tf.summary.create_noop

Write a histogram summary.

tf.summary.histogram(
    name, data, step=None, buckets=None, description=None
)

Used in the notebooks

Used in the tutorials
Research tools

Arguments
`name`	A name for this summary. The summary tag used for TensorBoard will be this name prefixed by any active name scopes.
`data`	A `Tensor` of any shape. Must be castable to `float64`.
`step`	Explicit `int64`-castable monotonic step value for this summary. If omitted, this defaults to `tf.summary.experimental.get_step()`, which must not be None.
`buckets`	Optional positive `int`. The output will have this many buckets, except in two edge cases. If there is no data, then there are no buckets. If there is data but all points have the same value, then there is one bucket whose left and right endpoints are the same.
`description`	Optional long-form description for this summary, as a constant `str`. Markdown is supported. Defaults to empty.

Returns
True on success, or false if no summary was emitted because no default summary writer was available.

Raises
`ValueError`	if a default writer exists, but no step was provided and `tf.summary.experimental.get_step()` is None.

TensorFlow

tf.summary / create_noop_writer

Used in the notebooks

Arguments

Returns

Raises

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.summary / create_noop_writer

Used in the notebooks

Arguments

Returns

Raises