// `GradientTape::Watch`.) The op_id is simply a unique index assigned to each
// op executed under the tape. A separate map (`tensorflow::eager::OpTape`)
// maintains the map from `op_id` to a `OpTapeEntry` which stores the `op_type`,
// inputs and outputs and the gradient function These data structures combined
// allow us to trace the data dependencies between operations and hence compute
// gradients.
//

#include "tensorflow/core/platform/types.h"

namespace tensorflow {
namespace eager {

// Represents an entry in the tape.
template <typename BackwardFunction, typename TapeTensor>
struct OpTapeEntry {
  string op_type;
  std::vector<TapeTensor> output_tensor_info;
  std::vector<int64_t> input_tensor_id;

  // TODO(apassos) consider narrowing down this interface.
  BackwardFunction* backward_function;