TensorFlow is open-source Python library designed by Google to develop Machine Learning models and deep learning neural networks. bincount() is present in TensorFlow’s math module. It is used to count occurrences of a each number in integer array.
Syntax: tensorflow.math.bincount( arr, weights, minlength, maxlength, dtype, name)
- arr: It’s tensor of dtype int32 with non-negative values.
- weights(optional): It’s a tensor of same shape as arr. Count of each value in arr is incremented by it’s corresponding weight.
- minlength(optional): It defines the minimum length of returnted output.
- maxlength(optional): It defines the maximum length of returnted output. Bin of the values in arr that are greater than or equal to maxlength is not calculated.
- dtype(optional): It determines the dtype of returned output if weight is none.
- name(optional): It’s an optional argument that defines the name for the operation.
It returns a vector with the same dtype as weights or the given dtype. Index of the vector defines the value and it’s value defines the bin of index in arr.
a: tf.Tensor([1 2 3 4 5 1 7 3 1 1 5], shape=(11,), dtype=int32) Result: tf.Tensor([0 4 1 2 1 2 0 1], shape=(8,), dtype=int32) # bin of 0 in input is 0, bin of 1 in input is 4 and so on
Example 2: This example provides weights, so instead of 1 values are incremented by the corresponding weight.
a: tf.Tensor([1 2 3 4 5 1 7 3 1 1 5], shape=(11,), dtype=int32) weight: tf.Tensor([0 2 1 0 2 1 3 3 1 0 5], shape=(11,), dtype=int32) Result: tf.Tensor([0 2 2 4 0 7 0 3], shape=(8,), dtype=int32)
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