// shape is explicitly requested where possible.
  int (*num_dims)(void* data, TF_Status* status);

  // Computes the axis length at `dim_index`.
  int64_t (*dim)(void* data, int dim_index, TF_Status* status);

  void (*deallocator)(void* data);

  // Summarizes the value of this tensor. The caller takes ownership of the

// license that can be found in the LICENSE file.

#include <string.h>

#include "_cgo_export.h"

void
callback(void *f)
{
	// use some stack space
	volatile char data[64*1024];

	data[0] = 0;
	goCallback(f);
        data[sizeof(data)-1] = 0;
}

void
callGoFoo(void)
{
	extern void goFoo(void);
	goFoo();
}

void
IntoC(void)
{
	BackIntoGo();
}

void
Issue1560InC(void)

  return SetAttrShape(attr_name, shape.dim_sizes().data(), shape.dims());
}

inline Status AbstractOperation::SetAttrStringList(
    const char* attr_name, absl::Span<string const> values) {
  std::vector<const char*> raw_strs;
  std::vector<size_t> lengths;
  raw_strs.reserve(values.size());
  lengths.reserve(values.size());
  for (const auto& s : values) {
    raw_strs.emplace_back(s.data());
    lengths.emplace_back(s.size());

// Returns the number of elements in dimension `dim_index`.
// Tensor representation on device can be transposed from its representation
// on host. The data contained in dimension `dim_index` on device
// can correspond to the data contained in another dimension in on-host
// representation. The dimensions are indexed using the standard TensorFlow
// major-to-minor order (slowest varying dimension first),

///   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

      : region_(std::move(region)), ops_(ops) {}

  ~ModularReadOnlyMemoryRegion() override { ops_->cleanup(region_.get()); };

  const void* data() override { return ops_->data(region_.get()); }
  uint64 length() override { return ops_->length(region_.get()); }

 private:
  std::unique_ptr<TF_ReadOnlyMemoryRegion> region_;
  const TF_ReadOnlyMemoryRegionOps* ops_;  // not owned

  typedef void (*MemoryReleaser)(void* data, size_t len, void* arg);

  // Create a tensor instance from the given data buffer and description.
  // `memory_releaser` will be called on destruction, and it's responsible for
  // cleaning up the underlying buffer.
  virtual AbstractTensorInterface* CreateTensor(
      DataType dtype, const int64_t* dims, int num_dims, void* data, size_t len,

// 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.
//
// `ZerosLike` is not expected to be called and returns a nullptr. The creation

                    ForwardOperation*);

// Sets the attrs in the `ForwardOperation`.
Status SetAttrString(AbstractOperation*, const char* attr_name,
                     const char* data, size_t length, ForwardOperation*);
Status SetAttrInt(AbstractOperation*, const char* attr_name, int64_t value,
                  ForwardOperation*);
Status SetAttrFloat(AbstractOperation*, const char* attr_name, float value,

  // tensor are combined into a single entry.
  const TensorSliceReader::VarToShapeMap& GetVariableToShapeMap() const;

  // Returns a map from variable names to their data types.  Slices of a
  // partitioned tensor are combined into a single entry.
  const TensorSliceReader::VarToDataTypeMap& GetVariableToDataTypeMap() const;