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)
tensorflow_backend.py 文件源码
python
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