fix ccocr import problem and args nproc conflict with --nproc-per-node

docs/en/EvalByLMDeploy.md

@@ -23,5 +23,5 @@ lmdeploy serve api_server OpenGVLab/InternVL2-8B --model-name InternVL2-8B
 ## Step 2: Evaluation
 
 ```bash
-python run.py --data MMStar --model lmdeploy --verbose --nproc 64
+python run.py --data MMStar --model lmdeploy --verbose --api_nproc 64
 ```

docs/en/Quickstart.md

@@ -66,7 +66,7 @@ We use `run.py` for evaluation. To use the script, you can use `$VLMEvalKit/run.
 - `--data (list[str])`: Set the dataset names that are supported in VLMEvalKit (names can be found in the codebase README).
 - `--model (list[str])`: Set the VLM names that are supported in VLMEvalKit (defined in `supported_VLM` in `vlmeval/config.py`).
 - `--mode (str, default to 'all', choices are ['all', 'infer'])`: When `mode` set to "all", will perform both inference and evaluation; when set to "infer", will only perform the inference.
-- `--nproc (int, default to 4)`: The number of threads for OpenAI API calling.
+- `--api_nproc (int, default to 4)`: The number of threads for OpenAI API calling.
 - `--work-dir (str, default to '.')`: The directory to save evaluation results.
 
 **Command for Evaluating Image Benchmarks **

docs/zh-CN/EvalByLMDeploy.md

@@ -24,5 +24,5 @@ lmdeploy serve api_server OpenGVLab/InternVL2-8B --model-name InternVL2-8B
 ## 第2步 评测
 
 ```bash
-python run.py --data MMStar --model InternVL2-8B --verbose --nproc 64
+python run.py --data MMStar --model InternVL2-8B --verbose --api_nproc 64
 ```

docs/zh-CN/Quickstart.md

@@ -65,7 +65,7 @@ pip install -e .
 - `--data (list[str])`: 设置在 VLMEvalKit 中支持的数据集名称（可以在代码库首页的 README 中找到支持的数据集列表）
 - `--model (list[str])`: 设置在 VLMEvalKit 中支持的 VLM 名称（在 `vlmeval/config.py` 中的 `supported_VLM` 中定义）
 - `--mode (str, 默认值为 'all', 可选值为 ['all', 'infer'])`：当 mode 设置为 "all" 时，将执行推理和评估；当设置为 "infer" 时，只执行推理
-- `--nproc (int, 默认值为 4)`: 调用 API 的线程数
+- `--api_nproc (int, 默认值为 4)`: 调用 API 的线程数
 - `--work-dir (str, default to '.')`: 存放测试结果的目录
 
 **用于评测图像多模态评测集的命令**

run.py

@@ -131,7 +131,7 @@ def parse_args():
     # Infer + Eval or Infer Only
     parser.add_argument('--mode', type=str, default='all', choices=['all', 'infer'])
     # API Kwargs, Apply to API VLMs and Judge API LLMs
-    parser.add_argument('--nproc', type=int, default=4, help='Parallel API calling')
+    parser.add_argument('--api_nproc', type=int, default=4, help='Parallel API calling')
     parser.add_argument('--retry', type=int, default=None, help='retry numbers for API VLMs')
     # Explicitly Set the Judge Model
     parser.add_argument('--judge', type=str, default=None)
@@ -285,15 +285,15 @@ def main():
                         dataset=dataset,
                         result_file_name=result_file_base,
                         verbose=args.verbose,
-                        api_nproc=args.nproc)
+                        api_nproc=args.api_nproc)
                 elif dataset.TYPE == 'MT':
                     model = infer_data_job_mt(
                         model,
                         work_dir=pred_root,
                         model_name=model_name,
                         dataset=dataset,
                         verbose=args.verbose,
-                        api_nproc=args.nproc,
+                        api_nproc=args.api_nproc,
                         ignore_failed=args.ignore)
                 else:
                     model = infer_data_job(
@@ -302,13 +302,13 @@ def main():
                         model_name=model_name,
                         dataset=dataset,
                         verbose=args.verbose,
-                        api_nproc=args.nproc,
+                        api_nproc=args.api_nproc,
                         ignore_failed=args.ignore)
 
                 # Set the judge kwargs first before evaluation or dumping
 
                 judge_kwargs = {
-                    'nproc': args.nproc,
+                    'nproc': args.api_nproc,
                     'verbose': args.verbose,
                     'retry': args.retry if args.retry is not None else 3
                 }

vlmeval/dataset/image_ccocr.py

@@ -6,13 +6,6 @@
 from functools import partial
 import pandas as pd
 
-try:
-    from .utils.ccocr_evaluator import evaluator_map_info as ccocr_evaluator_map
-except ImportError as err:
-    import warnings
-    warnings.warn('The dependency of CCOCR evaluator is not properly installed')
-    warnings.warn(f'{type(err)}: {err}')
-
 from .image_base import ImageBaseDataset
 from ..smp import *
 
@@ -176,6 +169,12 @@ def evaluate(self, eval_file, **judge_kwargs):
         data_name = set([str(x) for x in df['split']]).pop()
 
         data_info = {"op": op_name, "group": group_name, "dataset": data_name,  "num": len(gt_info)}
+        try:
+            from .utils.ccocr_evaluator import evaluator_map_info as ccocr_evaluator_map
+        except ImportError as err:
+            import warnings
+            warnings.warn('The dependency of CCOCR evaluator is not properly installed')
+            warnings.warn(f'{type(err)}: {err}')
         eval_func = ccocr_evaluator_map.get(group_name, None)
         if eval_func is None:
             raise ValueError("error: evaluator not defined for: {}".format(group_name))

vlmeval/tools.py

@@ -480,7 +480,7 @@ def extract_dataset(file_name):
 
         dataset = extract_dataset(data_file)
         assert dataset is not None, f'Cannot infer dataset name from {data_file}'
-        kwargs = {'nproc': args.nproc}
+        kwargs = {'nproc': args.api_nproc}
         if args.judge is not None:
             kwargs['model'] = args.judge
         if args.retry is not None: