Add DeepSpeed Stable Diffusion Example (microsoft#233)

This PR adds a DeepSpeed Stable Diffusion example using the prompthero/midjourney-v4-diffusion model.

inference/huggingface/README.md

@@ -32,6 +32,7 @@ The DeepSpeed huggingface inference examples are organized into their correspond
 | [`text-generation/run-generation-script`](./text-generation/run-generation-script/) | [`README`](./text-generation/run-generation-script/README.md) | [`requirements`](./text-generation/run-generation-script/requirements.txt) |
 | [`text2text-generation`](./text2text-generation/) | [`README`](./text2text-generation/README.md) | [`requirements`](./text2text-generation/requirements.txt) |
 | [`translation`](./translation/) | [`README`](./translation/README.md) | [`requirements`](./translation/requirements.txt) |
+| [`stable-diffusion`](./stable-diffusion/) | [`README`](./stable-diffusion/README.md) | [`requirements`](./stable-diffusion/requirements.txt) |
 
 Most examples can be run as follows:
 <pre>deepspeed --num_gpus [number of GPUs] test-[model].py</pre>

inference/huggingface/stable-diffusion/README.md

@@ -0,0 +1,24 @@
+
+# DeepSpeed Stable Diffusion Example
+
+# Setup
+Python dependencies:
+<pre>
+pip install -r requirements.txt
+</pre>
+
+# Usage
+Examples can be run as follows:
+<pre>deepspeed --num_gpus [number of GPUs] test-[model].py</pre>
+
+# Example Output
+Command:
+<pre>
+deepspeed --num_gpus 1 test-stable-diffusion.py
+</pre>
+
+Output:
+<pre>
+./baseline.png
+./deepspeed.png
+</pre>

inference/huggingface/stable-diffusion/requirements.txt

@@ -0,0 +1,3 @@
+deepspeed
+torch
+diffusers

inference/huggingface/stable-diffusion/test-stable-diffusion.py

@@ -0,0 +1,32 @@
+import deepspeed
+import torch
+import os
+
+from diffusers import DiffusionPipeline
+
+prompt = "a dog on a rocket"
+
+model = "prompthero/midjourney-v4-diffusion"
+local_rank = int(os.getenv("LOCAL_RANK", "0"))
+device = torch.device(f"cuda:{local_rank}")
+world_size = int(os.getenv('WORLD_SIZE', '4'))
+generator = torch.Generator(device=torch.cuda.current_device())
+
+pipe = DiffusionPipeline.from_pretrained(model, torch_dtype=torch.half)
+pipe = pipe.to(device)
+
+generator.manual_seed(0xABEDABE7)
+baseline_image = pipe(prompt, guidance_scale=7.5, generator=generator).images[0]
+baseline_image.save(f"baseline.png")
+
+# NOTE: DeepSpeed inference supports local CUDA graphs for replaced SD modules
+pipe = deepspeed.init_inference(
+    pipe,
+    dtype=torch.half,
+    replace_with_kernel_inject=True,
+    enable_cuda_graph=True,
+)
+
+generator.manual_seed(0xABEDABE7)
+deepspeed_image = pipe(prompt, guidance_scale=7.5, generator=generator).images[0]
+deepspeed_image.save(f"deepspeed.png")