revert file

Author: JewelRoam

graph_net/paddle/test_compiler.py

@@ -112,15 +112,12 @@ def test_single_model(args):
     print("-- Run with compiled mode")
     build_strategy = paddle.static.BuildStrategy()
     # build_strategy.build_cinn_pass = True
-    compilation_start_time = time.time()
     compiled_model = paddle.jit.to_static(
         model_dy,
         input_spec=input_spec,
         build_strategy=build_strategy,
         full_graph=True,
     )
-    compilation_end_time = time.time()
-    compilation_duration = compilation_end_time - compilation_start_time
     compiled_model.eval()
     for _ in range(args.warmup if args.warmup > 0 else 0):
         compiled_model(**input_dict)
@@ -170,7 +167,7 @@ def print_cmp(key, func, **kwargs):
     print_cmp("cmp.diff_count_atol2_rtol1", get_cmp_diff_count, atol=1e-2, rtol=1e-1)
 
     print(
-        f"{args.log_prompt} duration model_path:{args.model_path} eager:{eager_duration_box.value} compiled:{compiled_duration_box.value} compilation_time:{compilation_duration}",
+        f"{args.log_prompt} duration model_path:{args.model_path} eager:{eager_duration_box.value} compiled:{compiled_duration_box.value}",
         file=sys.stderr,
     )
 

graph_net/torch/utils.py

@@ -10,8 +10,6 @@
 import inspect
 import math
 
-kLiteralTensorSize = 64
-
 
 def apply_templates(forward_code: str) -> str:
     tab = "    "
@@ -54,7 +52,7 @@ def process_tensor(tensor):
 
         info = tensor_info(tensor)
         if tensor.dtype in [torch.int8, torch.int16, torch.int32, torch.int64]:
-            if tensor.numel() < kLiteralTensorSize:
+            if tensor.numel() < 64:
                 return {
                     "type": "small_int_tensor",
                     "data": tensor.clone(),
@@ -67,7 +65,7 @@ def process_tensor(tensor):
                     "max_val": tensor.max().item(),
                     "info": info,
                 }
-        elif tensor.numel() < kLiteralTensorSize:
+        elif tensor.numel() < 64:
             return {"type": "small_tensor", "data": tensor.clone(), "info": info}
         else:
             return {"type": "random_tensor", "info": info}
@@ -82,7 +80,7 @@ def process_tensor(tensor):
     def handle_named_tensors(tensor):
         info = tensor_info(tensor)
         if tensor.dtype in [torch.int8, torch.int16, torch.int32, torch.int64]:
-            if tensor.numel() < kLiteralTensorSize:
+            if tensor.numel() < 64:
                 return {
                     "info": info,
                     "data": tensor.clone(),
@@ -95,7 +93,7 @@ def handle_named_tensors(tensor):
                     "max_val": tensor.max().item(),
                     "type": "big_int_tensor_by_range",
                 }
-        if tensor.numel() < kLiteralTensorSize:
+        if tensor.numel() < 64:
             return {"info": info, "data": tensor.clone(), "type": "small_tensor"}
         else:
             return {"info": info, "data": None, "type": "random_tensor"}