tf.compat.v1.summary.scalar

Outputs a Summary protocol buffer containing a single scalar value.

tf.compat.v1.summary.scalar(
    name, tensor, collections=None, family=None
)

Migrate to TF2

This API is not compatible with eager execution or tf.function. To migrate to TF2, please use tf.summary.scalar instead. Please check Migrating tf.summary usage to TF 2.0 for concrete steps for migration. tf.summary.scalar can also log training metrics in Keras, you can check Logging training metrics in Keras for detials.

TF1 Arg Name	TF2 Arg Name	Note
`name`	`name`	-
`tensor`	`data`	-
-	`step`	Explicit int64-castable monotonic step value. If omitted, this defaults to `tf.summary.experimental.get_step()`.
`collections`	Not Supported	-
`family`	Removed	Please use `tf.name_scope` instead to manage summary name prefix.
-	`description`	Optional long-form `str` description for the summary. Markdown is supported. Defaults to empty.

The generated Summary has a Tensor.proto containing the input Tensor.

Args
`name`	A name for the generated node. Will also serve as the series name in TensorBoard.
`tensor`	A real numeric Tensor containing a single value.
`collections`	Optional list of graph collections keys. The new summary op is added to these collections. Defaults to `[GraphKeys.SUMMARIES]`.
`family`	Optional; if provided, used as the prefix of the summary tag name, which controls the tab name used for display on Tensorboard.

Returns
A scalar `Tensor` of type `string`. Which contains a `Summary` protobuf.

Raises
`ValueError`	If tensor has the wrong shape or type.