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import tensorflow as tf
tf.compat.v1.disable_eager_execution()
x = tf.compat.v1.placeholder(shape=[1, None], dtype=tf.int32, name='Hole')
i = tf.compat.v1.placeholder(shape=[1, None], dtype=tf.int32, name='Hole_2')
def c(ii):
rs = tf.compat.v1.shape(ii)
r1 = rs[1]
return tf.compat.v1.less(r1, 10)
def b(ii):
return tf.concat([ii, x], axis=1)
# this loop changes i's shape from [1, 0] -> [1, 1] -> [1, 2] -> ... -> [1, 10]
r = tf.compat.v1.while_loop(
c, b, [i], name="While", shape_invariants=[tf.TensorShape([1, None])])
output = tf.compat.v1.identity(r, name="Output")
# by adding the following code, [[123 1 2 3 1 2 3 1 2 3]] and (1, 10) will be printed
#
'''
import numpy as np
i_val = np.array([[123]], dtype=np.int32)
x_val = np.array([[1, 2, 3]], dtype=np.int32)
with tf.compat.v1.Session() as sess:
result = sess.run(r, feed_dict={x:x_val, i:i_val})
print(result)
print(result.shape)
'''
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