<filename>uberduck_ml_dev/monitoring/generate.py
# AUTOGENERATED! DO NOT EDIT! File to edit: nbs/monitoring.generate.ipynb (unless otherwise specified).

__all__ = ['MODEL_TYPES']

# Cell
from ..data_loader import prepare_input_sequence

MODEL_TYPES = ["OD", "OD", "OD", "OD", "OD", "D"]


def _get_inference(model, vocoder, texts, speaker_ids, symbol_set, arpabet):

    text_padded, input_lengths = prepare_input_sequence(
        texts, cpu_run=False, arpabet=arpabet, symbol_set=symbol_set
    )
    input_ = text_padded, input_lengths, speaker_ids
    output = model.inference(input_)
    audio = vocoder.infer(output[1][:1])
    return audio
<filename>uberduck_ml_dev/monitoring/generate.py
# AUTOGENERATED! DO NOT EDIT! File to edit: nbs/monitoring.generate.ipynb (unless otherwise specified).

__all__ = ['MODEL_TYPES']

# Cell
from ..data_loader import prepare_input_sequence

MODEL_TYPES = ["OD", "OD", "OD", "OD", "OD", "D"]


def _get_inference(model, vocoder, texts, speaker_ids, symbol_set, arpabet):

    text_padded, input_lengths = prepare_input_sequence(
        texts, cpu_run=False, arpabet=arpabet, symbol_set=symbol_set
    )
    input_ = text_padded, input_lengths, speaker_ids
    output = model.inference(input_)
    audio = vocoder.infer(output[1][:1])
    return audio
# AUTOGENERATED! DO NOT EDIT! File to edit: nbs/monitoring.generate.ipynb (unless otherwise specified). # Cell