Arm backend: Format docs for remaining files in backends/arm/test/

.lintrunner.toml

@@ -511,7 +511,6 @@ include_patterns = ['backends/arm/**/*.py']
 exclude_patterns = [
   'third-party/**',
   '**/third-party/**',
-  'backends/arm/test/**',
 ]
 command = [
   'python','-m','lintrunner_adapters','run','docformatter_linter','--config=pyproject.toml','--','@{{PATHSFILE}}'

backends/arm/test/common.py

@@ -27,24 +27,24 @@
 
 
 def get_time_formatted_path(path: str, log_prefix: str) -> str:
-    """
-    Returns the log path with the current time appended to it. Used for debugging.
+    """Returns the log path with the current time appended to it. Used for
+    debugging.
 
     Args:
         path: The path to the folder where the log file will be stored.
         log_prefix: The name of the test.
 
     Example output:
         './my_log_folder/test_INT_artifact_28-Nov-14:14:38.log'
+
     """
     return str(
         Path(path) / f"{log_prefix}_{datetime.now().strftime('%d-%b-%H:%M:%S')}.log"
     )
 
 
 def maybe_get_tosa_collate_path() -> str | None:
-    """
-    Checks the environment variable TOSA_TESTCASES_BASE_PATH and returns the
+    """Checks the environment variable TOSA_TESTCASES_BASE_PATH and returns the
     path to the where to store the current tests if it is set.
     """
     tosa_test_base = os.environ.get("TOSA_TESTCASES_BASE_PATH")
@@ -161,8 +161,8 @@ def get_vgf_compile_spec(
     custom_path: Optional[str] = None,
     tosa_debug_mode: VgfCompileSpec.DebugMode | None = None,
 ) -> VgfCompileSpec:
-    """Get the ArmCompileSpec for the default VGF tests, to modify
-    the compile spec before calling .build() to finalize it.
+    """Get the ArmCompileSpec for the default VGF tests, to modify the compile
+    spec before calling .build() to finalize it.
     """
 
     if not custom_path:
@@ -198,7 +198,9 @@ def get_vgf_compile_spec(
     raises=FileNotFoundError,
     reason="Did not find Corstone-300 FVP or executor_runner on path",
 )
-"""Xfails a test if Corsone300 FVP is not installed, or if the executor runner is not built"""
+"""Xfails a test if Corsone300 FVP is not installed, or if the executor runner
+is not built.
+"""
 
 XfailIfNoCorstone320 = pytest.mark.xfail(
     condition=not (
@@ -207,21 +209,23 @@ def get_vgf_compile_spec(
     raises=FileNotFoundError,
     reason="Did not find Corstone-320 FVP or executor_runner on path",
 )
-"""Xfails a test if Corsone320 FVP is not installed, or if the executor runner is not built"""
+"""Xfails a test if Corsone320 FVP is not installed, or if the executor runner
+is not built.
+"""
 
 SkipIfNoModelConverter = pytest.mark.skipif(  # type: ignore[call-arg]
     condition=not (model_converter_installed()),
     raises=FileNotFoundError,
     reason="Did not find model-converter on path",
 )
-"""Skips a test if model-converter is not installed"""
+"""Skips a test if model-converter is not installed."""
 
 XfailfNoVKMLEmulationLayer = pytest.mark.xfail(
     condition=not (vkml_emulation_layer_installed()),
     raises=TypeError,
     reason="VKML environment is not set properly or executor_runner path is misused",
 )
-"""Xfails a test if VKML Emulation Layer is not installed"""
+"""Xfails a test if VKML Emulation Layer is not installed."""
 
 xfail_type = str | tuple[str, type[Exception]]
 
@@ -238,12 +242,14 @@ def parametrize(
     strict: bool = True,
     flakies: dict[str, int] | None = None,
 ) -> Decorator:
-    """
-    Custom version of pytest.mark.parametrize with some syntatic sugar and added xfail functionality
-        - test_data is expected as a dict of (id, test_data) pairs
-        - alllows to specifiy a dict of (id, failure_reason) pairs to mark specific tests as xfail.
-          Failure_reason can be str, type[Exception], or tuple[str, type[Exception]].
-          Strings set the reason for failure, the exception type sets expected error.
+    """Custom version of pytest.mark.parametrize with some syntatic sugar and
+    added xfail functionality.
+
+    - test_data is expected as a dict of (id, test_data) pairs
+    - alllows to specifiy a dict of (id, failure_reason) pairs to mark specific tests as xfail.
+      Failure_reason can be str, type[Exception], or tuple[str, type[Exception]].
+      Strings set the reason for failure, the exception type sets expected error.
+
     """
     if xfails is None:
         xfails = {}
@@ -253,7 +259,9 @@ def parametrize(
         flakies = {}
 
     def decorator_func(func: Callable[_P, _R]) -> Callable[_P, _R]:
-        """Test data is transformed from a dict of (id, data) pairs to a list of pytest params to work with the native pytests parametrize function"""
+        """Test data is transformed from a dict of (id, data) pairs to a list of
+        pytest params to work with the native pytests parametrize function.
+        """
         pytest_testsuite = []
         for id, test_parameters in test_data.items():
             if id in flakies:

backends/arm/test/conftest.py

@@ -64,10 +64,10 @@ def pytest_sessionfinish(session, exitstatus):
 
 @pytest.fixture(autouse=True)
 def set_random_seed():
-    """
-    Control random numbers in Arm test suite. Default behavior is to use a fixed
-    seed (0), which ensures reproducible tests. Use the env variable ARM_TEST_SEED
-    to set a custom seed, or set it to RANDOM for random seed behavior.
+    """Control random numbers in Arm test suite. Default behavior is to use a
+    fixed seed (0), which ensures reproducible tests. Use the env variable
+    ARM_TEST_SEED to set a custom seed, or set it to RANDOM for random seed
+    behavior.
 
     Examples:
     As default use fixed seed (0) for reproducible tests
@@ -76,6 +76,7 @@ def set_random_seed():
         ARM_TEST_SEED=RANDOM pytest --config-file=/dev/null --verbose -s --color=yes  backends/arm/test/ops/test_avg_pool.py -k <TESTCASE>
     Rerun with a specific seed
         ARM_TEST_SEED=3478246 pytest --config-file=/dev/null --verbose -s --color=yes  backends/arm/test/ops/test_avg_pool.py -k <TESTCASE>
+
     """
     import torch
 
@@ -100,12 +101,12 @@ def set_random_seed():
 
 
 def is_option_enabled(option: str, fail_if_not_enabled: bool = False) -> bool:
-    """
-    Returns whether an option is successfully enabled, i.e. if the flag was
+    """Returns whether an option is successfully enabled, i.e. if the flag was
     given to pytest and the necessary requirements are available.
 
-    The optional parameter 'fail_if_not_enabled' makes the function raise
-      a RuntimeError instead of returning False.
+    The optional parameter 'fail_if_not_enabled' makes the function raise a
+    RuntimeError instead of returning False.
+
     """
 
     if hasattr(pytest, "_test_options") and option in pytest._test_options and pytest._test_options[option]:  # type: ignore[attr-defined]
@@ -118,11 +119,11 @@ def is_option_enabled(option: str, fail_if_not_enabled: bool = False) -> bool:
 
 
 def get_option(option: str) -> Any | None:
-    """
-    Returns the value of an pytest option if it is set, otherwise None.
+    """Returns the value of an pytest option if it is set, otherwise None.
 
     Args:
         option (str): The option to check for.
+
     """
     if option in pytest._test_options:  # type: ignore[attr-defined]
         return pytest._test_options[option]  # type: ignore[attr-defined]

backends/arm/test/misc/test_dim_order.py

@@ -1,4 +1,4 @@
-# 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.
@@ -21,9 +21,8 @@
 
 
 class ChannelsLastInput(torch.nn.Module):
-    """
-    Test a complex case with (channels last, channels first) input,
-    and  (channels first, channels last) output.
+    """Test a complex case with (channels last, channels first) input, and
+    (channels first, channels last) output.
     """
 
     inputs: input_t1 = (
@@ -39,9 +38,7 @@ def forward(self, x, y):
 
 
 class ChannelsFirstOutput(torch.nn.Module):
-    """
-    Test coverting to channels_first inside the delegate.
-    """
+    """Test coverting to channels_first inside the delegate."""
 
     inputs: input_t1 = (
         torch.arange(1, 25, dtype=torch.float32)
@@ -55,9 +52,7 @@ def forward(self, x):
 
 
 class ChannelsLastOutput(torch.nn.Module):
-    """
-    Test changing of dim_order inside the delegate.
-    """
+    """Test changing of dim_order inside the delegate."""
 
     inputs: input_t1 = (torch.arange(1, 9, dtype=torch.float32).reshape((1, 2, 2, 2)),)
 
@@ -68,8 +63,8 @@ def forward(self, x):
 
 
 class ChannelsLastInsidePartition(torch.nn.Module):
-    """
-    Test dim_order changes inside the partiton, but no dim_order changes at input/output.
+    """Test dim_order changes inside the partiton, but no dim_order changes at
+    input/output.
     """
 
     inputs: input_t1 = (torch.randn((1, 2, 3, 3)),)

backends/arm/test/misc/test_extract_io_params_tosa.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.
@@ -45,9 +45,7 @@ def test_roundtrip_extracts_io_params_tosa_INT(
     quantizer_cls,
     partitioner_cls,
 ):
-    """
-    Validates that IO quantization parameters round-trip for both flows.
-    """
+    """Validates that IO quantization parameters round-trip for both flows."""
     example_inputs = (
         torch.ones(1, 5),
         torch.full((1, 5), 2.0),

backends/arm/test/misc/test_non_persistent_buffers.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.
@@ -14,9 +14,7 @@
 
 
 class NonPersistentBuffer(nn.Module):
-    """
-    Min code version registering a non-persistent input buffer.
-    """
+    """Min code version registering a non-persistent input buffer."""
 
     def __init__(self):
         super().__init__()
@@ -33,17 +31,15 @@ def forward(self, x):
 
 @parametrize("test_data", test_input)
 def test_non_persistent_buffer_tosa_FP(test_data: input_t):
-    """
-    Test validates Arm backend handling of non-persistent buffers
-    and ensures that there are no asserts or errors when they are used.
+    """Test validates Arm backend handling of non-persistent buffers and ensures
+    that there are no asserts or errors when they are used.
     """
     TosaPipelineFP[input_t](NonPersistentBuffer(), test_data, "").run()
 
 
 @parametrize("test_data", test_input)
 def test_non_persistent_buffer_tosa_INT(test_data: input_t):
-    """
-    Test validates Arm backend handling of non-persistent buffers
-    and ensures that there are no asserts or errors when they are used.
+    """Test validates Arm backend handling of non-persistent buffers and ensures
+    that there are no asserts or errors when they are used.
     """
     TosaPipelineINT[input_t](NonPersistentBuffer(), test_data, "").run()

backends/arm/test/misc/test_partition_decomposed_quantized_ops.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.
@@ -48,7 +48,11 @@
 
 
 class SoftplusModule(torch.nn.Module):
-    """Module containing an addition followed by a Softplus. Softplus is currently not supported by TosaBackend."""
+    """Module containing an addition followed by a Softplus.
+
+    Softplus is currently not supported by TosaBackend.
+
+    """
 
     def __init__(self):
         super().__init__()
@@ -59,8 +63,11 @@ def forward(self, x: torch.Tensor):
 
 
 class LinearResidualModule(torch.nn.Module):
-    """Module containing a residual and a linear layer followed by GELU and a Dropout.
+    """Module containing a residual and a linear layer followed by GELU and a
+    Dropout.
+
     GELU is currently not supported by TosaBackend nor TosaQuantizer.
+
     """
 
     def __init__(

backends/arm/test/misc/test_qat_training_loop.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.
@@ -46,8 +46,12 @@ def evaluate_model(model, inputs, expected_outputs):
 
 def test_qat_training_loop_tosa_INT():
     """Test the QAT training loop with a simple MLP model.
-    This function creates a simple MLP model, prepares it for QAT, runs a training loop,
-    and evaluates the quantized model to make sure everything works as expected."""
+
+    This function creates a simple MLP model, prepares it for QAT, runs a
+    training loop, and evaluates the quantized model to make sure everything
+    works as expected.
+
+    """
 
     model = MLP()
     logger.info("Starting training loop test")

backends/arm/test/misc/test_quant_custom_meta.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.
@@ -19,11 +19,13 @@ def forward(self, x, y):
 
 @pytest.mark.parametrize("fp_extension", [True, False])
 def test_qdq_squeezed_fp_op_tosa_INT_FP(fp_extension: bool):
-    """Test that a float operation surrounded by quantize-dequantize pairs
-    is correctly handled by the partitioner and the TOSA backend.
+    """Test that a float operation surrounded by quantize-dequantize pairs is
+    correctly handled by the partitioner and the TOSA backend.
+
     Pattern:
     q -> dq -> add -> q -> dq -> sigmoid -> q -> dq -> mul -> dq -> q
                         |_____unquantized_____|
+
     """
     aten_op = "torch.ops.aten.add.Tensor"
     exir_op = "executorch_exir_dialects_edge__ops_aten_add_Tensor"
@@ -67,11 +69,13 @@ def forward(self, x, y):
 
 @pytest.mark.parametrize("fp_extension", [True, False])
 def test_quantized_to_float_transition_tosa_INT_FP(fp_extension: bool):
-    """Test that a model executing quantized ops followed by float ops
-    is correctly handled by the partitioner and the TOSA backend.
+    """Test that a model executing quantized ops followed by float ops is
+    correctly handled by the partitioner and the TOSA backend.
+
     Pattern:
     q -> dq -> mul -> q -> dq -> add -> q -> dq -> sigmoid -> conv
                                            |___unquantized___|
+
     """
     aten_op = "torch.ops.aten.add.Tensor"
     exir_op = "executorch_exir_dialects_edge__ops_aten_add_Tensor"