标签：的区别 cte nbsp optional tin win int lex ble
Args: x: A `Tensor`. Must be one of the following types: `bfloat16`, `half`, `float32`, `float64`, `uint8`, `int8`, `int16`, `int32`, `int64`, `complex64`, `complex128`, `string`. y: A `Tensor`. Must have the same type as `x`. name: A name for the operation (optional). Returns: A `Tensor`. Has the same type as `x`.
Adds `bias` to `value`. This is (mostly) a special case of `tf.add` where `bias` is restricted to 1-D. Broadcasting is supported, so `value` may have any number of dimensions. Unlike `tf.add`, the type of `bias` is allowed to differ from `value` in the case where both types are quantized. Args: value: A `Tensor` with type `float`, `double`, `int64`, `int32`, `uint8`, `int16`, `int8`, `complex64`, or `complex128`. bias: A 1-D `Tensor` with size matching the last dimension of `value`. Must be the same type as `value` unless `value` is a quantized type, in which case a different quantized type may be used. data_format: A string. ‘NHWC‘ and ‘NCHW‘ are supported. name: A name for the operation (optional).
Returns: A `Tensor` with the same type as `value`.
【TensorFlow基础】tf.add 和 tf.nn.bias_add 的区别
标签：的区别 cte nbsp optional tin win int lex ble
原文地址：https://www.cnblogs.com/wuliytTaotao/p/9497367.html
