error_example.py

import tensorflow as tf
from tensorflow.keras.backend import placeholder

print(tf.__version__)
print(tf.executing_eagerly())

x = placeholder(shape=(1, 1), dtype=tf.float32, name='x')
t = placeholder(shape=(1, 1), dtype=tf.float32, name='t')

W0 = tf.Variable(tf.random.normal((1,20)), dtype=tf.float32)
W1 = tf.Variable(tf.random.normal((2,20)), dtype=tf.float32)
W2 = tf.Variable(tf.random.normal((20,1)), dtype=tf.float32)

# Working basic version

with tf.GradientTape() as g:
    g.watch(x)
    inpt = x
    print(inpt)
    ur = tf.sigmoid(tf.matmul(inpt, W0))
    ur = tf.sigmoid(tf.matmul(ur, W2))
u_t = g.gradient(ur, x)
print(u_t)

# Not working version

with tf.GradientTape() as g:
    g.watch(x)
    g.watch(t)
    inpt = tf.concat([x,t], 1)
    print(inpt)
    ur = tf.sigmoid(tf.matmul(inpt, W1))
    ur = tf.sigmoid(tf.matmul(ur, W2))
u_t = g.gradient(ur, x)
print(u_t)