fixed ipex issue

Author: Egor-Krivov

dl_bench/llm.py

@@ -3,7 +3,7 @@
 import math
 
 import torch
-import intel_extension_for_pytorch as ipex
+# import intel_extension_for_pytorch as ipex
 import numpy as np
 from transformers import (
     AutoModelForCausalLM,
@@ -76,14 +76,15 @@ def inference(self, backend):
         # self.flops_per_sample = get_macs(self.model, self.in_shape, backend) * 2
         self.model = backend.prepare_eval_transformer(self.model)
 
-        self.model.eval()
         enabled = backend.dtype != torch.float32
 
         n_items = 0
         outputs = []
         fw_times = []
 
-        self.model.eval()
+
+        # Ipex gives error with eval, other backends have no effect
+        # self.model.eval()
         for i in range(self.n_iter):
             print(f"Epoch {i+1}/{self.n_iter}")
             cast = torch.autocast(enabled=enabled, device_type=backend.device_name)

dl_bench/utils.py

@@ -132,7 +132,7 @@ def prepare_eval_transformer(self, model):
         model = model.to(memory_format=torch.channels_last)
 
         model.to(self.device)
-        with torch.inference_mode():
+        with torch.no_grad():
             model.eval()
             return self._compile_transformer_model(
                 self.compile_mode, model, dtype=self.dtype