Spaces:
Sleeping
Sleeping
File size: 2,007 Bytes
5672777 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 |
# 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.
"""Tests for convert_3d_2plus1d."""
import os
from absl import flags
import tensorflow as tf, tf_keras
from official.projects.movinet.modeling import movinet
from official.projects.movinet.modeling import movinet_model
from official.projects.movinet.tools import convert_3d_2plus1d
FLAGS = flags.FLAGS
class Convert3d2plus1dTest(tf.test.TestCase):
def test_convert_model(self):
saved_model_path = self.get_temp_dir()
input_checkpoint_path = os.path.join(saved_model_path, 'ckpt-input')
output_checkpoint_path = os.path.join(saved_model_path, 'ckpt')
model_3d_2plus1d = movinet_model.MovinetClassifier(
backbone=movinet.Movinet(
model_id='a0',
conv_type='3d_2plus1d',
se_type='2plus3d'),
num_classes=600)
model_3d_2plus1d.build([1, 1, 1, 1, 3])
save_checkpoint = tf.train.Checkpoint(model=model_3d_2plus1d)
save_checkpoint.save(input_checkpoint_path)
FLAGS.input_checkpoint_path = f'{input_checkpoint_path}-1'
FLAGS.output_checkpoint_path = output_checkpoint_path
FLAGS.model_id = 'a0'
FLAGS.use_positional_encoding = False
FLAGS.num_classes = 600
FLAGS.verify_output = True
convert_3d_2plus1d.main('unused_args')
print(os.listdir(saved_model_path))
self.assertTrue(tf.io.gfile.exists(f'{output_checkpoint_path}-1.index'))
if __name__ == '__main__':
tf.test.main()
|