diff --git a/modules/GSOC/E2_ESRGAN/lib/train.py b/modules/GSOC/E2_ESRGAN/lib/train.py
index 2920fc3884c1b8b67e25e727841bd7320580bb45..4294d634fcbd3cc04fc93ad943243fe31f18f5ca 100644
--- a/modules/GSOC/E2_ESRGAN/lib/train.py
+++ b/modules/GSOC/E2_ESRGAN/lib/train.py
@@ -285,19 +285,21 @@ class Trainer(object):
           for _step in decay_steps.copy():
             if num_step >= _step:
               decay_steps.pop(0)
-              g_current_lr = self.strategy.reduce(
-                  tf.distribute.ReduceOp.MEAN,
-                  G_optimizer.learning_rate, axis=None)
-
-              d_current_lr = self.strategy.reduce(
-                  tf.distribute.ReduceOp.MEAN,
-                  D_optimizer.learning_rate, axis=None)
-
-              logging.debug(
-                  "Current LR: G = %s, D = %s" %
-                  (g_current_lr, d_current_lr))
-              logging.debug(
-                  "[Phase 2] Decayed Learing Rate by %f." % decay_factor)
+              # TDR, Let's don't print this out, causes an error in the next line
+              # g_current_lr = self.strategy.reduce(
+              #     tf.distribute.ReduceOp.MEAN,
+              #     G_optimizer.learning_rate, axis=None)
+              #
+              # d_current_lr = self.strategy.reduce(
+              #     tf.distribute.ReduceOp.MEAN,
+              #     D_optimizer.learning_rate, axis=None)
+              #
+              # logging.debug(
+              #     "Current LR: G = %s, D = %s" %
+              #     (g_current_lr, d_current_lr))
+              # logging.debug(
+              #     "[Phase 2] Decayed Learing Rate by %f." % decay_factor)
+
               G_optimizer.learning_rate.assign(G_optimizer.learning_rate * decay_factor)
               D_optimizer.learning_rate.assign(D_optimizer.learning_rate * decay_factor)