chore: import upstream snapshot with attribution

2026-07-13 13:36:55 +08:00
commit c8a779b1bb
1887 changed files with 3245738 additions and 0 deletions
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+#
+# SPDX-FileCopyrightText: Copyright (c) 1993-2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+
+import os
+import tensorflow as tf
+from examples.data.data_loader import _NUM_CLASSES, _DEFAULT_IMAGE_SIZE, _NUM_CHANNELS
+from typing import Tuple
+
+MODELS_CLASSES_DICT = {
+    "resnet_50v1": tf.keras.applications.ResNet50,
+    "resnet_101v1": tf.keras.applications.ResNet101,
+    "resnet_152v1": tf.keras.applications.ResNet152,
+    "resnet_50v2": tf.keras.applications.ResNet50V2,
+    "resnet_101v2": tf.keras.applications.ResNet101V2,
+    "resnet_152v2": tf.keras.applications.ResNet152V2,
+    "mobilenet_v1": tf.keras.applications.MobileNet,
+    "mobilenet_v2": tf.keras.applications.MobileNetV2,
+    "inception_v3": tf.keras.applications.InceptionV3,
+}
+
+
+def get_tfkeras_model(model_name: str = "mobilenet_v1", shape: Tuple = None) -> tf.keras.Model:
+    """
+    Creates a native tf.keras.applications model.
+
+    Args:
+        model_name (str): Options={model_name_options}.
+
+    Returns:
+        model (tf.keras.Model): model corresponding to 'model_name'.
+
+    Raises:
+        ValueError: raised when 'model_name' is not supported.
+    """.format(
+        model_name_options=list(MODELS_CLASSES_DICT.keys())
+    )
+    try:
+        model_class = MODELS_CLASSES_DICT[model_name]
+    except ValueError:
+        raise ValueError("Model {} was not found!".format(model_name))
+    print("Loading model as {}".format(model_class))
+
+    if shape is None:
+        shape = (
+            _DEFAULT_IMAGE_SIZE[model_name],
+            _DEFAULT_IMAGE_SIZE[model_name],
+            _NUM_CHANNELS,
+        )
+
+    input_img = tf.keras.layers.Input(shape=shape, name="input_1")
+    model = model_class(
+        include_top=True,
+        weights="imagenet",
+        input_tensor=input_img,
+        input_shape=None,
+        pooling=None,
+        classes=_NUM_CLASSES,
+        classifier_activation="softmax",
+    )
+
+    return model
+
+
+def print_model_weights_shapes(model):
+    """
+    Print shape of each layer weight.
+    Args:
+        model: Keras model
+    """
+    print([model.get_weights()[i].shape for i in range(len(model.get_weights()))])
+
+
+def ensure_dir(dirname):
+    """
+    Create directory is doesn't exist already.
+    Args:
+        dirname: Name of the directory to create.
+    """
+    if not os.path.exists(dirname):
+        os.makedirs(dirname)