TensorFlow中，想要維度增加一維，可以使用tf.expand_dims(input, dim, name=None)函數。當然，我們常用tf.reshape(input, shape=[])也可以達到相同效果，但是有些時候在構建圖的過程中，placeholder沒有被feed具體的值，這時就會包下面的錯誤：TypeError: Expected binary or unicode string, got 1

在這種情況下，我們就可以考慮使用expand_dims來將維度加1。比如我自己代碼中遇到的情況，在對圖像維度降到二維做特定操作后，要還原成四維[batch, height, width, channels]，前后各增加一維。如果用reshape，則因為上述原因報錯

one_img2 = tf.reshape(one_img, shape=[1, one_img.get_shape()[0].value, one_img.get_shape()[1].value, 1])

用下面的方法可以實現：

one_img = tf.expand_dims(one_img, 0)one_img = tf.expand_dims(one_img, -1) #-1表示最后一維

在最后，給出官方的例子和說明

# 't' is a tensor of shape [2]shape(expand_dims(t, 0)) ==> [1, 2]shape(expand_dims(t, 1)) ==> [2, 1]shape(expand_dims(t, -1)) ==> [2, 1]# 't2' is a tensor of shape [2, 3, 5]shape(expand_dims(t2, 0)) ==> [1, 2, 3, 5]shape(expand_dims(t2, 2)) ==> [2, 3, 1, 5]shape(expand_dims(t2, 3)) ==> [2, 3, 5, 1]

Args:

input: A Tensor.
dim: A Tensor. Must be one of the following types: int32, int64. 0-D (scalar). Specifies the dimension index at which to expand the shape of input.
name: A name for the operation (optional).

Returns:

A Tensor. Has the same type as input. Contains the same data as input, but its shape has an additional dimension of size 1 added.

以上這篇TensorFlow用expand_dim()來增加維度的方法就是小編分享給大家的全部內容了，希望能給大家一個參考，也希望大家多多支持武林站長站。