我正在尝试使用网络特定层的渐变作为下一层的输入（相对于图层权重的导数）。我的代码太长了，无法将其全部放在这里，但下面是有问题的部分（仅在插入后才会破坏）
weights = tf.get_collection(tf.GraphKeys.TRAINABLE_VARIABLES, scope="conv5/weights:0")
deriv = tf.gradients(net, weights)
deriv = tf.squeeze(deriv)
deriv = tf.expand_dims(deriv, 0)
batch_deriv = tf.tile(deriv, [batch_size, 1, 1])
h = tf.reduce_sum(net, axis=1)# maybe normalize ?
new_feature_map = tf.concat([h, batch_deriv], axis=1)
我收到以下错误:(在优化器中，而不是在我的模型中，但我不知道为什么）
File "/usr/lib/pycharm-community/helpers/pydev/pydevd.py", line 1596, in <module>
globals = debugger.run(setup['file'], None, None, is_module)
File "/usr/lib/pycharm-community/helpers/pydev/pydevd.py", line 974, in run
pydev_imports.execfile(file, globals, locals) # execute the script
File ".../train.py", line 272, in <module>
train()
File ".../train.py", line 133, in train
train_op = optimizer.minimize(loss, global_step=batch)
File ".../local/lib/python2.7/site-packages/tensorflow/python/training/optimizer.py", line 315, in minimize
grad_loss=grad_loss)
File ".../local/lib/python2.7/site-packages/tensorflow/python/training/optimizer.py", line 386, in compute_gradients
colocate_gradients_with_ops=colocate_gradients_with_ops)
File ".../local/lib/python2.7/site-packages/tensorflow/python/ops/gradients_impl.py", line 551, in gradients
out_grads[i] = control_flow_ops.ZerosLikeOutsideLoop(op, i)
File ".../local/lib/python2.7/site-packages/tensorflow/python/ops/control_flow_ops.py", line 1305, in ZerosLikeOutsideLoop
pred = op_ctxt.pred
AttributeError: 'NoneType' object has no attribute 'pred'
任何人都知道为什么会发生这种情况以及如何解决它？
更新
似乎改变了行
new_feature_map = tf.concat([h, batch_deriv], axis=1)
到
new_feature_map = tf.concat([h, tf.stop_gradient(batch_deriv) ], axis=1)
“修复”它（它不再是dowsnt错误），但我不知道为什么。另外 - 在评估期间（在测试集上），似乎不计算梯度。
任何人都知道如何解决这个问题？