Merge pull request #25 from erezalg/master

fix deprecation warning

examples/tensorflow_eager.py

@@ -31,7 +31,7 @@ import tensorflow as tf
 from tensorflow.examples.tutorials.mnist import input_data
 from trains import Task
 
-tf.enable_eager_execution()
+tf.compat.v1.enable_eager_execution()
 
 task = Task.init(project_name='examples', task_name='Tensorflow eager mode')
 
@@ -160,11 +160,11 @@ def discriminator_loss(discriminator_real_outputs, discriminator_gen_outputs):
     A scalar loss Tensor.
   """
 
-  loss_on_real = tf.losses.sigmoid_cross_entropy(
+  loss_on_real = tf.compat.v1.losses.sigmoid_cross_entropy(
       tf.ones_like(discriminator_real_outputs),
       discriminator_real_outputs,
       label_smoothing=0.25)
-  loss_on_generated = tf.losses.sigmoid_cross_entropy(
+  loss_on_generated = tf.compat.v1.losses.sigmoid_cross_entropy(
       tf.zeros_like(discriminator_gen_outputs), discriminator_gen_outputs)
   loss = loss_on_real + loss_on_generated
   tf.contrib.summary.scalar('discriminator_loss', loss)
@@ -182,7 +182,7 @@ def generator_loss(discriminator_gen_outputs):
   Returns:
     A scalar loss Tensor.
   """
-  loss = tf.losses.sigmoid_cross_entropy(
+  loss = tf.compat.v1.losses.sigmoid_cross_entropy(
       tf.ones_like(discriminator_gen_outputs), discriminator_gen_outputs)
   tf.contrib.summary.scalar('generator_loss', loss)
   return loss
@@ -208,12 +208,12 @@ def train_one_epoch(generator, discriminator, generator_optimizer,
   total_discriminator_loss = 0.0
   for (batch_index, images) in enumerate(dataset):
     with tf.device('/cpu:0'):
-      tf.assign_add(step_counter, 1)
+      tf.compat.v1.assign_add(step_counter, 1)
 
     with tf.contrib.summary.record_summaries_every_n_global_steps(
         log_interval, global_step=step_counter):
       current_batch_size = images.shape[0]
-      noise = tf.random_uniform(
+      noise = tf.random.uniform(
           shape=[current_batch_size, noise_dim],
           minval=-1.,
           maxval=1.,
@@ -271,9 +271,9 @@ def main(_):
   model_objects = {
       'generator': Generator(data_format),
       'discriminator': Discriminator(data_format),
-      'generator_optimizer': tf.train.AdamOptimizer(FLAGS.lr),
+      'generator_optimizer': tf.compat.v1.train.AdamOptimizer(FLAGS.lr),
-      'discriminator_optimizer': tf.train.AdamOptimizer(FLAGS.lr),
+      'discriminator_optimizer': tf.compat.v1.train.AdamOptimizer(FLAGS.lr),
-      'step_counter': tf.train.get_or_create_global_step(),
+      'step_counter': tf.compat.v1.train.get_or_create_global_step(),
   }
 
   # Prepare summary writer and checkpoint info
@@ -355,4 +355,4 @@ if __name__ == '__main__':
 
   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)

trains/binding/frameworks/tensorflow_bind.py

@@ -154,7 +154,7 @@ class EventTrainsWriter(object):
         self.histogram_granularity = histogram_granularity
         self.histogram_update_freq_multiplier = histogram_update_freq_multiplier
         self._logger = logger
-        self._visualization_mode = 'RGB'  # 'BGR'
+        self._visualization_mode = 'BGR'
         self._variants = defaultdict(lambda: ())
         self._scalar_report_cache = {}
         self._hist_report_cache = {}
@@ -582,7 +582,7 @@ class PatchSummaryToEventTransformer(object):
                     setattr(SummaryToEventTransformer, 'trains',
                             property(PatchSummaryToEventTransformer.trains_object))
             except Exception as ex:
-                getLogger(TrainsFrameworkAdapter).debug(str(ex))
+                getLogger(TrainsFrameworkAdapter).warning(str(ex))
 
         if 'torch' in sys.modules:
             try:
@@ -596,7 +596,7 @@ class PatchSummaryToEventTransformer(object):
                 # this is a new version of TensorflowX
                 pass
             except Exception as ex:
-                getLogger(TrainsFrameworkAdapter).debug(str(ex))
+                getLogger(TrainsFrameworkAdapter).warning(str(ex))
 
         if 'tensorboardX' in sys.modules:
             try:
@@ -612,7 +612,7 @@ class PatchSummaryToEventTransformer(object):
                 # this is a new version of TensorflowX
                 pass
             except Exception as ex:
-                getLogger(TrainsFrameworkAdapter).debug(str(ex))
+                getLogger(TrainsFrameworkAdapter).warning(str(ex))
 
             if PatchSummaryToEventTransformer.__original_getattributeX is None:
                 try:
@@ -626,7 +626,7 @@ class PatchSummaryToEventTransformer(object):
                     # this is a new version of TensorflowX
                     pass
                 except Exception as ex:
-                    getLogger(TrainsFrameworkAdapter).debug(str(ex))
+                    getLogger(TrainsFrameworkAdapter).warning(str(ex))
 
     @staticmethod
     def _patched_add_eventT(self, *args, **kwargs):
@@ -871,7 +871,7 @@ class PatchTensorFlowEager(object):
             except ImportError:
                 pass
             except Exception as ex:
-                getLogger(TrainsFrameworkAdapter).debug(str(ex))
+                getLogger(TrainsFrameworkAdapter).warning(str(ex))
 
     @staticmethod
     def _get_event_writer(writer):
@@ -1244,13 +1244,12 @@ class PatchTensorflowModelIO(object):
         try:
             # make sure we import the correct version of save
             import tensorflow
-            from tensorflow.saved_model.experimental import save
+            from tf.saved_model import save
             # actual import
             import tensorflow.saved_model.experimental as saved_model
         except ImportError:
             # noinspection PyBroadException
             try:
-                # TODO: we might want to reverse the order, so we do not get the deprecated warning
                 # make sure we import the correct version of save
                 import tensorflow
                 from tensorflow.saved_model import save

trains/utilities/seed.py

@@ -64,11 +64,11 @@ def make_deterministic(seed=1337, cudnn_deterministic=False):
 
         if not eager_mode_bypass:
             try:
-                tf.set_random_seed(seed)
+                tf.compat.v1.set_random_seed(seed)
             except Exception:
                 pass
             try:
-                tf.random.set_random_seed(seed)
+                tf.compat.v1.set_random_seed(seed)
             except Exception:
                 pass