implement _add_noise for dpm solver

src/refiners/foundationals/latent_diffusion/solvers/dpm.py

@@ -174,7 +174,30 @@ def _timesteps_from_sigmas(self, sigmas: torch.Tensor) -> torch.Tensor:
             timestep = (1 - interpolation_weights) * low_indices + interpolation_weights * high_indices
             timesteps.append(timestep)
 
-        return torch.cat(timesteps).round()
+        return torch.cat(timesteps).round().int()
+
+    def _add_noise(
+        self,
+        x: torch.Tensor,
+        noise: torch.Tensor,
+        step: int,
+    ) -> torch.Tensor:
+        """Add noise to the input tensor using the solver's parameters.
+
+        Args:
+            x: The input tensor to add noise to.
+            noise: The noise tensor to add to the input tensor.
+            step: The current step of the diffusion process.
+
+        Returns:
+            The input tensor with added noise.
+        """
+        cumulative_scale_factors = self.cumulative_scale_factors[step]
+        noise_stds = self.noise_std[step]
+
+        # noisify the latents, arXiv:2006.11239 Eq. 4
+        noised_x = cumulative_scale_factors * x + noise_stds * noise
+        return noised_x
 
     def _solver_tensors_from_sigmas(self, sigmas: torch.Tensor) -> SolverTensors:
         """Generate the tensors from the sigmas."""