Class AsyncConsoleLogger

• Defined in File async_console_logger.hpp

Base Type

• public holoscan::AsyncDataLoggerResource (Class AsyncDataLoggerResource)

class AsyncConsoleLogger : public holoscan::AsyncDataLoggerResource

Async version of BasicConsoleLogger using dual-queue architecture.

This class provides the same console logging functionality as BasicConsoleLogger but uses asynchronous processing with separate queues for metadata and data content. This reduces the impact on the main execution thread while maintaining the same output format and functionality.

==Parameters==

All parameters from AsyncDataLoggerResource plus:

• serializer : std::shared_ptr<SimpleTextSerializer>

  • Text serialization resource (optional). A SimpleTextSerializer initialized with default parameters will be automatically added if none is provided.

Inherited parameters from DataLoggerResource:

• log_inputs: bool (optional, default: true)

• log_outputs: bool (optional, default: true)

• log_metadata: bool (optional, default: true)

• log_tensor_data_content: bool (optional, default: false)

• allowlist_patterns: std::vector<std::string> (optional, default: empty)

• denylist_patterns: std::vector<std::string> (optional, default: empty)

See the DataLoggerResource documentation for details on these inherited parameters.

AsyncDataLoggerResource specific parameters:

• max_queue_size: size_t (optional, default: 50000)

  • Maximum number of entries in the data queue. When enable_large_data_queue is `true, The data queue handles tensor headers without full tensor content. Otherwise tensor data content will also be in this queue. In both cases, whether tensor data content is logged at all is controlled by log_tensor_data_content. Default is 50000.

• worker_sleep_time: nanoseconds (optional, default: 50000ns = 50μs)

  • Sleep duration in nanoseconds when the data queue is empty. Lower values reduce latency but increase CPU usage. Default is 50000 (50μs).

• queue_policy: AsyncQueuePolicy (optional, default: AsyncQueuePolicy::kReject)

  • The queue_policy parameter controls how queue overflow is handled. Can be AsyncQueuePolicy::kReject (default) to reject new items with a warning, or kRaise to throw an exception. In the YAML configuration for this parameter, you can use string values “reject” or “raise” (case-insensitive).

• large_data_max_queue_size: size_t (optional, default: 1000)

  • Maximum number of entries in the large data queue. Default is 1000.

• large_data_worker_sleep_time: nanoseconds (optional, default: 50000ns = 50μs)

  • Sleep duration in nanoseconds when the large data queue is empty. Lower values reduce latency but increase CPU usage. Default is 50000 (50μs).

• large_data_queue_policy: bool (optional, default: AsyncQueuePolicy::kReject)

  • The large_data_queue_policy parameter controls how queue overflow is handled for the large data queue. Can be AsyncQueuePolicy::kReject (default) to reject new items with a warning, or kRaise to throw an exception. In the YAML configuration for this parameter, you can use string values “reject” or “raise” (case-insensitive).

• enable_large_data_queue: bool (optional, default: true);

  • Whether to enable the large data queue and worker thread for processing full tensor content. Default is True.*

Public Functions

HOLOSCAN_RESOURCE_FORWARD_ARGS_SUPER (AsyncConsoleLogger, AsyncDataLoggerResource) AsyncConsoleLogger()=default

virtual void setup(ComponentSpec &spec) override

Define the resource specification.

Parameters

spec – The reference to the component specification.

virtual void initialize() override

Initialize the component.

This method is called only once when the component is created for the first time, and use of light-weight initialization.

virtual bool log_backend_specific(const std::any &data, const std::string &unique_id, int64_t acquisition_timestamp = -1, const std::shared_ptr<MetadataDictionary> &metadata = nullptr, IOSpec::IOType io_type = IOSpec::IOType::kOutput) override

Logs backend-specific data types.

This method is called for logging backend-specific data types (intended for use with backends that have separate emit/receive codepaths for backend-specific types). The data parameter is kept as std::any here to avoid making the base interface specific to a particular backend, but a backend-specific concrete implementation should be provided as needed via run-time type checking.

A concrete example of a backend-specific type is the GXF Entity type which is a heterogeneous collection of components. An implementation of this method for GXF entities is provided in the concrete implementation of the GXFConsoleLogger.

The unique_id for the message will have the form:

• operator_name.port_name

• operator_name.port_name:index (for multi-receivers with N:1 connection)

For distributed applications, the fragment name will also appear in the unique id:

• fragment_name.operator_name.port_name

• fragment_name.operator_name.port_name:index

Parameters

• data – The backend-specific data to log, passed as std::any.

• unique_id – A unique identifier for the message.

• acquisition_timestamp – Timestamp when the data was acquired (-1 if unknown).

• metadata – Associated metadata dictionary for the message.

• io_type – The type of I/O port (kInput or kOutput).

Returns

true if logging was successful, false if backend-specific logging is not supported.