latent_diffusion.solver: fix assert msg

Author: piercus

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

@@ -65,7 +65,7 @@ def __call__(self, x: Tensor, predicted_noise: Tensor, step: int, generator: Gen
         Returns:
             The denoised version of the input data `x`.
         """
-        assert self.first_inference_step <= step < self.num_inference_steps, "invalid step {step}"
+        assert self.first_inference_step <= step < self.num_inference_steps, f"invalid step {step}"
 
         timestep, previous_timestep = (
             self.timesteps[step],

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

@@ -308,7 +308,7 @@ def __call__(
         Returns:
             The denoised version of the input data `x`.
         """
-        assert self.first_inference_step <= step < self.num_inference_steps, "invalid step {step}"
+        assert self.first_inference_step <= step < self.num_inference_steps, f"invalid step {step}"
 
         scale_factor = self.cumulative_scale_factors[step]
         noise_ratio = self.noise_std[step]

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

@@ -89,7 +89,7 @@ def __call__(self, x: Tensor, predicted_noise: Tensor, step: int, generator: Gen
         Returns:
             The denoised version of the input data `x`.
         """
-        assert self.first_inference_step <= step < self.num_inference_steps, "invalid step {step}"
+        assert self.first_inference_step <= step < self.num_inference_steps, f"invalid step {step}"
 
         if self.params.model_prediction_type == ModelPredictionType.SAMPLE:
             x0 = predicted_noise  # the model does not actually predict the noise but x0