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# Copyright 2023 The TensorFlow Authors. All Rights Reserved.
#
# 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.
"""A script to export TF-Hub SavedModel."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
from absl import app
from absl import flags
import tensorflow as tf, tf_keras
from official.legacy.image_classification.efficientnet import efficientnet_model
FLAGS = flags.FLAGS
flags.DEFINE_string("model_name", None, "EfficientNet model name.")
flags.DEFINE_string("model_path", None, "File path to TF model checkpoint.")
flags.DEFINE_string("export_path", None,
"TF-Hub SavedModel destination path to export.")
def export_tfhub(model_path, hub_destination, model_name):
"""Restores a tf_keras.Model and saves for TF-Hub."""
model_configs = dict(efficientnet_model.MODEL_CONFIGS)
config = model_configs[model_name]
image_input = tf_keras.layers.Input(
shape=(None, None, 3), name="image_input", dtype=tf.float32)
x = image_input * 255.0
outputs = efficientnet_model.efficientnet(x, config)
hub_model = tf_keras.Model(image_input, outputs)
ckpt = tf.train.Checkpoint(model=hub_model)
ckpt.restore(model_path).assert_existing_objects_matched()
hub_model.save(
os.path.join(hub_destination, "classification"), include_optimizer=False)
feature_vector_output = hub_model.get_layer(name="top_pool").get_output_at(0)
hub_model2 = tf_keras.Model(image_input, feature_vector_output)
hub_model2.save(
os.path.join(hub_destination, "feature-vector"), include_optimizer=False)
def main(argv):
if len(argv) > 1:
raise app.UsageError("Too many command-line arguments.")
export_tfhub(FLAGS.model_path, FLAGS.export_path, FLAGS.model_name)
if __name__ == "__main__":
app.run(main)
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