Created
December 11, 2017 18:56
-
-
Save abaranovskis-redsamurai/811d090a8e8636744e854ba037519ada to your computer and use it in GitHub Desktop.
TensorFlow Linear Regression Model Access with Custom REST API using Flask
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
import numpy as np | |
import tensorflow as tf | |
from flask import Flask, jsonify, request | |
from flask_cors import CORS, cross_origin | |
app = Flask(__name__) | |
CORS(app) | |
@app.route("/redsam/api/v0.1/points", methods=['GET', 'POST']) | |
def linear_regression_train(): | |
# CUSTOMIZABLE: Collect/Prepare data | |
steps = 100 | |
learn_rate = 0.0001 | |
if request.method == 'POST': | |
steps = request.json['steps'] | |
learn_rate = request.json['learnrate'] | |
# Model linear regression y = Wx + b | |
x = tf.placeholder(tf.float32, [None, 1]) | |
W = tf.Variable(tf.zeros([1,1])) | |
b = tf.Variable(tf.zeros([1])) | |
product = tf.matmul(x,W) | |
y = product + b | |
y_ = tf.placeholder(tf.float32, [None, 1]) | |
# Cost function sum((y_-y)**2) | |
cost = tf.reduce_mean(tf.square(y_-y)) | |
# Training using Gradient Descent to minimize cost | |
train_step = tf.train.GradientDescentOptimizer(learn_rate).minimize(cost) | |
sess = tf.Session() | |
init = tf.initialize_all_variables() | |
sess.run(init) | |
all_points = []; | |
eq_vals = []; | |
for i in range(steps): | |
# Create fake data for y = W.x + b where W = 2, b = 0 | |
xs = np.array([[i]]) | |
ys = np.array([[2*i]]) | |
# Train | |
feed = { x: xs, y_: ys } | |
sess.run(train_step, feed_dict=feed) | |
all_points.append({"x": xs[0][0], "y": ys[0][0]}); | |
# NOTE: W should be close to 2, and b should be close to 0 | |
eq_vals.append({'w': str(sess.run(W)[0][0]), "b": str(sess.run(b)[0]), | |
"cost": '{0:f}'.format(sess.run(cost, feed_dict=feed))}); | |
response = jsonify(results=[eq_vals, all_points]) | |
return response | |
if __name__ == "__main__": | |
app.run(host='0.0.0.0') |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment