Print the specified inputs.

# Aliases:

• tf.compat.v1.print
• tf.compat.v2.print

 tf.print(
    *inputs,
    **kwargs
)

# Used in the guide:

• Betterperformancewith tf.function and AutoGraph
• Using the SavedModelformat

# Used in the tutorials:

• Betterperformancewith tf.function A TensorFlow operator that prints the specified inputs to a desired output stream or logging level. The inputs may be dense or sparse Tensors, primitive python objects, data structures that contain tensors, and printable Python objects. Printed tensors will recursively show the first and last elements of each dimension to summarize.

# Example:

Single-input usage:

 tensor = tf.range(10)
tf.print(tensor, output_stream=sys.stderr)

(This prints "[0 1 2 ... 7 8 9]" to sys.stderr) Multi-input usage:

 tensor = tf.range(10)
tf.print("tensors:", tensor, {2: tensor * 2}, output_stream=sys.stdout)

(This prints "tensors: [0 1 2 ... 7 8 9] {2: [0 2 4 ... 14 16 18]}" to sys.stdout) Changing the input separator:

 tensor_a = tf.range(2)
tensor_b = tensor_a * 2
tf.print(tensor_a, tensor_b, output_stream=sys.stderr, sep=',')

(This prints "[0 1],[0 2]" to sys.stderr) tf.functionUsage in a :

 @tf.function
def f():
    tensor = tf.range(10)
    tf.print(tensor, output_stream=sys.stderr)
    return tensor

range_tensor = f()

(This prints "[0 1 2 ... 7 8 9]" to sys.stderr) tf.function@compatibility(TF 1.x Graphs and Sessions) In graphs manually created outside of , this method returns the created TF operator that prints the data. To make sure the operator runs, users need to pass the produced op to tf.compat.v1.Session's run method, or to use the op as a control dependency for executed ops by specifying with tf.compat.v1.control_dependencies([print_op]). @end_compatibility

Compatibility usage in TF 1.x graphs: (This prints "tensors: [0 1 2 ... 7 8 9] {2: [0 2 4 ... 14 16 18]}" to sys.stdout)

# Args:

# Returns:

tf.compat.v1None when executing eagerly. During graph tracing this returns a TF operator that prints the specified inputs in the specified output stream or logging level. This operator will be automatically executed except inside of graphs and sessions.

# Raises:

• ValueError: If an unsupported output stream is specified.

# Python2 Compatibility

In python 2.7, make sure to import the following: from __future__ import print_function