Class TensorSlice

tensorflow/core/framework/tensor_slice.h:34–202

// tensor.

class TensorSlice {
 public:
  // Construct a tensor slice: you have a number of ways:
  // -- creating an empty slice
  // -- from just a dimension (in this case it will create a full slice)
  // -- from an array of pairs of integers.
  // -- from a TensorSliceProto protocol buffer
  // -- from a string format of "start,length:start,length..." where each
  //    "start,length" pair represents the slice on one dimension. We allow a
  //    special "-" that means "everything for this dimension". One such example
  //    is:  0,10:-:14,1:-:-
  TensorSlice() {}
  explicit TensorSlice(int dim);
  explicit TensorSlice(const TensorSliceProto& proto);
  explicit TensorSlice(std::initializer_list<std::pair<int64, int64>> extents);

  // This factory methods should be used instead of the constructor that takes a
  // `TensorSliceProto` if calling code cannot validate that the sizes specify a
  // valid `TensorSlice`.
  static Status BuildTensorSlice(const TensorSliceProto& proto,
                                 TensorSlice* output);

  static Status Parse(const string& str, TensorSlice* output);
  static TensorSlice ParseOrDie(const string& str) {
    TensorSlice ret;
    Status s = Parse(str, &ret);
    if (!s.ok()) {
      LOG(FATAL) << "Could not parse TensorSlice";
    }
    return ret;
  }

  void Clear();

  // Accessors
  int dims() const { return starts_.size(); }

  int64 start(int d) const {
    DCHECK_GE(d, 0);
    DCHECK_LT(d, dims());
    return starts_[d];
  }

  int64 length(int d) const {
    DCHECK_GE(d, 0);
    DCHECK_LT(d, dims());
    return lengths_[d];
  }

  int64 end(int d) const {
    DCHECK_GE(d, 0);
    DCHECK_LT(d, dims());
    return start(d) + length(d);
  }

  void set_start(int d, int64 x) {
    DCHECK_GE(d, 0);
    DCHECK_LT(d, dims());