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.gitmodules

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

README.md

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+# edge-maxxing-newdream-sdxl
+
+This holds the baseline for the SDXL Nvidia GeForce RTX 4090 contest, which can be forked freely and optimized
+
+Some recommendations are as follows:
+- Installing dependencies should be done in pyproject.toml, including git dependencies
+- Compiled models should be included directly in the repository(rather than compiling during loading), loading time matters far more than file sizes
+- Avoid changing `src/main.py`, as that includes mostly protocol logic. Most changes should be in `models` and `src/pipeline.py`
+- Change `requirements.txt` to add extra arguments to be used when installing the package
+
+For testing, you need a docker container with pytorch and ubuntu 22.04,
+you can download your listed dependencies with `pip install -r requirements.txt -e .`, and then running `start_inference`

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==0.30.2",
+    "transformers==4.41.2",
+    "accelerate==0.31.0",
+    "omegaconf==2.3.0",
+    "edge-maxxing-pipelines @ git+https://github.com/womboai/edge-maxxing#subdirectory=pipelines",
+]
+
+[project.scripts]
+start_inference = "main:main"

requirements.txt

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+OptTf-0.1.6-py3-none-any.whl

src/edge_maxxing_4090_newdream.egg-info/PKG-INFO

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+Metadata-Version: 2.1
+Name: edge-maxxing-4090-newdream
+Version: 1.0.0
+Summary: An edge-maxxing model submission for the 4090 newdream contest
+Requires-Python: <3.11,>=3.10
+Requires-Dist: diffusers==0.30.2
+Requires-Dist: transformers==4.41.2
+Requires-Dist: accelerate==0.31.0
+Requires-Dist: omegaconf==2.3.0
+Requires-Dist: edge-maxxing-pipelines@ git+https://github.com/womboai/edge-maxxing#subdirectory=pipelines

src/edge_maxxing_4090_newdream.egg-info/SOURCES.txt

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+README.md
+pyproject.toml
+src/main.py
+src/pipeline.py
+src/edge_maxxing_4090_newdream.egg-info/PKG-INFO
+src/edge_maxxing_4090_newdream.egg-info/SOURCES.txt
+src/edge_maxxing_4090_newdream.egg-info/dependency_links.txt
+src/edge_maxxing_4090_newdream.egg-info/entry_points.txt
+src/edge_maxxing_4090_newdream.egg-info/requires.txt
+src/edge_maxxing_4090_newdream.egg-info/top_level.txt

src/edge_maxxing_4090_newdream.egg-info/dependency_links.txt

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+

src/edge_maxxing_4090_newdream.egg-info/entry_points.txt

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+[console_scripts]
+start_inference = main:main

src/edge_maxxing_4090_newdream.egg-info/requires.txt

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+diffusers==0.30.2
+transformers==4.41.2
+accelerate==0.31.0
+omegaconf==2.3.0
+edge-maxxing-pipelines@ git+https://github.com/womboai/edge-maxxing#subdirectory=pipelines

src/edge_maxxing_4090_newdream.egg-info/top_level.txt

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+main
+pipeline

src/main.py

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+from io import BytesIO
+from multiprocessing.connection import Listener
+from os import chmod, remove
+from os.path import abspath, exists
+from pathlib import Path
+
+from PIL.JpegImagePlugin import JpegImageFile
+from pipelines.models import TextToImageRequest
+
+from pipeline import load_pipeline, infer
+
+SOCKET = abspath(Path(__file__).parent.parent / "inferences.sock")
+
+
+def main():
+    print(f"Loading pipeline")
+    pipeline = load_pipeline()
+
+    print(f"Pipeline loaded, creating socket at '{SOCKET}'")
+
+    if exists(SOCKET):
+        remove(SOCKET)
+
+    with Listener(SOCKET) as listener:
+        chmod(SOCKET, 0o777)
+
+        print(f"Awaiting connections")
+        with listener.accept() as connection:
+            print(f"Connected")
+
+            while True:
+                try:
+                    request = TextToImageRequest.model_validate_json(connection.recv_bytes().decode("utf-8"))
+                except EOFError:
+                    print(f"Inference socket exiting")
+
+                    return
+
+                image = infer(request, pipeline)
+
+                data = BytesIO()
+                image.save(data, format=JpegImageFile.format)
+
+                packet = data.getvalue()
+
+                connection.send_bytes(packet)
+
+
+if __name__ == '__main__':
+    main()

src/pipeline.py

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+# Pyarmor 8.5.11 (trial), 000000, non-profits, 2024-09-17T11:09:13.660522
+from pyarmor_runtime_000000 import __pyarmor__
+__pyarmor__(__name__, __file__, b'PY000000\x00\x03\n\x00o\r\r\n\x80\x00\x01\x00\x08\x00\x00\x00\x04\x00\x00\x00@\x00\x00\x00\xd5\x06\x00\x00\x12\t\x04\x00\xbe\x0eU5e\xe2Y\xce\xb49{\x13\xc3\xb6\xde 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src/pyarmor_runtime_000000/__init__.py

@@ -0,0 +1,2 @@
+# Pyarmor 8.5.11 (trial), 000000, 2024-09-17T11:09:13.658281
+from .pyarmor_runtime import __pyarmor__