为什么我连接矩阵和向量是错误的？

Question

这是我在 theano 中的代码

max_max=200
beReplaced=T.matrix()
toReplace=T.matrix()
timeArray=T.arange(max_max)


def f(v,k,w):
    return T.concatenate([w[:k],v,w[k+1:]],axis=0)

result,_=theano.scan(f,
                     sequences=[toReplace,timeArray],
                     outputs_info=beReplaced)

我想做的是逐行将 beReplaced 替换为 toReplace。我这样做的方法是 concatenate w 的上部，v 和 lower 部分 w.

v是toReplace.

行

这是错误报告

Traceback (most recent call last):
  File "/Users/qiansteven/Desktop/NLP/RNN/my.py", line 20, in <module>
    outputs_info=np.zeros((5,5),dtype=np.float64))
  File "/usr/local/lib/python2.7/site-packages/theano/scan_module/scan.py", line 745, in scan
    condition, outputs, updates = scan_utils.get_updates_and_outputs(fn(*args))
  File "/Users/qiansteven/Desktop/NLP/RNN/my.py", line 16, in f
    return T.concatenate([a,b,c],axis=0)
  File "/usr/local/lib/python2.7/site-packages/theano/tensor/basic.py", line 4225, in concatenate
    return join(axis, *tensor_list)
  File "/usr/local/lib/python2.7/site-packages/theano/gof/op.py", line 611, in __call__
    node = self.make_node(*inputs, **kwargs)
  File "/usr/local/lib/python2.7/site-packages/theano/tensor/basic.py", line 3750, in make_node
    axis, tensors, as_tensor_variable_args, output_maker)
  File "/usr/local/lib/python2.7/site-packages/theano/tensor/basic.py", line 3816, in _make_node_internal
    raise TypeError("Join() can only join tensors with the same "
TypeError: Join() can only join tensors with the same number of dimensions.

怎么了？？？？？？？？？

Answer 1

将toReplace放入non_sequences，否则每个timestep只会取其中的一片。 Theano 尝试将向量与矩阵连接时会报错。

def f(k,w,v): #NOTE the argument order change
    return T.concatenate([w[:k],v,w[k+1:]],axis=0)

result,_=theano.scan(f,
                     sequences=timeArray,
                     outputs_info=beReplaced,
                     non_sequences=toReplace)

Answer 2

解决方案是连接 v.dimshuffle('x',0) 并解决模糊问题。

为什么我连接矩阵和向量是错误的？

Why I am wrong to concatenate matrix and vector?

theano

theano.scan