Programming, Artificial Intelligence, Machine Learning, Data Science, Python.
nn.ModuleList( [ TransformerEncoderBlock(input_dim, num_heads, feedforward_dim, dropout) for _ in range(num_layers) ] ) def forward(self, x, mask=None): seq_length = x.shape[1] positions = torch.arange(0, seq_length).expand(x.shape[0], seq_length).to(x.device) x = self.word_embeddings(x) +