tf.math.bincount | TensorFlow v2.0.0 (original) (raw)
tf.math.bincount
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Counts the number of occurrences of each value in an integer array.
tf.math.bincount(
arr, weights=None, minlength=None, maxlength=None, dtype=tf.dtypes.int32,
name=None
)
If minlength and maxlength are not given, returns a vector with lengthtf.reduce_max(arr) + 1 if arr is non-empty, and length 0 otherwise. If weights are non-None, then index i of the output stores the sum of the value in weights at each index where the corresponding value in arr isi.
values = tf.constant([1,1,2,3,2,4,4,5])
tf.math.bincount(values) #[0 2 2 1 2 1]
Vector length = Maximum element in vector values is 5. Adding 1, which is 6 will be the vector length.
Each bin value in the output indicates number of occurrences of the particular index. Here, index 1 in output has a value 2. This indicates value 1 occurs two times in values.
values = tf.constant([1,1,2,3,2,4,4,5])
weights = tf.constant([1,5,0,1,0,5,4,5])
tf.math.bincount(values, weights=weights) #[0 6 0 1 9 5]
Bin will be incremented by the corresponding weight instead of 1. Here, index 1 in output has a value 6. This is the summation of weights corresponding to the value in values.
| Args | |
|---|---|
| arr | An int32 tensor of non-negative values. |
| weights | If non-None, must be the same shape as arr. For each value inarr, the bin will be incremented by the corresponding weight instead of 1. |
| minlength | If given, ensures the output has length at least minlength, padding with zeros at the end if necessary. |
| maxlength | If given, skips values in arr that are equal or greater thanmaxlength, ensuring that the output has length at most maxlength. |
| dtype | If weights is None, determines the type of the output bins. |
| name | A name scope for the associated operations (optional). |
| Returns |
|---|
| A vector with the same dtype as weights or the given dtype. The bin values. |
| Raises |
|---|
| InvalidArgumentError if negative values are provided as an input. |