Add TensorRT SD/txt2img Community Pipeline to diffusers along with TensorRT utils

examples/community/README.md

@@ -31,7 +31,7 @@ MagicMix | Diffusion Pipeline for semantic mixing of an image and a text prompt
 | UnCLIP Image Interpolation Pipeline | Diffusion Pipeline that allows passing two images/image_embeddings and produces images while interpolating between their image-embeddings | [UnCLIP Image Interpolation Pipeline](#unclip-image-interpolation-pipeline)                   | -                                                                                                                                                                                                                  | [Naga Sai Abhinay Devarinti](https://github.com/Abhinay1997/) | 
 | DDIM Noise Comparative Analysis Pipeline | Investigating how the diffusion models learn visual concepts from each noise level (which is a contribution of [P2 weighting (CVPR 2022)](https://arxiv.org/abs/2204.00227)) | [DDIM Noise Comparative Analysis Pipeline](#ddim-noise-comparative-analysis-pipeline) | - |[Aengus (Duc-Anh)](https://github.com/aengusng8) |
 | CLIP Guided Img2Img Stable Diffusion Pipeline | Doing CLIP guidance for image to image generation with Stable Diffusion | [CLIP Guided Img2Img Stable Diffusion](#clip-guided-img2img-stable-diffusion) | - | [Nipun Jindal](https://github.com/nipunjindal/) | 
-
+| TensorRT Stable Diffusion Pipeline | Accelerates the Stable Diffusion Text2Image Pipeline using TensorRT | [TensorRT Stable Diffusion Pipeline](#tensorrt-text2image-stable-diffusion-pipeline) | - |[Asfiya Baig](https://github.com/asfiyab-nvidia) |
 
 
 To load a custom pipeline you just need to pass the `custom_pipeline` argument to `DiffusionPipeline`, as one of the files in `diffusers/examples/community`. Feel free to send a PR with your own pipelines, we will merge them quickly.
@@ -1130,3 +1130,34 @@ Init Image
 Output Image
 
 ![img2img_clip_guidance](https://huggingface.co/datasets/njindal/images/resolve/main/clip_guided_img2img.jpg)
+
+### TensorRT Text2Image Stable Diffusion Pipeline
+
+The TensorRT Pipeline can be used to accelerate the Text2Image Stable Diffusion Inference run.
+
+NOTE: The ONNX conversions and TensorRT engine build may take up to 30 minutes.
+
+```python
+import torch
+from diffusers import DDIMScheduler
+from diffusers.pipelines.stable_diffusion import StableDiffusionPipeline
+
+# Use the DDIMScheduler scheduler here instead
+scheduler = DDIMScheduler.from_pretrained("stabilityai/stable-diffusion-2-1",
+                                            subfolder="scheduler")
+
+pipe = StableDiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-2-1",
+                                                custom_pipeline="stable_diffusion_tensorrt_txt2img",
+                                                revision='fp16',
+                                                torch_dtype=torch.float16,
+                                                scheduler=scheduler,)
+
+# re-use cached folder to save ONNX models and TensorRT Engines
+pipe.set_cached_folder("stabilityai/stable-diffusion-2-1", revision='fp16',)
+
+pipe = pipe.to("cuda")
+
+prompt = "a beautiful photograph of Mt. Fuji during cherry blossom"
+image = pipe(prompt).images[0]
+image.save('tensorrt_mt_fuji.png')
+```