tf.math.count_nonzero      View source on GitHub    Computes number of nonzero elements across dimensions of a tensor. 
tf.math.count_nonzero(
    input,
    axis=None,
    keepdims=None,
    dtype=tf.dtypes.int64,
    name=None
)
 Reduces input along the dimensions given in axis. Unless keepdims is true, the rank of the tensor is reduced by 1 for each entry in axis. If keepdims is true, the reduced dimensions are retained with length 1. If axis has no entries, all dimensions are reduced, and a tensor with a single element is returned. 
Note: Floating point comparison to zero is done by exact floating point equality check. Small values are not rounded to zero for purposes of the nonzero check.
 For example: x = tf.constant([[0, 1, 0], [1, 1, 0]])
tf.math.count_nonzero(x)  # 3
tf.math.count_nonzero(x, 0)  # [1, 2, 0]
tf.math.count_nonzero(x, 1)  # [1, 2]
tf.math.count_nonzero(x, 1, keepdims=True)  # [[1], [2]]
tf.math.count_nonzero(x, [0, 1])  # 3


Note: Strings are compared against zero-length empty string "". Any string with a size greater than zero is already considered as nonzero.
 For example: x = tf.constant(["", "a", "  ", "b", ""])
tf.math.count_nonzero(x) # 3, with "a", "  ", and "b" as nonzero strings.

 


 Args
  input   The tensor to reduce. Should be of numeric type, bool, or string.  
  axis   The dimensions to reduce. If None (the default), reduces all dimensions. Must be in the range [-rank(input), rank(input)).  
  keepdims   If true, retains reduced dimensions with length 1.  
  dtype   The output dtype; defaults to tf.int64.  
  name   A name for the operation (optional).   
 


 Returns   The reduced tensor (number of nonzero values).  
  

    
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