// the result will be used as a constraint for device placement. See the
  // documentation for DeviceName for more details.
  //
  // The value will override the previous value - that is, no "merging" of
  // existing and given constraints will be performed.
  virtual Status SetDeviceName(const char* name) = 0;

  virtual Status AddInput(AbstractTensorHandle* input) = 0;

# limitations under the License.
# ==============================================================================
# This script uploads all staged artifacts from all previous builds in the same
# job chain to GCS and PyPI.
source "${BASH_SOURCE%/*}/utilities/setup.sh"

# Update the version numbers for Nightly only, then fetch the version numbers

                f'{"=" * 140}')
        break
      k -= 1

    # A low-effort attempt to find the bazel command that triggered the
    # invocation.
    bazel_comm_min_line_i = (previous_end_line if previous_end_line is not None
                             else 0)
    while k > bazel_comm_min_line_i:
      backtrack_line = log_lines[k]
      # Don't attempt to parse multi-line commands broken up by backslashes

                    const TFE_OpAttrs* attributes, int expected_max_outputs,
                    CancellationManager& cancellation_manager,
                    absl::optional<int64_t> step_id = absl::nullopt);
  // Block until the previous `StartExecute` operation has executed. Forwards
  // the status from `TFE_Execute` and returns outputs if the status is OK.
  std::vector<TensorHandlePtr> Join(TF_Status* status);

                                                 TF_Status* status);

// \brief Get a pointer to a symbol from a dynamic library.
//
// "handle" should be a pointer returned from a previous call to
// TF_LoadLibraryFromEnv. On success, place OK in status and return a pointer to
// the located symbol. Otherwise returns nullptr and set error status.
TF_CAPI_EXPORT extern void* TF_GetSymbolFromLibrary(void* handle,

                    int expected_max_outputs,
                    CancellationManager& cancellation_manager,
                    std::optional<int64_t> step_id = std::nullopt) const;

  // Blocks until the previous `StartExecute` has run `TFE_Execute` on each
  // device. If is_async=false (constructor argument) this means the ops have
  // run and have results. If is_async=true it means that all of the

within a machine across multiple computational devices, including multicore CPUs, general purpose GPUs, and custom-designed ASICs known as Tensor Processing Units (TPUs). This architecture gives flexibility to the application developer, whereas in previous “parameter server” designs the management of shared state is built into the system, TensorFlow enables developers to experiment with novel optimizations and training algorithms. TensorFlow supports a variety of applications, with a focus on training...

      : max_age_(max_age),
        max_entries_(max_entries),
        timer_seconds_(timer_seconds) {}

  /// Insert `value` with key `key`. This will replace any previous entry with
  /// the same key.
  void Insert(const std::string& key, const T& value) {
    if (max_age_ == 0) {
      return;
    }
    absl::MutexLock lock(&mu_);
    InsertLocked(key, value);
  }

//
// The provided ApiDefs will be merged with existing ones in the map, with
// precedence given to the newly added version in case of conflicts with
// previous calls to TF_ApiDefMapPut.
TF_CAPI_EXPORT extern void TF_ApiDefMapPut(TF_ApiDefMap* api_def_map,
                                           const char* text, size_t text_len,

  // available to be called/referenced by its name in this context.
  virtual Status RegisterFunction(AbstractFunction*) = 0;
  // Remove a function. 'func' argument is the name of a previously added
  // FunctionDef. The name is in fdef.signature.name.
  virtual Status RemoveFunction(const string& func) = 0;

 private:
  const AbstractContextKind kind_;
};

namespace internal {