namespace tensorflow {
namespace filesystem_registration {

// Implementation for filesystem registration
//
// Don't call this directly. Instead call `RegisterFilesystemPlugin`.
// Exposed only for static registration of local filesystems.
Status RegisterFilesystemPluginImpl(const TF_FilesystemPluginInfo* info);

}  // namespace filesystem_registration
}  // namespace tensorflow

"""Import API packages test.

This is a Python test that verifies whether API v2 packages can be imported
from the current build or not.

It uses the `_api/v2/api_packages.txt` file from the local wheel file.
The `_api/v2/api_packages.txt` file is created during the process of generating
TensorFlow API v2 init files and is stored in the wheel file after the build.

See README.md file for "how to run" instruction.
"""

#include "tensorflow/c/tf_file_statistics.h"
#include "tensorflow/c/tf_status.h"

// Implementation of a filesystem for POSIX environments.
// This filesystem will support `file://` and empty (local) URI schemes.

static void* plugin_memory_allocate(size_t size) { return calloc(1, size); }
static void plugin_memory_free(void* ptr) { free(ptr); }

// SECTION 1. Implementation for `TF_RandomAccessFile`

#       export TF_ANY_SCRIPT=ci/official/wheel.sh
#       ./any.sh
#
# 3. DO THE SAME WITH A LOCAL CACHE OR RBE:
#       export TF_ANY_EXTRA_ENV=ci/official/envs/public_cache,ci/official/envs/disk_cache
#       ...
#       ./any.sh
#     or
#       export TF_ANY_EXTRA_ENV=ci/official/envs/local_rbe
#       ./any.sh
#       ...
set -euxo pipefail
cd "$(dirname "$0")/../../"  # tensorflow/

// order, and type) the op declaration.  For example, the "Concat" op
// has registration:
//   REGISTER_OP("Concat")
//       .Input("concat_dim: int32")
//       .Input("values: N * T")
//       .Output("output: T")
//       .Attr("N: int >= 2")
//       .Attr("T: type");
// that defines two inputs, "concat_dim" and "values" (in that order).

    console.log(pr_resp);
    throw `PR:{pr_number} needs to be valid and closed (merged)`;
  }
  const pr_title = pr_resp.data.title;
  // Assign to PR owner and reviewers
  const assignees = pr_resp.data.assignees.concat(pr_resp.data.requested_reviewers);
  let assignee_logins = assignees.map(x => x.login);
  assignee_logins.push(pr_resp.data.user.login);
  console.log(assignee_logins);
  // Create an new GH Issue and reference the Original PR

      return underlying_devices_;
    }
  }
  std::vector<std::string> local_names;
  local_names.reserve(underlying_devices_.size());
  for (const DeviceNameUtils::ParsedName& parsed_component :
       parsed_components) {
    local_names.push_back(
        absl::StrCat(parsed_component.type, ":", parsed_component.id));
  }
  return local_names;
}

std::unique_ptr<ParallelTensor> ParallelTensor::FromTensorHandles(

  // Pack 3 variable handles into one TFE_TensorHandle.
  // When remote is false, function device is placed on task0. Handle types are
  // REMOTE, REMOTE, LOCAL on task0. When remote is true, function device is
  // placed on task1, Handle types are LOCAL, REMOTE, LOCAL on task1.
  int num_replicas = 3;
  std::vector<TFE_TensorHandle*> handles = {h0, h1, h2};
  TFE_TensorHandle* packed_handle =

// filesystem to indicate that the content has been persisted.
TF_CAPI_EXPORT extern void TF_SyncWritableFile(TF_WritableFileHandle* handle,
                                               TF_Status* status);

// Flush local buffers to the filesystem. If the process terminates after a
// successful flush, the contents may still be persisted, since the underlying
// filesystem may eventually flush the contents.  If the OS or machine crashes

  // A cancellation manager to use if the caller does not provide one. When ops
  // are executed asynchronously this must outlive the queued op, so it can't be
  // function-local to Execute.
  mutable std::unique_ptr<CancellationManager> default_cancellation_manager_;
};

// Contains a tuple of tensors, one on each of the `underlying_devices_` of the
// ParallelDevice.
class ParallelTensor {