In [2]:

    

import tensorflow as tf

g = tf.Graph()

with g.as_default():
    X = tf.placeholder(tf.float32, name="X")
    
    W1 = tf.placeholder(tf.float32, name="W1")
    b1 = tf.placeholder(tf.float32, name="b1")
    
    a1 = tf.nn.relu(tf.matmul(X, W1) + b1)
    
    W2 = tf.placeholder(tf.float32, name="W2")
    b2 = tf.placeholder(tf.float32, name="b2")
    
    a2 = tf.nn.relu(tf.matmul(a1, W2) + b2)

    W3 = tf.placeholder(tf.float32, name="W3")
    b3 = tf.placeholder(tf.float32, name="b3")
    
    y_hat = tf.matmul(a2, W3) + b3
    
tf.summary.FileWriter("logs", g).close()


    

In [3]:

    

g = tf.Graph()

with g.as_default():
    X = tf.placeholder(tf.float32, name="X")
    
    with tf.name_scope("Layer1"):
        W1 = tf.placeholder(tf.float32, name="W1")
        b1 = tf.placeholder(tf.float32, name="b1")

        a1 = tf.nn.relu(tf.matmul(X, W1) + b1)
    
    with tf.name_scope("Layer2"):
        W2 = tf.placeholder(tf.float32, name="W2")
        b2 = tf.placeholder(tf.float32, name="b2")

        a2 = tf.nn.relu(tf.matmul(a1, W2) + b2)

    with tf.name_scope("Layer3"):
        W3 = tf.placeholder(tf.float32, name="W3")
        b3 = tf.placeholder(tf.float32, name="b3")

        y_hat = tf.matmul(a2, W3) + b3
    
tf.summary.FileWriter("logs", g).close()


    

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