Tensorflow将3D批量张量与2D权重相乘

Question

我有两个张力，形状如下所示，

batch.shape = [?, 5, 4]
weight.shape = [3, 5]

通过将权重乘以批处理中的每个元素，我想得到

result.shape = [?, 3, 4]

实现这一目标的最有效方法是什么？

Answer 1

试试这个：

newbatch = tf.transpose(batch,[1,0,2])
newbatch = tf.reshape(newbatch,[5,-1])
result = tf.matmul(weight,newbatch)
result = tf.reshape(result,[3,-1,4])
result = tf.transpose(result, [1,0,2])

或更紧凑：

newbatch = tf.reshape(tf.transpose(batch,[1,0,2]),[5,-1])
result = tf.transpose(tf.reshape(tf.matmul(weight,newbatch),[3,-1,4]), [1,0,2])

Answer 2

尝试一下：

tf.einsum("ijk,aj-> iak",batch,weight)

任意维度Refer this for more information的张量之间的广义收缩