PyUpgrade 3.8 updates (#55)

Co-authored-by: UltralyticsAssistant <[email protected]>

benchmark/evaluate_famous_models.py

@@ -23,6 +23,6 @@
             dsize = (1, 3, 299, 299)
         inputs = torch.randn(dsize).to(device)
         total_ops, total_params = profile(model, (inputs,), verbose=False)
-        print("%s | %.2f | %.2f" % (name, total_params / (1000**2), total_ops / (1000**3)))
+        print(f"{name} | {total_params / (1000**2):.2f} | {total_ops / (1000**3):.2f}")
     except Exception as e:
         print(f"Warning: failed to process {e}")

benchmark/evaluate_rnn_models.py

@@ -34,13 +34,7 @@
         total_ops, total_params = profile(model, (inputs[0],), verbose=False)
     else:
         total_ops, total_params = profile(model, (inputs,), verbose=False)
-    print(
-        "{} | {:.2f} | {:.2f}".format(
-            name,
-            total_params / 1e6,
-            total_ops / 1e9,
-        )
-    )
+    print(f"{name} | {total_params / 1e6:.2f} | {total_ops / 1e9:.2f}")
 
 # validate batch_first support
 inputs = torch.randn(100, 32, input_size)

thop/profile.py

@@ -69,8 +69,8 @@ def add_hooks(m):
 
         if hasattr(m, "total_ops") or hasattr(m, "total_params"):
             logging.warning(
-                "Either .total_ops or .total_params is already defined in %s. "
-                "Be careful, it might change your code's behavior." % str(m)
+                f"Either .total_ops or .total_params is already defined in {str(m)}. "
+                "Be careful, it might change your code's behavior."
             )
 
         m.register_buffer("total_ops", torch.zeros(1, dtype=default_dtype))

thop/vision/basic_hooks.py

@@ -44,7 +44,7 @@ def count_convNd_ver2(m: _ConvNd, x, y: torch.Tensor):
     x = x[0]
 
     # N x H x W (exclude Cout)
-    output_size = torch.zeros((y.size()[:1] + y.size()[2:])).numel()
+    output_size = torch.zeros(y.size()[:1] + y.size()[2:]).numel()
     # # Cout x Cin x Kw x Kh
     # kernel_ops = m.weight.nelement()
     # if m.bias is not None: