In TF1-styled sessions, an explicit control dependency declaration is needed
to execute the tf.print operation. Refer to the documentation of
tf.print for more details.
Description
This is an identity op (behaves like tf.identity) with the side effect
of printing data when evaluating.
Args
input_
A tensor passed through this op.
data
A list of tensors to print out when op is evaluated.
message
A string, prefix of the error message.
first_n
Only log first_n number of times. Negative numbers log always;
this is the default.
summarize
Only print this many entries of each tensor. If None, then a
maximum of 3 elements are printed per input tensor.
name
A name for the operation (optional).
Returns
A Tensor. Has the same type and contents as input_.
sess = tf.compat.v1.Session()
with sess.as_default():
tensor = tf.range(10)
print_op = tf.print(tensor)
with tf.control_dependencies([print_op]):
out = tf.add(tensor, tensor)
sess.run(out)
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-01-23 UTC."],[],[]]