Removing the tfa dependency

setup.cfg

@@ -34,7 +34,6 @@ install_requires =
     pandas
     tqdm
     tensorflow
-    tensorflow-addons
     segmentation-models
     xarray
     rioxarray

tensorflow_caney/utils/callbacks.py

@@ -1,7 +1,6 @@
 import sys
 import tensorflow as tf
 import segmentation_models as sm
-import tensorflow_addons as tfa
 from typing import List
 
 __all__ = ["get_callbacks"]
@@ -20,5 +19,5 @@ def get_callbacks(callbacks: List[str]) -> List:
         try:
             callback_functions.append(eval(callback))
         except (NameError, AttributeError) as err:
-            sys.exit(f'{err}. Accepted callbacks from {tf}, {sm}, {tfa}')
+            sys.exit(f'{err}. Accepted callbacks from {tf}, {sm}')
     return callback_functions

tensorflow_caney/utils/losses.py

@@ -1,7 +1,6 @@
 import sys
 import numpy as np
 import tensorflow as tf
-import tensorflow_addons as tfa
 import segmentation_models as sm
 import tensorflow_caney as tfc
 
@@ -31,7 +30,7 @@ def get_loss(loss: str) -> Any:
     try:
         loss_function = eval(loss)
     except (NameError, AttributeError) as err:
-        sys.exit(f'{err}. Accepted loss from {tf}, {sm}, {tfa}.')
+        sys.exit(f'{err}. Accepted loss from {tf}, {sm}.')
     return loss_function
 
 

tensorflow_caney/utils/metrics.py

@@ -4,7 +4,6 @@
 import tensorflow as tf
 from typing import Any, List
 import segmentation_models as sm
-import tensorflow_addons as tfa
 from tensorflow.keras import backend as K
 from sklearn.metrics import accuracy_score
 from sklearn.metrics import precision_score
@@ -39,7 +38,7 @@ def get_metrics(metrics: List[str]) -> Any:
         try:
             metric_functions.append(eval(metric))
         except (NameError, AttributeError) as err:
-            sys.exit(f'{err}. Accepted metrics from {tf}, {sm}, {tfa}')
+            sys.exit(f'{err}. Accepted metrics from {tf}, {sm}')
     return metric_functions
 
 

tensorflow_caney/utils/model.py

@@ -4,7 +4,6 @@
 import tensorflow as tf
 import tensorflow_caney
 import tensorflow_caney as tfc
-import tensorflow_addons as tfa
 import segmentation_models as sm
 from keras_unet_collection import models as kuc
 
@@ -37,7 +36,7 @@ def get_model(model: str) -> Any:
         model_function = eval(model)
     except (NameError, AttributeError) as err:
         sys.exit(
-            f'{err}. Accepted models from {tf}, {sm}, {tfa}, {tfc}, {kuc}')
+            f'{err}. Accepted models from {tf}, {sm}, {tfc}, {kuc}')
     return model_function
 
 

tensorflow_caney/utils/optimizers.py

@@ -1,7 +1,6 @@
 import sys
 import tensorflow as tf
 import segmentation_models as sm
-import tensorflow_addons as tfa
 from typing import Any
 
 __all__ = ["get_optimizer"]
@@ -18,5 +17,5 @@ def get_optimizer(optimizer: str) -> Any:
     try:
         optimizer = eval(optimizer)
     except (NameError, AttributeError) as err:
-        sys.exit(f'{err}. Accepted optimizers from {tf}, {sm}, {tfa}')
+        sys.exit(f'{err}. Accepted optimizers from {tf}, {sm}')
     return optimizer