black reformatting

llvm · Apr 29, 2024 · da9f005 · da9f005
1 parent e70d835
commit da9f005
Showing 1 changed file with 28 additions and 19 deletions.
diff --git a/projects/pt1/python/torch_mlir_e2e_test/test_suite/conv.py b/projects/pt1/python/torch_mlir_e2e_test/test_suite/conv.py
@@ -1047,46 +1047,55 @@ def Conv2dQInt8Module_basic(module, tu: TestUtils):
     bias = torch.rand(3)
     module.forward(inputVec, weight, bias)
 
+
 N = 10
 Cin = 5
 Cout = 7
 Hin = 10
 Win = 8
 Hker = 3
 Wker = 2
+
+
 class ConvTranspose2DQInt8Module(torch.nn.Module):
 
     def __init__(self):
         super().__init__()
 
     @export
-    @annotate_args([
-        None,
-        ([-1, -1, -1, -1], torch.int8, True),
-        ([-1, -1, -1, -1], torch.int8, True),
-        ([-1], torch.float, True),
-    ])
+    @annotate_args(
+        [
+            None,
+            ([-1, -1, -1, -1], torch.int8, True),
+            ([-1, -1, -1, -1], torch.int8, True),
+            ([-1], torch.float, True),
+        ]
+    )
     def forward(self, input, weight, bias):
         qinput = torch._make_per_tensor_quantized_tensor(input, 0.01, -25)
         qinput = torch.dequantize(qinput)
         qweight = torch._make_per_tensor_quantized_tensor(weight, 0.01, 50)
         qweight = torch.dequantize(qweight)
         qbias = torch.quantize_per_tensor(bias, 0.0001, 0, torch.qint32)
         qbias = torch.dequantize(qbias)
-        qz =  torch.ops.aten.convolution(qinput, 
-                                qweight,
-                                bias=qbias,
-                                stride=[2,1],
-                                padding=[1,1],
-                                dilation=[1,1],
-                                transposed=True,
-                                output_padding=[0,0],
-                                groups=1)
+        qz = torch.ops.aten.convolution(
+            qinput,
+            qweight,
+            bias=qbias,
+            stride=[2, 1],
+            padding=[1, 1],
+            dilation=[1, 1],
+            transposed=True,
+            output_padding=[0, 0],
+            groups=1,
+        )
         return qz
 
+
 @register_test_case(module_factory=lambda: ConvTranspose2DQInt8Module())
 def ConvTranspose2DQInt8_basic(module, tu: TestUtils):
-    module.forward(tu.randint(N, Cin, Hin, Win, low=-128, high=127).to(torch.int8),
-                   tu.randint(Cin, Cout, Hker, Wker, low=-128, high=127).to(torch.int8),
-                   torch.rand(Cout),
-                   )
+    module.forward(
+        tu.randint(N, Cin, Hin, Win, low=-128, high=127).to(torch.int8),
+        tu.randint(Cin, Cout, Hker, Wker, low=-128, high=127).to(torch.int8),
+        torch.rand(Cout),
+    )