C5W1 - bidirectional RNN alternatives?

so I was wondering whether this version of “many to many” introduced in the course can also serve as bidirectional RNN

because from this schematic representation, we should have Tx+Ty+1 activations (considering only 1 layer), which is similar to what we have in bidirectional RNNs when Tx=Ty.
And also even the first y_hat will have full information on all the x sequences.

But maybe some drawbacks such as vanishing gradients?

Bidirectional nature gives the ability to look at the inputs from both ends. So, as long you have computational resources, this could be a good approach unless having unidirectional approach is sufficient on the problem.