// inspect values. This would let people e.g. copy over most attributes and then
// modify some based on their values.

// A reference to an op's name -> attribute mapping
typedef struct TFE_OpAttrs TFE_OpAttrs;

// Fetch a reference to `op`'s attributes. The returned reference is only valid
// while `op` is alive.
TF_CAPI_EXPORT extern const TFE_OpAttrs* TFE_OpGetAttrs(const TFE_Op* op);

  // a nullptr if none is available.
  //
  // Returns a borrowed reference, i.e. does not run VSpace::MarkAsResult on its
  // return value. The caller should increment the reference count before
  // deleting the ForwardAccumulator or calling DeleteGradient if keeping a
  // persistent reference to a non-null result.
  Gradient* FetchJVP(int64_t tensor_id);

// If assume_valid_feeds is true, it can help infer shapes in the fanout of fed
// nodes. This may cause incorrectness in graph analyses, but is useful for
// simulation or scheduling.
// If aggressive_shape_inference is true, nodes are executed on the host to
// identify output values when possible and does other aggressive strategies.
// This may cause incorrectness in graph analyses, but is useful for simulation
// or scheduling.

TF_CAPI_EXPORT extern int TFE_OpGetFlatInputCount(const TFE_Op* op,
                                                  TF_Status* status);
// Returns a borrowed reference to one of `op`'s inputs. Use
// `TFE_TensorHandleCopySharingTensor` to make a new reference.
TF_CAPI_EXPORT extern TFE_TensorHandle* TFE_OpGetFlatInput(const TFE_Op* op,
                                                           int index,

// `shape_inference::InferenceContext` constructor. Note the following:
//   - The inputs of the `op` are not used for shape inference. So, it is
//     OK to not have the inputs properly set in `op`. See `input_tensors`
//     if you want shape inference to consider the input tensors of the
//     op for shape inference.
//   - The types need not be set in `input_shapes` as it is not used.