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import random | |
import numpy as np | |
from bytewax import Dataflow, inputs, parse, run_cluster | |
def random_datapoints(): | |
for epoch in range(100): | |
if epoch % 5 == 0: | |
yield f'data', np.nan |
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#!/bin/bash | |
cat >Dockerfile <<EOL | |
FROM docker.registry.github.com/github/virga-wrapper/base-flask:latest | |
ADD model.py /working | |
EOL | |
curl -L https://gist.githubusercontent.com/awmatheson/f9fd5394e7addf962aabd29ff68b5035/raw/a65218b404fd6fee5dbabb12f506180e2c9a22ea/model.py -o model.py -s |
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class Model(): | |
"""This defines the necessary attributes for the model object | |
""" | |
def __init__(self): | |
# specify your data for fitting here | |
self.X_fit = [] | |
self.Y_fit = [] | |
self.model_store = "really.awesome.fast.model.store" | |
self.feature_store = "really.awesome.fast.feature.store" |