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|
Computes number of nonzero elements across dimensions of a tensor. (deprecated arguments) (deprecated arguments)
tf.compat.v1.count_nonzero(
input_tensor=None,
axis=None,
keepdims=None,
dtype=tf.dtypes.int64,
name=None,
reduction_indices=None,
keep_dims=None,
input=None
)
Reduces input_tensor 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.
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
For example:
x = tf.constant(["", "a", " ", "b", ""])
tf.math.count_nonzero(x) # 3, with "a", " ", and "b" as nonzero strings.
Args |
|---|
input_tensor
bool, or
string.
axis
None (the default), reduces all
dimensions. Must be in the range [-rank(input_tensor),
rank(input_tensor)).
keepdims
dtype
tf.int64.
name
reduction_indices
keep_dims
keepdims.
input
Returns | |
|---|---|
| The reduced tensor (number of nonzero values). |
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