e5a431f8966a56c3de398f7f969b41f1deec6d70,tests/distributions/test_transforms.py,TransformTests,test_lower_cholesky_affine,#TransformTests#,145

Before Change

            transform = T.LowerCholeskyAffine(loc, scale_tril)
            self._test_inverse(input_dim, transform)
            self._test_jacobian(input_dim, transform)
            for shape in [(3,), (3, 4)]:
                self._test_shape(shape + (input_dim,), transform)

    def test_batchnorm_inverses(self):
        for input_dim in [2, 5, 10]:
            transform = T.batchnorm(input_dim)
            transform._inverse(torch.normal(torch.arange(0., input_dim), torch.arange(1., 1. + input_dim) / input_dim))

After Change

            scale_tril = scale_tril.tril(0)
            return T.LowerCholeskyAffine(loc, scale_tril)

        self._test(transform_factory)

    def test_neural_autoregressive(self):
        for activation in ["ELU", "LeakyReLU", "sigmoid", "tanh"]:
            self._test(partial(T.neural_autoregressive, activation=activation), inverse=False)

Instances