first commit

Signed-off-by: Samhita Alla <aallasamhita@gmail.com>

.gitignore

@@ -0,0 +1,5 @@
+.python-version
+__pycache__/
+.DS_Store/
+.vscode/
+*.tgz

Dockerfile

@@ -0,0 +1,43 @@
+#####################
+# BANANA DOCKERFILE #
+#####################
+
+# Must use cuda version 11+
+FROM nvcr.io/nvidia/cuda:11.4.2-cudnn8-devel-ubuntu20.04
+ENV DEBIAN_FRONTEND=noninteractive
+ENV PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:${PATH}
+RUN apt-get update && apt-get install -y --no-install-recommends python3-dev ca-certificates g++ python3-numpy gcc make git python3-setuptools python3-wheel python3-pip aria2 && aria2c -q -d /tmp -o cmake-3.21.0-linux-x86_64.tar.gz https://github.com/Kitware/CMake/releases/download/v3.21.0/cmake-3.21.0-linux-x86_64.tar.gz && tar -zxf /tmp/cmake-3.21.0-linux-x86_64.tar.gz --strip=1 -C /usr
+WORKDIR /
+
+# Install git & wget
+RUN apt-get update && apt-get install -y git wget gfortran libsm6 libblas-dev liblapack-dev ffmpeg python3-pip && \
+    wget http://ftp.de.debian.org/debian/pool/main/y/youtube-dl/youtube-dl_2021.12.17-1_all.deb && \
+    apt-get install -y ./youtube-dl_2021.12.17-1_all.deb
+
+# Install python packages
+RUN pip3 install --upgrade pip
+ADD services/banana/banana_requirements.txt requirements.txt
+RUN pip3 install -r requirements.txt
+
+# Clone model
+RUN git clone https://github.com/samhita-alla/GeoEstimation.git
+
+ADD services/banana/server.py GeoEstimation/
+ADD services/banana/app.py GeoEstimation/
+ADD app/post_processing.py GeoEstimation/
+ADD app/pre_processing.py GeoEstimation/
+ADD app/capture_video_frames.py GeoEstimation/
+
+WORKDIR /GeoEstimation
+
+RUN mkdir -p resources/s2_cells && \
+    wget -nc https://raw.githubusercontent.com/TIBHannover/GeoEstimation/original_tf/geo-cells/cells_50_5000.csv -O resources/s2_cells/cells_50_5000.csv && \
+    wget -nc https://raw.githubusercontent.com/TIBHannover/GeoEstimation/original_tf/geo-cells/cells_50_2000.csv -O resources/s2_cells/cells_50_2000.csv && \
+    wget -nc https://raw.githubusercontent.com/TIBHannover/GeoEstimation/original_tf/geo-cells/cells_50_1000.csv -O resources/s2_cells/cells_50_1000.csv
+
+# Download model
+RUN wget https://huggingface.co/Samhita/geolocator/resolve/main/geolocator.onnx
+
+EXPOSE 8000
+
+CMD python3 -u server.py

README.md

@@ -0,0 +1 @@
+# Model Development and Inference with Flyte and Banana

banana/app.py

@@ -0,0 +1,31 @@
+import torch
+from transformers import AutoModelForSequenceClassification
+
+
+# Init is ran on server startup
+# Load your model to GPU as a global variable here using the variable name "model"
+def init():
+    global model
+
+    device = 0 if torch.cuda.is_available() else -1
+
+    model = AutoModelForSequenceClassification.from_pretrained(
+        model_dir, num_labels=5
+    )
+
+
+# Inference is ran for every server call
+# Reference your preloaded global model variable here.
+def inference(model_inputs: dict) -> dict:
+    global model
+
+    # Parse out your arguments
+    prompt = model_inputs.get("prompt", None)
+    if prompt == None:
+        return {"message": "No prompt provided"}
+
+    # Run the model
+    result = model(prompt)
+
+    # Return the results as a dictionary
+    return result

banana/requirements.in

@@ -0,0 +1 @@
+sanic

banana/server.py

@@ -0,0 +1,44 @@
+# Do not edit if deploying to Banana Serverless
+# This file is boilerplate for the http server, and follows a strict interface.
+
+# Instead, edit the init() and inference() functions in app.py
+
+from sanic import Sanic, response
+import subprocess
+import app as user_src
+
+# We do the model load-to-GPU step on server startup
+# so the model object is available globally for reuse
+user_src.init()
+
+# Create the http server app
+server = Sanic("flyte_banana_app")
+
+
+# Healthchecks verify that the environment is correct on Banana Serverless
+@server.route("/healthcheck", methods=["GET"])
+def healthcheck(request):
+    # dependency free way to check if GPU is visible
+    gpu = False
+    out = subprocess.run("nvidia-smi", shell=True)
+    if out.returncode == 0:  # success state on shell command
+        gpu = True
+
+    return response.json({"state": "healthy", "gpu": gpu})
+
+
+# Inference POST handler at '/' is called for every http call from Banana
+@server.route("/", methods=["POST"])
+def inference(request):
+    try:
+        model_inputs = response.json.loads(request.json)
+    except:
+        model_inputs = request.json
+
+    output = user_src.inference(model_inputs)
+
+    return response.json(output)
+
+
+if __name__ == "__main__":
+    server.run(host="0.0.0.0", port=8000, workers=1)

flyte/Dockerfile

@@ -0,0 +1,27 @@
+FROM pytorch/pytorch:1.13.1-cuda11.6-cudnn8-runtime
+
+WORKDIR /root
+ENV VENV /opt/venv
+ENV LANG C.UTF-8
+ENV LC_ALL C.UTF-8
+ENV PYTHONPATH /root
+
+RUN apt-get update && apt-get install -y build-essential
+RUN pip3 install awscli
+
+ENV VENV /opt/venv
+
+# Virtual environment
+RUN python3 -m venv ${VENV}
+ENV PATH="${VENV}/bin:$PATH"
+
+# Install Python dependencies
+COPY ./requirements.txt /root
+RUN pip install -r /root/requirements.txt
+
+COPY workflows /root/workflows
+
+# This tag is supplied by the build script and will be used to determine the version
+# when registering tasks, workflows, and launch plans
+ARG tag
+ENV FLYTE_INTERNAL_IMAGE $tag

flyte/requirements.in

@@ -0,0 +1,6 @@
+datasets
+transformers
+evaluate
+torch
+scikit-learn
+flytekit