Added test unit for style transfer

bob/learn/tensorflow/test/test_style_transfer.py

+from __future__ import print_function
+import os
+import shutil
+from glob import glob
+from tempfile import mkdtemp
+from click.testing import CliRunner
+from bob.io.base.test_utils import datafile
+import pkg_resources
+
+import tensorflow as tf
+
+from bob.learn.tensorflow.utils import load_mnist, create_mnist_tfrecord
+from bob.learn.tensorflow.utils.hooks import LoggerHookEstimator
+from bob.learn.tensorflow.loss import mean_cross_entropy_loss
+from bob.learn.tensorflow.utils import reproducible
+from .test_estimator_onegraph import run_logitstrainer_mnist
+
+from bob.learn.tensorflow.estimators import Logits
+from bob.learn.tensorflow.network import dummy
+from bob.learn.tensorflow.script.style_transfer import style_transfer
+
+#from bob.learn.tensorflow.script.db_to_tfrecords import db_to_tfrecords
+#from bob.learn.tensorflow.script.train import train
+#from bob.learn.tensorflow.script.eval import eval as eval_script
+#from bob.learn.tensorflow.script.train_and_evaluate import train_and_evaluate
+
+dummy_config = datafile('style_transfer.py', __name__)
+CONFIG = '''
+from bob.learn.tensorflow.network import dummy
+architecture = dummy
+import pkg_resources
+     
+checkpoint_dir = "./temp/"
+
+style_end_points = ["conv1"]
+content_end_points = ["fc1"]
+
+scopes = {"Dummy/":"Dummy/"}
+
+'''
+
+
+#tfrecord_train = "./train_mnist.tfrecord"
+model_dir = "./temp"
+output_style_image = 'output_style.png'
+
+learning_rate = 0.1
+data_shape = (28, 28, 1)  # size of atnt images
+data_type = tf.float32
+batch_size = 32
+epochs = 1
+steps = 100
+
+
+def test_style_transfer():
+    with open(dummy_config, 'w') as f:
+        f.write(CONFIG)
+
+    # Trainer logits
+
+    # CREATING FAKE MODEL USING MNIST
+    _, run_config,_,_,_ = reproducible.set_seed() 
+    trainer = Logits(
+        model_dir=model_dir,
+        architecture=dummy,
+        optimizer=tf.train.GradientDescentOptimizer(learning_rate),
+        n_classes=10,
+        loss_op=mean_cross_entropy_loss,
+        config=run_config)
+    run_logitstrainer_mnist(trainer)
+
+    # Style transfer using this fake model
+    runner = CliRunner()
+    result = runner.invoke(style_transfer,
+                           args=[pkg_resources.resource_filename( __name__, 'data/dummy_image_database/m301_01_p01_i0_0_GRAY.png'),
+                               output_style_image, dummy_config])
+
+    #assert result.exit_code == 0, '%s\n%s\n%s' % (result.exc_info, result.output, result.exception)
+
+    try:
+        os.unlink(tfrecord_train)
+        os.unlink(tfrecord_validation)
+        os.unlink(dummy_config)
+        os.unlink(dummy_config)
+        shutil.rmtree(model_dir, ignore_errors=True)
+    except Exception:
+        pass
+    
+