modified: .idea/.name

	modified:   .idea/workspace.xml
	modified:   BETA_E_Model_T&T.ipynb
	deleted:    Utils/New_SGD.py
	modified:   Utils/Other.py
	modified:   Utils/README.md
	modified:   Utils/lr_find.py
	modified:   Utils/one_cycle.py
	deleted:    Utils/swap_ema_weights.py

Utils/Other.py

@@ -1,7 +1,6 @@
 from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score
 from Utils.print_color_V2_NEW import print_Color_V2
 from Utils.print_color_V1_OLD import print_Color
-import keras.backend as K
 from tabulate import tabulate
 from numba import cuda
 import numpy as np
@@ -141,9 +140,10 @@ def set_optimizer_attribute(optimizer, attribute, value, verbose: bool = False):
         verbose: Whether to print a message if the attribute does not exist.
     """
     if hasattr(optimizer, attribute):
-        K.set_value(getattr(optimizer, attribute), value)
+        setattr(optimizer, attribute, value)
     else:
-        print(f"The optimizer does not have an attribute named '{attribute}'") if verbose else None
+        if verbose:
+            print(f"The optimizer does not have an attribute named '{attribute}'")
 
 
 def print_optimizer_info(model):

Utils/README.md

@@ -19,9 +19,6 @@
 
 ## Timeout_input.py (by Me)
 
-## swap_ema_weights and New_SGD.py (\`**smi**\` copy of keras 3)
-- ### github repo used: [keras](https://github.com/keras-team/keras)
-
 ## FixedDropout.py (by Me)
 For EfficientNet model Example:
 ```python

Utils/lr_find.py

@@ -1,13 +1,10 @@
+import keras
 import tempfile
-
 import matplotlib.pyplot as plt
 import numpy as np
-
 import tensorflow as tf
-from tensorflow import keras
 from tqdm.auto import tqdm
-
-K = keras.backend
+import keras.src.legacy.backend as K
 
 
 class Scheduler:
@@ -59,9 +56,9 @@ class LrFinder:
 
     def __init__(
         self,
-        model: tf.keras.Model,
-        optimizer: tf.keras.optimizers.Optimizer,
-        loss_fn: tf.keras.losses.Loss,
+        model: keras.Model,
+        optimizer: keras.optimizers.Optimizer,
+        loss_fn: keras.losses.Loss,
     ) -> None:
         self.lrs = []
         self.losses = []

Utils/one_cycle.py

@@ -1,9 +1,7 @@
-from tensorflow import keras
+import keras
 import math
 import matplotlib.pyplot as plt
-
-K = keras.backend
-
+import keras.src.legacy.backend as K
 
 class OneCycleLr(keras.callbacks.Callback):
     """