Is there any way get nn.TransformerDecoder tutotrial?

Hey every one myself is teddy this is my first post,i already have code for nn.TransformerEncoder but i also need tutorial or code for nn.TransformerDecoder, can anyone help?

Hi Teddy,

The nn.TransformerDecoder in PyTorch is used to create the decoder part of a Transformer model. It’s commonly used in sequence-to-sequence tasks, language translation, and other natural language processing applications. Here’s a simplified example of how to use nn.TransformerDecoder:

import torch
import torch.nn as nn

# Define the parameters
d_model = 512  # Model dimension
nhead = 8     # Number of attention heads
num_layers = 6  # Number of decoder layers
dim_feedforward = 2048  # Feedforward dimension

# Create the decoder
decoder = nn.TransformerDecoder(
    nn.TransformerDecoderLayer(d_model, nhead, dim_feedforward),

# Input and target sequences
tgt = torch.rand(10, 32, d_model)  # (sequence_length, batch_size, d_model)
memory = torch.rand(20, 32, d_model)  # (sequence_length, batch_size, d_model)

# Output from the decoder
output = decoder(tgt, memory)

In this example:

d_model is the dimension of model (e.g., word embeddings or features).
nhead is the number of attention heads.
num_layers is the number of decoder layers.
dim_feedforward is the dimension of the feedforward network within each layer.
You’ll need to adjust these parameters to fit your specific task and data. The decoder is used to generate predictions or decode sequences based on the target sequence and memory (output from the encoder).

For a more comprehensive tutorial and code, I recommend referring to the official PyTorch documentation and examples, as well as online resources and tutorials related to sequence-to-sequence tasks with Transformers.


ookay i undertsand iam also looking for latest GAN tutorials and RT2 tutorial