// or removed during the graph transformation. This includes feed and fetch
// nodes, keep_ops, init_ops. Fills in `values` and `lengths`, each of which
// must point to an array of length at least `num_values`.
//
// The elements of values will point to addresses in `storage` which must be at
// least `storage_size` bytes in length.  `num_values` and `storage` can be
// obtained from TF_GetNodesToPreserveSize
//

// `proto` must point to an array of `proto_len` bytes representing a
// binary-serialized TensorShapeProto.
TF_CAPI_EXPORT extern void TF_SetAttrTensorShapeProto(
    TF_OperationDescription* desc, const char* attr_name, const void* proto,
    size_t proto_len, TF_Status* status);
// `protos` and `proto_lens` must point to arrays of length `num_shapes`.
// `protos[i]` must point to an array of `proto_lens[i]` bytes

                                                TF_Status* status);

// Execute the operation defined by 'op' and return handles to computed
// tensors in `retvals`.
//
// 'retvals' must point to a pre-allocated array of TFE_TensorHandle* and
// '*num_retvals' should be set to the size of this array. It is an error if
// the size of 'retvals' is less than the number of outputs. This call sets

///   1. Opaque plugin private data structures and wrappers for type safety;
///   2. Function tables for plugin functionality;
///   3. Versioning metadata;
///   4. Plugin registration API and the DSO entry point.

#ifdef __cplusplus
extern "C" {
#endif  // __cplusplus

/// SECTION 1. Opaque data structures to hold plugin specific data
/// ----------------------------------------------------------------------------
///

/// modular world. Once all TensorFlow filesystems are converted to use the
/// plugin based approach, this file will replace the one in core/platform and
/// the names will lose the `Modular` part. Until that point, the `Modular*`
/// classes here are experimental and subject to breaking changes.
/// For documentation on these methods, consult `core/platform/filesystem.h`.

namespace tensorflow {