Looking at the following diagram and the code you wrote , which is :

import torch.nn as nn

class RNN(nn.Module):
    def __init__(self, input_size, hidden_size, output_size):
        super(RNN, self).__init__()

        self.hidden_size = hidden_size

        self.i2h = 

The readme states that it has "By default... an embedding size for the vocabulary of 32"

However, it looks like 64 in the code
https://github.com/Conchylicultor/DeepQA/blob/31c7f0ec988292166aea718ebd4cd0d4d053f9b3/chatbot/chatbot.py#L126

I add a function(according the code in the tutorial4) to calculate the bleu score, but i get the vey low score(0.09), could you tell me why?
This is code to calculate bleu:

def translate_sentence(sentence, src_field, trg_field, model, device, max_len = 50):
    
    model.eval()
        
    if isinstance(sentence, str):
        nlp = spacy.load('de')
        tokens = [token.te

The README states:
If you already had a version of PyTorch installed on your system, please verify that the active torch package is at least version 0.1.11

However, my version of PyTorch (0.3.1) >= 0.1.11, but there are compatibility issues. The README should be updated to reflect the actual minimum version supported.

Given that the code uses no_grad, which is introduced in 0.4.0, the minim

The code would already produce charts in English. However, the current charts are in French.

One would need to try all the exercises to regenerate new charts, incorporate them in the notebook, and then regenerate the README in a clean way, as well as the .py file if the code in the notebook changed.

The French branch (which is named francais) should remain untouched.

I want to integrate the model programmatically, how to receive more detailed information from the output model. How are the tensors named and structured in the graph to receive information like this (if available):

input:

image data bytes

output:

bounding box location
score/probability
single character location

tf_seq2seq_chatbot son$ sh setup.sh
Cloning into 'Seq2Seq_Upgrade_TensorFlow'...
Permission denied (publickey).
fatal: Could not read from remote repository.

bash setup.sh returns above error

I don't know what is the problem

https://github.com/JayParks/tf-seq2seq/blob/master/seq2seq_model.py#L368
It gives that the dimension 0 of inputs and attention do not match (as we are tile_batching it to batch_size * beam_width). Didn't you get any error while running with beam_search?

Thanks for this wonderful library, but it would be much more intuitive for users to get started by providing some simple but clearly training process on self-defined dataset.