Set gloabal policy (float32)

my_app.py

@@ -1,6 +1,7 @@
 import gradio as gr
 import tensorflow as tf
 from huggingface_hub import from_pretrained_keras
+from tensorflow.keras import mixed_precision
 
 # Load your trained models
 model1 = from_pretrained_keras("ml-debi/EfficientNetB0-Food101")
@@ -36,8 +37,11 @@ def predict(image):
     #model = model1 if model_selection == "EfficentNetB0 Fine Tune" else model2
 
     #print(model.summary())
+    if mixed_precision.global_policy() == "mixed_float16":
+        mixed_precision.set_global_policy(policy="float32")
 
     image = preprocess(image)
+    print(mixed_precision.global_policy())
     prediction = model1.predict(image)
     print("model prediction", prediction)
     predicted_class = classes[int(tf.argmax(prediction, axis=1))]