// APIs for generically dealing with op attributes (e.g. when forwarding them
// through custom device implementations).
//
// TODO(allenl): Currently these are black boxes, but we should have some way to
// 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;

  // A sequence of thread wrappers, one per device, for executing operations in
  // parallel.
  //
  // Conceptually this is a thread pool with one thread per device. It requires
  // less synchronization than a thread pool would for this task, since Execute
  // acquires each thread in order (and so only one Execute will schedule
  // blocking collective operations at a time), and avoids some dynamic
  // allocation/scheduling.
  //

// least `max_values`.
//
// The elements of values will point to addresses in `storage` which must be at
// least `storage_size` bytes in length.  Ideally, max_values would be set to
// TF_AttrMetadata.list_size and `storage` would be at least
// TF_AttrMetadata.total_size, obtained from TF_OperationGetAttrMetadata(oper,
// attr_name).
//
// Fails if storage_size is too small to hold the requested number of strings.

    // can do its work.
    //
    // Rather than re-entering and delegating Accumulate like this, we could
    // instead allow ForwardAccumulator some control over the current tape set
    // (so it can deactivate itself and activate its GradientTape). Currently
    // that is managed by the language binding and would require relatively
    // messy callbacks.
    call_state_.top().backward_tape->RecordOperation(

  //
  // If false, a caller might implement pretty-printing by resolving and
  // iterating over the resulting tensor. This may still be viable if resolving
  // the handle loses information, but `SummarizeValue` would be more precise.
  virtual bool PreferCustomSummarizer() const { return false; }

  // Returns a string which summarizes the value of this TensorHandle, for
  // debugging. Does not include a shape or dtype.
  //

#include "tensorflow/c/experimental/filesystem/filesystem_interface.h"
#include "tensorflow/core/platform/file_system.h"

/// This file builds classes needed to hold a filesystem implementation in the
/// 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*`