verts the input images into latents, adds noise to the image embeddings, and makes a prediction:   Copied model_pred = prior(
    noisy_latents,
    timestep=timesteps,
    proj_embedding=prompt_embeds,
    encoder_hidden_states=text_encoder_hidden_states,
    attention_mask=text_mask,
).predicted_image_embedding If you want to learn more about how the training loop works, check out the Understanding pipelines, models and schedulers tutorial wh