Refactor test and imports

Author: keyprocedure

backends/xnnpack/_passes/channels_last_tagged_reshape_pass.py

@@ -8,11 +8,12 @@
 
 import torch
 from executorch.backends.xnnpack._passes.xnnpack_pass import XNNPACKPass
-from executorch.backends.xnnpack.utils.utils import is_param_node
 from executorch.backends.xnnpack.utils.quant_utils import is_dynamic_qdq
+from executorch.backends.xnnpack.utils.utils import is_param_node
 from executorch.exir.dialects._ops import ops as exir_ops
 from executorch.exir.pass_base import PassResult
 
+
 # TODO(T151254305) use subgraph_rewriter
 class ChannelsLastTaggedReshapePass(XNNPACKPass):
     """

backends/xnnpack/test/ops/test_conv2d.py

@@ -30,10 +30,7 @@
 )
 from executorch.backends.xnnpack.test.test_xnnpack_utils import randomize_bn
 from executorch.backends.xnnpack.test.tester import Quantize, Tester
-from executorch.backends.xnnpack.test.tester.tester import (
-    Partition,
-    ToEdgeTransformAndLower,
-)
+from executorch.backends.xnnpack.test.tester.tester import ToEdgeTransformAndLower
 from executorch.exir.dialects._ops import ops as exir_ops
 
 
@@ -176,7 +173,7 @@ def get_inputs(self):
         return (torch.randn(2, 2, 4, 4),)
 
 
-class DQConv2d(torch.nn.Module):
+class Conv2dDynamicQuant(torch.nn.Module):
     def __init__(self):
         super().__init__()
         self.conv = torch.nn.Conv2d(3, 10, 3)
@@ -750,8 +747,8 @@ def forward(self, x):
             .run_method_and_compare_outputs(qtol=1)
         )
 
-    def test_qs8_dq_conv2d(self) -> None:
-        model = DQConv2d()
+    def test_dq_conv2d(self) -> None:
+        model = Conv2dDynamicQuant()
         self._test_dq(
             model,
             model.get_inputs(),