Natural Language Processing Tutorial for Deep Learning Researchers - add decoder self_attention_mask (using torch.gt) and enc_self_attn · Honey-Xin/nlp-tutorial@5b4fb5e
We can see here that the attention mask is simply cleared out. Is this intentional? from transformers import BertModel config_path = 'bert-base-uncased' config = BertModel.config_class.from_pretrained(config_path) print(f'is_decoder: {config.is_decoder}') outputs False 👍 1 Member ...
"而Cross Attention模块Q、K是Encoder的输出"应该是encoder的K,V是encoder的输出吧,decoder侧作为Q,因为Q是带有mask的信息只是做一个权重作用,右下角那块是从起始符号一个个生成的,然而整个任务的主体应该是我们在encoder侧的输入,所以V肯定来自于左边encoder的结果,至于Q和K来自哪里:如果Q来自于encode,那么cross a...
we will further benefit from these complementary models and realize broader applications with a single system. This paper proposes four-decoder joint modeling (4D) of CTC, attention, RNN-T, and mask-predict, which has the following three advantages: 1) The four decoders are jointly trained so...
After received the error:ValueError: Required inputs (['decoder_input_ids']) are missing from input feed (['input_ids', 'attention_mask'])I tried to adddecoder_input_idsto input feed with this code: from transformers import AutoTokenizer from onnxruntime import InferenceSession import numpy...