blob: 44e98011ddd2a86776cf9ef8feda87a6773b5cc1 [file] [log] [blame]
#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);
auto* output = Output(0);
int numDims = data.ndim();
int numAxes = axes_.size();
if (numAxes == 0) {
output->Resize(numDims);
int64_t* output_data = output->template mutable_data<int64_t>();
context_.CopyBytesSameDevice(
numDims * sizeof(int64_t), data.sizes().data(), output_data);
return true;
}
output->Resize(numAxes);
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