logging to TensorBoard and Weights & Biases.  Quantitative Evaluation In this section, we will walk you through how to evaluate three different diffusion pipelines using: CLIP score CLIP directional similarity FID  Text-guided image generation CLIP score measures the compatibility of image-caption pairs. Higher CLIP scores imply higher compatibility 🔼. The CLIP score is a quantitative measurement of the qualitative concept “compatibility”. Image-caption pair compatibility can also be thought of as the semantic similarity between the image and the caption. CLIP score was found to have high correlation with human judgement. Let’s first load a StableDiffusionPipeline:   Copied from diffusers import StableDiffusionPipeline