STM32CubeAI-Keras Sequential model with multiple inputs gives INTERNAL ERROR: unpack_from requires a buffer of at least 4 bytes
I've followed this tinyML for stm32 from Digikey "TinyML: Getting Started with STM32 X-CUBE-AI | Digi-Key Electronics" reference,and got no Errors in STM32CubeMX when I clicked "Analyze" button after I've uploaded the tfLitemodel.
Later I've tried this
import tensorflow as tf
from tensorflow.keras.layers import *
from tensorflow.keras.models import Sequential, Model
from tensorflow.keras.optimizers import Adam, RMSprop
import numpy as np
input1 = Input(shape=(1,))
input2 = Input(shape=(1,))
input = Concatenate()([input1, input2])
x = Dense(2)(input)
x = Dense(1)(x)
model = Model(inputs=[input1, input2], outputs=x)
model.summary()
model.compile(
optimizer = RMSprop(lr=0.02,rho=0.9,epsilon=None,decay=0),
loss = 'mean_squared_error'
)
x1=np.array([2600, 3000, 3200, 3600, 4000 ,4100])
x2=np.array([3.0 ,4.0,4.0,3.0, 5.0,6.0])
y=np.array([550000,565000,610000, 595000,760000,810000])
history = model.fit([x1, x2], y,epochs=500)
model.predict([np.array([3000]),np.array([4])])
The python code executes without error and even prediction is working fine. Yet when I've uploaded this tfLite model in stm32cubeMX and went for "Analyze" button , I get "INTERNAL ERROR: unpack_from requires a buffer of at least 4 bytes"
PS : I'm using stm32 x-cube-ai : 5.1.2 version
Also, the reference code uses Sequential Model, while my code doesn't