22-p22_sin_cos_sqr

import math
import tensorflow as tf
import numpy as np
from matplotlib import pyplot


HIDDEN_UNITS = 200
SAMPLES = 200


def sqrt(a_value, b_value, lr=0.01, epoches=2000):
    g = tf.Graph()
    with g.as_default():
        a = tf.placeholder(tf.float32, [None], 'a')
        a2 = tf.reshape(a, [-1, 1])  # [-1, 1]
        # w = tf.get_variable('w', [1, 200], tf.float32)
        # b = tf.get_variable('b', [200], tf.float32)
        # y = tf.matmul(a2, w) + b  # [-1, 200]
        y = tf.layers.dense(a2, HIDDEN_UNITS, activation=tf.nn.relu)  # [-1, 200]

        # w = tf.get_variable('w2', [200, 1], tf.float32)
        # b = tf.get_variable('b2', [1], tf.float32)
        # y = tf.matmul(y, w) + b  # [-1, 1]
        y_predict = tf.layers.dense(y, 4, use_bias=False)  # [-1, 3]

        b = tf.placeholder(tf.float32, [None, 4], 'b')  # [-1, 3]
        loss = tf.reduce_mean(tf.square(y_predict - b))

        opt = tf.train.AdamOptimizer(lr)
        train_op = opt.minimize(loss)

    with tf.Session(graph=g) as session:
        session.run(tf.global_variables_initializer())
        for _ in range(epoches):
            session.run(train_op, {a: a_value, b: b_value})
        return session.run(y_predict, {a: a_value})


if __name__ == '__main__':
    a_value = np.random.uniform(-math.pi, math.pi, [SAMPLES])
    a_value = np.array(sorted(a_value))
    b_value = [np.sin(a_value), np.cos(a_value), a_value**2/10, np.sqrt(np.abs(a_value))]
    b_value = np.transpose(b_value, [1, 0])  # [-1, 3]

    predict = sqrt(a_value, b_value)

    # pyplot.plot(a_value, b_value)
    pyplot.plot(a_value, predict)
    pyplot.show()

D:\Anaconda\python.exe D:/AI20/06_codes/deeplearning_20/p22_sin_cos_sqr.py
2020-02-27 18:09:08.258672: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2

Process finished with exit code 0