fix

optimum_benchmark/backends/base.py

@@ -70,14 +70,11 @@ def __init__(self, config: BackendConfigT):
 
         elif self.config.library == "llama_cpp":
             self.logger.info("\t+ Benchmarking a LlamaCpp model")
-            # TOD: need a custom method to extract shapes from gguf
-            self.model_shapes = extract_transformers_shapes_from_artifacts(
-                self.pretrained_config, self.pretrained_processor
-            )
             self.pretrained_processor = None
-            self.generation_config = None
             self.pretrained_config = None
+            self.generation_config = None
             self.automodel_loader = None
+            self.model_shapes = {}
 
         else:
             self.logger.info("\t+ Benchmarking a Transformers model")

optimum_benchmark/backends/llama_cpp/backend.py

@@ -41,15 +41,10 @@ def llama_cpp_kwargs(self) -> Dict[str, Any]:
             "echo": False,
         }
 
-    def prepare_input_shapes(self, input_shapes: Dict[str, Any]) -> Dict[str, Any]:
-        if self.config.task == "text-generation":
-            if input_shapes["batch_size"] != 1:
-                raise ValueError("Batch size must be 1 for LlamaCpp text generation")
-
-        return input_shapes
-
     def prepare_inputs(self, inputs: Dict[str, Any]) -> Dict[str, Any]:
         if self.config.task == "text-generation":
+            if inputs["input_ids"].shape[0] != 1:
+                raise ValueError("Batch size must be 1 for LlamaCpp text generation")
             return {"tokens": inputs["input_ids"].squeeze(0).tolist()}
 
         elif self.config.task == "feature-extraction":

optimum_benchmark/launchers/torchrun/launcher.py

@@ -24,10 +24,6 @@ class TorchrunLauncher(Launcher[TorchrunConfig]):
     def __init__(self, config: TorchrunConfig):
         super().__init__(config)
 
-        if sys.platform == "win32":
-            self.logger.info("\t+ Disabline libuv on Windows")
-            os.environ["USE_LIBUV"] = "0"
-
         if get_start_method(allow_none=True) != self.config.start_method:
             self.logger.info(f"\t+ Setting multiprocessing start method to {self.config.start_method}")
             set_start_method(self.config.start_method, force=True)
@@ -164,8 +160,14 @@ def entrypoint(worker: Callable[..., BenchmarkReport], worker_args: List[Any], l
         device = torch.device("cuda", rank)
         torch.cuda.set_device(device)
 
+    if sys.platform == "win32":
+        logger.info("\t+ Disabling libuv for Windows")
+        init_method = "env://?use_libuv=0"
+    else:
+        init_method = "env://"
+
     logger.info("\t+ Initializing torch.distributed process group")
-    torch.distributed.init_process_group()
+    torch.distributed.init_process_group(init_method=init_method)
 
     try:
         report = worker(*worker_args)