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  1. app.py +5 -5
app.py CHANGED
@@ -265,15 +265,12 @@ def diffusion_chat(question, max_it, pause_length, sharpness, clustering, noise_
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  noised_answer, just_noised_indices = confidence_guided_noising(
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  current_tokens, answer_start, confidences, noise_clipping, threshold=threshold, noise_start=noise_start
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  )
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- just_noised_indices = []
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  else:
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  noised_answer, just_noised_indices = noisify_answer(
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  current_tokens, answer_start, threshold=threshold, clustering=clustering, noise_start = noise_start,
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  )
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- # Compose full input again: prompt + noised answer
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- current_tokens = ori_input_tokens[:answer_start] + noised_answer[answer_start:]
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-
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  # --- RED HIGHLIGHT ---
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  decoded_tokens = tokenizer.convert_ids_to_tokens(current_tokens[answer_start:])
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  highlighted = []
@@ -288,8 +285,11 @@ def diffusion_chat(question, max_it, pause_length, sharpness, clustering, noise_
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  else:
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  highlighted.append(token_str)
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  yield f"<b>Iteration {i+1}/{max_it} (before noising):</b><br>" + "".join(highlighted).replace('\n', '<br>')
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- time.sleep(pause_length)
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  answer_ids = current_tokens[answer_start:]
 
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  noised_answer, just_noised_indices = confidence_guided_noising(
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  current_tokens, answer_start, confidences, noise_clipping, threshold=threshold, noise_start=noise_start
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  )
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+ # just_noised_indices = []
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  else:
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  noised_answer, just_noised_indices = noisify_answer(
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  current_tokens, answer_start, threshold=threshold, clustering=clustering, noise_start = noise_start,
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  )
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  # --- RED HIGHLIGHT ---
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  decoded_tokens = tokenizer.convert_ids_to_tokens(current_tokens[answer_start:])
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  highlighted = []
 
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  else:
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  highlighted.append(token_str)
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+ # Compose full input again: prompt + noised answer
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+ current_tokens = ori_input_tokens[:answer_start] + noised_answer[answer_start:]
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+
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  yield f"<b>Iteration {i+1}/{max_it} (before noising):</b><br>" + "".join(highlighted).replace('\n', '<br>')
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+ # time.sleep(pause_length)
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  answer_ids = current_tokens[answer_start:]