experiments/STT-tensorflow
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Merge pull request #30704 from siju-samuel:depr_removed_contrib_gan_examples

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PiperOrigin-RevId: 258371737
This commit is contained in:
TensorFlower Gardener 2019-07-16 08:36:11 -07:00
commit f2df2c2865
3 changed files with 9 additions and 9 deletions
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6
tensorflow/contrib/eager/python/examples/gan/mnist.py
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@ -278,8 +278,8 @@ def main(_):
model_objects = {
'generator': Generator(data_format),
'discriminator': Discriminator(data_format),
'generator_optimizer': tf.train.AdamOptimizer(FLAGS.lr),
'discriminator_optimizer': tf.train.AdamOptimizer(FLAGS.lr),
'generator_optimizer': tf.compat.v1.train.AdamOptimizer(FLAGS.lr),
'discriminator_optimizer': tf.compat.v1.train.AdamOptimizer(FLAGS.lr),
'step_counter': tf.train.get_or_create_global_step(),
}
@ -363,4 +363,4 @@ if __name__ == '__main__':
help='disables GPU usage even if a GPU is available')
FLAGS, unparsed = parser.parse_known_args()
tf.app.run(main=main, argv=[sys.argv[0]] + unparsed)
tf.compat.v1.app.run(main=main, argv=[sys.argv[0]] + unparsed)

8
tensorflow/contrib/eager/python/examples/gan/mnist_graph_test.py
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@ -49,9 +49,9 @@ class MnistGraphGanBenchmark(tf.test.Benchmark):
generator = mnist.Generator(data_format())
discriminator = mnist.Discriminator(data_format())
with tf.variable_scope('generator'):
generator_optimizer = tf.train.AdamOptimizer(0.001)
generator_optimizer = tf.compat.v1.train.AdamOptimizer(0.001)
with tf.variable_scope('discriminator'):
discriminator_optimizer = tf.train.AdamOptimizer(0.001)
discriminator_optimizer = tf.compat.v1.train.AdamOptimizer(0.001)
# Run models and compute loss
noise_placeholder = tf.placeholder(tf.float32,
@ -96,7 +96,7 @@ class MnistGraphGanBenchmark(tf.test.Benchmark):
(generator_train, discriminator_train, noise_placeholder
) = self._create_graph(batch_size)
with tf.Session() as sess:
with tf.compat.v1.Session() as sess:
tf.contrib.summary.initialize(graph=tf.get_default_graph(),
session=sess)
@ -132,7 +132,7 @@ class MnistGraphGanBenchmark(tf.test.Benchmark):
generated_images = generator(noise_placeholder)
init = tf.global_variables_initializer()
with tf.Session() as sess:
with tf.compat.v1.Session() as sess:
sess.run(init)
noise = np.random.uniform(-1.0, 1.0, size=[batch_size, NOISE_DIM])
num_burn, num_iters = (30, 1000)

4
tensorflow/contrib/eager/python/examples/gan/mnist_test.py
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@ -67,9 +67,9 @@ class MnistEagerGanBenchmark(tf.test.Benchmark):
generator = mnist.Generator(data_format())
discriminator = mnist.Discriminator(data_format())
with tf.variable_scope('generator'):
generator_optimizer = tf.train.AdamOptimizer(0.001)
generator_optimizer = tf.compat.v1.train.AdamOptimizer(0.001)
with tf.variable_scope('discriminator'):
discriminator_optimizer = tf.train.AdamOptimizer(0.001)
discriminator_optimizer = tf.compat.v1.train.AdamOptimizer(0.001)
with tf.contrib.summary.create_file_writer(
tempfile.mkdtemp(), flush_millis=SUMMARY_FLUSH_MS).as_default():