“One-to-many sequence problems are sequence problems where the input data has one time-step, and the output contains a vector of multiple values or multiple time-steps.”

I am trying to make a One-to-many LSTM based model in pytorch.

It is a binary classification problem there is only 2 classes. However, the labels should be a vector of 2 classes so for example:

```
LABEL VECTOR [array([0., 1.]), array([0., 1.]), array([0., 1.]), array([0., 1.]), array([0., 1.]), array([0., 1.]), array([0., 1.]), array([0., 1.]), array([0., 1.]), array([0., 1.]), array([1., 0.]), array([1., 0.]), array([1., 0.]), array([1., 0.]), array([1., 0.]), array([0., 1.])]
```

**num_classes = 2**

```
from torch import nn
#define Model
class LSTMClassifier(nn.Module):
def __init__(self, input_size, lstm1_hidden_size,num_layers, num_classes):
super(LSTMClassifier, self).__init__()
#shape = (1,8192,16)
self.lstm1 = nn.LSTM(input_size=input_size, hidden_size=lstm1_hidden_size, num_layers=num_layers, batch_first=True)
self.classifier = nn.Linear(lstm1_hidden_size, num_classes)
self.sigmoid = nn.Sigmoid()
def forward(self, x):
lstm_out, _ = self.lstm1(x) #hidden state & cell state returned
pred = self.classifier(lstm_out)
pred = self.sigmoid(pred)
return pred
```

This model outputs a target shape of **(1,num_segments,2)**

The shape of the data is:

**(1,num_segments,8192)**

The shape of the labels is:

**(1,num_segments,16,2)**

Again the labels look like the following:

- there are always fixed 16 labels, each having binary classification with 2 columns. Each column may be a 0 or 1. Thus 2 classes. So I want the output of the LSTM model to be a sequence of binary classifications.

```
LABEL VECTOR [array([0., 1.]), array([0., 1.]), array([0., 1.]), array([0., 1.]), array([0., 1.]), array([0., 1.]), array([0., 1.]), array([0., 1.]), array([0., 1.]), array([0., 1.]), array([1., 0.]), array([1., 0.]), array([1., 0.]), array([1., 0.]), array([1., 0.]), array([0., 1.])]
```

Right now the error I am getting is:

ValueError: Target size (torch.Size([1, 7, 16, 2])) must be the same as input size (torch.Size([1, 7, 2]))

How can I structure this LSTM pytorch model to get an output as a vector of Binary Classification labels?