qat.pipelines.waveform package
- class EchoExecutePipeline(config, model=None, loader=None, target_data=None, engine=None)
Bases:
UpdateablePipelineA pipeline that executes
ExecutablewithWaveformProgrampackages using theEchoEngine, which simply passes through the waveform buffers.An engine cannot be provided to the pipeline, as the EchoEngine is used directly.
Warning
It is intended for executing compiled programs, and is not capable of compilation. Please use an appropriate compilation pipeline to prepare programs for execution.
- Parameters:
config¶ (
PipelineConfig) – The pipeline configuration with the name of the pipeline, and any additional parameters that can be configured in the pipeline.model¶ (
Union[None,QuantumHardwareModel,PhysicalHardwareModel]) – The hardware model to feed into the pipeline. Defaults to None.loader¶ (
Optional[BaseModelLoader]) – The hardware loader used to load the hardware model which can be used to later refresh the hardware model. Defaults to None.target_data¶ (
Optional[TargetData]) – The data concerning the target device, defaults to Noneengine¶ (
Optional[NativeEngine]) – The engine to use for the pipeline, defaults to None.
- Raises:
ValueError – If neither model nor loader is provided.
- class EchoPipeline(config, model=None, loader=None, target_data=None, engine=None)
Bases:
UpdateablePipelineA pipeline that compiles programs using the
PydWaveformBackendand executes them using theEchoEngine.An engine cannot be provided to the pipeline, as the EchoEngine is used directly.
- Parameters:
config¶ (
PipelineConfig) – The pipeline configuration with the name of the pipeline, and any additional parameters that can be configured in the pipeline.model¶ (
Union[None,QuantumHardwareModel,PhysicalHardwareModel]) – The hardware model to feed into the pipeline. Defaults to None.loader¶ (
Optional[BaseModelLoader]) – The hardware loader used to load the hardware model which can be used to later refresh the hardware model. Defaults to None.target_data¶ (
Optional[TargetData]) – The data concerning the target device, defaults to Noneengine¶ (
Optional[NativeEngine]) – The engine to use for the pipeline, defaults to None.
- Raises:
ValueError – If neither model nor loader is provided.
- class PipelineConfig(**data)
Bases:
BaseModelBase class for configuring updateable pipelines. Subclasses of
UpdateablePipelineshould be paried with their own configuration class which specifies custom configuration parameters, and/or sets custom defaults.Create a new model by parsing and validating input data from keyword arguments.
Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.
self is explicitly positional-only to allow self as a field name.
- model_config: ClassVar[ConfigDict] = {}
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
-
name:
str
- class WaveformCompilePipeline(config, model=None, loader=None, target_data=None, engine=None)
Bases:
UpdateablePipelineA pipeline that compiles programs using the
PydWaveformBackend.Warning
This pipeline is for compilation purposes only and does not execute programs. Please select an appropriate execution pipeline if you wish to execute compiled programs.
- Parameters:
config¶ (
PipelineConfig) – The pipeline configuration with the name of the pipeline, and any additional parameters that can be configured in the pipeline.model¶ (
Union[None,QuantumHardwareModel,PhysicalHardwareModel]) – The hardware model to feed into the pipeline. Defaults to None.loader¶ (
Optional[BaseModelLoader]) – The hardware loader used to load the hardware model which can be used to later refresh the hardware model. Defaults to None.target_data¶ (
Optional[TargetData]) – The data concerning the target device, defaults to Noneengine¶ (
Optional[NativeEngine]) – The engine to use for the pipeline, defaults to None.
- Raises:
ValueError – If neither model nor loader is provided.