// 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

 *
 * `use_function` indicates whether to use graph mode(true) or eager(false).
 *
 * `numerical_grad` is the pointer to the AbstractTensorHandle* which will
 * hold the numerical gradient data at the end of the function.
 */
Status CalcNumericalGrad(AbstractContext* ctx, Model forward,
                         absl::Span<AbstractTensorHandle* const> inputs,
                         int input_index, bool use_function,

// optimization pass. Nodes modified during optimization pass have to be
// invalidated, to prevent further incorrect optimizations based on wrong shape
// and data type properties.
typedef struct TF_GraphProperties TF_GraphProperties;

// Create GraphProperties. The item must outlive the properties.
TF_CAPI_EXPORT extern TF_GraphProperties* TF_NewGraphProperties(

TFE_TensorHandle* TestMatrixTensorHandle(TFE_Context* ctx);

// Return a tensor handle containing 2D matrix containing given data and
// dimensions
TFE_TensorHandle* TestMatrixTensorHandleWithInput(TFE_Context* ctx,
                                                  float data[], int64_t dims[],
                                                  int num_dims);

// Get a Matrix TensorHandle with given float values and dimensions

                                       TF_FileStatistics* stats,
                                       TF_Status* status);

// Creates or truncates the given filename and returns a handle to be used for
// appending data to the file. If status is TF_OK, *handle is updated and the
// caller is responsible for freeing it (see TF_CloseWritableFile).
TF_CAPI_EXPORT extern void TF_NewWritableFile(const char* filename,

        TF_NewTensor(
            datatype_enum, /*dims=*/nullptr, /*num_dims=*/0,
            device_value.release(), sizeof(DataType),
            [](void* data, size_t, void* arg) {
              delete reinterpret_cast<DataType*>(data);
            },
            nullptr),
        TF_DeleteTensor);
    // TODO(allenl): Here and when executing regular operations, we could hold

void Close(const TF_WritableFile* file, TF_Status* status);
}  // namespace tf_writable_file

namespace tf_read_only_memory_region {
void Cleanup(TF_ReadOnlyMemoryRegion* region);
const void* Data(const TF_ReadOnlyMemoryRegion* region);
uint64_t Length(const TF_ReadOnlyMemoryRegion* region);
}  // namespace tf_read_only_memory_region

namespace tf_gcs_filesystem {
typedef struct GcsFileStat {

    TF_Status* status) {
  TFE_CustomDevice device;
  void* device_info;
  tensorflow::parallel_device::AllocateParallelDevice(
      device_name, underlying_devices.data(), underlying_devices.size(),
      &device, &device_info);
  TFE_RegisterCustomDevice(context, device, device_name, device_info, status);
}

}  // namespace parallel_device
}  // namespace tensorflow

// --------------------------------------------------------------------------
// Used to return strings across the C API. The caller does not take ownership
// of the underlying data pointer and is not responsible for freeing it.
typedef struct TF_StringView {
  const char* data;
  size_t len;
} TF_StringView;

// --------------------------------------------------------------------------

// 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)