将一个图表复制到另一个图表
将一个图表复制到另一个图表
提问于 2019-10-26 14:45:45
我想将一个加载的图复制到另一个图中。这就是我想要做的
import tensorflow as tf
import numpy as np
import cv2
input_names = ['image_tensor']
pb_fname1 = "/Users/vedanshu/frozen_graph/ssd_tomato_l1_frozen_graph.pb"
def get_frozen_graph(graph_file):
"""Read Frozen Graph file from disk."""
with tf.gfile.FastGFile(graph_file, "rb") as f:
graph_def = tf.GraphDef()
graph_def.ParseFromString(f.read())
return graph_def
trt_graph1 = get_frozen_graph(pb_fname1)
detection_graph1 = tf.Graph()
with detection_graph1.as_default():
tf.import_graph_def(trt_graph1, name='')
tf_sess1 = tf.Session(graph=detection_graph1)
tf_input1 = tf_sess1.graph.get_tensor_by_name(input_names[0] + ':0')
tf_scores1 = tf_sess1.graph.get_tensor_by_name('detection_scores:0')
tf_boxes1 = tf_sess1.graph.get_tensor_by_name('detection_boxes:0')
tf_classes1 = tf_sess1.graph.get_tensor_by_name('detection_classes:0')
tf_num_detections1 = tf_sess1.graph.get_tensor_by_name('num_detections:0')现在，我想将tf_input1、tf_scores1、tf_boxes1、tf_num_detections1复制到另一个图中。目前我正在尝试使用copy_op_to_graph (废弃的)，如下所示：
detection_graph2 = tf.Graph()
namespace = "Ved"
copied_variables = []
tf_num_detections1_copy = tf.contrib.copy_graph.copy_op_to_graph(tf_num_detections1, detection_graph2,copied_variables, namespace)但这给我抛出了以下错误：
WARNING: The TensorFlow contrib module will not be included in TensorFlow 2.0.
For more information, please see:
* https://github.com/tensorflow/community/blob/master/rfcs/20180907-contrib-sunset.md
* https://github.com/tensorflow/addons
If you depend on functionality not listed there, please file an issue.
---------------------------------------------------------------------------
RecursionError Traceback (most recent call last)
<ipython-input-9-807d2dc0bb17> in <module>
3 # grid_roies_copy = tf.contrib.copy_graph.copy_op_to_graph(grid_roies, detection_graph2, copied_variables, namespace)
4 # tf_input1_copy = tf.contrib.copy_graph.copy_op_to_graph(tf_input1, detection_graph2,copied_variables, namespace)
----> 5 tf_num_detections1_copy = tf.contrib.copy_graph.copy_op_to_graph(tf_num_detections1, detection_graph2,copied_variables, namespace)
/usr/local/lib/python3.7/site-packages/tensorflow/contrib/copy_graph/python/util/copy_elements.py in copy_op_to_graph(org_instance, to_graph, variables, scope)
167 #output.
168 op = org_instance.op
--> 169 new_op = copy_op_to_graph(op, to_graph, variables, scope)
170 output_index = op.outputs.index(org_instance)
171 new_tensor = new_op.outputs[output_index]
/usr/local/lib/python3.7/site-packages/tensorflow/contrib/copy_graph/python/util/copy_elements.py in copy_op_to_graph(org_instance, to_graph, variables, scope)
195 #If it has inputs, call this function recursively on each.
196 new_inputs = [
--> 197 copy_op_to_graph(x, to_graph, variables, scope) for x in op.inputs
198 ]
199
/usr/local/lib/python3.7/site-packages/tensorflow/contrib/copy_graph/python/util/copy_elements.py in <listcomp>(.0)
195 #If it has inputs, call this function recursively on each.
196 new_inputs = [
--> 197 copy_op_to_graph(x, to_graph, variables, scope) for x in op.inputs
198 ]
199
... last 3 frames repeated, from the frame below ...
/usr/local/lib/python3.7/site-packages/tensorflow/contrib/copy_graph/python/util/copy_elements.py in copy_op_to_graph(org_instance, to_graph, variables, scope)
167 #output.
168 op = org_instance.op
--> 169 new_op = copy_op_to_graph(op, to_graph, variables, scope)
170 output_index = op.outputs.index(org_instance)
171 new_tensor = new_op.outputs[output_index]
RecursionError: maximum recursion depth exceeded while calling a Python object回答 1
Stack Overflow用户
发布于 2019-10-26 21:51:42
多亏了答案here，我才能用export_meta_graph和import_scoped_meta_graph解决这个问题。
import tensorflow as tf
import numpy as np
import cv2
input_names = ['image_tensor']
pb_fname1 = "/Users/vedanshu/frozen_graph/ssd_tomato_l1_frozen_graph.pb"
def get_frozen_graph(graph_file):
"""Read Frozen Graph file from disk."""
with tf.gfile.FastGFile(graph_file, "rb") as f:
graph_def = tf.GraphDef()
graph_def.ParseFromString(f.read())
return graph_def
trt_graph1 = get_frozen_graph(pb_fname1)
detection_graph1 = tf.Graph()
with detection_graph1.as_default():
tf.import_graph_def(trt_graph1, name='')
tf_sess1 = tf.Session(graph=detection_graph1)
from tensorflow.python.framework import meta_graph
graph = tf.get_default_graph()
tf_sess_main = tf.Session(graph=graph)
meta_graph1 = tf.train.export_meta_graph(graph=detection_graph1)
meta_graph.import_scoped_meta_graph(meta_graph1, import_scope='ved_graph1',)
# Print the name of all Ops in default graph
for op in tf.get_default_graph().get_operations():
print(op.name)
print()现在我可以将张量从一个图导入到另一个图，如下所示：
tf_input1 = graph.get_tensor_by_name('ved_graph1/image_tensor:0')
tf_scores1 = graph.get_tensor_by_name('ved_graph1/detection_scores:0')
tf_boxes1 = graph.get_tensor_by_name('ved_graph1/detection_boxes:0')
tf_classes1 = graph.get_tensor_by_name('ved_graph1/detection_classes:0')
tf_num_detections1 = graph.get_tensor_by_name('ved_graph1/num_detections:0')所有上述张量都会导入到默认图中。
页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：
https://stackoverflow.com/questions/58568663
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