tensorflow_backend.py 文件源码

def 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`.
    """
    axis = _normalize_axis(axis, ndim(x))
    if x.dtype.base_dtype == tf.bool:
        x = tf.cast(x, floatx())
    m = tf.reduce_mean(x, reduction_indices=axis, keep_dims=True)
    devs_squared = tf.square(x - m)
    return tf.reduce_mean(devs_squared,
                          reduction_indices=axis,
                          keep_dims=keepdims)