def create_pipeline(data_path, batch_size, audio_frame_length,
prediction_only):
"""Create a pipeline to pre and post process the data.
Inputs:
- String data_path: path to the tfrecord file
- Int batch_size: size of a batch
- Float audio_frame_length: Length to which the audio will be trimmed in second
Outputs:
- Processeur pipeline: the pipeline to perform pre and post processing
- Int sr: The sampling rate of the audio record in data_path"""
data_loader = DataLoader.LoadData(data_path,
sr=16000,
batch_size=batch_size,
audio_frame_length=audio_frame_length)
dataset = data_loader.create_dataset()
pipeline = Processing.Processeur(data_loader.sr,
dataset,
data_loader.length,
audio_frame_length,
window_size=0.025,
overlap=0.75,
prediction_only=prediction_only)
return pipeline, data_loader.sr
