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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 l1_loss(tensor, weight=1.0, scope=None):
 """Define a L1Loss, useful for regularize, i.e. lasso. Args: tensor: tensor to regularize. weight: scale the loss by this factor. scope: Optional scope for name_scope. Returns: the L1 loss op. """

  with tf.name_scope(scope, 'L1Loss', [tensor]):
    weight = tf.convert_to_tensor(weight,
                                  dtype=tensor.dtype.base_dtype,
                                  name='loss_weight')
    loss = tf.multiply(weight, tf.reduce_sum(tf.abs(tensor)), name='value')
    tf.add_to_collection(LOSSES_COLLECTION, loss)
    return loss