Runtime

class tensorrt_rtx.Runtime(self: tensorrt_rtx.tensorrt_rtx.Runtime, logger: tensorrt_rtx.tensorrt_rtx.ILogger)

Allows a serialized ICudaEngine to be deserialized.

Variables:

  • error_recorder – IErrorRecorder Application-implemented error reporting interface for TensorRT objects.

  • gpu_allocator – IGpuAllocator The GPU allocator to be used by the Runtime . All GPU memory acquired will use this allocator. If set to None, the default allocator will be used (Default: cudaMalloc/cudaFree).

  • DLA_core – int The DLA core that the engine executes on. Must be between 0 and N-1 where N is the number of available DLA cores.

  • num_DLA_cores – int The number of DLA engines available to this builder.

  • logger – ILogger The logger provided when creating the refitter.

  • max_threads – int The maximum thread that can be used by the Runtime.

  • temporary_directory – str The temporary directory to use when loading executable code for engines. If set to None (the default), TensorRT will attempt to find a suitable directory for use using platform-specific heuristics: - On UNIX/Linux platforms, TensorRT will first try the TMPDIR environment variable, then fall back to /tmp - On Windows, TensorRT will try the TEMP environment variable.

  • tempfile_control_flags – int Flags which control whether TensorRT is allowed to create in-memory or temporary files. See TempfileControlFlag for details.

  • engine_host_code_allowed – bool Whether this runtime is allowed to deserialize engines that contain host executable code (Default: False).

Parameters:

logger – The logger to use.

__del__(self: tensorrt_rtx.tensorrt_rtx.Runtime) → None
__exit__(exc_type, exc_value, traceback)

Context managers are deprecated and have no effect. Objects are automatically freed when the reference count reaches 0.

__init__(self: tensorrt_rtx.tensorrt_rtx.Runtime, logger: tensorrt_rtx.tensorrt_rtx.ILogger) → None
Parameters:

logger – The logger to use.

deserialize_cuda_engine(*args, **kwargs)

Overloaded function.

  1. deserialize_cuda_engine(self: tensorrt_rtx.tensorrt_rtx.Runtime, serialized_engine: buffer) -> tensorrt_rtx.tensorrt_rtx.ICudaEngine

    Deserialize an ICudaEngine from host memory.

    arg serialized_engine:

    The buffer that holds the serialized ICudaEngine.

    returns:

    The ICudaEngine, or None if it could not be deserialized.

  2. deserialize_cuda_engine(self: tensorrt_rtx.tensorrt_rtx.Runtime, stream_reader_v2: tensorrt_rtx.tensorrt_rtx.IStreamReaderV2) -> tensorrt_rtx.tensorrt_rtx.ICudaEngine

    Deserialize an ICudaEngine from a stream reader v2.

    arg stream_reader:

    The PyStreamReaderV2 that will read the serialized ICudaEngine. This enables deserialization from a file directly, with possible benefits to performance.

    returns:

    The ICudaEngine, or None if it could not be deserialized.

get_plugin_registry(self: tensorrt_rtx.tensorrt_rtx.Runtime) → tensorrt_rtx.tensorrt_rtx.IPluginRegistry

Get the local plugin registry that can be used by the runtime.

Returns:

The local plugin registry that can be used by the runtime.

load_runtime(self: tensorrt_rtx.tensorrt_rtx.Runtime, path: str) → tensorrt_rtx.tensorrt_rtx.Runtime

Load IRuntime from the file.

This method loads a runtime library from a shared library file. The runtime can then be used to execute a plan file built with BuilderFlag.VERSION_COMPATIBLE and BuilderFlag.EXCLUDE_LEAN_RUNTIME both set and built with the same version of TensorRT as the loaded runtime library.

Variables:

path – Path to the runtime lean library.

Returns:

The IRuntime, or None if it could not be loaded.