I have tried various ways to convert my Keras model to core ml using core ml tools, but it gives me this error.
Keras layer '<class 'tensorflow.python.keras.engine.input_layer.InputLayer'>' not supported.
This is how my model looks.
img_input = layers.Input(shape=(224, 224, 3))
seed = 230
numpy.random.seed(seed)
x = layers.Conv2D(16, 3, activation='relu')(img_input)
x = layers.MaxPooling2D(2)(x)
x = layers.Conv2D(32, 3, activation='relu')(x)
x = layers.MaxPooling2D(2)(x)
x = layers.Flatten()(x)
x = layers.Dense(128, activation='relu')(x)
x = layers.Dropout(0.4)(x)
output = layers.Dense(3, activation='softmax')(x)
model = Model(img_input, output)
model.compile(loss='sparse_categorical_crossentropy', optimizer='adam', metrics=['accuracy'])