Python – tensorflow.math.bincount()

TensorFlow 是由 Google 设计的开源Python库，用于开发机器学习模型和深度学习神经网络。 bincount()存在于 TensorFlow 的数学模块中。它用于计算整数数组中每个数字的出现次数。

Syntax: tensorflow.math.bincount( arr, weights, minlength, maxlength, dtype, name)

Parameters:

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.

Returns:
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.

编程需要懂一点英语

示例 1：

Python3

# importing the library
import tensorflow as tf
 
# initializing the input
a = tf.constant([1,2,3,4,5,1,7,3,1,1,5], dtype = tf.int32)
 
# printing the input
print('a: ',a)
 
# evaluating bin
r = tf.math.bincount(a)
 
# printing result
print("Result: ",r)

Python3

# importing the library
import tensorflow as tf
 
# initializing the input
a = tf.constant([1,2,3,4,5,1,7,3,1,1,5], dtype = tf.int32)
weight = tf.constant([0,2,1,0,2,1,3,3,1,0,5], dtype = tf.int32)
 
# printing the input
print('a: ',a)
print('weight: ',weight)
 
# evaluating bin
r = tf.math.bincount(arr = a,weights = weight)
 
# printing result
print("Result: ",r)

输出：

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

示例 2：此示例提供了权重，因此值不是 1，而是按相应的权重递增。

Python3

# importing the library
import tensorflow as tf
 
# initializing the input
a = tf.constant([1,2,3,4,5,1,7,3,1,1,5], dtype = tf.int32)
weight = tf.constant([0,2,1,0,2,1,3,3,1,0,5], dtype = tf.int32)
 
# printing the input
print('a: ',a)
print('weight: ',weight)
 
# evaluating bin
r = tf.math.bincount(arr = a,weights = weight)
 
# printing result
print("Result: ",r)

输出：

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)