tf.debugging.check_numerics
    
    
      
    
    
      
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Checks a tensor for NaN and Inf values.
tf.debugging.check_numerics(
    tensor, message, name=None
)
When run, reports an InvalidArgument error if tensor has any values
that are not a number (NaN) or infinity (Inf). Otherwise, returns the input
tensor.
Example usage:
a = tf.Variable(1.0)
tf.debugging.check_numerics(a, message='')
b = tf.Variable(np.nan)
try:
  tf.debugging.check_numerics(b, message='Checking b')
except Exception as e:
  assert "Checking b : Tensor had NaN values" in e.message
c = tf.Variable(np.inf)
try:
  tf.debugging.check_numerics(c, message='Checking c')
except Exception as e:
  assert "Checking c : Tensor had Inf values" in e.message
| Args | 
|---|
| tensor | A Tensor. Must be one of the following types:bfloat16,half,float32,float64. | 
| message | A string. Prefix of the error message. | 
| name | A name for the operation (optional). | 
| Returns | 
|---|
| A Tensor. Has the same type astensor. | 
  
  
 
  
    
    
      
       
    
    
  
  
  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 2021-08-16 UTC.
  
  
  
    
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