

padding_idx (int, optional) -- See module
           initialization documentation. Default: "None".
Return type:
     EmbeddingBag
Examples:
 >>> # FloatTensor containing pretrained weights
 >>> weight = torch.FloatTensor([[1, 2.3, 3], [4, 5.1, 6.3]])
 >>> embeddingbag = nn.EmbeddingBag.from_pretrained(weight)
 >>> # Get embeddings for index 1
 >>> input = torch.LongTensor([[1, 0]])
 >>> embeddingbag(input)
 tensor([[ 2.5000,  3.7000,  4.6500]])


