def test_prior_get_vae(): """ Prior.get_vae returns its VAE """ prior = DummyPrior() vae = DummyVAE() prior.set_vae(vae) testing.assert_same_object(prior.get_vae(), vae)
def test_conditional_get_vae(): """ Conditional.get_vae returns its VAE """ mlp = MLP(layers=[Linear(layer_name="h", dim=5, irange=0.01)]) conditional = DummyConditional(mlp=mlp, name="conditional") vae = DummyVAE() conditional.set_vae(vae) testing.assert_same_object(conditional.get_vae(), vae)
def test_conditional_get_vae(): """ Conditional.get_vae returns its VAE """ mlp = MLP(layers=[Linear(layer_name='h', dim=5, irange=0.01)]) conditional = DummyConditional(mlp=mlp, name='conditional') vae = DummyVAE() conditional.set_vae(vae) testing.assert_same_object(conditional.get_vae(), vae)
def test_prior_set_vae(): """ Prior.set_vae adds a reference to the vae and adopts the vae's rng and batch_size attributes """ prior = DummyPrior() vae = DummyVAE() prior.set_vae(vae) testing.assert_same_object(prior.vae, vae) testing.assert_same_object(prior.rng, vae.rng) testing.assert_equal(prior.batch_size, vae.batch_size)
def test_conditional_set_vae(): """ Conditional.set_vae adds a reference to the vae and adopts the vae's rng and batch_size attributes """ mlp = MLP(layers=[Linear(layer_name="h", dim=5, irange=0.01)]) conditional = DummyConditional(mlp=mlp, name="conditional") vae = DummyVAE() conditional.set_vae(vae) testing.assert_same_object(conditional.vae, vae) testing.assert_same_object(conditional.rng, vae.rng) testing.assert_equal(conditional.batch_size, vae.batch_size)
def test_conditional_set_vae(): """ Conditional.set_vae adds a reference to the vae and adopts the vae's rng and batch_size attributes """ mlp = MLP(layers=[Linear(layer_name='h', dim=5, irange=0.01)]) conditional = DummyConditional(mlp=mlp, name='conditional') vae = DummyVAE() conditional.set_vae(vae) testing.assert_same_object(conditional.vae, vae) testing.assert_same_object(conditional.rng, vae.rng) testing.assert_equal(conditional.batch_size, vae.batch_size)
def test_conditional_initialize_parameters(): """ Conditional.initialize_parameters does the following: * Set its input_space and ndim attributes * Calls its MLP's set_mlp method * Sets its MLP's input_space * Validates its MLP * Sets its params and param names """ mlp = MLP(layers=[Linear(layer_name='h', dim=5, irange=0.01, max_col_norm=0.01)]) conditional = DummyConditional(mlp=mlp, name='conditional') vae = DummyVAE() conditional.set_vae(vae) input_space = VectorSpace(dim=5) conditional.initialize_parameters(input_space=input_space, ndim=5) testing.assert_same_object(input_space, conditional.input_space) testing.assert_equal(conditional.ndim, 5) testing.assert_same_object(mlp.get_mlp(), conditional) testing.assert_same_object(mlp.input_space, input_space) mlp_params = mlp.get_params() conditional_params = conditional.get_params() assert all([mp in conditional_params for mp in mlp_params]) assert all([cp in mlp_params for cp in conditional_params])
def test_conditional_initialize_parameters(): """ Conditional.initialize_parameters does the following: * Set its input_space and ndim attributes * Calls its MLP's set_mlp method * Sets its MLP's input_space * Validates its MLP * Sets its params and param names """ mlp = MLP(layers=[Linear(layer_name="h", dim=5, irange=0.01, max_col_norm=0.01)]) conditional = DummyConditional(mlp=mlp, name="conditional") vae = DummyVAE() conditional.set_vae(vae) input_space = VectorSpace(dim=5) conditional.initialize_parameters(input_space=input_space, ndim=5) testing.assert_same_object(input_space, conditional.input_space) testing.assert_equal(conditional.ndim, 5) testing.assert_same_object(mlp.get_mlp(), conditional) testing.assert_same_object(mlp.input_space, input_space) mlp_params = mlp.get_params() conditional_params = conditional.get_params() assert all([mp in conditional_params for mp in mlp_params]) assert all([cp in mlp_params for cp in conditional_params])