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# Copyright 2016 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.
# ==============================================================================
"""API tests for the projector plugin in TensorBoard."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
import shutil
import tensorflow as tf
from google.protobuf import text_format
class ProjectorApiTest(tf.test.TestCase):
def testVisualizeEmbeddings(self):
# Create a dummy configuration.
config = tf.contrib.tensorboard.plugins.projector.ProjectorConfig()
config.model_checkpoint_path = 'test'
emb1 = config.embeddings.add()
emb1.tensor_name = 'tensor1'
emb1.metadata_path = 'metadata1'
# Call the API method to save the configuration to a temporary dir.
temp_dir = self.get_temp_dir()
self.addCleanup(shutil.rmtree, temp_dir)
writer = tf.summary.FileWriter(temp_dir)
tf.contrib.tensorboard.plugins.projector.visualize_embeddings(writer,
config)
# Read the configuratin from disk and make sure it matches the original.
with tf.gfile.GFile(os.path.join(temp_dir, 'projector_config.pbtxt')) as f:
config2 = tf.contrib.tensorboard.plugins.projector.ProjectorConfig()
text_format.Parse(f.read(), config2)
self.assertEqual(config, config2)
if __name__ == "__main__":
tf.test.main()
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