Remove unnecessary logging, add recommended model to VGSL library

src/data/data_handling.py

@@ -118,9 +118,6 @@ def load_initial_charlist(charlist_location: str, existing_model: str,
                                     f"{charlist_location} and "
                                     "replace_final_layer is False.")
 
-        logging.info("Using charlist: %s", charlist)
-        logging.info("Charlist length: %s", len(charlist))
-
     return charlist, removed_padding
 
 

src/data/manager.py

@@ -232,7 +232,7 @@ def _create_data(self,
         # Update the charlist if it has changed
         if not self.charlist:
             self.charlist = sorted(list(characters))
-            logging.info("Created charlist: %s", self.charlist)
+            logging.debug("Updated charlist: %s", self.charlist)
 
         logging.info("Created data for %s with %s samples",
                      partition_name, len(partitions))

src/main.py

@@ -77,6 +77,8 @@ def main():
 
         # Replace the charlist with the one from the data manager
         charlist = data_manager.charlist
+        logging.info("Using charlist: %s", charlist)
+        logging.info("Charlist length: %s", len(charlist))
 
         # Additional model customization such as freezing layers, replacing
         # layers, or adjusting for float32

src/model/vgsl_model_generator.py

@@ -306,7 +306,11 @@ def get_model_libary() -> dict:
                 ("None,64,None,4 Bn Ce3,3,16 RB3,3,16 RB3,3,16 RBd3,3,32 "
                  "RB3,3,32 RB3,3,32 RB3,3,32 RB3,3,32 RBd3,3,64 RB3,3,64 "
                  "RB3,3,64 RB3,3,64 RB3,3,64 RBd3,3,128 RB3,3,128 Rc "
-                 "Bl256,D20 Bl256,D20 Bl256,D20 O1s92")
+                 "Bl256,D20 Bl256,D20 Bl256,D20 O1s92"),
+            "recommended":
+                ("None,64,None,1 Cr3,3,24 Mp2,2,2,2 Bn Cr3,3,48 Mp2,2,2,2 Bn "
+                 "Cr3,3,96 Mp2,2,2,2 Bn Cr3,3,96 Mp2,2,2,2 Bn Rc Bl512 D50 "
+                 "Bl512 D50 Bl512 D50 Bl512 D50 Bl512 D50 O1s92")
         }
 
         return model_library
@@ -638,8 +642,6 @@ def conv2d_generator(self,
         # Check parameter length and generate corresponding Conv2D layer
         if len(conv_filter_params) == 3:
             x, y, d = conv_filter_params
-            logging.warning(
-                "No stride provided, setting default stride of (1,1)")
             return layers.Conv2D(d,
                                  kernel_size=(y, x),
                                  strides=(1, 1),

src/setup/environment.py

@@ -13,6 +13,22 @@
 from setup.config import Config
 
 
+class TensorFlowLogFilter(logging.Filter):
+    """Filter to exclude specific TensorFlow logging messages.
+
+    This filter checks each log record for specific phrases that are to be
+    excluded from the logs. If any of the specified phrases are found in a log
+    message, the message is excluded from the logs.
+    """
+
+    def filter(self, record):
+        # Exclude logs containing the specific message
+        exclude_phrases = [
+            "Reduce to /job:localhost/replica:0/task:0/device:CPU:",
+        ]
+        return not any(phrase in record.msg for phrase in exclude_phrases)
+
+
 def set_deterministic(seed: int) -> None:
     """
     Sets the environment and random seeds to ensure deterministic behavior in
@@ -121,6 +137,7 @@ def setup_logging() -> None:
 
     # Remove the default Tensorflow logger handlers and use our own
     tf_logger = tf.get_logger()
+    tf_logger.addFilter(TensorFlowLogFilter())
     while tf_logger.handlers:
         tf_logger.handlers.pop()