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Merge branch 'master' into tf2

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This commit is contained in:
Romain Hennequin
2020-09-25 13:32:57 +02:00
committed by GitHub
parent 1d91e419de e6aeaa1179
commit f6498d54c9
39 changed files with 326 additions and 377 deletions
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66
tests/test_eval.py
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@@ -3,7 +3,7 @@
""" Unit testing for Separator class. """
__email__ = 'research@deezer.com'
__email__ = 'spleeter@deezer.com'
__author__ = 'Deezer Research'
__license__ = 'MIT License'
@@ -25,33 +25,36 @@ from spleeter.commands import evaluate
from spleeter.utils.configuration import load_configuration
res_4stems = { "vocals": {
"SDR": -0.007,
"SAR": -19.231,
"SIR": -4.528,
"ISR": 0.000
BACKENDS = ["tensorflow", "librosa"]
TEST_CONFIGURATIONS = {el:el for el in BACKENDS}
res_4stems = {
"vocals": {
"SDR": 3.25e-05,
"SAR": -11.153575,
"SIR": -1.3849,
"ISR": 2.75e-05
},
"drums": {
"SDR": -0.071,
"SAR": -14.496,
"SIR": -4.987,
"ISR": 0.001
"SDR": -0.079505,
"SAR": -15.7073575,
"SIR": -4.972755,
"ISR": 0.0013575
},
"bass":{
"SDR": -0.001,
"SAR": -12.426,
"SIR": -7.198,
"ISR": -0.001
"SDR": 2.5e-06,
"SAR": -10.3520575,
"SIR": -4.272325,
"ISR": 2.5e-06
},
"other":{
"SDR": -1.453,
"SAR": -14.899,
"SIR": -4.678,
"ISR": -0.015
"SDR": -1.359175,
"SAR": -14.7076775,
"SIR": -4.761505,
"ISR": -0.01528
}
}
def generate_fake_eval_dataset(path):
"""
generate fake evaluation dataset
@@ -71,26 +74,15 @@ def generate_fake_eval_dataset(path):
aa.save(filename, data, fs)
def test_evaluate():
"""
test evaluate command
"""
with TemporaryDirectory() as path:
# generate fake dataset
generate_fake_eval_dataset(path)
# set up arguments of command
@pytest.mark.parametrize('backend', TEST_CONFIGURATIONS)
def test_evaluate(backend):
with TemporaryDirectory() as directory:
generate_fake_eval_dataset(directory)
p = create_argument_parser()
arguments = p.parse_args(["evaluate", "-p", "spleeter:4stems", "--mus_dir", path])
arguments = p.parse_args(["evaluate", "-p", "spleeter:4stems", "--mus_dir", directory, "-B", backend])
params = load_configuration(arguments.configuration)
# run evaluation
metrics = evaluate.entrypoint(arguments, params)
# assert that the metric as not changed compared to reference value
# (Note that this fails with tensorflow backend)
for instrument, metric in metrics.items():
for metric, value in metric.items():
assert np.allclose(np.median(value), res_4stems[instrument][metric], atol=1e-3)
for m, value in metric.items():
assert np.allclose(np.median(value), res_4stems[instrument][m], atol=1e-3)