在同一个python进程中运行多个tensorflow会话时出错

我有一个具有此层次结构的项目:

project
├── libs
│   ├── __init__.py
│   ├── sub_lib1
│   │   ├── file1.py
│   │   └── __init__.py
│   └── sub_lib2
│       ├── file2.py
│       └── __init__.py
└── main.py

main.py的内容:

from libs.sub_lib1.file1 import func1
from libs.sub_lib2.file2 import func2


#some code

func1(parameters)

#some code

func2(parameters)

#some code

文件内容1.py:

#import some packages
import tensorflow as tf

def func1(parameters):

    #some code

    config = tf.ConfigProto()
    config.gpu_options.allow_growth=True
    tf.reset_default_graph()
    x = tf.placeholder(tf.float32,shape=[None,IMG_SIZE_ALEXNET,IMG_SIZE_ALEXNET,3])
    y_true = tf.placeholder(tf.float32,shape=[None,output_classes])
    with tf.Session(config=config) as session:
        saver.restore(session, "path to the model1")
        k = session.run([tf.nn.softmax(y_pred)], feed_dict={x:test_x , hold_prob1:1,hold_prob2:1})
    #some code
    return(the_results)

文件内容2.py:

#import some packages
import tensorflow as tf

def func2(parameters):

    #some code

    config = tf.ConfigProto()
    config.gpu_options.allow_growth=True
    sess = tf.Session(config=config)
    with gfile.GFile('path the model2', 'rb') as f:
        graph_def = tf.GraphDef()
        graph_def.ParseFromString(f.read())
        sess.graph.as_default()
        tf.import_graph_def(graph_def, name='')
    sess.run(tf.global_variables_initializer())
    #Get the needed tensors 
    input_img = sess.graph.get_tensor_by_name('Placeholder:0')
    output_cls_prob = sess.graph.get_tensor_by_name('Reshape_2:0')
    output_box_pred = sess.graph.get_tensor_by_name('rpn_bbox_pred/Reshape_1:0')
    #some code to prepare and resize the image
    cls_prob, box_pred = sess.run([output_cls_prob, output_box_pred], feed_dict={input_img: blobs['data']})
    #some code
    return(the_results)

运行main.py时,出现以下错误:

Traceback (most recent call last):
  File "main.py", line 46, in <module>
    func2(parameters)
  File "/home/hani/opti/libs/sub_lib2/file2.py", line 76, in func2
    cls_prob, box_pred = sess.run([output_cls_prob, output_box_pred], feed_dict={input_img: blobs['data']})
  File "/home/hani/.virtualenvs/opti/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 929, in run
    run_metadata_ptr)
  File "/home/hani/.virtualenvs/opti/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1128, in _run
    str(subfeed_t.get_shape())))
ValueError: Cannot feed value of shape (1, 600, 863, 3) for Tensor 'Placeholder:0', which has shape '(?, 227, 227, 3)'

经过一些调试,我在第二个模型中没有找到任何具有(?)的张量。,227,227,3)形状。相反,我发现张量x(由 x = tf.placeholder(tf.float32,shape=[None,IMG_SIZE_ALEXNET,IMG_SIZE_ALEXNET,3]) 在func1文件1)中有(?,227,227,3)形状。 我检查了输入的形状 input_img = sess.graph.get_tensor_by_name('Placeholder:0') 在来自文件2的func2中,我找到了它(?,227,227,3)当我运行main.py时。但是,当我运行file2.py时(通过运行 python file2.py ,我没有得到这个错误,我发现输入的形状是占位符形状:(???,3)。
所以我假设这两个模型都有相同的张量名称( 占位符 )当我在main.py中同时导入file1和file2时,占位符的第一个形状(?,227,227,3)保留在GPU内存中。
我试过 session.close() 在file1.py中,但它不起作用!
在同一进程中使用多个TensorFlow会话,而不会混淆它们,是否有更合适的方法?或者简单地说,如何在同一个Python进程中启动另一个前正确关闭TensorFlow会话?