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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 _minimize_and_clip(optimizer, objective, var_list, clip_val=10):
 """Minimized `objective` using `optimizer` w.r.t. variables in `var_list` while ensure the norm of the gradients for each variable is clipped to `clip_val` """

    gradients = optimizer.compute_gradients(objective, var_list=var_list)
    for i, (grad, var) in enumerate(gradients):
        if grad is not None:
            gradients[i] = (tf.clip_by_norm(grad, clip_val), var)
    return gradients