Hello everybody,

I am trying to rewrite a simulation code written with Tensorflow using Pytorch.

I am new to Pytorch and I am still learning to work with tensors in general.

I am stuck at rewriting tf.while_loop(), which, as I managed to understand, is a special function in Tensorflow:

```
t_out,v_out,s_out,m_out,d_out,f_s_out = tf.while_loop(\
c,
b,
loop_vars=[t0,V,S,m0,d0,full_stim],
shape_invariants=[t0.get_shape(),
tf.TensorShape([self.N*4, None]),
tf.TensorShape([self.N*4, self.syn_size]),
tf.TensorShape([self.N*4, 1])
tf.TensorShape([self.N*4, 1]),
tf.TensorShape([self.N*4,None])])
return v_out,s_out,m_out,d_out
```

What is the equivalent of this in Pytorch?

Another thing, how do I run a simulation? In Tensorflow it is with this line:

```
v_sim,s_sim,m_sim,d_sim = tf.Session(config=self.config).run([self.v_out,
self.s_out,
self.m_out,
self.d_out],
feed_dict={self.V: self.v_state,
self.S: self.s_state,
self.m0: self.m_state,
self.d0: self.d_state,
self.s_offset: 0,
self.stim: stimulus})
```

How do I do something similar in Pytorch?

Thank you in advance for your help and I am sorry if these questions seem stupid.