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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def validate_inputs(u_kn, N_k, f_k):
 """Check types and return inputs for MBAR calculations. Parameters u_kn or q_kn : np.ndarray, shape=(n_states, n_samples), dtype='float' The reduced potential energies or unnormalized probabilities N_k : np.ndarray, shape=(n_states), dtype='int' The number of samples in each state f_k : np.ndarray, shape=(n_states), dtype='float' The reduced free energies of each state Returns ------- u_kn or q_kn : np.ndarray, shape=(n_states, n_samples), dtype='float' The reduced potential energies or unnormalized probabilities N_k : np.ndarray, shape=(n_states), dtype='float' The number of samples in each state. Converted to float because this cast is required when log is calculated. f_k : np.ndarray, shape=(n_states), dtype='float' The reduced free energies of each state """

    n_states, n_samples = u_kn.shape

    u_kn = ensure_type(u_kn, 'float', 2, "u_kn or Q_kn", shape=(n_states, n_samples))
    N_k = ensure_type(N_k, 'float', 1, "N_k", shape=(n_states,), warn_on_cast=False)  # Autocast to float because will be eventually used in float calculations.
    f_k = ensure_type(f_k, 'float', 1, "f_k", shape=(n_states,))

    return u_kn, N_k, f_k