Apply lintrunner --all-files -a (#275)

Summary:
Pretty big bang fix for all existing linter issues captured by #266.  They are:

* F401 imported but unused
* B028 No explicit stacklevel argument found
* C901 too complex (ignored with `# noqa: C901`)
* C419 Unnecessary list comprehension
* F841 local variable is assigned to but never used
* B023 Function definition does not bind loop variable (only once in `backends/xnnpack/test/test_xnnpack_quantized.py`)
* EXE001 Shebang is present but the file is not executable

### Testing

All tests pass on CI and `lintrunner --all-files -a` passes locally.

Pull Request resolved: #275

Test Plan: `arc lint` && `lintrunner --all-files -a` locally

Reviewed By: guangy10

Differential Revision: D49175246

Pulled By: huydhn

fbshipit-source-id: 1d035dd791f9bdafbae14b6d9132e8ca6cf52b9f

Author: huydhn

backends/transforms/TARGETS

@@ -20,5 +20,6 @@ python_library(
     deps = [
         "//caffe2:torch",
         "//executorch/exir:sym_util",
+        "//executorch/exir/dialects:lib",
     ],
 )

backends/transforms/__init__.py

@@ -6,7 +6,7 @@
 
 # pyre-strict
 
-from executorch.backends.transforms.addmm_mm_to_linear import (
+from executorch.backends.transforms.addmm_mm_to_linear import (  # noqa: F401
     apply_addmm_mm_to_linear_transform,
     get_shape,
 )

backends/vulkan/serialization/vulkan_graph_schema.py

@@ -12,7 +12,7 @@
 
 from dataclasses import dataclass
 from enum import IntEnum
-from typing import List, Union
+from typing import List
 
 
 class VkDatatype(IntEnum):

backends/xnnpack/partition/xnnpack_partitioner.py

@@ -347,7 +347,7 @@ def qualify_nodes(self, input_nodes: List[torch.fx.Node]) -> bool:
         Disqualify the whole module if one of the nodes fails to satisfy.
         """
         return all(
-            [XnnpackOperatorSupport.check_constraint(node) for node in input_nodes]
+            XnnpackOperatorSupport.check_constraint(node) for node in input_nodes
         )
 
     def get_module_partitions(

backends/xnnpack/passes/TARGETS

@@ -21,6 +21,5 @@ python_library(
         "//executorch/exir:pass_base",
         "//executorch/exir/dialects:lib",
         "//executorch/exir/passes:const_prop_pass",
-        "//executorch/exir/passes:lib",
     ],
 )

backends/xnnpack/passes/channels_last_tagged_reshape_pass.py

@@ -344,7 +344,7 @@ def input_to_nchw(
             target_node=target_node,
         )
 
-    def call(self, graph_module: torch.fx.GraphModule):
+    def call(self, graph_module: torch.fx.GraphModule):  # noqa: C901
         graph = graph_module.graph
         original_nodes = list(graph.nodes)
         for node in original_nodes:

backends/xnnpack/test/TARGETS

@@ -25,7 +25,6 @@ python_unittest(
         "//executorch/bundled_program:core",
         "//executorch/bundled_program/serialize:lib",
         "//executorch/exir:lib",
-        "//executorch/exir:tracer",
         "//executorch/exir/backend:backend_api",
         "//executorch/exir/passes:spec_prop_pass",
         "//executorch/extension/pybindings:portable_lib",  # @manual
@@ -54,7 +53,6 @@ python_unittest(
         "//executorch/bundled_program:core",
         "//executorch/bundled_program/serialize:lib",
         "//executorch/exir:lib",
-        "//executorch/exir:tracer",
         "//executorch/exir/backend:backend_api",
         "//executorch/exir/dialects:lib",
         "//executorch/exir/passes:spec_prop_pass",
@@ -84,7 +82,6 @@ python_unittest(
         "//executorch/bundled_program:core",
         "//executorch/bundled_program/serialize:lib",
         "//executorch/exir:lib",
-        "//executorch/exir:tracer",
         "//executorch/exir/backend:backend_api",
         "//executorch/exir/passes:spec_prop_pass",
         "//executorch/extension/pybindings:portable_lib",  # @manual

backends/xnnpack/test/test_xnnpack_quantized.py

@@ -46,18 +46,17 @@ def just_quant(x):
         self.lower_module_and_test_output(just_quant, sample_input)
 
     def test_xnnpack_qmax_pool_2d(self):
-        for maxpool_params in [(4,), (4, 2), (4, 2, 2)]:
-
-            class maxpool(torch.nn.Module):
-                def __init__(self):
-                    super().__init__()
-                    self.max = torch.nn.MaxPool2d(*maxpool_params)
+        class maxpool(torch.nn.Module):
+            def __init__(self, maxpool_params):
+                super().__init__()
+                self.max = torch.nn.MaxPool2d(*maxpool_params)
 
-                def forward(self, x):
-                    return self.max(x)
+            def forward(self, x):
+                return self.max(x)
 
+        for maxpool_params in [(4,), (4, 2), (4, 2, 2)]:
             example_input = (torch.ones(1, 2, 8, 8),)
-            self.quantize_and_test_model(maxpool(), example_input)
+            self.quantize_and_test_model(maxpool(maxpool_params), example_input)
 
     def test_xnnpack_qadd(self):
         class Add(torch.nn.Module):

backends/xnnpack/test/test_xnnpack_utils.py

@@ -35,7 +35,6 @@
 from executorch.exir.backend.backend_api import to_backend, validation_disabled
 
 from executorch.exir.passes.spec_prop_pass import SpecPropPass
-from executorch.exir.tracer import _default_decomposition_table
 
 from executorch.extension.pybindings.portable_lib import (  # @manual
     _load_for_executorch_from_buffer,

backends/xnnpack/test/tester/tester.py

@@ -290,7 +290,7 @@ def __init__(
             self._stage_name(Serialize): [],
         }
         assert all(
-            [stage in self.pipeline for stage in self.stages]
+            stage in self.pipeline for stage in self.stages
         ), "Invalid Tester internal state!"
 
         # Current stage name