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A context manager for use when defining a Python op.
tf.name_scope(
    name
)
  This context manager pushes a name scope, which will make the name of all operations added within it have a prefix.
For example, to define a new Python op called my_op:
def my_op(a, b, c, name=None):
  with tf.name_scope("MyOp") as scope:
    a = tf.convert_to_tensor(a, name="a")
    b = tf.convert_to_tensor(b, name="b")
    c = tf.convert_to_tensor(c, name="c")
    # Define some computation that uses `a`, `b`, and `c`.
    return foo_op(..., name=scope)
 When executed, the Tensors a, b, c, will have names MyOp/a, MyOp/b, and MyOp/c.
Inside a tf.function, if the scope name already exists, the name will be made unique by appending _n. For example, calling my_op the second time will generate MyOp_1/a, etc.
| Args | |
|---|---|
| name | The prefix to use on all names created within the name scope. | 
| Raises | |
|---|---|
| ValueError | If name is not a string. | 
| Attributes | |
|---|---|
| name | |
__enter____enter__()
Start the scope block.
| Returns | |
|---|---|
| The scope name. | 
__exit__
__exit__(
    type_arg, value_arg, traceback_arg
)
  
    © 2022 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 4.0.
Code samples licensed under the Apache 2.0 License.
    https://www.tensorflow.org/versions/r2.9/api_docs/python/tf/name_scope