Spaces:
Running
on
Zero
Running
on
Zero
Fix time_elapsed issue
Browse files
app.py
CHANGED
@@ -223,12 +223,19 @@ def diffusion_chat(question, max_it, pause_length, sharpness, clustering, noise_
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last_tokens = []
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prev_decoded_tokens = []
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for i in range(max_it):
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print('Generating output')
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# Model step
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generated_tokens, confidences = generate_diffusion_text(current_tokens)
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# Save full output for noising step
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current_tokens = ori_input_tokens[:answer_start] + generated_tokens[answer_start:]
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@@ -289,7 +296,7 @@ def diffusion_chat(question, max_it, pause_length, sharpness, clustering, noise_
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current_tokens = ori_input_tokens[:answer_start] + noised_answer[answer_start:]
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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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-
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answer_ids = current_tokens[answer_start:]
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last_tokens = []
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prev_decoded_tokens = []
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generation_start = time.time()
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for i in range(max_it):
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print('Generating output')
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# Model step
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generated_tokens, confidences = generate_diffusion_text(current_tokens)
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elapsed = time.time() - generation_start
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remaining = pause_length - elapsed
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if remaining > 0:
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time.sleep(remaining)
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# Save full output for noising step
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current_tokens = ori_input_tokens[:answer_start] + generated_tokens[answer_start:]
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current_tokens = ori_input_tokens[:answer_start] + noised_answer[answer_start:]
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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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generation_start = time.time()
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answer_ids = current_tokens[answer_start:]
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