tf2

core/leras/layers/MsSsim.py

@@ -1,5 +1,6 @@
 from core.leras import nn
 tf = nn.tf
+tf2 = nn.tf2
 
 class MsSsim(nn.LayerBase):
     default_power_factors = (0.0448, 0.2856, 0.3001, 0.2363, 0.1333)
@@ -20,15 +21,7 @@ class MsSsim(nn.LayerBase):
         y_true_t = tf.transpose(tf.cast(y_true, tf.float32), [0, 2, 3, 1])
         y_pred_t = tf.transpose(tf.cast(y_pred, tf.float32), [0, 2, 3, 1])
 
-
+        loss = tf2.image.ssim_multiscale(y_true_t, y_pred_t, max_val, power_factors=self.power_factors)
-        def assign_device(op):
+        return (1.0 - loss) / 2.0
-            if op.type != 'Assert' or op.type != 'ListDiff':
-                return '/gpu:0'
-            else:
-                return '/cpu:0'
-
-        with tf.device(assign_device):
-            loss = tf.image.ssim_multiscale(y_true_t, y_pred_t, max_val, power_factors=self.power_factors)
-            return (1.0 - loss) / 2.0
 
 nn.MsSsim = MsSsim

core/leras/nn.py

@@ -31,6 +31,7 @@ class nn():
     current_DeviceConfig = None
 
     tf = None
+    tf2 = None
     tf_sess = None
     tf_sess_config = None
     tf_default_device = None
@@ -40,7 +41,7 @@ class nn():
     conv2d_spatial_axes = None
 
     floatx = None
-    
+
     @staticmethod
     def initialize(device_config=None, floatx="float32", data_format="NHWC"):
 
@@ -50,7 +51,7 @@ class nn():
             nn.setCurrentDeviceConfig(device_config)
 
             # Manipulate environment variables before import tensorflow
-            
+
             if 'CUDA_VISIBLE_DEVICES' in os.environ.keys():
                 os.environ.pop('CUDA_VISIBLE_DEVICES')
 
@@ -77,15 +78,17 @@ class nn():
                 io.log_info("Caching GPU kernels...")
 
             import tensorflow
-            
+
             tf_version = getattr(tensorflow,'VERSION', None)
             if tf_version is None:
                 tf_version = tensorflow.version.GIT_VERSION
                 if tf_version[0] == 'v':
                     tf_version = tf_version[1:]
-                
+
             if tf_version[0] == '2':
                 tf = tensorflow.compat.v1
+                tf2 = tensorflow
+                nn.tf2 = tf2
             else:
                 tf = tensorflow
 
@@ -93,7 +96,7 @@ class nn():
             # Disable tensorflow warnings
             tf_logger = logging.getLogger('tensorflow')
             tf_logger.setLevel(logging.ERROR)
-            
+
             if tf_version[0] == '2':
                 tf.disable_v2_behavior()
             nn.tf = tf
@@ -105,7 +108,7 @@ class nn():
             import core.leras.optimizers
             import core.leras.models
             import core.leras.archis
-            
+
             # Configure tensorflow session-config
             if len(device_config.devices) == 0:
                 nn.tf_default_device = "/CPU:0"
@@ -118,7 +121,7 @@ class nn():
             config.gpu_options.force_gpu_compatible = True
             config.gpu_options.allow_growth = True
             nn.tf_sess_config = config
-            
+
         if nn.tf_sess is None:
             nn.tf_sess = tf.Session(config=nn.tf_sess_config)
 
@@ -273,7 +276,7 @@ class nn():
         @staticmethod
         def ask_choose_device(*args, **kwargs):
             return nn.DeviceConfig.GPUIndexes( nn.ask_choose_device_idxs(*args,**kwargs) )
-        
+
         def __init__ (self, devices=None):
             devices = devices or []