I am trying to create a 3 to 1 LSTM
The LSTM must take sequence of 3 words, each embedded vector of size 100
So, my input size is (batch_size, 3, 100). So, what is the way to achieve this? I am new to pytorch, so, please help me with this
Usually LSTMs are used for inputs with varying length, for exactly 3 inputs with a total vector size of 300 you can just use a few nn.Linear layers.
Nevertheless, if you want to use an LSTM, you want the following:

input_dim
is 100 
embed_dim
can be anything you want, let’s say 128 here. (This will be the size of your output)  You only want one output but you are getting 3 (as of now). The simplest idea is just to take the last output (StackOverflow answer here.)[https://stackoverflow.com/questions/62204109/returnsequencesfalseequivalentinpytorchlstm].
Your final code will look like this:
model = torch.nn.LSTM(input_size=100, hidden_size=128, num_layers=1)
output = model(input)[1]
isn’t output the first element of the tuple returned as per doc? the o/p has shape (seq_len, batch, num_directions * hidden_size). Since my model in many to 1, I will take last seq I think? so
output,_,_ = model(input)
output = output[2]
Right, sorry, I forgot about the output outputs from LSTM.