`diart.blocks.base`#

Module Contents#

Classes#

`HyperParameter`	Represents a pipeline hyper-parameter that can be tuned by diart
`PipelineConfig`	Configuration containing the required
`Pipeline`	Represents a streaming audio pipeline

Attributes#

`TauActive`
`RhoUpdate`
`DeltaNew`

class diart.blocks.base.HyperParameter#

Represents a pipeline hyper-parameter that can be tuned by diart

name: Text#: Name of the hyper-parameter (e.g. tau_active)

low: float#: Lowest value that this parameter can take

high: float#: Highest value that this parameter can take

static from_name(name)#

Create a HyperParameter object given its name.

Parameters:: name (str) – Name of the hyper-parameter
Return type:: HyperParameter

diart.blocks.base.TauActive#

diart.blocks.base.RhoUpdate#

diart.blocks.base.DeltaNew#

class diart.blocks.base.PipelineConfig#

Bases: abc.ABC

Configuration containing the required parameters to build and run a pipeline

abstract property duration: float#

The duration of an input audio chunk (in seconds)

Return type:: float

abstract property step: float#

The step between two consecutive input audio chunks (in seconds)

Return type:: float

abstract property latency: float#

The algorithmic latency of the pipeline (in seconds). At time t of the audio stream, the pipeline will output predictions for time t - latency.

Return type:: float

abstract property sample_rate: int#

The sample rate of the input audio stream

Return type:: int

get_file_padding(filepath)#

Parameters:: filepath (diart.audio.FilePath) –
Return type:: Tuple[float, float]

class diart.blocks.base.Pipeline#

Bases: abc.ABC

Represents a streaming audio pipeline

abstract property config: PipelineConfig#

Return type:: PipelineConfig

abstract static get_config_class()#

Return type:: type

abstract static suggest_metric()#

Return type:: pyannote.metrics.base.BaseMetric

abstract static hyper_parameters()#

Return type:: Sequence[HyperParameter]

abstract reset()#

abstract set_timestamp_shift(shift)#

Parameters:: shift (float) –

abstract __call__(waveforms)#

Runs the next steps of the pipeline given a list of consecutive audio chunks.

Parameters:: waveforms (Sequence[SlidingWindowFeature]) – Consecutive chunk waveforms for the pipeline to ingest
Returns:: For each input waveform, a tuple containing the pipeline output and its respective audio
Return type:: Sequence[Tuple[Any, SlidingWindowFeature]]

diart.blocks.base#

Module Contents#

Classes#

Attributes#

`diart.blocks.base`#