refactor evaluation, upgrade trl to 074

Former-commit-id: ed09ebe2c1926ffdb0520b3866f7fd03a9aed046

src/llmtuner/extras/misc.py

@@ -1,6 +1,8 @@
 import gc
+import os
+import sys
 import torch
-from typing import TYPE_CHECKING, Tuple
+from typing import TYPE_CHECKING, Any, Dict, Optional, Tuple
 from transformers import InfNanRemoveLogitsProcessor, LogitsProcessorList
 
 try:
@@ -17,6 +19,7 @@ except ImportError:
     _is_bf16_available = torch.cuda.is_bf16_supported()
 
 if TYPE_CHECKING:
+    from transformers import HfArgumentParser
     from transformers.modeling_utils import PreTrainedModel
 
 
@@ -74,7 +77,7 @@ def infer_optim_dtype(model_dtype: torch.dtype) -> torch.dtype:
         return torch.float32
 
 
-def get_logits_processor() -> LogitsProcessorList:
+def get_logits_processor() -> "LogitsProcessorList":
     r"""
     Gets logits processor that removes NaN and Inf logits.
     """
@@ -93,6 +96,17 @@ def torch_gc() -> None:
         torch.cuda.ipc_collect()
 
 
+def parse_args(parser: "HfArgumentParser", args: Optional[Dict[str, Any]] = None) -> Tuple[Any]:
+    if args is not None:
+        return parser.parse_dict(args)
+    elif len(sys.argv) == 2 and sys.argv[1].endswith(".yaml"):
+        return parser.parse_yaml_file(os.path.abspath(sys.argv[1]))
+    elif len(sys.argv) == 2 and sys.argv[1].endswith(".json"):
+        return parser.parse_json_file(os.path.abspath(sys.argv[1]))
+    else:
+        return parser.parse_args_into_dataclasses()
+
+
 def dispatch_model(model: "PreTrainedModel") -> "PreTrainedModel":
     r"""
     Dispatches a pre-trained model to GPUs with balanced memory.