使用assign和eval（或sess.run）分配：
import numpy as npimport tensorflow as tfnpc = np.array([[1.,2.],[3.,4.]])tfc = tf.Variable(npc) # Use variablerow = np.array([[.1,.2]])with tf.Session() as sess: tf.initialize_all_variables().run() # need to initialize all variables print('tfc:n', tfc.eval()) print('npc:n', npc) for i in range(2): for j in range(2): npc[i,j] += row[0,j] tfc.assign(npc).eval() # assign_sub/assign_add is also available. print('modified tfc:n', tfc.eval()) print('modified npc:n', npc)它输出：
tfc: [[ 1. 2.] [ 3. 4.]]npc: [[ 1. 2.] [ 3. 4.]]modified tfc: [[ 1.1 2.2] [ 3.1 4.2]]modified npc: [[ 1.1 2.2] [ 3.1 4.2]]
