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Few small nits in GPT-2's code examples

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Stanislas Polu
2019-02-21 09:15:27 +00:00
parent cbb7fad319
commit ff22b3acc0
1 changed files with 4 additions and 3 deletions
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@@ -427,7 +427,7 @@ model.to('cuda')
with torch.no_grad(): with torch.no_grad():
hidden_states_1, past = model(tokens_tensor_1) hidden_states_1, past = model(tokens_tensor_1)
# past can be used to reuse precomputed hidden state in a subsequent predictions # past can be used to reuse precomputed hidden state in a subsequent predictions
# (see beam-search examples in the run_gpt2.py example # (see beam-search examples in the run_gpt2.py example).
hidden_states_2, past = model(tokens_tensor_2, past=past) hidden_states_2, past = model(tokens_tensor_2, past=past)
``` ```
@@ -439,14 +439,15 @@ model = GPT2LMHeadModel.from_pretrained('gpt2')
model.eval() model.eval()
# If you have a GPU, put everything on cuda # If you have a GPU, put everything on cuda
tokens_tensor_1 = tokens_tensor.to('cuda') tokens_tensor_1 = tokens_tensor_1.to('cuda')
tokens_tensor_2 = tokens_tensor_2.to('cuda')
model.to('cuda') model.to('cuda')
# Predict all tokens # Predict all tokens
with torch.no_grad(): with torch.no_grad():
predictions_1, past = model(tokens_tensor_1) predictions_1, past = model(tokens_tensor_1)
# past can be used to reuse precomputed hidden state in a subsequent predictions # past can be used to reuse precomputed hidden state in a subsequent predictions
# (see beam-search examples in the run_gpt2.py example # (see beam-search examples in the run_gpt2.py example).
predictions_2, past = model(tokens_tensor_2, past=past) predictions_2, past = model(tokens_tensor_2, past=past)
# get the predicted last token # get the predicted last token