How can I change the shape of a variable in TensorFlow?

Question

TensorFlow tutorial says that at creation time we need to specify the shape of tensors. That shape automatically becomes the shape of the tensor. It also says that TensorF

Answer 1

Documentation shows methods for reshaping. They are:

• reshape
• squeeze (removes dimensions of size 1 from the shape of a tensor)
• expand_dims (adds dimensions of size 1)

as well as bunch of methods to get shape, size, rank of your tensor. Probably the most used is reshape and here is a code example with a couple of edge cases (-1):

import tensorflow as tf

v1 = tf.Variable([
    [1, 2, 3, 4],
    [5, 6, 7, 8],
    [9, 10, 11, 12]
])
v2 = tf.reshape(v1, [2, 6])
v3 = tf.reshape(v1, [2, 2, -1])
v4 = tf.reshape(v1, [-1])
# v5 = tf.reshape(v1, [2, 4, -1]) will fail, because you can not find such an integer for -1
v6 = tf.reshape(v1, [1, 4, 1, 3, 1])
v6_shape = tf.shape(v6)
v6_squeezed = tf.squeeze(v6)
v6_squeezed_shape = tf.shape(v6_squeezed)

init = tf.initialize_all_variables()

sess = tf.Session()
sess.run(init)
a, b, c, d, e, f, g = sess.run([v2, v3, v4, v6, v6_shape, v6_squeezed, v6_squeezed_shape])
# print all variables to see what is there
print e # shape of v6
print g # shape of v6_squeezed