Move files from /tests_models to /tests.

Author: MartinPavella

backends/nxp/quantizer/utils.py

@@ -1,5 +1,5 @@
 # Copyright (c) Meta Platforms, Inc. and affiliates.
-# Copyright 2024-2025 NXP
+# Copyright 2024-2026 NXP
 # All rights reserved.
 #
 # This source code is licensed under the BSD-style license found in the

…/nxp/tests_models/calibration_dataset.py backends/nxp/tests/calibration_dataset.pybackends/nxp/tests_models/calibration_dataset.py renamed to backends/nxp/tests/calibration_dataset.py backends/nxp/tests_models/calibration_dataset.py renamed to backends/nxp/tests/calibration_dataset.py

@@ -21,7 +21,7 @@
 
 NSYS_PATH = pathlib.Path(shutil.which("nsys"))
 NSYS_CONFIG_PATH = os.path.join(
-    PROJECT_DIR, "backends", "nxp", "tests_models", "neutron-imxrt700.ini"
+    PROJECT_DIR, "backends", "nxp", "tests", "neutron-imxrt700.ini"
 )
 NSYS_FIRMWARE_PATH = os.path.join(
     os.path.dirname(eiq_neutron_sdk.__file__),

backends/nxp/tests_models/config.py backends/nxp/tests/config.pybackends/nxp/tests_models/config.py renamed to backends/nxp/tests/config.py

@@ -12,6 +12,6 @@
 
     logger.debug("Importing from executorch-integration")
 except ImportError:
-    import executorch.backends.nxp.tests_models.config as test_config  # noqa F401
+    import executorch.backends.nxp.tests.config as test_config  # noqa F401
 
     logger.debug("Importing from executorch")

…ends/nxp/tests_models/config_importer.py backends/nxp/tests/config_importer.pybackends/nxp/tests_models/config_importer.py renamed to backends/nxp/tests/config_importer.py backends/nxp/tests_models/config_importer.py renamed to backends/nxp/tests/config_importer.py

@@ -8,7 +8,7 @@
 import pathlib
 import shutil
 
-from executorch.backends.nxp.tests_models.outputs_dir_importer import outputs_dir
+from executorch.backends.nxp.tests.outputs_dir_importer import outputs_dir
 
 
 def pytest_addoption(parser):

backends/nxp/tests_models/conftest.py backends/nxp/tests/conftest.pybackends/nxp/tests_models/conftest.py renamed to backends/nxp/tests/conftest.py

@@ -14,8 +14,8 @@
 import numpy as np
 import torch
 from executorch.backends.nxp.backend.ir.converter.conversion import translator
+from executorch.backends.nxp.tests.calibration_dataset import CalibrationDataset
 from executorch.backends.nxp.tests.executorch_pipeline import ModelInputSpec
-from executorch.backends.nxp.tests_models.calibration_dataset import CalibrationDataset
 from torch import Tensor
 
 

…ends/nxp/tests_models/dataset_creator.py backends/nxp/tests/dataset_creator.pybackends/nxp/tests_models/dataset_creator.py renamed to backends/nxp/tests/dataset_creator.py backends/nxp/tests_models/dataset_creator.py renamed to backends/nxp/tests/dataset_creator.py

@@ -96,19 +96,19 @@ def _get_default_quantizer(target_spec: NeutronTargetSpec, use_qat: bool) -> Qua
 
 
 def to_model_input_spec(
-    input_spec: tuple[ModelInputSpec, ...] | tuple[int, ...] | list[tuple[int, ...]]
+    input_spec: Iterable[ModelInputSpec, ...] | tuple[int, ...] | list[tuple[int, ...]]
 ) -> tuple[ModelInputSpec, ...]:
     match input_spec:
         case tuple() | list() if all(
             isinstance(spec, ModelInputSpec) for spec in input_spec
         ):
-            return input_spec
+            return tuple(input_spec)
         case tuple() if all(isinstance(spec, int) for spec in input_spec):
             return (ModelInputSpec(input_spec),)
         case list() if all(
             isinstance(input_shape, tuple) for input_shape in input_spec
         ):
-            return tuple([ModelInputSpec(spec) for spec in input_spec])
+            return tuple(ModelInputSpec(spec) for spec in input_spec)
         case _:
             raise TypeError(f"Unsupported type {type(input_spec)}")
 
@@ -175,7 +175,7 @@ def _get_example_input(
 
 def to_quantized_edge_program(
     model: torch.nn.Module,
-    input_spec: list[ModelInputSpec] | tuple[int, ...] | list[tuple[int, ...]],
+    input_spec: Iterable[ModelInputSpec] | tuple[int, ...] | list[tuple[int, ...]],
     operators_not_to_delegate: list[str] = None,
     get_calibration_inputs_fn: GetCalibrationInputsFn = get_random_calibration_inputs,
     target: str = "imxrt700",
@@ -266,7 +266,7 @@ def to_quantized_edge_program(
 
 def to_quantized_executorch_program(
     model: torch.nn.Module,
-    input_spec: tuple[ModelInputSpec, ...] | tuple[int, ...] | list[tuple[int, ...]],
+    input_spec: Iterable[ModelInputSpec] | tuple[int, ...] | list[tuple[int, ...]],
     use_qat: bool = False,
     train_fn: Callable[[torch.fx.GraphModule], None] | None = None,
     use_neutron_for_format_conversion: bool = True,
@@ -302,7 +302,7 @@ def to_quantized_executorch_program(
 
 def to_edge_program(
     model: nn.Module,
-    input_spec: tuple[ModelInputSpec, ...] | tuple[int, ...] | list[tuple[int, ...]],
+    input_spec: Iterable[ModelInputSpec] | tuple[int, ...] | list[tuple[int, ...]],
 ) -> EdgeProgramManager:
     calibration_inputs = get_random_calibration_inputs(to_model_input_spec(input_spec))
 

backends/nxp/tests/executorch_pipeline.py

@@ -7,22 +7,19 @@
 
 import pytest
 import torch
-from executorch.backends.nxp.tests.executorch_pipeline import ModelInputSpec
-
-from executorch.backends.nxp.tests_models.config_importer import test_config
-from executorch.backends.nxp.tests_models.dataset_creator import CopyDatasetCreator
 
-from executorch.backends.nxp.tests_models.executors import (
-    convert_run_compare,
-    ReferenceModel,
-)
-from executorch.backends.nxp.tests_models.graph_verifier import (
+from executorch.backends.nxp.tests.config_importer import test_config
+from executorch.backends.nxp.tests.dataset_creator import CopyDatasetCreator
+from executorch.backends.nxp.tests.executorch_pipeline import ModelInputSpec
+from executorch.backends.nxp.tests.graph_verifier import (
     BaseGraphVerifier,
     NonDelegatedNode,
 )
-from executorch.backends.nxp.tests_models.model_output_comparator import (
+from executorch.backends.nxp.tests.model_output_comparator import (
     NumericalStatsOutputComparator,
 )
+
+from executorch.backends.nxp.tests.nsys_testing import lower_run_compare, ReferenceModel
 from executorch.examples.nxp.experimental.cifar_net.cifar_net import (
     CifarNet,
     store_test_data,
@@ -64,7 +61,7 @@ def test_cifarnet(mocker, cifar_test_files, channels_last):
     comparator = NumericalStatsOutputComparator(
         max_mse_error=1.0e-3, is_classification_task=True
     )
-    convert_run_compare(
+    lower_run_compare(
         model,
         [input_spec],
         dataset_creator=CopyDatasetCreator(cifar_test_files),
@@ -94,7 +91,7 @@ def test_cifarnet_qat(mocker, cifar_test_files):
     comparator = NumericalStatsOutputComparator(
         max_mse_error=8e-2, is_classification_task=True
     )
-    convert_run_compare(
+    lower_run_compare(
         model,
         input_shape,
         dataset_creator=CopyDatasetCreator(cifar_test_files),