Arm backend: Format docs in backends/arm/test/ops

backends/arm/test/ops/test_adaptive_avg_pool2d.py

@@ -1,4 +1,4 @@
-# Copyright 2025 Arm Limited and/or its affiliates.
+# Copyright 2025-2026 Arm Limited and/or its affiliates.
 #
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
@@ -173,7 +173,9 @@ def test_adaptive_avg_pool2d_u55_INT(test_module):
 @common.parametrize("test_module", u55_test_modules)
 @common.XfailIfNoCorstone300
 def test_adaptive_avg_pool2d_u55_INT_a16w8(test_module):
-    """Test adaptive_avg_pool2d with 16A8W quantization on U55 (16-bit activations, 8-bit weights)"""
+    """Test adaptive_avg_pool2d with 16A8W quantization on U55 (16-bit
+    activations, 8-bit weights)
+    """
     model, input_tensor = test_module()
     pipeline = EthosU55PipelineINT[input_t](
         model,
@@ -202,7 +204,9 @@ def test_adaptive_avg_pool2d_u85_INT(test_module):
 @common.parametrize("test_module", test_modules)
 @common.XfailIfNoCorstone320
 def test_adaptive_avg_pool2d_u85_INT_a16w8(test_module):
-    """Test adaptive_avg_pool2d with 16A8W quantization on U85 (16-bit activations, 8-bit weights)"""
+    """Test adaptive_avg_pool2d with 16A8W quantization on U85 (16-bit
+    activations, 8-bit weights)
+    """
     model, input_tensor = test_module()
     pipeline = EthosU85PipelineINT[input_t](
         model,

backends/arm/test/ops/test_add.py

@@ -280,7 +280,9 @@ def test_add_tensor_vgf_quant(test_data: input_t1):
 
 @common.parametrize("test_data", Add.test_data)
 def test_add_tensor_tosa_INT_16a8w(test_data: input_t1):
-    """Test add operation with 16A8W quantization (16-bit activations, 8-bit weights)"""
+    """Test add operation with 16A8W quantization (16-bit activations, 8-bit
+    weights)
+    """
     per_channel_quantization = False
 
     pipeline = TosaPipelineINT[input_t1](
@@ -302,7 +304,9 @@ def test_add_tensor_tosa_INT_16a8w(test_data: input_t1):
 @common.parametrize("test_data", Add.test_data)
 @common.XfailIfNoCorstone300
 def test_add_tensor_u55_INT_16a8w(test_data: input_t1):
-    """Test add operation with 16A8W quantization on U55 (16-bit activations, 8-bit weights)"""
+    """Test add operation with 16A8W quantization on U55 (16-bit activations,
+    8-bit weights)
+    """
     per_channel_quantization = False
 
     pipeline = EthosU55PipelineINT[input_t1](
@@ -323,7 +327,9 @@ def test_add_tensor_u55_INT_16a8w(test_data: input_t1):
 @common.parametrize("test_data", Add.test_data)
 @common.XfailIfNoCorstone320
 def test_add_tensor_u85_INT_16a8w(test_data: input_t1):
-    """Test add operation with 16A8W quantization on U85 (16-bit activations, 8-bit weights)"""
+    """Test add operation with 16A8W quantization on U85 (16-bit activations,
+    8-bit weights)
+    """
     per_channel_quantization = False
 
     pipeline = EthosU85PipelineINT[input_t1](

backends/arm/test/ops/test_addmm.py

@@ -190,7 +190,9 @@ def test_addmm_vgf_quant(test_data: input_t1):
 
 @common.parametrize("test_data", test_data_suite)
 def test_addmm_16a8w_tosa_INT(test_data: input_t1):
-    """Test addmm (FC layer) operation with 16A8W quantization (16-bit activations, 8-bit weights)"""
+    """Test addmm (FC layer) operation with 16A8W quantization (16-bit
+    activations, 8-bit weights)
+    """
     per_channel_quantization = False
 
     pipeline = TosaPipelineINT[input_t1](
@@ -214,7 +216,9 @@ def test_addmm_16a8w_tosa_INT(test_data: input_t1):
     reason="Vela compilation fails with 'Invalid arguments' for int16 addmm operations"
 )
 def test_addmm_16a8w_u55_INT(test_data: input_t1):
-    """Test addmm (FC layer) operation with 16A8W quantization on U55 (16-bit activations, 8-bit weights)"""
+    """Test addmm (FC layer) operation with 16A8W quantization on U55 (16-bit
+    activations, 8-bit weights)
+    """
     per_channel_quantization = False
 
     pipeline = EthosU55PipelineINT[input_t1](
@@ -234,7 +238,9 @@ def test_addmm_16a8w_u55_INT(test_data: input_t1):
 @common.parametrize("test_data", test_data_suite)
 @common.XfailIfNoCorstone320
 def test_addmm_16a8w_u85_INT(test_data: input_t1):
-    """Test addmm (FC layer) operation with 16A8W quantization on U85 (16-bit activations, 8-bit weights)"""
+    """Test addmm (FC layer) operation with 16A8W quantization on U85 (16-bit
+    activations, 8-bit weights)
+    """
     per_channel_quantization = False
 
     pipeline = EthosU85PipelineINT[input_t1](

backends/arm/test/ops/test_alias_copy.py

@@ -19,12 +19,12 @@
 
 
 class AliasCopy(torch.nn.Module):
-    """
-    Tests proper handling of alias_copy when used directly.
+    """Tests proper handling of alias_copy when used directly.
+
+    alias_copy can also appear from PyTorch/ExecuTorch optimizations such as
+    `x.transpose(0, 0)`. This is optimized to an alias_copy but not before dq/q
+    operators are added.
 
-    alias_copy can also appear from PyTorch/ExecuTorch optimizations
-    such as `x.transpose(0, 0)`. This is optimized to an alias_copy but
-    not before dq/q operators are added.
     """
 
     aten_op = "torch.ops.aten.alias_copy.default"

backends/arm/test/ops/test_amax.py

@@ -280,7 +280,9 @@ def test_amax_tosa_INT_a16w8(test_data: Amax.input_t):
 @common.parametrize("test_data", Amax.test_data)
 @common.XfailIfNoCorstone320
 def test_amax_u85_INT_a16w8(test_data: Amax.input_t):
-    """Test amax with 16A8W quantization on U85 (16-bit activations, 8-bit weights)"""
+    """Test amax with 16A8W quantization on U85 (16-bit activations, 8-bit
+    weights)
+    """
     data, dim, keep_dims = test_data()
     module = Amax(dim, keep_dims)
     pipeline = EthosU85PipelineINT[Max.input_t](

backends/arm/test/ops/test_amin.py

@@ -276,7 +276,9 @@ def test_amin_tosa_INT_a16w8(test_data: Amin.input_t):
 @common.parametrize("test_data", Amin.test_data)
 @common.XfailIfNoCorstone320
 def test_amin_u85_INT_a16w8(test_data: Min.input_t):
-    """Test amin with 16A8W quantization on U85 (16-bit activations, 8-bit weights)"""
+    """Test amin with 16A8W quantization on U85 (16-bit activations, 8-bit
+    weights)
+    """
     data, dim, keep_dims = test_data()
     pipeline = EthosU85PipelineINT[Amin.input_t](
         Amin(dim, keep_dims),

backends/arm/test/ops/test_avg_pool2d.py

@@ -35,8 +35,11 @@ def forward(self, *args, **kwargs):
 
 
 class BecomesMeanInToEdge(torch.nn.Module):
-    """This averagepool will be converted to mean when lowering to edge. This causes the decompose_meandim  pass to not
-    trigger until the backend pipeline, which requires extra care.
+    """This averagepool will be converted to mean when lowering to edge.
+
+    This causes the decompose_meandim pass to not trigger until the backend
+    pipeline, which requires extra care.
+
     """
 
     def forward(self, x: torch.Tensor):
@@ -207,7 +210,9 @@ def test_avg_pool2d_u55_INT(test_module):
 @common.parametrize("test_module", test_modules)
 @common.XfailIfNoCorstone300
 def test_avg_pool2d_16a8w_u55_INT(test_module):
-    """Test avg_pool2d with 16A8W quantization on U55 (16-bit activations, 8-bit weights)"""
+    """Test avg_pool2d with 16A8W quantization on U55 (16-bit activations, 8-bit
+    weights)
+    """
     model, input_tensor = test_module()
     pipeline = EthosU55PipelineINT[input_t](
         model,
@@ -238,7 +243,9 @@ def test_avg_pool2d_u85_INT(test_module):
 @common.parametrize("test_module", test_modules)
 @common.XfailIfNoCorstone320
 def test_avg_pool2d_16a8w_u85_INT(test_module):
-    """Test avg_pool2d with 16A8W quantization on U85 (16-bit activations, 8-bit weights)"""
+    """Test avg_pool2d with 16A8W quantization on U85 (16-bit activations, 8-bit
+    weights)
+    """
     model, input_tensor = test_module()
     pipeline = EthosU85PipelineINT[input_t](
         model,

backends/arm/test/ops/test_batch_norm.py

@@ -1,6 +1,6 @@
 # Copyright (c) Meta Platforms, Inc. and affiliates.
 # All rights reserved.
-# Copyright 2024-2025 Arm Limited and/or its affiliates.
+# Copyright 2024-2026 Arm Limited and/or its affiliates.
 #
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
@@ -266,9 +266,7 @@ def test_native_batch_norm_legit_no_training_vgf_quant_conv(test_data: Tuple):
 
 
 class BatchNorm2dNoStats(torch.nn.Module):
-    """
-    Decomposes into _native_batch_norm_legit.no_stats
-    """
+    """Decomposes into _native_batch_norm_legit.no_stats."""
 
     aten_ops = ["torch.ops.aten.batch_norm.default"]
 

backends/arm/test/ops/test_cat.py

@@ -198,7 +198,9 @@ def test_cat_vgf_quant(test_data: Tuple):
 
 @common.parametrize("test_data", Cat.test_parameters)
 def test_cat_16a8w_tosa_INT(test_data: Tuple):
-    """Test cat operation with 16A8W quantization (16-bit activations, 8-bit weights)"""
+    """Test cat operation with 16A8W quantization (16-bit activations, 8-bit
+    weights)
+    """
     per_channel_quantization = False
 
     pipeline = TosaPipelineINT[input_t1](
@@ -219,7 +221,9 @@ def test_cat_16a8w_tosa_INT(test_data: Tuple):
 @common.parametrize("test_data", Cat.test_parameters)
 @common.XfailIfNoCorstone300
 def test_cat_16a8w_u55_INT(test_data: Tuple):
-    """Test cat operation with 16A8W quantization on U55 (16-bit activations, 8-bit weights)"""
+    """Test cat operation with 16A8W quantization on U55 (16-bit activations,
+    8-bit weights)
+    """
     per_channel_quantization = False
 
     pipeline = EthosU55PipelineINT[input_t1](
@@ -240,7 +244,9 @@ def test_cat_16a8w_u55_INT(test_data: Tuple):
 @common.parametrize("test_data", Cat.test_parameters)
 @common.XfailIfNoCorstone320
 def test_cat_16a8w_u85_INT(test_data: Tuple):
-    """Test cat operation with 16A8W quantization on U85 (16-bit activations, 8-bit weights)"""
+    """Test cat operation with 16A8W quantization on U85 (16-bit activations,
+    8-bit weights)
+    """
     per_channel_quantization = False
 
     pipeline = EthosU85PipelineINT[input_t1](

backends/arm/test/ops/test_clamp.py

@@ -175,7 +175,9 @@ def test_clamp_u55_INT(test_data):
 @common.parametrize("test_data", test_data_suite)
 @common.XfailIfNoCorstone300
 def test_clamp_u55_INT_16a8w(test_data):
-    """Test clamp operation with 16A8W quantization on U55 (16-bit activations, 8-bit weights)"""
+    """Test clamp operation with 16A8W quantization on U55 (16-bit activations,
+    8-bit weights)
+    """
     input_tensor, min_val, max_val = test_data()
     model = Clamp(min_val, max_val)
     pipeline = EthosU55PipelineINT[input_t](
@@ -208,7 +210,9 @@ def test_clamp_u85_INT(test_data):
 @common.parametrize("test_data", test_data_suite)
 @common.XfailIfNoCorstone320
 def test_clamp_u85_INT_16a8w(test_data):
-    """Test clamp operation with 16A8W quantization on U85 (16-bit activations, 8-bit weights)"""
+    """Test clamp operation with 16A8W quantization on U85 (16-bit activations,
+    8-bit weights)
+    """
     input_tensor, min_val, max_val = test_data()
     model = Clamp(min_val, max_val)
     pipeline = EthosU85PipelineINT[input_t](
@@ -453,7 +457,9 @@ def test_clamp_u55_INT_tensor(test_data):
 @common.parametrize("test_data", test_data_suite_tensor_INT32)
 @common.XfailIfNoCorstone300
 def test_clamp_u55_INT_16a8w_tensor(test_data):
-    """Test clamp operation with 16A8W quantization on U55 (16-bit activations, 8-bit weights)"""
+    """Test clamp operation with 16A8W quantization on U55 (16-bit activations,
+    8-bit weights)
+    """
     input_tensor, min_val, max_val = test_data()
     model = Clamp(min_val, max_val)
     pipeline = EthosU55PipelineINT[input_t](
@@ -486,7 +492,9 @@ def test_clamp_u85_INT_tensor(test_data):
 @common.parametrize("test_data", test_data_suite_tensor_INT32)
 @common.XfailIfNoCorstone320
 def test_clamp_u85_INT_16a8w_tensor(test_data):
-    """Test clamp operation with 16A8W quantization on U85 (16-bit activations, 8-bit weights)"""
+    """Test clamp operation with 16A8W quantization on U85 (16-bit activations,
+    8-bit weights)
+    """
     input_tensor, min_val, max_val = test_data()
     model = Clamp(min_val, max_val)
     pipeline = EthosU85PipelineINT[input_t](

backends/arm/test/ops/test_cond.py

@@ -193,7 +193,9 @@ def _create() -> tuple[torch.nn.Module, input_t2]:
 def _make_calibration_samples(
     module: torch.nn.Module, example_inputs: tuple
 ) -> tuple[tuple[torch.Tensor, ...], ...]:
-    """Return one example input that triggers the if branch, and one that triggers the else branch."""
+    """Return one example input that triggers the if branch, and one that
+    triggers the else branch.
+    """
 
     if isinstance(module, CondTwoArgsOneOutput):
         # Predicate is sum(lhs-rhs) > 0

backends/arm/test/ops/test_conv1d.py

@@ -26,9 +26,10 @@
 
 
 class Conv1d(torch.nn.Module):
-    """
-    Creates one or many chained 1D-convolutions. For multiple convolutions, the
-    respective parameteres are provided as lists.
+    """Creates one or many chained 1D-convolutions.
+
+    For multiple convolutions, the respective parameters are provided as lists.
+
     """
 
     def __init__(

backends/arm/test/ops/test_conv2d.py

@@ -26,9 +26,10 @@
 
 
 class Conv2d(torch.nn.Module):
-    """
-    Creates one or many chained 2D-convolutions. For multiple convolutions, the
-    respective parameteres are provided as lists.
+    """Creates one or many chained 2D-convolutions.
+
+    For multiple convolutions, the respective parameters are provided as lists.
+
     """
 
     def __init__(
@@ -674,7 +675,9 @@ def test_convolution_2d_tosa_INT_a16w8(test_data: input_t):
 @common.parametrize("test_data", test_data_INT)
 @common.XfailIfNoCorstone300
 def test_convolution_2d_u55_INT_a16w8(test_data: input_t):
-    """Test conv2d with 16A8W quantization on U55 (16-bit activations, 8-bit weights)"""
+    """Test conv2d with 16A8W quantization on U55 (16-bit activations, 8-bit
+    weights)
+    """
     model, per_channel_quantization = test_data()
     pipeline = EthosU55PipelineINT[input_t](
         model,
@@ -691,7 +694,9 @@ def test_convolution_2d_u55_INT_a16w8(test_data: input_t):
 @common.parametrize("test_data", test_data_INT)
 @common.XfailIfNoCorstone320
 def test_convolution_2d_u85_INT_a16w8(test_data: input_t):
-    """Test conv2d with 16A8W quantization on U85 (16-bit activations, 8-bit weights)"""
+    """Test conv2d with 16A8W quantization on U85 (16-bit activations, 8-bit
+    weights)
+    """
     model, per_channel_quantization = test_data()
     pipeline = EthosU85PipelineINT[input_t](
         model,

backends/arm/test/ops/test_conv3d.py

@@ -26,9 +26,10 @@
 
 
 class Conv3d(torch.nn.Module):
-    """
-    Creates one or many chained 3D-convolutions. For multiple convolutions, the
-    respective parameteres are provided as lists.
+    """Creates one or many chained 3D-convolutions.
+
+    For multiple convolutions, the respective parameters are provided as lists.
+
     """
 
     def __init__(
@@ -128,11 +129,12 @@ def forward(self, x):
 
 
 class Conv3dMultiOp(torch.nn.Module):
-    """
-    Mixed Conv3d/Conv2d pipeline used to verify spatial-rank propagation across ops.
+    """Mixed Conv3d/Conv2d pipeline used to verify spatial-rank propagation
+    across ops.
 
     Topology:
         conv3d -> reshape -> conv2d -> reshape/permutation -> conv2d -> reshape -> add(5D)
+
     """
 
     def __init__(self, dtype=torch.float):
@@ -578,7 +580,9 @@ def test_convolution_3d_tosa_INT_multi_op():
 
 
 def test_convolution_3d_tosa_FP_depthwise():
-    """Depthwise or Grouped Conv3d should be rejected until grouped support exists."""
+    """Depthwise or Grouped Conv3d should be rejected until grouped support
+    exists.
+    """
     model = DepthwiseConv3d()
     pipeline = TosaPipelineFP[input_t](
         model,

backends/arm/test/ops/test_conv_combos.py

@@ -22,9 +22,8 @@
 
 from torch.nn.parameter import Parameter
 
-
 """
-This file contain unit tests where conv are combined with other ops.
+This file contains unit tests where conv are combined with other ops.
 """
 
 

backends/arm/test/ops/test_conv_constant_pad_nd.py

@@ -1,4 +1,4 @@
-# Copyright 2025 Arm Limited and/or its affiliates.
+# Copyright 2025-2026 Arm Limited and/or its affiliates.
 #
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
@@ -35,8 +35,6 @@
     "2dim_last1dim": (torch.rand(1, 1, 16), (1, 1, 0, 0), 1),
     "2dim_last2dim": (torch.rand(1, 1, 16), (1, 0, 1, 1), 2),
 }
-
-
 """Tests conv + pad."""