30028c6256de0cef715095e3994e396025c068d4,pixyz/distributions/exponential_distributions.py,RelaxedCategorical,sample,#RelaxedCategorical#Any#Any#Any#Any#Any#,257

Before Change

    def sample(self, x_dict={}, batch_n=None, sample_shape=torch.Size(), return_all=True, reparam=False):
        // check whether the input is valid or convert it to valid dictionary.
        x_dict = self._check_input(x_dict)
        input_dict = {}

        // conditioned
        if len(self.input_var) != 0:
            input_dict.update(get_dict_values(x_dict, self.input_var, return_dict=True))

        self.set_dist(input_dict, batch_n=batch_n, sampling=True)
        output_dict = self.get_sample(reparam=reparam,
                                      sample_shape=sample_shape)

After Change

            else:
                raise ValueError()

    def sample(self, x_dict={}, batch_n=None, sample_shape=torch.Size(), return_all=True, reparam=False):
        // check whether the input is valid or convert it to valid dictionary.
        input_dict = self._get_input_dict(x_dict)

        self.set_dist(input_dict, batch_n=batch_n, sampling=True)
        output_dict = self.get_sample(reparam=reparam, sample_shape=sample_shape)

Instances