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Running
on
Zero
# Copyright (c) Meta Platforms, Inc. and affiliates. | |
# All rights reserved. | |
# | |
# This source code is licensed under the license found in the | |
# LICENSE file in the root directory of this source tree. | |
import random | |
import numpy as np | |
import torch | |
from audiocraft.models import EncodecModel | |
from audiocraft.modules import SEANetEncoder, SEANetDecoder | |
from audiocraft.quantization import DummyQuantizer | |
class TestEncodecModel: | |
def _create_encodec_model(self, | |
sample_rate: int, | |
channels: int, | |
dim: int = 5, | |
n_filters: int = 3, | |
n_residual_layers: int = 1, | |
ratios: list = [5, 4, 3, 2], | |
**kwargs): | |
frame_rate = np.prod(ratios) | |
encoder = SEANetEncoder(channels=channels, dimension=dim, n_filters=n_filters, | |
n_residual_layers=n_residual_layers, ratios=ratios) | |
decoder = SEANetDecoder(channels=channels, dimension=dim, n_filters=n_filters, | |
n_residual_layers=n_residual_layers, ratios=ratios) | |
quantizer = DummyQuantizer() | |
model = EncodecModel(encoder, decoder, quantizer, frame_rate=frame_rate, | |
sample_rate=sample_rate, channels=channels, **kwargs) | |
return model | |
def test_model(self): | |
random.seed(1234) | |
sample_rate = 24_000 | |
channels = 1 | |
model = self._create_encodec_model(sample_rate, channels) | |
for _ in range(10): | |
length = random.randrange(1, 10_000) | |
x = torch.randn(2, channels, length) | |
res = model(x) | |
assert res.x.shape == x.shape | |
def test_model_renorm(self): | |
random.seed(1234) | |
sample_rate = 24_000 | |
channels = 1 | |
model_nonorm = self._create_encodec_model(sample_rate, channels, renormalize=False) | |
model_renorm = self._create_encodec_model(sample_rate, channels, renormalize=True) | |
for _ in range(10): | |
length = random.randrange(1, 10_000) | |
x = torch.randn(2, channels, length) | |
codes, scales = model_nonorm.encode(x) | |
codes, scales = model_renorm.encode(x) | |
assert scales is not None | |