tf.data.experimental.cardinality
    
    
      
    
    
      
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Returns the cardinality of dataset, if known.
tf.data.experimental.cardinality(
    dataset
)
Used in the notebooks
The operation returns the cardinality of dataset. The operation may return
tf.data.experimental.INFINITE_CARDINALITY if dataset contains an infinite
number of elements or tf.data.experimental.UNKNOWN_CARDINALITY if the
analysis fails to determine the number of elements in dataset (e.g. when the
dataset source is a file).
dataset = tf.data.Dataset.range(42)
print(tf.data.experimental.cardinality(dataset).numpy())
42
dataset = dataset.repeat()
cardinality = tf.data.experimental.cardinality(dataset)
print((cardinality == tf.data.experimental.INFINITE_CARDINALITY).numpy())
True
dataset = dataset.filter(lambda x: True)
cardinality = tf.data.experimental.cardinality(dataset)
print((cardinality == tf.data.experimental.UNKNOWN_CARDINALITY).numpy())
True
| Returns | 
|---|
| A scalar tf.int64Tensorrepresenting the cardinality ofdataset. If
the cardinality is infinite or unknown, the operation returns the named
constantINFINITE_CARDINALITYandUNKNOWN_CARDINALITYrespectively. | 
  
  
 
  
    
    
      
       
    
    
  
  
  Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates. Some content is licensed under the numpy license.
  Last updated 2024-04-26 UTC.
  
  
  
    
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