pytorch embedding index out of range
I'm following this tutorial here https://cs230-stanford.github.io/pytorch-nlp.html. In there a neural model is created, using nn.Module, with an embedding layer, which is initialized here

self.embedding = nn.Embedding(params['vocab_size'], params['embedding_dim'])


vocab_size is the total number of training samples, which is 4000.  embedding_dim is 50.  The relevant piece of the forward method is below

def forward(self, s):
        # apply the embedding layer that maps each token to its embedding
        s = self.embedding(s)   # dim: batch_size x batch_max_len x embedding_dim


I get this exception when passing a batch to the model like so
model(train_batch)
train_batch is a numpy array of dimension batch_sizexbatch_max_len.  Each sample is a sentence, and each sentence is padded so that it has the length of the longest sentence in the batch.


  File
  "/Users/liam_adams/Documents/cs512/research_project/custom/model.py",
  line 34, in forward
      s = self.embedding(s)   # dim: batch_size x batch_max_len x embedding_dim   File
  "/Users/liam_adams/Documents/cs512/venv_research/lib/python3.7/site-packages/torch/nn/modules/module.py",
  line 493, in call
      result = self.forward(*input, **kwargs)   File "/Users/liam_adams/Documents/cs512/venv_research/lib/python3.7/site-packages/torch/nn/modules/sparse.py",
  line 117, in forward
      self.norm_type, self.scale_grad_by_freq, self.sparse)   File "/Users/liam_adams/Documents/cs512/venv_research/lib/python3.7/site-packages/torch/nn/functional.py",
  line 1506, in embedding
      return torch.embedding(weight, input, padding_idx, scale_grad_by_freq, sparse) RuntimeError: index out of range at
  ../aten/src/TH/generic/THTensorEvenMoreMath.cpp:193


Is the problem here that the embedding is initialized with different dimensions than those of my batch array?  My batch_size will be constant but batch_max_len will change with every batch. This is how its done in the tutorial.

Found the answer here https://discuss.pytorch.org/t/embeddings-index-out-of-range-error/12582

I'm converting words to indexes, but I had the indexes based off the total number of words, not vocab_size which is a smaller set of the most frequent words.
