我试图在tensorflow中绘制图形，但遇到以下错误：
ValueError：Tensor（transformation_0 / output / output：0“，shape =（），dtype = float32）必须与Tensor在同一个图形中（”variables / total_output：0“，shape =（），dtype = float32_ref）
这是代码：
import tensorflow as tf
# Explicitly create a Graph object
graph =tf.Graph()
with graph.as_default():
with tf.name_scope("variables"):
# Variable to keep track of how many times the graph has been run
global_step = tf.Variable(0, dtype=tf.int32, trainable=False, name="global_step")
# Variable that keeps track of the sum of all output values over time:
total_output = tf.Variable(0.0, dtype=tf.float32, trainable=False, name="total_output")
# Primary transformation Operations
with tf.name_scope("transformation"):
# Separate input layer
with tf.name_scope("input"):
# Create input placeholder- takes in a Vector
a = tf.placeholder(tf.float32, shape=[None],name="input_placeholder_a")
# Separate middle layer
with tf.name_scope("intermediate_layer"):
b = tf.reduce_prod(a, name="product_b")
c = tf.reduce_sum(a, name="sum_c")
# Separate output layer
with tf.name_scope("output"):
output = tf.add(b, c, name="output")
with tf.name_scope("update"):
# Increments the total_output Variable by the latest output
update_total = total_output.assign_add(output)
# Increments the above `global_step` Variable, should be run whenever #the graph is run
increment_step = global_step.assign_add(1)
# Summary Operations
with tf.name_scope("summaries"):
avg = tf.div(update_total, tf.cast(increment_step, tf.float32), name="average")
# Creates summaries for output node
tf.scalar_summary(b'Output', output, name="output_summary")
tf.scalar_summary(b'Sum of outputs over time', update_total, name="total_summary")
tf.scalar_summary(b'Average of outputs over time', avg, name="average_summary")
# Global Variables and Operations
with tf.name_scope("global_ops"):
# Initialization Op
init = tf.initialize_all_variables()
# Merge all summaries into one Operation
merged_summaries = tf.merge_all_summaries()
# Start a Session, using the explicitly created Graph
sess = tf.Session(graph=graph)
# Open a SummaryWriter to save summaries
writer = tf.train.SummaryWriter('./improved_graph', graph)
# Initialize Variables
sess.run(init)
def run_graph(input_tensor):
"""
Helper function; runs the graph with given input tensor and saves summaries
"""
feed_dict = {a: input_tensor}
_, step, summary = sess.run([output, increment_step, merged_summaries],
feed_dict=feed_dict)
writer.add_summary(summary, global_step=step)
# Run the graph with various inputs
run_graph([2,8])
run_graph([3,1,3,3])
run_graph([8])
run_graph([1,2,3])
run_graph([11,4])
run_graph([4,1])
run_graph([7,3,1])
run_graph([6,3])
run_graph([0,2])
run_graph([4,5,6])
# Write the summaries to disk
writer.flush()
# Close the SummaryWriter
writer.close()
# Close the session
sess.close()
2 回答
你有没有尝试过：
1）改变
对于：
2）并删除：
我有同样的错误，这些变化解决了它 .
试试这个，删除shape = [无]