transformer
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Description
Trax is a library for deep learning that focuses on sequence models and reinforcement learning. It combines performance with code clarity and maintained documentation and tests.
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Sorry to bother, I'll be brief. I don't think the "maintained documentation" part of the statement is true (yet?). I like the work and I respect every project that goes deep down on neural network
PositionalEmbedding
The position embedding in the BERT is not the same as in the transformer. Why not use the form in bert?
I don't understand the conditional sentence in the loop when infer, it is always false。
if tf.reduce_sum(y_hat, 1) == self.token2idx[""]: break
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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.teIt would be great to have instructions on how to train a language model from scratch - not just loading the paper's model.
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I have installed in my project expo install react-native-svg.
I have exported the svg as a component by doing:
import Logo from './logo.svg';
export default Logo;It can render on native but fail on the web.
bundle.js:69367 Warning: </static/media/splashScreen.0f923900.svg /> is using incorrect casing. Use PascalCase for React components, or lowercase for HTML ele
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Hello,
I discovered Laravel and Lumen. I want to create a clean API. I would like to implement JSON API. I tested your library.
I discovered some errors in the documentation.
For the controller, it would indicate the need to put the controller in the directory "app/Http/Controllers/Api".
Since the namespace of the controller is not correct. There must be "App/Http/Controllers/Api".
In the r
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Excuse me, https://github.com/graykode/nlp-tutorial/blob/master/1-1.NNLM/NNLM-Torch.py#L50 The comment here may be wrong. It should be
X = X.view(-1, n_step * m) # [batch_size, n_step * m]Sorry for disturbing you.