deploy_sklearn.py

import ray
from ray import serve

# Connect to the running Ray Serve instance.
ray.init(address='auto', ignore_reinit_error=True)
serve.init()
# Deploy the model.
serve.create_backend("sklearn_backend", SKLearnBackend)
serve.create_endpoint("sentiment_endpoint", backend="sklearn_backend", route="/sentiment")

deploy_transformers.py

import ray
from ray import serve
ray.init(address="auto", ignore_reinit_error=True)
serve.init()
serve.create_backend("pytorch_backend", PyTorchBackend)
serve.set_traffic("sentiment_endpoint", {"pytorch_backend": 1.0})

sklearn.py

import joblib
import s3fs

class SKLearnBackend:
    def __init__(self):
        fs = s3fs.S3FileSystem(anon=True)
        with fs.open('ray-serve-blog/unigram_vectorizer.joblib', 'rb') as f:
            self.vectorizer = joblib.load(f)
        with fs.open('ray-serve-blog/unigram_tf_idf_transformer.joblib',
 'rb') as f:
            self.preprocessor = joblib.load(f)
        with fs.open('ray-serve-blog/unigram_tf_idf_classifier.joblib',
 'rb') as f:
            self.classifier = joblib.load(f)
    def __call__(self, request):
        vectorized = self.vectorizer.transform([request.data])
        transformed = self.preprocessor.transform(vectorized)
        [result] = self.classifier.predict(transformed)
        if result == 1:
            return 'POSITIVE'
        else:
            return 'NEGATIVE'

start_serve.py

import ray
from ray import serve
ray.init(address='auto') # Connect to the running Ray cluster.
serve.init() # Start the Ray Serve processes within the Ray cluster.

test_request.py

import requests
input_text = "Ray Serve eases the pain of model serving"
result = requests.get("http://127.0.0.1:8000/sentiment", data=input_text).text
print("Result for '{}': {}".format(input_text, result))

transformers.py

from transformers import pipeline
class PyTorchBackend:
 def __init__(self):
 self.classifier = pipeline("sentiment-analysis")
 def __call__(self, request):
 [result] = self.classifier(str(request.data))
 return result["label"]