test

optimum_benchmark/backends/py_txi/backend.py

@@ -63,40 +63,33 @@ def prepare_generation_config(self) -> None:
 
     def create_no_weights_model(self) -> None:
         self.no_weights_model = os.path.join(self.tmpdir.name, "no_weights_model")
-        self.logger.info("\t+ Creating no weights model directory")
         os.makedirs(self.no_weights_model, exist_ok=True)
-        self.logger.info("\t+ Creating no weights model state dict")
         state_dict = torch.nn.Linear(1, 1).state_dict()
-        self.logger.info("\t+ Saving no weights model safetensors")
         safetensor = os.path.join(self.no_weights_model, "model.safetensors")
         save_file(tensors=state_dict, filename=safetensor, metadata={"format": "pt"})
-        self.logger.info("\t+ Saving no weights model pretrained config")
-        self.pretrained_config.save_pretrained(save_directory=self.no_weights_model)
-        self.logger.info("\t+ Saving no weights model pretrained processor")
-        self.pretrained_processor.save_pretrained(save_directory=self.no_weights_model)
-        # unlike Transformers, TXI won't accept any missing tensors so we need to materialize the model
-        self.logger.info(f"\t+ Loading no weights model from {self.no_weights_model}")
         with fast_weights_init():
+            # unlike Transformers, TXI won't accept any missing tensors so we need to materialize the model
             self.pretrained_model = self.automodel_loader.from_pretrained(
                 self.no_weights_model, **self.config.model_kwargs, device_map="auto", _fast_init=False
             )
-        self.logger.info("\t+ Saving no weights model")
-        self.pretrained_model.save_pretrained(save_directory=self.no_weights_model)
+        save_file(tensors=self.pretrained_model.state_dict(), filename=safetensor, metadata={"format": "pt"})
         del self.pretrained_model
         torch.cuda.empty_cache()
 
-        if self.config.task in TEXT_GENERATION_TASKS:
-            self.logger.info("\t+ Modifying generation config for fixed length generation")
+        if self.pretrained_config is not None:
+            self.pretrained_config.save_pretrained(save_directory=self.no_weights_model)
+        if self.pretrained_processor is not None:
+            self.pretrained_processor.save_pretrained(save_directory=self.no_weights_model)
+        if self.generation_config is not None:
             self.generation_config.eos_token_id = None
             self.generation_config.pad_token_id = None
-            self.logger.info("\t+ Saving new pretrained generation config")
             self.generation_config.save_pretrained(save_directory=self.no_weights_model)
 
     def load_model_with_no_weights(self) -> None:
-        self.config.volumes[self.tmpdir.name] = {"bind": "/no_weights_data/", "mode": "rw"}
-        original_model, self.config.model = self.config.model, "/no_weights_data/no_weights_model/"
+        self.config.volumes = (self.config.volumes, {self.tmpdir.name: {"bind": self.tmpdir.name, "mode": "rw"}})
+        original_model, self.config.model = self.config.model, self.no_weights_model
         self.load_model_from_pretrained()
-        self.config.model = original_model
+        self.config.model, self.config.volumes = original_model
 
     def load_model_from_pretrained(self) -> None:
         if self.config.task in TEXT_GENERATION_TASKS:

tests/configs/cpu_inference_py_txi_gpt2.yaml

@@ -9,3 +9,6 @@ defaults:
   - override backend: py-txi
 
 name: cpu_inference_py_txi_gpt2
+
+backend:
+  cuda_graphs: 0

tests/configs/cuda_inference_py_txi_gpt2.yaml

@@ -9,3 +9,6 @@ defaults:
   - override backend: py-txi
 
 name: cuda_inference_py_txi_gpt2
+
+backend:
+  cuda_graphs: 0