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authorDmitrii Agibov <dmitrii.agibov@arm.com>2022-09-08 14:24:39 +0100
committerDmitrii Agibov <dmitrii.agibov@arm.com>2022-09-09 17:21:48 +0100
commitf5b293d0927506c2a979a091bf0d07ecc78fa181 (patch)
tree4de585b7cb6ed34da8237063752270189a730a41 /src/mlia/nn/tensorflow/utils.py
parentcde0c6ee140bd108849bff40467d8f18ffc332ef (diff)
downloadmlia-f5b293d0927506c2a979a091bf0d07ecc78fa181.tar.gz
MLIA-386 Simplify typing in the source code
- Enable deferred annotations evaluation - Use builtin types for type hints whenever possible - Use | syntax for union types - Rename mlia.core._typing into mlia.core.typing Change-Id: I3f6ffc02fa069c589bdd9e8bddbccd504285427a
Diffstat (limited to 'src/mlia/nn/tensorflow/utils.py')
-rw-r--r--src/mlia/nn/tensorflow/utils.py15
1 files changed, 7 insertions, 8 deletions
diff --git a/src/mlia/nn/tensorflow/utils.py b/src/mlia/nn/tensorflow/utils.py
index b1034d9..6250f56 100644
--- a/src/mlia/nn/tensorflow/utils.py
+++ b/src/mlia/nn/tensorflow/utils.py
@@ -2,11 +2,12 @@
# SPDX-FileCopyrightText: Copyright The TensorFlow Authors. All Rights Reserved.
# SPDX-License-Identifier: Apache-2.0
"""Collection of useful functions for optimizations."""
+from __future__ import annotations
+
import logging
from pathlib import Path
from typing import Callable
from typing import Iterable
-from typing import Union
import numpy as np
import tensorflow as tf
@@ -101,21 +102,19 @@ def convert_tf_to_tflite(model: str, quantized: bool = False) -> Interpreter:
return tflite_model
-def save_keras_model(model: tf.keras.Model, save_path: Union[str, Path]) -> None:
+def save_keras_model(model: tf.keras.Model, save_path: str | Path) -> None:
"""Save Keras model at provided path."""
# Checkpoint: saving the optimizer is necessary.
model.save(save_path, include_optimizer=True)
-def save_tflite_model(
- model: tf.lite.TFLiteConverter, save_path: Union[str, Path]
-) -> None:
+def save_tflite_model(model: tf.lite.TFLiteConverter, save_path: str | Path) -> None:
"""Save TFLite model at provided path."""
with open(save_path, "wb") as file:
file.write(model)
-def is_tflite_model(model: Union[Path, str]) -> bool:
+def is_tflite_model(model: str | Path) -> bool:
"""Check if model type is supported by TFLite API.
TFLite model is indicated by the model file extension .tflite
@@ -124,7 +123,7 @@ def is_tflite_model(model: Union[Path, str]) -> bool:
return model_path.suffix == ".tflite"
-def is_keras_model(model: Union[Path, str]) -> bool:
+def is_keras_model(model: str | Path) -> bool:
"""Check if model type is supported by Keras API.
Keras model is indicated by:
@@ -139,7 +138,7 @@ def is_keras_model(model: Union[Path, str]) -> bool:
return model_path.suffix in (".h5", ".hdf5")
-def is_tf_model(model: Union[Path, str]) -> bool:
+def is_tf_model(model: str | Path) -> bool:
"""Check if model type is supported by TensorFlow API.
TensorFlow model is indicated if its directory (meaning saved model)