase::GradientMakerBase; |
| vector<OperatorDef> GetGradientDefs() override { |
| ArgumentHelper arg_helper(def_); |
| float exponent = arg_helper.GetSingleArgument<float>("exponent", 0.0); |
| Argument scale_arg; |
| scale_arg.set_name("scale"); |
| scale_arg.set_f(exponent); |
| Argument pow_arg; |
| pow_arg.set_name("exponent"); |
| pow_arg.set_f(exponent - 1); |
| return vector<OperatorDef>{CreateOperatorDef( |
| "Pow", |
| "", |
| std::vector<string>{I(0)}, |
| std::vector<string>{GI(0)}, |
| std::vector<Argument>{pow_arg}), |
| CreateOperatorDef( |
| "Mul", |
| "", |
| std::vector<string>{GI(0), GO(0)}, |
| std::vector<string>{GI(0)}), |
| CreateOperatorDef( |
| "Scale", |
| "", |
| std::vector<string>{GI(0)}, |
| std::vector<string>{GI(0)}, |
| std::vector<Argument>{scale_arg})}; |
| } |
| virtual bool CopyArguments() const override { |
| return false; |
| } |
| }; |
| |
| REGISTER_GRADIENT(Pow, GetPowGradient); |
| |
| } // namespace caffe2 |