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Given the following text problem statement, write Python code to implement the functionality described below in problem statement
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Problem:
I'm using tensorflow 2.10.0.
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Python Code:
import tensorflow as tf
tf.compat.v1.disable_eager_execution()
input = [10, 20, 30]
def g(input):
    ds = tf.data.Dataset.from_tensor_slices(input)
    ds = ds.flat_map(lambda x: tf.data.Dataset.from_tensor_slices([x, x + 1, x + 2]))
    element = tf.compat.v1.data.make_one_shot_iterator(ds).get_next()
    result = []
    with tf.compat.v1.Session() as sess:
        for _ in range(9):
            result.append(sess.run(element))
    return result
result = g(input)
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