我正在尝试从train_step
找到以tf.report_uninitialized_variables(),
结尾的变量,但如果没有eager execution.
则无法在张量上进行迭代我得到你需要使用tf.map_fn,
但我不太了解它。
这就是我所拥有的:
variables = []
for s, t in zip(tf.report_uninitialized_variables().eval(session=sess),
tf.report_uninitialized_variables()):
if 'train_step' in s:
variables.append(t)
train_step_init = tf.variables_initializer(variables, name='train_step_init')
答案 0 :(得分:0)
原来我能做到:
variables = []
for i, v in enumerate(tf.global_variables()):
name = v.name.split(':')[0].encode('ASCII')
if name in sess.run(tf.report_uninitialized_variables()[0]):
if b'train_step' in name:
variables.append(v)
train_step_init = tf.variables_initializer(variables)
sess.run(train_step_init)