Python TensorFlow中np.std（）的等价物是什么？

只需寻找TensorFlow中np.std（）的等价物即可计算张量的标准偏差。

要获得均值和方差，只需使用

tf.nn.moments

mean, var = tf.nn.moments(x, axes=[1])

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有关

tf.nn.moments

参数的更多信息，请参见，您也可以在以下改编自Keras的代码中使用

reduce_std

：

#coding=utf-8
import numpy as np
import tensorflow as tf

def reduce_var(x, axis=None, keepdims=False):
    """Variance of a tensor, alongside the specified axis.

    # Arguments
        x: A tensor or variable.
        axis: An integer, the axis to compute the variance.
        keepdims: A boolean, whether to keep the dimensions or not.
            If `keepdims` is `False`, the rank of the tensor is reduced
            by 1. If `keepdims` is `True`,
            the reduced dimension is retained with length 1.

    # Returns
        A tensor with the variance of elements of `x`.
    """
    m = tf.reduce_mean(x, axis=axis, keep_dims=True)
    devs_squared = tf.square(x - m)
    return tf.reduce_mean(devs_squared, axis=axis, keep_dims=keepdims)

def reduce_std(x, axis=None, keepdims=False):
    """Standard deviation of a tensor, alongside the specified axis.

    # Arguments
        x: A tensor or variable.
        axis: An integer, the axis to compute the standard deviation.
        keepdims: A boolean, whether to keep the dimensions or not.
            If `keepdims` is `False`, the rank of the tensor is reduced
            by 1. If `keepdims` is `True`,
            the reduced dimension is retained with length 1.

    # Returns
        A tensor with the standard deviation of elements of `x`.
    """
    return tf.sqrt(reduce_var(x, axis=axis, keepdims=keepdims))

if __name__ == '__main__':
    x_np = np.arange(10).reshape(2, 5).astype(np.float32)
    x_tf = tf.constant(x_np)
    with tf.Session() as sess:
        print(sess.run(reduce_std(x_tf, keepdims=True)))
        print(sess.run(reduce_std(x_tf, axis=0, keepdims=True)))
        print(sess.run(reduce_std(x_tf, axis=1, keepdims=True)))
    print(np.std(x_np, keepdims=True))
    print(np.std(x_np, axis=0, keepdims=True))
    print(np.std(x_np, axis=1, keepdims=True))

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如何在C++ API中实现这一点？我只看到C++中的均值的文档：我想你必须自己计算变量。sum[（x-u）^2]您可能可以深入了解python源代码，了解它们如何调用后端，以了解如何更有效地计算方差。注意：这计算的是均值和“方差”，而不是“标准差”。我使用的是tf1.4，tf.nn。出于某些原因，矩量不能给出正确的结果。。。我尝试了你的版本，第一次就成功了：）+1如果我想将其用作丢失函数，是否需要将keepdims设置为True？