Spaces:
Sleeping
Sleeping
add chunk size function
Browse files
app.py
CHANGED
@@ -182,7 +182,7 @@ def summary_translate(src_text, temp_tgt_text, tgt_language):
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translation = generate_translation(prompt_style, prompt)
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translations.append(translation)
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-
best, score = evaluate_candidates(src_text, translations,
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if cand_list:
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return best, score
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return "", 0
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@@ -318,13 +318,13 @@ def process_text(text, src_language, target_language, max_iterations_value, thre
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bfn_combined_translation = ' '.join(bfn_translated_chunks)
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mpc_combined_translation = ' '.join(mpc_translated_chunks)
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-
orig, best_score = summary_translate(org_combined_translation, target_language)
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orig_output = f"{orig}\n\nScore: {best_score:.2f}"
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-
plan2align_trans, best_score = summary_translate(p2a_combined_translation, target_language)
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plan2align_output = f"{plan2align_trans}\n\nScore: {best_score:.2f}"
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best_candidate, best_score = summary_translate(bfn_combined_translation, target_language)
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best_of_n_output = f"{best_candidate}\n\nScore: {best_score:.2f}"
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mpc_candidate, best_score = summary_translate(mpc_combined_translation, target_language)
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mpc_output = f"{mpc_candidate}\n\nScore: {mpc_score:.2f}"
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# if "Original" in translation_methods:
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@@ -371,7 +371,7 @@ with gr.Blocks(title="Test-Time Machine Translation with Plan2Align") as demo:
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task_language_input = gr.Dropdown(
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choices=target_languages,
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value="English",
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label="
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)
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max_iterations_input = gr.Number(label="Max Iterations", value=6)
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threshold_input = gr.Number(label="Threshold", value=0.7)
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@@ -382,7 +382,7 @@ with gr.Blocks(title="Test-Time Machine Translation with Plan2Align") as demo:
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label="Translation Methods"
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)
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chunk_size_input = gr.Number( # ✅ add chunk function
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label="Chunk Size (
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value=-1
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)
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translate_button = gr.Button("Translate")
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translation = generate_translation(prompt_style, prompt)
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translations.append(translation)
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+
best, score = evaluate_candidates(src_text, translations, tgt_language, session_id)
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if cand_list:
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return best, score
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return "", 0
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bfn_combined_translation = ' '.join(bfn_translated_chunks)
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mpc_combined_translation = ' '.join(mpc_translated_chunks)
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+
orig, best_score = summary_translate(text, org_combined_translation, target_language)
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orig_output = f"{orig}\n\nScore: {best_score:.2f}"
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+
plan2align_trans, best_score = summary_translate(text, p2a_combined_translation, target_language)
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plan2align_output = f"{plan2align_trans}\n\nScore: {best_score:.2f}"
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best_candidate, best_score = summary_translate(text, bfn_combined_translation, target_language)
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best_of_n_output = f"{best_candidate}\n\nScore: {best_score:.2f}"
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mpc_candidate, best_score = summary_translate(text, mpc_combined_translation, target_language)
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mpc_output = f"{mpc_candidate}\n\nScore: {mpc_score:.2f}"
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# if "Original" in translation_methods:
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task_language_input = gr.Dropdown(
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choices=target_languages,
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value="English",
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label="Target Language"
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)
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max_iterations_input = gr.Number(label="Max Iterations", value=6)
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threshold_input = gr.Number(label="Threshold", value=0.7)
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label="Translation Methods"
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)
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chunk_size_input = gr.Number( # ✅ add chunk function
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label="Chunk Size (-1 for all)",
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value=-1
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)
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translate_button = gr.Button("Translate")
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