tf.compat.v1.flags.mark_bool_flags_as_mutual

Ensures that only one flag among flag_names is not None.

View aliases

Compat aliases for migration

tf.compat.v1.app.flags.mark_flags_as_mutual_exclusive

tf.compat.v1.flags.mark_flags_as_mutual_exclusive(
    flag_names, required=False, flag_values=_flagvalues.FLAGS
)

Important note: This validator checks if flag values are None, and it does not distinguish between default and explicit values. Therefore, this validator does not make sense when applied to flags with default values other than None, including other false values (e.g. False, 0, '', []). That includes multi flags with a default value of [] instead of None.

Args
`flag_names`	[str], names of the flags.
`required`	bool. If true, exactly one of the flags must have a value other than None. Otherwise, at most one of the flags can have a value other than None, and it is valid for all of the flags to be None.
`flag_values`	flags.FlagValues, optional FlagValues instance where the flags are defined.

TensorFlow

tf.compat / v1 / v1.flags.mark_bool_flags_as_mutual_exclusive

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Args

TensorFlow

tf

tf.audio

tf.autograph

tf.bitwise

tf.compat

tf.config

tf.data

tf.debugging

tf.distribute

tf.dtypes

tf.errors

tf.estimator

tf.experimental

tf.feature_column

tf.graph_util

tf.image

tf.initializers

tf.io

tf.keras

tf.linalg

tf.lite

tf.lookup

tf.losses

tf.math

tf.metrics

tf.nest

tf.nn

tf.optimizers

tf.quantization

tf.queue

tf.ragged

tf.random

tf.raw_ops

tf.saved_model

tf.sets

tf.signal

tf.sparse

tf.strings

tf.summary

tf.sysconfig

tf.test

tf.tpu

tf.train

tf.version

tf.xla

tf.compat / v1 / v1.flags.mark_bool_flags_as_mutual_exclusive

View aliases

Args