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fix a bug in getting the value of prev_word_inds #180

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fix a bug in getting the value of prev_word_inds #180

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0d0be3b
fix a bug in getting the value of prev_word_inds
moon4869 Jul 28, 2022
43d0ea2
fix a same bug in getting the value of prev_word_inds
moon4869 Jul 28, 2022
a8032d2
fix a parameter bug in "plt.subplot"
moon4869 Jul 28, 2022
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4 changes: 2 additions & 2 deletions caption.py
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Original file line number Diff line number Diff line change
Expand Up @@ -104,7 +104,7 @@ def caption_image_beam_search(encoder, decoder, image_path, word_map, beam_size=
top_k_scores, top_k_words = scores.view(-1).topk(k, 0, True, True) # (s)

# Convert unrolled indices to actual indices of scores
prev_word_inds = top_k_words / vocab_size # (s)
prev_word_inds = torch.div(top_k_words, vocab_size, rounding_mode='floor') # (s)
next_word_inds = top_k_words % vocab_size # (s)

# Add new words to sequences, alphas
Expand Down Expand Up @@ -167,7 +167,7 @@ def visualize_att(image_path, seq, alphas, rev_word_map, smooth=True):
for t in range(len(words)):
if t > 50:
break
plt.subplot(np.ceil(len(words) / 5.), 5, t + 1)
plt.subplot(int(np.ceil(len(words) / 5.)), 5, t + 1)

plt.text(0, 1, '%s' % (words[t]), color='black', backgroundcolor='white', fontsize=12)
plt.imshow(image)
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2 changes: 1 addition & 1 deletion eval.py
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Expand Up @@ -121,7 +121,7 @@ def evaluate(beam_size):
top_k_scores, top_k_words = scores.view(-1).topk(k, 0, True, True) # (s)

# Convert unrolled indices to actual indices of scores
prev_word_inds = top_k_words / vocab_size # (s)
prev_word_inds = torch.div(top_k_words, vocab_size, rounding_mode='floor') # (s)
next_word_inds = top_k_words % vocab_size # (s)

# Add new words to sequences
Expand Down