Below is my model code and expecting to have embedding weight updated as training is progressing but it is not being updated. Only embedding which is being updated is of index = 0 which is ‘unk’ word. Am I missing anything in the model ? Could it be possible someone to help on this ? I am struggling for last few days.
class FeedForwardModel(nn.Module):
    def __init__(self, embedding_matrix, embed_dim):
        super().__init__()
        self.embedding = nn.EmbeddingBag.from_pretrained(torch.FloatTensor(embedding_matrix))
        self.fc1 = nn.Linear(embed_dim, 10)
        self.fc2 = nn.Linear(10, 1)
        self.output = nn.Sigmoid()
        self.init_weights()
        
    def __init__(self, num_embeddings, embed_dim):
        super().__init__()
        self.embedding = nn.EmbeddingBag(num_embeddings, embedding_dim)
        self.fc1 = nn.Linear(embed_dim, 10)
        self.fc2 = nn.Linear(10, 1)
        self.output = nn.Sigmoid()
        self.embedding.weight.data.uniform_(-0.5, 0.5)
        self.embedding.weight.requires_grad = True
        self.init_weights()
                  
        
    def forward(self, input, offsets):
        #print(input)
        #print(self.embedding.weight[1:3])
        embedded = self.embedding(input, offsets)
        h1 = F.tanh(self.fc1(embedded))
        h2 = self.fc2(h1)
        return self.output(h2)
    
    def init_weights(self):
        initrange = 0.5
        self.fc1.weight.data.uniform_(-initrange, initrange)
        self.fc2.weight.data.uniform_(-initrange, initrange)
        self.fc1.bias.data.zero_()
        self.fc2.bias.data.zero_()