def __init__(self, emb_type, **kwargs):
super(TextEmbedding, self).__init__()
self.model_data_dir = kwargs.get("model_data_dir", None)
self.embedding_dim = kwargs.get("embedding_dim", None)
# Update kwargs here
if emb_type == "identity":
self.module = Identity()
self.module.text_out_dim = self.embedding_dim
elif emb_type == "vocab":
self.module = VocabEmbedding(**kwargs)
self.module.text_out_dim = self.embedding_dim
elif emb_type == "preextracted":
self.module = PreExtractedEmbedding(**kwargs)
elif emb_type == "bilstm":
self.module = BiLSTMTextEmbedding(**kwargs)
elif emb_type == "attention":
self.module = AttentionTextEmbedding(**kwargs)
elif emb_type == "torch":
vocab_size = kwargs["vocab_size"]
embedding_dim = kwargs["embedding_dim"]
self.module = nn.Embedding(vocab_size, embedding_dim)
self.module.text_out_dim = self.embedding_dim
else:
raise NotImplementedError("Unknown question embedding '%s'" %
emb_type)
self.text_out_dim = self.module.text_out_dim
def __init__(self, encoder_type, in_dim, **kwargs):
super(ImageEncoder, self).__init__()
if encoder_type == "default":
self.module = Identity()
self.module.in_dim = in_dim
self.module.out_dim = in_dim
elif encoder_type == "finetune_faster_rcnn_fpn_fc7":
self.module = FinetuneFasterRcnnFpnFc7(in_dim, **kwargs)
else:
raise NotImplementedError("Unknown Image Encoder: %s" %
encoder_type)
self.out_dim = self.module.out_dim