[Tasks] Fix MMBench

lmms_eval/tasks/mmbench/_default_template_mmbench_cn_yaml

@@ -0,0 +1,22 @@
+dataset_path: lmms-lab/MMBench
+dataset_kwargs:
+  token: True
+doc_to_target: "answer"
+dataset_name: "cn"
+output_type: generate_until
+doc_to_visual: !function cn_utils.mmbench_doc_to_visual
+doc_to_text: !function cn_utils.mmbench_doc_to_text
+generation_kwargs:
+  max_new_tokens: 256
+  temperature: 0
+  top_p: 0
+  num_beams: 1
+  do_sample: false
+process_results: !function cn_utils.mmbench_process_results
+model_specific_prompt_kwargs:
+  default:
+    pre_prompt: ""
+    post_prompt: "\n请直接使用所提供的选项字母作为答案回答。"
+model_specific_generation_kwargs:
+  llava:
+    image_aspect_ratio: original

lmms_eval/tasks/mmbench/_default_template_mmbench_en_yaml

@@ -0,0 +1,25 @@
+dataset_path: lmms-lab/MMBench
+dataset_kwargs:
+  token: True
+doc_to_target: "answer"
+model_specific_prompt_kwargs:
+  default:
+    pre_prompt: ""
+    post_prompt: "\nAnswer with the option's letter from the given choices directly."
+doc_to_visual: !function en_utils.mmbench_doc_to_visual
+doc_to_text: !function en_utils.mmbench_doc_to_text
+doc_to_target: "answer"
+process_results: !function en_utils.mmbench_process_results
+model_specific_generation_kwargs:
+  llava:
+    image_aspect_ratio: original
+output_type: generate_until
+dataset_name: "en"
+generation_kwargs:
+  until:
+    - "ASSISTANT:"
+  max_new_tokens: 1024
+  temperature: 0
+  top_p: 0
+  num_beams: 1
+  do_sample: false

lmms_eval/tasks/mmbench/cc_utils.py

@@ -7,6 +7,7 @@
 
 eval_logger = logging.getLogger("lmms-eval")
 from lmms_eval.tasks.mmbench.mmbench_evals import MMBench_Evaluator
+from lmms_eval.tasks._task_utils.file_utils import generate_submission_file
 
 with open(Path(__file__).parent / "mmbench_cn.yaml", "r") as f:
     raw_data = f.readlines()
@@ -66,9 +67,9 @@ def mmbench_cn_cc_process_results(doc, results):
     return data
 
 
-def mmbench_cn_cc_aggregate_results(results):
+def mmbench_cn_cc_aggregate_results(results, args):
     df = pd.DataFrame(results)
-    os.makedirs("./submissions", exist_ok=True)
-    with pd.ExcelWriter("./submissions/mmbench_cn_cc_results.xlsx") as writer:
+    file = generate_submission_file("mmbench_cn_cc_results.xlsx", args)
+    with pd.ExcelWriter(file) as writer:
         df.to_excel(writer, index=False)
-    eval_logger.info(f"Saved results to mmbench_cn_cc_results.xlsx")
+    eval_logger.info(f"Saved results to {file}")

lmms_eval/tasks/mmbench/cn_utils.py

@@ -83,8 +83,7 @@ def mmbench_aggregate_dev_results(results, args):
 
 def mmbench_aggregate_test_results(results, args):
     df = pd.DataFrame(results)
-    Path(args.output_path).joinpath("submissions").mkdir(parents=True, exist_ok=True)
-    excel_write_path = Path(args.output_path) / "submissions" / f"mmbench_cn_test_results.xlsx"
+    excel_write_path = generate_submission_file("mmbench_cn_test_results.xlsx", args)
     with pd.ExcelWriter(excel_write_path) as writer:
         df.to_excel(writer, index=False)
     eval_logger.info(f"Saved results to {excel_write_path}")

lmms_eval/tasks/mmbench/en_utils.py

@@ -36,15 +36,15 @@ def mmbench_doc_to_text(doc, model_specific_prompt_kwargs=None):
         "answer": doc.get("answer", None),
         "options": options_prompt,
         "category": doc["category"],
-        "L2-category": doc["l2-category"],
+        "L2-category": doc["L2-category"],
         "options_dict": options_dict,
         "index": doc["index"],
         "hint": doc["hint"],
         "source": doc["source"],
         "split": doc["split"],
     }
 
-    query_prompt = f"{data['hint']} {data['question']} {data['options']}" if pd.notna(data["hint"]) else f"{data['question']} {data['options']}"
+    query_prompt = f"{data['hint']} {data['question']} {data['options']}" if pd.notna(data["hint"]) and data["hint"] != "nan" else f"{data['question']} {data['options']}"
 
     if model_specific_prompt_kwargs:
         query_prompt = f"{query_prompt}\n{model_specific_prompt_kwargs['post_prompt']}"
@@ -64,7 +64,7 @@ def mmbench_process_results(doc, results):
             "source": doc["source"],
             "split": doc["split"],
             "category": doc["category"],
-            "L2-category": doc["l2-category"],
+            "L2-category": doc["L2-category"],
         }
     }
     option_candidate = ["A", "B", "C", "D", "E"]
@@ -83,8 +83,7 @@ def mmbench_aggregate_dev_results(results, args):
 
 def mmbench_aggregate_test_results(results, args):
     df = pd.DataFrame(results)
-    Path(args.output_path).joinpath("submissions").mkdir(parents=True, exist_ok=True)
-    excel_write_path = Path(args.output_path) / "submissions" / f"mmbench_en_test_results.xlsx"
+    excel_write_path = generate_submission_file("mmbench_en_test_results.xlsx", args)
     with pd.ExcelWriter(excel_write_path) as writer:
         df.to_excel(writer, index=False)
     eval_logger.info(f"Saved results to {excel_write_path}")

lmms_eval/tasks/mmbench/mmbench_cc.yaml

@@ -1,9 +1,8 @@
-dataset_path: lmms-lab/MMBench_CN
+dataset_path: lmms-lab/MMBench
+dataset_name: cc
 dataset_kwargs:
   token: True
-group: mmbench_cn
 task: "mmbench_cn_cc"
-dataset_name: "chinese_culture"
 test_split: test
 output_type: generate_until
 doc_to_visual: !function cc_utils.mmbench_doc_to_visual

lmms_eval/tasks/mmbench/mmbench_cn.yaml

@@ -5,4 +5,6 @@ task:
   - mmbench_cn_cc
 metadata:
   version: 0.0
-  sys_prompt: "有如下几个选项："
+  gpt_eval_model_name: "gpt-3.5-turbo"
+  quick_extract: true
+  sys_prompt: "有如下几个选项："

lmms_eval/tasks/mmbench/mmbench_cn_dev.yaml

@@ -1,33 +1,7 @@
-dataset_path: lmms-lab/MMBench_CN
-dataset_kwargs:
-  token: True
-group: mmbench_cn
 task: "mmbench_cn_dev"
-dataset_name: "default"
 test_split: "dev"
-output_type: generate_until
-doc_to_visual: !function cn_utils.mmbench_doc_to_visual
-doc_to_text: !function cn_utils.mmbench_doc_to_text
-doc_to_target: "answer"
-generation_kwargs:
-  max_new_tokens: 256
-  temperature: 0
-  top_p: 0
-  num_beams: 1
-  do_sample: false
-process_results: !function cn_utils.mmbench_process_results
 metric_list:
   - metric: submission
+    higher_is_better: true
     aggregation: !function cn_utils.mmbench_aggregate_dev_results
-metadata:
-  version: 0.0
-  gpt_eval_model_name: "gpt-3.5-turbo"
-  quick_extract: true
-
-model_specific_prompt_kwargs:
-  default:
-    pre_prompt: ""
-    post_prompt: "\n请直接使用所提供的选项字母作为答案回答。"
-model_specific_generation_kwargs:
-  llava:
-    image_aspect_ratio: original
+include: _default_template_mmbench_cn_yaml

lmms_eval/tasks/mmbench/mmbench_cn_test.yaml

@@ -1,33 +1,7 @@
-dataset_path: lmms-lab/MMBench_CN
-dataset_kwargs:
-  token: True
-task: "mmbench_cn_test"
-dataset_name: "default"
+task: mmbench_cn_test
 test_split: test
-output_type: generate_until
-doc_to_visual: !function cn_utils.mmbench_doc_to_visual
-doc_to_text: !function cn_utils.mmbench_doc_to_text
-doc_to_target: "answer"
-generation_kwargs:
-  max_new_tokens: 256
-  temperature: 0
-  top_p: 0
-  num_beams: 1
-  do_sample: false
-process_results: !function cn_utils.mmbench_process_results
 metric_list:
   - metric: submission
     aggregation: !function cn_utils.mmbench_aggregate_test_results
     higher_is_better: true
-metadata:
-  version: 0.0
-  gpt_eval_model_name: "gpt-3.5-turbo"
-  quick_extract: true
-
-model_specific_prompt_kwargs:
-  default:
-    pre_prompt: ""
-    post_prompt: "\n请直接使用所提供的选项字母作为答案回答。"
-model_specific_generation_kwargs:
-  llava:
-    image_aspect_ratio: original
+include: _default_template_mmbench_cn_yaml

lmms_eval/tasks/mmbench/mmbench_en.yaml

@@ -5,11 +5,3 @@ task:
 metadata:
   version: 0.0
   sys_prompt: "There are several options:"
-
-model_specific_prompt_kwargs:
-  default:
-    pre_prompt: ""
-    post_prompt: "\nAnswer with the option's letter from the given choices directly."
-model_specific_generation_kwargs:
-  llava:
-    image_aspect_ratio: original

lmms_eval/tasks/mmbench/mmbench_en_dev.yaml

@@ -1,23 +1,7 @@
-dataset_path: lmms-lab/MMBench_EN
-dataset_kwargs:
-  token: True
 task: "mmbench_en_dev"
 test_split: dev
-output_type: generate_until
-doc_to_visual: !function en_utils.mmbench_doc_to_visual
-doc_to_text: !function en_utils.mmbench_doc_to_text
-doc_to_target: "answer"
-generation_kwargs:
-  until:
-    - "ASSISTANT:"
-  max_new_tokens: 1024
-  temperature: 0
-  top_p: 0
-  num_beams: 1
-  do_sample: false
-process_results: !function en_utils.mmbench_process_results
+include: _default_template_mmbench_en_yaml
 metric_list:
   - metric: submission
     aggregation: !function en_utils.mmbench_aggregate_dev_results
-metadata:
-  version: 0.0
+    higher_is_better: true

lmms_eval/tasks/mmbench/mmbench_en_test.yaml

@@ -1,22 +1,7 @@
-dataset_path: lmms-lab/MMBench_EN
-dataset_kwargs:
-  token: True
 task: "mmbench_en_test"
 test_split: test
-output_type: generate_until
-doc_to_visual: !function en_utils.mmbench_doc_to_visual
-doc_to_text: !function en_utils.mmbench_doc_to_text
-doc_to_target: "answer"
-generation_kwargs:
-  max_new_tokens: 256
-  temperature: 0
-  top_p: 0
-  num_beams: 1
-  do_sample: false
-process_results: !function en_utils.mmbench_process_results
+include: _default_template_mmbench_en_yaml
 metric_list:
   - metric: submission
     aggregation: !function en_utils.mmbench_aggregate_test_results
     higher_is_better: true
-metadata:
-  version: 0.0