def std(x, axis=None, keepdims=False):
    '''Standard deviation of a tensor, alongside the specificied axis.
    '''
    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.sqrt(tf.reduce_mean(devs_squared,
                                  reduction_indices=axis,
                                  keep_dims=keepdims))
dataset/ETHPy150Open fchollet/keras/keras/backend/tensorflow_backend.py/std/original