我正在尝试在千层面中找到索引 2d max pooling
network = batch_norm(Conv2DLayer(
network, num_filters=filter_size, filter_size=(kernel, kernel),pad=pad,
nonlinearity=lasagne.nonlinearities.rectify,
W=lasagne.init.GlorotUniform(),name="conv"), name="BN")
pool_in = lasagne.layers.get_output(network)
network = MaxPool2DLayer(network, pool_size=(pool_size, pool_size),stride=2,name="pool")
pool_out = lasagne.layers.get_output(network)
ind1 = T.grad(T.sum(pool_out), wrt=pool_in)
当我尝试构建模型时，它会引发错误
DisconnectedInputError: grad method was asked to compute the gradient with respect to a variable that is not part of the computational graph of the cost, or is used only by a non-differentiable operator: Elemwise{mul,no_inplace}.0
Backtrace when the node is created:
File "//anaconda/lib/python2.7/site-packages/IPython/core/interactiveshell.py", line 2871, in run_cell
interactivity=interactivity, compiler=compiler, result=result)
File "//anaconda/lib/python2.7/site-packages/IPython/core/interactiveshell.py", line 2975, in run_ast_nodes
if self.run_code(code, result):
File "//anaconda/lib/python2.7/site-packages/IPython/core/interactiveshell.py", line 3035, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-28-0b136cc660e2>", line 1, in <module>
network = build_model()
File "<ipython-input-27-20acc3fe0d98>", line 8, in build_model
pool_in = lasagne.layers.get_output(network)
File "//anaconda/lib/python2.7/site-packages/lasagne/layers/helper.py", line 191, in get_output
all_outputs[layer] = layer.get_output_for(layer_inputs, **kwargs)
File "//anaconda/lib/python2.7/site-packages/lasagne/layers/special.py", line 52, in get_output_for
return self.nonlinearity(input)
File "//anaconda/lib/python2.7/site-packages/lasagne/nonlinearities.py", line 157, in rectify
return theano.tensor.nnet.relu(x)
在千层面层中间输出上编码函数的正确方法是什么。