ValueError: as_list() is not defined on an unknown TensorShape. Error with lambda function

I'm trying to build and train a model with keras, but I'm facing the error "ValueError: as_list() is not defined on an unknown TensorShape.". Follows the most bare bone code I could build that still shows the issue:

import numpy as np
import tensorflow as tf

def func(x):
    return x

def create_dataset(vect):
    a = [vect]
    b = [vect] 

    dataset = tf.data.Dataset.from_tensor_slices((a, b))

    py_func = lambda x, y: (tf.numpy_function(func, [x], tf.float32), y)    ##LINE 1 !                                                                            
    dataset = dataset.map(py_func)                                          ##LINE 2 !

    dataset = dataset.map(lambda data, label: (tf.expand_dims(data, axis=0), tf.expand_dims(label, axis=0))) 
    return dataset

vect = np.array([-0.18441772, -0.17321777, -0.16046143, -0.14782715, -0.13504028,
       -0.12179565, -0.10858154, -0.09503174, -0.08117676, -0.06964111],
      dtype=np.float32)

example_dataset = create_dataset(vect)
example_list = list(example_dataset)
input_shape_m = example_list[0][0].shape #which is TensorShape([1, 10])

def DeepModel(input_shape):

    X_input = tf.keras.Input(input_shape)
    X = tf.keras.layers.Dense(10)(X_input)
    model = tf.keras.Model(inputs=X_input, outputs=X)

    return model

model = MyModel(input_shape_m[1:]) 
model.compile(optimizer='adam', loss='mse', metrics=['accuracy'])

history = model.fit(example_dataset, epochs=5)

This will give me the error I've said when running the last line of code.

If instead I comment the lines of code "LINE 1" and "LINE 2", the code will run just fine and it will not give me any error. Why is that? Thank you so much already