what is the kind of max pooling in this nlp questionhierarchy description
问题 I'm trying to implement this description and that what I did I generated uni_gram & bi_gram & tri_gram of shape(?,15,512) "using padding " & then for each word I concatenate the three feature vector (?,3,512) and then I apply to them Globalmaxpooling1D I do not know if I implemented it well or not so can any one help me ? Q = Input(shape=(15,)) V = Input(shape=(512,196)) word_level = Embedding ( vocab_size , 512 , input_length=max_length)(Q) uni_gram = Conv1D( 512 , kernel_size = 1 ,