def test_DenseClassifier():
"""Tests probflow.applications.DenseClassifier"""
# Data
x = np.random.randn(100, 5).astype('float32')
w = np.random.randn(5, 1).astype('float32')
y = x @ w + 1
y = np.round(1.0 / (1.0 + np.exp(-y))).astype('float32')
# Create the model
model = apps.DenseClassifier([5, 20, 15, 2])
# Fit the model
model.fit(x, y, batch_size=10, epochs=11)
# Predictive functions
model.predict(x)
def test_MultinomialDenseClassifier():
"""Tests probflow.applications.DenseClassifier w/ >2 output classes"""
# Data
x = np.random.randn(100, 5).astype('float32')
w = np.random.randn(5, 3).astype('float32')
b = np.random.randn(1, 3).astype('float32')
y = x @ w + b
y = np.argmax(y, axis=1).astype('int32')
# Create the model
model = apps.DenseClassifier([5, 20, 15, 3])
# Fit the model
model.fit(x, y, batch_size=10, epochs=11)
# Predictive functions
model.predict(x)