nn_q_table.py 文件源码

def copy_all_vars(from_namespace, to_namespace, affine_coefficient=1.0):
    assert affine_coefficient >= 0.0 and affine_coefficient <= 1.0
    copy_ops = []
    with tf.variable_scope("", reuse=True):  # for grabbing the targets by full namespace
        for src_var in tf.all_variables():
            # ignore any variable not in src namespace
            if not src_var.name.startswith(from_namespace):
                continue
            # fetch reference to target variable with the same name as the src variable
            assert src_var.name.endswith(":0")
            target_var_name = src_var.name.replace(from_namespace, to_namespace).replace(":0", "")
            target_var = tf.get_variable(target_var_name, src_var.get_shape())
            # create a copy op to clobber target with src
            # target = alpha * src + (1.0-alpha) * target
            copy_ops.append(target_var.assign_sub(affine_coefficient * (target_var - src_var)))
    single_copy_op = tf.group(*copy_ops)
    return single_copy_op