mirror of
https://github.com/vale981/ray
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78 lines
2.1 KiB
Python
78 lines
2.1 KiB
Python
# fmt: off
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# __doc_import_begin__
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from ray import serve
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import pickle
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import json
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import numpy as np
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import os
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import tempfile
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from sklearn.datasets import load_iris
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from sklearn.ensemble import GradientBoostingClassifier
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from sklearn.metrics import mean_squared_error
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# __doc_import_end__
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# fmt: on
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# __doc_instantiate_model_begin__
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model = GradientBoostingClassifier()
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# __doc_instantiate_model_end__
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# __doc_data_begin__
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iris_dataset = load_iris()
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data, target, target_names = (
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iris_dataset["data"],
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iris_dataset["target"],
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iris_dataset["target_names"],
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)
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np.random.shuffle(data), np.random.shuffle(target)
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train_x, train_y = data[:100], target[:100]
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val_x, val_y = data[100:], target[100:]
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# __doc_data_end__
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# __doc_train_model_begin__
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model.fit(train_x, train_y)
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print("MSE:", mean_squared_error(model.predict(val_x), val_y))
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# Save the model and label to file
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MODEL_PATH = os.path.join(
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tempfile.gettempdir(), "iris_model_gradient_boosting_classifier.pkl"
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)
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LABEL_PATH = os.path.join(tempfile.gettempdir(), "iris_labels.json")
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with open(MODEL_PATH, "wb") as f:
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pickle.dump(model, f)
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with open(LABEL_PATH, "w") as f:
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json.dump(target_names.tolist(), f)
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# __doc_train_model_end__
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# __doc_define_servable_begin__
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@serve.deployment(route_prefix="/classifier")
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class BoostingModel:
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def __init__(self, model_path, label_path):
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with open(model_path, "rb") as f:
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self.model = pickle.load(f)
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with open(label_path) as f:
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self.label_list = json.load(f)
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async def __call__(self, starlette_request):
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payload = await starlette_request.json()
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print("Worker: received starlette request with data", payload)
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input_vector = [
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payload["sepal length"],
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payload["sepal width"],
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payload["petal length"],
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payload["petal width"],
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]
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prediction = self.model.predict([input_vector])[0]
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human_name = self.label_list[prediction]
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return {"result": human_name}
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# __doc_define_servable_end__
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# __doc_deploy_begin__
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app = BoostingModel.bind(MODEL_PATH, LABEL_PATH)
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# __doc_deploy_end__
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