|  | 
 | #pragma once | 
 |  | 
 | #include "caffe2/core/context.h" | 
 | #include "caffe2/core/operator.h" | 
 |  | 
 | namespace caffe2 { | 
 |  | 
 | // RecordShapeOp records the shape of the input tensor to a vector of int. You | 
 | // mostly don't need this operator explicitly, and it is mostly used in the | 
 | // autodiff process. | 
 | template <class Context> | 
 | class ShapeOp : public Operator<Context> { | 
 |  public: | 
 |   USE_OPERATOR_CONTEXT_FUNCTIONS; | 
 |   ShapeOp(const OperatorDef& operator_def, Workspace* ws) | 
 |       : Operator<Context>(operator_def, ws), | 
 |         axes_(OperatorBase ::GetRepeatedArgument<int>("axes")) {} | 
 |  | 
 |   bool RunOnDevice() override { | 
 |     auto& data = Input(DATA); | 
 |  | 
 |     int numDims = data.dim(); | 
 |     int numAxes = axes_.size(); | 
 |     if (numAxes == 0) { | 
 |       auto* output = Output(0, {numDims}, at::dtype<int64_t>()); | 
 |       int64_t* output_data = output->template mutable_data<int64_t>(); | 
 |       context_.CopyBytesSameDevice( | 
 |           numDims * sizeof(int64_t), data.sizes().data(), output_data); | 
 |       return true; | 
 |     } | 
 |  | 
 |     auto* output = Output(0, {numAxes}, at::dtype<int64_t>()); | 
 |     auto src = reinterpret_cast<const char*>(data.sizes().data()); | 
 |     auto out = reinterpret_cast<char*>(output->template mutable_data<int64_t>()); | 
 |     for (int i = 0; i < numAxes; i++) { | 
 |       auto axis = axes_[i]; | 
 |       CAFFE_ENFORCE_LT(axis, numDims, "Axis out of range"); | 
 |       CAFFE_ENFORCE_GE(axis, 0, "Each axis should be non-negative"); | 
 |       context_.CopyBytesSameDevice( | 
 |           sizeof(int64_t), src + axis * sizeof(int64_t), out); | 
 |       out += sizeof(int64_t); | 
 |     } | 
 |     return true; | 
 |   } | 
 |  | 
 |   INPUT_TAGS(DATA); | 
 |  | 
 |  private: | 
 |   vector<int> axes_; | 
 | }; | 
 |  | 
 | } // namespace caffe2 |