TFSM converted to keras

ConvertToKeras.py

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+import tensorflow as tf
+import keras
+
+# Originally TensorFlow 2.13.0 Keras 2.13.1
+print(tf.__version__)
+print(keras.__version__)
+
+# Load the old model using the folder
+inference_layer = keras.layers.TFSMLayer('saved_model/', call_endpoint='serving_default')
+
+# Specify the model architecture using an inference layer
+model = tf.keras.Sequential([
+    inference_layer,
+])
+
+# compile the model using the same parameters when first training the model
+model.compile(optimizer="adam",
+              loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True),
+              metrics=["accuracy"])
+
+# save the model as a .keras file (in line with Keras 3 specifications)
+model.save("leaf_model.keras")

leaf_model.keras

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+version https://git-lfs.github.com/spec/v1
+oid sha256:58ff288ea82cfc752f5aad9b0b7a3011c74547d2d8a93a7c483eb258d4568674
+size 16273237