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examples: add task summary table to llama-eval-new.py
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@@ -208,6 +208,18 @@ class Processor:
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print(f"Max tokens: {self.n_predict}")
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print()
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# Print task summary table
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print("Tasks:")
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print(" Task ID Dataset Prompt (first 40 chars) Expected Status")
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for i in range(min(n_cases, len(self.dataset.questions))):
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question = self.dataset.get_question(i)
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case_id = f"aime_{self.dataset.split}_{question['id']}"
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prompt = question["problem"]
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gold = self.dataset.get_answer(question)
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truncated_prompt = prompt[:40] + "..." if len(prompt) > 40 else prompt
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print(f" {case_id:<15} AIME2025 {truncated_prompt:<40} {gold:<10} pending")
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print()
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task_states: Dict[str, List[TaskState]] = {task: [] for task in self.eval_state.tasks}
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total = 0
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correct = 0
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