tf.contrib.metrics.streaming_concat( values, axis=0, max_size=None, metrics_collections=None, updates_collections=None, name=None )
See the guide: Metrics (contrib) > Metric
Concatenate values along an axis across batches.
streaming_concat creates two local variables,
size, that are used to store concatenated values. Internally,
array is used as storage for a dynamic array (if
None), which ensures that updates can be run in amortized constant time.
For estimation of the metric over a stream of data, the function creates an
update_op operation that appends the values of a tensor and returns the length of the concatenated axis.
This op allows for evaluating metrics that cannot be updated incrementally using the same framework as other streaming metrics.
Tensorto concatenate. Rank and the shape along all axes other than the axis to concatenate along must be statically known.
axis: optional integer axis to concatenate along.
max_size: optional integer maximum size of
valuealong the given axis. Once the maximum size is reached, further updates are no-ops. By default, there is no maximum size: the array is resized as necessary.
metrics_collections: An optional list of collections that
valueshould be added to.
updates_collections: An optional list of collections
update_opshould be added to.
name: An optional variable_scope name.
Tensorrepresenting the concatenated values.
update_op: An operation that concatenates the next values.
valuesdoes not have a statically known rank,
axisis not in the valid range or the size of
valuesis not statically known along any axis other than
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