Пример #1
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def test_bernoulli_vector_sample_from_conditional():
    """
    BernoulliVector.sample_from_conditional works when num_samples is provided
    """
    mlp = MLP(layers=[Linear(layer_name="h", dim=5, irange=0.01, max_col_norm=0.01)])
    conditional = BernoulliVector(mlp=mlp, name="conditional")
    vae = DummyVAE()
    conditional.set_vae(vae)
    input_space = VectorSpace(dim=5)
    conditional.initialize_parameters(input_space=input_space, ndim=5)
    mu = T.matrix("mu")
    conditional.sample_from_conditional([mu], num_samples=2)
Пример #2
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def test_bernoulli_vector_sample_from_conditional():
    """
    BernoulliVector.sample_from_conditional works when num_samples is provided
    """
    mlp = MLP(layers=[Linear(layer_name='h', dim=5, irange=0.01,
                             max_col_norm=0.01)])
    conditional = BernoulliVector(mlp=mlp, name='conditional')
    vae = DummyVAE()
    conditional.set_vae(vae)
    input_space = VectorSpace(dim=5)
    conditional.initialize_parameters(input_space=input_space, ndim=5)
    mu = T.matrix('mu')
    conditional.sample_from_conditional([mu], num_samples=2)
Пример #3
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def test_bernoulli_vector_reparametrization_trick():
    """
    BernoulliVector.sample_from_conditional raises an error when asked to
    sample using the reparametrization trick
    """
    mlp = MLP(layers=[Linear(layer_name="h", dim=5, irange=0.01, max_col_norm=0.01)])
    conditional = BernoulliVector(mlp=mlp, name="conditional")
    vae = DummyVAE()
    conditional.set_vae(vae)
    input_space = VectorSpace(dim=5)
    conditional.initialize_parameters(input_space=input_space, ndim=5)
    mu = T.matrix("mu")
    epsilon = T.tensor3("epsilon")
    conditional.sample_from_conditional([mu], epsilon=epsilon)
Пример #4
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def test_bernoulli_vector_reparametrization_trick():
    """
    BernoulliVector.sample_from_conditional raises an error when asked to
    sample using the reparametrization trick
    """
    mlp = MLP(layers=[Linear(layer_name='h', dim=5, irange=0.01,
                             max_col_norm=0.01)])
    conditional = BernoulliVector(mlp=mlp, name='conditional')
    vae = DummyVAE()
    conditional.set_vae(vae)
    input_space = VectorSpace(dim=5)
    conditional.initialize_parameters(input_space=input_space, ndim=5)
    mu = T.matrix('mu')
    epsilon = T.tensor3('epsilon')
    conditional.sample_from_conditional([mu], epsilon=epsilon)