I am a beginner to Pytorch and I have trained a custom built model. It looks like this:

```
stackedIndRNN_encoder(
(DIs): ModuleList(
(0): Linear(in_features=150, out_features=512, bias=True)
(1): Linear(in_features=512, out_features=512, bias=True)
(2): Linear(in_features=512, out_features=512, bias=True)
(3): Linear(in_features=512, out_features=512, bias=True)
(4): Linear(in_features=512, out_features=512, bias=True)
(5): Linear(in_features=512, out_features=512, bias=True)
)
(BNs): ModuleList(
(0): Batch_norm_step(
(bn): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
)
(1): Batch_norm_step(
(bn): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
)
(2): Batch_norm_step(
(bn): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
)
(3): Batch_norm_step(
(bn): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
)
(4): Batch_norm_step(
(bn): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
)
(5): Batch_norm_step(
(bn): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
)
)
(RNNs): ModuleList(
(0): IndRNN_onlyrecurrent()
(1): IndRNN_onlyrecurrent()
(2): IndRNN_onlyrecurrent()
(3): IndRNN_onlyrecurrent()
(4): IndRNN_onlyrecurrent()
(5): IndRNN_onlyrecurrent()
)
(lastfc): Linear(in_features=512, out_features=60, bias=True)
)
```

I want to access the output from the last layer, RNNs that is a ** 512-dimensional vector** that is inputted into the final fully connected layer, **lastfc**. I have tried forward hook in the following way:

```
RNNs_output = None
def RNN_hook(module, input_, output):
global RNNs_output
RNNs_output = output
model.lastfc.register_forward_hook(RNN_hook)
model(skeletons)
print(RNNs_output)
```

but I get None in RNNS_output. What am I doing wrong?