limitations under the License.
==============================================================================*/

// MakeCleanup(f) returns an RAII cleanup object that calls 'f' in its
// destructor. The easiest way to use MakeCleanup is with a lambda argument,
// capturing the return value in an 'auto' local variable. Most users will not
// need more sophisticated syntax than that.
//
// Example:

  mode_t open_mode = mode & (S_IRWXU | S_IRWXG | S_IRWXO);

  // O_WRONLY | O_CREAT | O_TRUNC:
  //   Open file for write and if file does not exist, create the file.
  //   If file exists, truncate its size to 0.
  int dst_fd = open(dst, O_WRONLY | O_CREAT | O_TRUNC, open_mode);
  if (dst_fd < 0) {
    close(src_fd);
    return -1;
  }

  // Both files have been opened, do the transfer.

-  return dynamic_addr - static_addr;
+    _DYNAMIC sysmbol is used here as its link-time address stored in
+    the special unrelocated first GOT entry.  */
+
+    extern ElfW(Dyn) _DYNAMIC[] attribute_hidden;
+    return (ElfW(Addr)) &_DYNAMIC - elf_machine_dynamic ();
 }
 
 /* Set up the loaded object described by L so its unrelocated PLT

The Code of Conduct also applies within project spaces and in public spaces whenever an individual is representing TensorFlow or its community. Examples of representing a project or community include using an official project e-mail address, posting via an official social media account, or acting as an appointed or de facto representative at an online or offline event. 

==============================================================================*/
#ifndef TENSORFLOW_C_EAGER_C_API_REMOTE_TEST_UTIL_H_
#define TENSORFLOW_C_EAGER_C_API_REMOTE_TEST_UTIL_H_

// Run a function containing a MatMul op and check its output.
// If heavy_load_on_streaming_rpc is true, send some rpc requests before the one
// which creates a remote input, to simulate a scenario that the remote input
// is not ready when we start running an op or a function.

// Deletes `debug_info`.
TF_CAPI_EXPORT extern void TFE_DeleteTensorDebugInfo(
    TFE_TensorDebugInfo* debug_info);

// Returns the number of dimensions used to represent the tensor on its device.
// The number of dimensions used to represent the tensor on device can be
// different from the number returned by TFE_TensorHandleNumDims.
// The return value was current at the time of TFE_TensorDebugInfo creation.

[requirements_updater](https://github.com/tensorflow/tensorflow/tree/master/ci/official/requirements_updater)
tool using the path to this wheel file.

### Hermetic Python

For details about hermetic Python and setting its toolchain version, see
[requirements updater readme](https://github.com/tensorflow/tensorflow/blob/master/ci/official/requirements_updater/README.md)

### Prerequisites for Local Testing

  EXPECT_EQ(calls, 3);
  // Advance the fake timestamp so that "a" becomes stale via its first block.
  env->SetNowSeconds(now + 2);
  // The pruning thread periodically compares env->NowSeconds() with the oldest
  // block's timestamp to see if it should evict any files. At the current fake
  // timestamp of `now` + 2, file "a" is stale because its first block is stale,
  // but file "b" is not stale yet. Thus, once the pruning thread wakes up (in

      memcpy(&buffer[total_bytes_transferred], &*begin, bytes_to_copy);
      total_bytes_transferred += bytes_to_copy;
    }
    if (data.size() < block_size_) {
      // The block was a partial block and thus signals EOF at its upper bound.
      break;
    }
  }
  TF_SetStatus(status, TF_OK, "");
  return total_bytes_transferred;
}

bool RamFileBlockCache::ValidateAndUpdateFileSignature(

// targets (not all since targets which have outputs in the tape will not have
// gradients available initially).
//
// Then we repeatedly pop an entry from the stack, run its backprop, and update
// the gradients of its inputs. Once we have computed all gradients for a single
// input we can mark this input as done, and this can trigger adding an entry to
// the stack if all outputs of that entry are now done.
//