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test_model.py
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test_model.py
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import numpy
import theano
from theano import tensor
from numpy.testing import assert_allclose, assert_raises
from blocks.bricks import MLP, Tanh
from blocks.model import Model
from blocks.graph import add_role, PARAMETER
from blocks.utils import shared_floatx
def test_model():
x = tensor.matrix('x')
mlp1 = MLP([Tanh(), Tanh()], [10, 20, 30], name="mlp1")
mlp2 = MLP([Tanh()], [30, 40], name="mlp2")
h1 = mlp1.apply(x)
h2 = mlp2.apply(h1)
model = Model(h2)
assert model.get_top_bricks() == [mlp1, mlp2]
# The order of parameters returned is deterministic but
# not sensible.
assert list(model.get_parameter_dict().items()) == [
('/mlp2/linear_0.b', mlp2.linear_transformations[0].b),
('/mlp1/linear_1.b', mlp1.linear_transformations[1].b),
('/mlp1/linear_0.b', mlp1.linear_transformations[0].b),
('/mlp1/linear_0.W', mlp1.linear_transformations[0].W),
('/mlp1/linear_1.W', mlp1.linear_transformations[1].W),
('/mlp2/linear_0.W', mlp2.linear_transformations[0].W)]
# Test getting and setting parameter values
mlp3 = MLP([Tanh()], [10, 10])
mlp3.allocate()
model3 = Model(mlp3.apply(x))
parameter_values = {
'/mlp/linear_0.W': 2 * numpy.ones((10, 10),
dtype=theano.config.floatX),
'/mlp/linear_0.b': 3 * numpy.ones(10, dtype=theano.config.floatX)}
model3.set_parameter_values(parameter_values)
assert numpy.all(
mlp3.linear_transformations[0].parameters[0].get_value() == 2)
assert numpy.all(
mlp3.linear_transformations[0].parameters[1].get_value() == 3)
got_parameter_values = model3.get_parameter_values()
assert len(got_parameter_values) == len(parameter_values)
for name, value in parameter_values.items():
assert_allclose(value, got_parameter_values[name])
# Test exception is raised if parameter shapes don't match
def helper():
parameter_values = {
'/mlp/linear_0.W': 2 * numpy.ones((11, 11),
dtype=theano.config.floatX),
'/mlp/linear_0.b': 3 * numpy.ones(11, dtype=theano.config.floatX)}
model3.set_parameter_values(parameter_values)
assert_raises(ValueError, helper)
# Test name conflict handling
mlp4 = MLP([Tanh()], [10, 10])
def helper():
Model(mlp4.apply(mlp3.apply(x)))
assert_raises(ValueError, helper)
def test_model_handles_brickless_parameteres():
x = tensor.matrix('x')
v = shared_floatx(numpy.zeros((10, 10)), name='V')
add_role(v, PARAMETER)
y = x.dot(v)
model = Model(y)
assert list(model.get_parameter_dict().items()) == [('V', v)]