snapshot...

modules/deeplearning/cloud_opd_fcn_abi.py

+import contextlib
+
 import tensorflow as tf
 
 from deeplearning.cloud_fraction_fcn_abi import get_label_data_5cat
@@ -88,6 +90,16 @@ if KERNEL_SIZE == 3:
 # ----------------------------------------
 
 
+@contextlib.contextmanager
+def options(options):
+  old_opts = tf.config.optimizer.get_experimental_options()
+  tf.config.optimizer.set_experimental_options(options)
+  try:
+    yield
+  finally:
+    tf.config.optimizer.set_experimental_options(old_opts)
+
+
 def build_residual_conv2d_block(conv, num_filters, block_name, activation=tf.nn.relu, padding='SAME',
                                 kernel_initializer='he_uniform', scale=None, kernel_size=3,
                                 do_drop_out=True, drop_rate=0.5, do_batch_norm=True):
@@ -654,8 +666,10 @@ class SRCNN:
         self.writer_train_valid_loss.close()
 
     def build_model(self):
-        self.build_srcnn()
-        self.model = tf.keras.Model(self.inputs, self.logits)
+        with options({'layout': False}):
+            print(tf.config.optimizer.get_experimental_options())
+            self.build_srcnn()
+            self.model = tf.keras.Model(self.inputs, self.logits)
 
     def restore(self, ckpt_dir):