Initial

.gitmodules

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+[submodule "sdxl-newdream-20"]
+    path = models/models--stablediffusionapi--newdream-sdxl-20/snapshots/4bdd502bca7abd1ea57ee12fba0b0f23052958cc
+    url = https://huggingface.co/stablediffusionapi/newdream-sdxl-20
+    branch = main
+

models/models--stablediffusionapi--newdream-sdxl-20/refs/main

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+4bdd502bca7abd1ea57ee12fba0b0f23052958cc

models/models--stablediffusionapi--newdream-sdxl-20/snapshots/4bdd502bca7abd1ea57ee12fba0b0f23052958cc

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+Subproject commit 4bdd502bca7abd1ea57ee12fba0b0f23052958cc

pyproject.toml

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+[build-system]
+requires = ["setuptools >= 61.0"]
+build-backend = "setuptools.build_meta"
+
+[project]
+name = "edge-maxxing-4090-newdream"
+description = "An edge-maxxing model submission for the 4090 newdream contest"
+requires-python = ">=3.10,<3.11"
+version = "1.0.0"
+dependencies = [
+    # "diffusers==0.29.0",
+    # "transformers==4.41.2",
+    # "accelerate==0.31.0",
+    # "omegaconf==2.3.0",
+    "edge-maxxing-pipelines @ git+ssh://git@github.com/womboai/edge-maxxing@docker-submissions#subdirectory=pipelines",
+]

src/main.py

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+from io import BytesIO
+from socket import socket, AF_UNIX, SOCK_STREAM
+from sys import byteorder
+
+from pipelines.models import TextToImageRequest
+
+from pipeline import load_pipeline, infer
+
+SOCKET = "/sandbox/inferences.sock"
+
+
+def main():
+    pipeline = load_pipeline()
+
+    with socket(AF_UNIX, SOCK_STREAM) as inference_socket:
+        inference_socket.bind(SOCKET)
+
+        inference_socket.listen(1)
+        connection, _ = inference_socket.accept()
+
+        with connection:
+            while True:
+                size = int.from_bytes(connection.recv(2), byteorder)
+
+                request = TextToImageRequest.model_validate_json(connection.recv(size).decode("utf-8"))
+
+                image = infer(request, pipeline)
+
+                data = BytesIO()
+                image.save(data, format=image.format)
+
+                packet = data.getvalue()
+
+                connection.send(len(packet).to_bytes(4, byteorder))
+                connection.send(packet)
+
+
+if __name__ == '__main__':
+    main()

src/pipeline.py

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+from PIL.Image import Image
+from diffusers import StableDiffusionXLPipeline
+from pipelines.models import TextToImageRequest
+from torch import Generator
+
+
+def load_pipeline() -> StableDiffusionXLPipeline:
+    pipeline = StableDiffusionXLPipeline.from_pretrained(
+        "stablediffusionapi/newdream-sdxl-20",
+        revision="4bdd502bca7abd1ea57ee12fba0b0f23052958cc",
+        cache_dir="./models",
+        local_files_only=True,
+    ).to("cuda")
+
+    pipeline(prompt="")
+
+    return pipeline
+
+
+def infer(request: TextToImageRequest, pipeline: StableDiffusionXLPipeline) -> Image:
+    generator = Generator(pipeline.device).manual_seed(request.seed) if request.seed else None
+
+    return pipeline(
+        prompt=request.prompt,
+        negative_prompt=request.negative_prompt,
+        width=request.width,
+        height=request.height,
+        generator=generator,
+    ).images