caffe2/operators/clip_op.cc

/**
 * 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/clip_op.h"

namespace caffe2 {

template <>
bool ClipOp<float, CPUContext>::RunOnDevice() {
  auto& X = Input(0);
  auto* Y = Output(0);
  Y->ResizeLike(X);
  EigenVectorMap<float>(Y->mutable_data<float>(), Y->size()) =
      ConstEigenVectorMap<float>(X.data<float>(), X.size())
          .cwiseMax(min_)
          .cwiseMin(max_);
  return true;
}

template <>
bool ClipGradientOp<float, CPUContext>::RunOnDevice() {
  auto& Y = Input(0);
  auto& dY = Input(1);
  auto* dX = Output(0);
  CAFFE_ENFORCE_GT(Y.size(), 0);
  CAFFE_ENFORCE_EQ(dY.size(), Y.size());
  dX->ResizeLike(Y);
  const float* Ydata = Y.data<float>();
  const float* dYdata = dY.data<float>();
  float* dXdata = dX->mutable_data<float>();
  for (int i = 0; i < Y.size(); ++i) {
    dXdata[i] = dYdata[i] * (Ydata[i] > min_ && Ydata[i] < max_);
  }
  return true;
}

REGISTER_CPU_OPERATOR(Clip, ClipOp<float, CPUContext>);
REGISTER_CPU_OPERATOR(ClipGradient, ClipGradientOp<float, CPUContext>);

OPERATOR_SCHEMA(Clip)
    .NumInputs(1)
    .NumOutputs(1)
    .AllowInplace({{0, 0}})
    .IdenticalTypeAndShape()
    .SetDoc(R"DOC(
Clip operator limits the given input within an interval. The interval is
specified with arguments 'min' and 'max'. They default to
numeric_limits::lowest() and numeric_limits::max() respectively. The clipping
operation can be done in in-place fashion too, where the input and output blobs
are the same.
)DOC")
    .Arg("min", "Minimum value, under which element is replaced by min")
    .Arg("max", "Maximum value, above which element is replaced by max")
    .Input(
        0,
        "input",
        "Input tensor (Tensor<float>) containing elements to be"
        "clipped")
    .Input(
        1,
        "output",
        "Output tensor (Tensor<float>) containing clipped"
        "input elements");

OPERATOR_SCHEMA(ClipGradient).NumInputs(2).NumOutputs(1).AllowInplace({{1, 0}});

class GetClipGradient : public GradientMakerBase {
  using GradientMakerBase::GradientMakerBase;
  vector<OperatorDef> GetGradientDefs() override {
    return SingleGradientDef(
        "ClipGradient", "",
        vector<string>{O(0), GO(0)},
        vector<string>{GI(0)});
  }
};
REGISTER_GRADIENT(Clip, GetClipGradient);
}  // namespace caffe2