mycommon.py 文件源码

def minimize_and_clip(optimizer, objective, var_list = None, clip_val=10, exclude = None):
    """
    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_value(grad, -clip_val, clip_val), var)
            if (exclude is None) or (var not in exclude):
                gradients[i] = (tf.clip_by_norm(grad, clip_val), var)
    return optimizer.apply_gradients(gradients)


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# Other NN Related