def save(self, path):
print(path)
try:
with SimpleNN.tensorflow_graph.as_default():
save_model(self.model, path + '.h5')
except Exception as e:
raise AlgorithmException(str(e))
def train(self, samples, labels):
print(samples)
print(
labels) # for some reason gridFS has problems without those prints
X, y = read_samples(samples,
labels,
normalized_length=self.SAMPLE_LENGTH)
y = self.to_categorical(y)
with SimpleNN.tensorflow_graph.as_default():
try:
self._prepare_model()
self.model.fit(X,
y,
epochs=self.parameters['epochs'],
validation_split=.25,
verbose=self.parameters['verbosity'])
except Exception as e:
raise AlgorithmException(str(e))
def save(self, path):
super().save(path)
raise AlgorithmException('path exception')
def predict(self, sample):
super().predict(sample)
raise AlgorithmException('predict exception')
def train(self, samples, labels):
super().train(samples, labels)
raise AlgorithmException("train exception")
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
if 'path' in kwargs:
raise AlgorithmException('load exception')
def train(self, samples, labels):
super().train(samples, labels)
self.su.update(error=self.error_msg)
raise AlgorithmException("train exception")