Arm backend: Enable MYPY in examples/arm

.lintrunner.toml

@@ -361,6 +361,7 @@ include_patterns = [
     'devtools/visualization/**/*.py',
     'docs/**/*.py',
     # 'examples/**/*.py',
+    'examples/arm/**/*.py',
     'examples/openvino/**/*.py',
     # 'exir/**/*.py',
     # 'extension/**/*.py',

examples/arm/image_classification_example_ethos_u/model_export/export_deit.py

@@ -6,8 +6,8 @@
 import argparse
 
 import torch
-import tqdm
-from datasets import DatasetDict, load_dataset
+import tqdm  # type: ignore[import]
+from datasets import DatasetDict, load_dataset  # type: ignore[import]
 
 from executorch.backends.arm.ethosu import EthosUCompileSpec, EthosUPartitioner
 from executorch.backends.arm.quantizer import (
@@ -21,7 +21,10 @@
 )
 from executorch.extension.export_util.utils import save_pte_program
 
-from torchao.quantization.pt2e.quantize_pt2e import convert_pt2e, prepare_pt2e
+from torchao.quantization.pt2e.quantize_pt2e import (  # type: ignore[import]
+    convert_pt2e,
+    prepare_pt2e,
+)
 from transformers import AutoImageProcessor
 from transformers.models.vit.modeling_vit import ViTForImageClassification
 

examples/arm/image_classification_example_ethos_u/model_export/train_deit.py

@@ -9,8 +9,8 @@
 
 import numpy as np
 import torch
-from datasets import DatasetDict, load_dataset
-from evaluate import load as load_metric
+from datasets import DatasetDict, load_dataset  # type: ignore[import]
+from evaluate import load as load_metric  # type: ignore[import]
 from transformers import AutoImageProcessor, set_seed, Trainer, TrainingArguments
 
 from transformers.models.vit.modeling_vit import ViTForImageClassification

examples/arm/image_classification_example_vgf/model_export/export_deit.py

@@ -6,8 +6,8 @@
 import argparse
 
 import torch
-import tqdm
-from datasets import DatasetDict, load_dataset
+import tqdm  # type: ignore[import]
+from datasets import DatasetDict, load_dataset  # type: ignore[import]
 
 from executorch.backends.arm.quantizer import (
     get_symmetric_quantization_config,
@@ -21,7 +21,10 @@
 )
 from executorch.extension.export_util.utils import save_pte_program
 
-from torchao.quantization.pt2e.quantize_pt2e import convert_pt2e, prepare_pt2e
+from torchao.quantization.pt2e.quantize_pt2e import (  # type: ignore[import]
+    convert_pt2e,
+    prepare_pt2e,
+)
 from transformers import AutoImageProcessor
 from transformers.models.vit.modeling_vit import ViTForImageClassification
 

examples/arm/image_classification_example_vgf/model_export/train_deit.py

@@ -9,8 +9,8 @@
 
 import numpy as np
 import torch
-from datasets import DatasetDict, load_dataset
-from evaluate import load as load_metric
+from datasets import DatasetDict, load_dataset  # type: ignore[import]
+from evaluate import load as load_metric  # type: ignore[import]
 from transformers import AutoImageProcessor, set_seed, Trainer, TrainingArguments
 
 from transformers.models.vit.modeling_vit import ViTForImageClassification

examples/arm/visualize.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.
@@ -17,8 +17,11 @@
 from executorch.devtools.visualization.visualization_utils import (
     visualize_model_explorer,
 )
-from model_explorer import config as model_explorer_config, node_data_builder as ndb
-from model_explorer.config import ModelSource
+from model_explorer import (  # type: ignore[import]
+    config as model_explorer_config,
+    node_data_builder as ndb,
+)
+from model_explorer.config import ModelSource  # type: ignore[import]
 
 COMPILER_OP_ID = "scheduled_id"
 
@@ -254,7 +257,7 @@ def validate_perf_mode_args(trace: str, tables: str) -> None:
 
 
 def set_pte_model_explorer_config(model_file, tosa_files, config):
-    from pte_adapter_model_explorer.main import PTEAdapter
+    from pte_adapter_model_explorer.main import PTEAdapter  # type: ignore[import]
 
     pte_adapter = PTEAdapter()