tf.keras.ops.bincount

Count the number of occurrences of each value in a tensor of integers.

tf.keras.ops.bincount(
    x, weights=None, minlength=0, sparse=False
)

x Input tensor. It must be of dimension 1, and it must only contain non-negative integer(s).
weights Weight tensor. It must have the same length as x. The default value is None. If specified, x is weighted by it, i.e. if n = x[i], out[n] += weight[i] instead of the default behavior out[n] += 1.
minlength An integer. The default value is 0. If specified, there will be at least this number of bins in the output tensor. If greater than max(x) + 1, each value of the output at an index higher than max(x) is set to 0.
sparse Whether to return a sparse tensor; for backends that support sparse tensors.

1D tensor where each element gives the number of occurrence(s) of its index value in x. Its length is the maximum between max(x) + 1 and minlength.

Examples:

x = keras.ops.array([1, 2, 2, 3], dtype="uint8")
keras.ops.bincount(x)
array([0, 1, 2, 1], dtype=int32)
weights = x / 2
weights
array([0.5, 1., 1., 1.5], dtype=float64)
keras.ops.bincount(x, weights=weights)
array([0., 0.5, 2., 1.5], dtype=float64)
minlength = (keras.ops.max(x).numpy() + 1) + 2 # 6
keras.ops.bincount(x, minlength=minlength)
array([0, 1, 2, 1, 0, 0], dtype=int32)