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【TensorFlow基础】tf.add 和 tf.nn.bias_add 的区别

发布时间:2020-12-14 03:49:29 所属栏目:大数据 来源:网络整理
导读:1. tf.add(x,?y,name) 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`.

1. tf.add(x,?y,name)

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`.

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2.?tf.nn.bias_add(value,bias,data_format=None,name=None)

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`,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`.

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3. tf.add 和 tf.nn.bias_add 的区别

  • tf.nn.bias_add 是 tf.add 中的一个特例,tf.nn.bias_add 中 bias 一定是 1 维的张量;
  • tf.nn.bias_add 中 value 最后一维长度和 bias 的长度一定得一样;
  • tf.nn.bias_add 中,当 value 是 quantized type 时,bias 可以取不同的 quantized type。但什么是 quantized type?TensorFlow API 中 tf.DType 页面显示,‘tf.qint8‘、‘tf.quint8‘、‘tf.qint16‘、‘tf.quint16‘、‘tf.qint32‘类型就是Quantized type。但这些类别具体如何使用并不知晓。

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References

TensorFlow API 1.10

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