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from typing import Dict |
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from data_generation.data_generation import param_descriptions |
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import numpy as np |
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from melody_synth.melody_generator import MelodyGenerator |
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from melody_synth.random_midi import RandomMidi |
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def decode_label(prediction: np.ndarray, |
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sample_rate: int, |
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n_samples: int, |
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return_params=False, |
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discard_parameters=[]): |
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"""Parses a network prediction array, synthesizes the described audio and returns it. |
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Parameters |
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---------- |
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prediction: np.ndarray |
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The network prediction array |
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sample_rate: int |
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Sample rate of the audio to generate. |
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n_samples: int |
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Number of samples per wav file. |
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return_params: bool |
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Whether or not to also return the parameters alongside the signal |
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discard_parameters: List[str] |
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Parameter names that should be discarded (set to their default value) |
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Returns |
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------- |
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np.ndarray: |
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The generated signal |
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""" |
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params: Dict[str, float] = {} |
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index = 0 |
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for i, param_description in enumerate(param_descriptions): |
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bits = len(param_description.values) |
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curr_prediction = prediction[index:index + bits] |
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hot_index = curr_prediction.argmax() |
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params[param_description.name] = param_description.parameter_value(hot_index).value |
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index += bits |
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for param_str in discard_parameters: |
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params[param_str] = 0 |
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synth = MelodyGenerator(sample_rate, |
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n_samples, n_samples) |
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randomMidi = RandomMidi() |
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strategy = {"rhythm_strategy": "single_note_rhythm", |
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"pitch_strategy": "fixed_pitch", |
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"duration_strategy": "fixed_duration", |
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} |
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midi_encode, midi = randomMidi(strategy) |
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signal = synth.get_melody(params, midi=midi).numpy() |
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if return_params: |
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return signal, params |
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return signal |
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