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mycroft-precise
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Add docstrings and clean up test slightly

pull/139/head
Åke Forslund 2020-04-09 07:32:15 +02:00
parent a99d229b0c
commit 6345c50b41
4 changed files with 32 additions and 8 deletions
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8
test/scripts/dummy_audio_folder.py
View File

@ -35,8 +35,14 @@ class DummyAudioFolder:
return min + (max - min) * np.random.random() * pr.buffer_t
def generate_samples(self, folder, name, value, duration):
"""Generate sample file.
The file is generated in the specified folder, with the specified name,
dummy value and duration.
"""
for i in range(self.count):
save_audio(join(folder, name.format(i)), np.array([value] * int(duration * pr.sample_rate)))
save_audio(join(folder, name.format(i)),
np.array([value] * int(duration * pr.sample_rate)))
def subdir(self, *parts):
folder = self.path(*parts)

15
test/scripts/test_combined.py
View File

@ -26,18 +26,27 @@ def read_content(filename):
def test_combined(train_folder, train_script):
"""Test a "normal" development cycle, train, evaluate and calc threshold.
"""
train_script.run()
params_file = train_folder.model + '.params'
assert isfile(train_folder.model)
assert isfile(params_file)
EvalScript.create(folder=train_folder.root, models=[train_folder.model]).run()
EvalScript.create(folder=train_folder.root,
models=[train_folder.model]).run()
# Ensure that the graph script generates a numpy savez file
out_file = train_folder.path('outputs.npz')
graph_script = GraphScript.create(folder=train_folder.root, models=[train_folder.model], output_file=out_file)
graph_script = GraphScript.create(folder=train_folder.root,
models=[train_folder.model],
output_file=out_file)
graph_script.run()
assert isfile(out_file)
# Esure the params are updated after threshold is calculated
params_before = read_content(params_file)
CalcThresholdScript.create(folder=train_folder.root, model=train_folder.model, input_file=out_file).run()
CalcThresholdScript.create(folder=train_folder.root,
model=train_folder.model,
input_file=out_file).run()
assert params_before != read_content(params_file)

4
test/scripts/test_engine.py
View File

@ -36,6 +36,10 @@ class FakeStdout:
def test_engine(train_folder, train_script):
"""
Test t hat the output format of the engina matches a decimal form in the
range 0.0 - 1.0.
"""
train_script.run()
with open(glob.glob(join(train_folder.root, 'wake-word', '*.wav'))[0], 'rb') as f:
data = f.read()

13
test/scripts/test_train.py
View File

@ -22,15 +22,20 @@ from test.scripts.dummy_audio_folder import DummyAudioFolder
class DummyTrainFolder(DummyAudioFolder):
def __init__(self, count=10):
super().__init__(count)
self.generate_samples(self.subdir('wake-word'), 'ww-{}.wav', 1.0, self.rand(0, 2 * pr.buffer_t))
self.generate_samples(self.subdir('not-wake-word'), 'nww-{}.wav', 0.0, self.rand(0, 2 * pr.buffer_t))
self.generate_samples(self.subdir('test', 'wake-word'), 'ww-{}.wav', 1.0, self.rand(0, 2 * pr.buffer_t))
self.generate_samples(self.subdir('test', 'not-wake-word'), 'nww-{}.wav', 0.0, self.rand(0, 2 * pr.buffer_t))
self.generate_samples(self.subdir('wake-word'), 'ww-{}.wav', 1.0,
self.rand(0, 2 * pr.buffer_t))
self.generate_samples(self.subdir('not-wake-word'), 'nww-{}.wav', 0.0,
self.rand(0, 2 * pr.buffer_t))
self.generate_samples(self.subdir('test', 'wake-word'), 'ww-{}.wav',
1.0, self.rand(0, 2 * pr.buffer_t))
self.generate_samples(self.subdir('test', 'not-wake-word'),
'nww-{}.wav', 0.0, self.rand(0, 2 * pr.buffer_t))
self.model = self.path('model.net')
class TestTrain:
def test_run_basic(self):
"""Run a training and check that a model is generated."""
folders = DummyTrainFolder(10)
script = TrainScript.create(model=folders.model, folder=folders.root)
script.run()