类型错误:张量是不可散列的。相反,使用 tensor.ref() 作为键。在 Keras 外科医生

Nik*_*nna 7 pruning keras vgg-net tf.keras

我正在使用 Kerassurgeon 模块进行修剪。我在 google colab 中使用 VGG-16 时遇到了这个错误。它适用于其他模型。有人可以帮我解决这个问题。

---> 17   model_new = surgeon.operate()<br>
     18   return model_new

>>/usr/local/lib/python3.6/dist-packages/kerassurgeon/surgeon.py in operate(self)
    152             sub_output_nodes = utils.get_node_inbound_nodes(node)
    153             outputs, output_masks = self._rebuild_graph(self.model.inputs,
--> 154                                                         sub_output_nodes)
    155 
    156             # Perform surgery at this node

>>/usr/local/lib/python3.6/dist-packages/kerassurgeon/surgeon.py in _rebuild_graph(self, graph_inputs, output_nodes, graph_input_masks)
    264         # Call the recursive _rebuild_rec method to rebuild the submodel up to
    265         # each output layer
--> 266         outputs, output_masks = zip(*[_rebuild_rec(n) for n in output_nodes])
    267         return outputs, output_masks
    268 

>>/usr/local/lib/python3.6/dist-packages/kerassurgeon/surgeon.py in <listcomp>(.0)
    264         # Call the recursive _rebuild_rec method to rebuild the submodel up to
    265         # each output layer
--> 266         outputs, output_masks = zip(*[_rebuild_rec(n) for n in output_nodes])
    267         return outputs, output_masks
    268 

>>/usr/local/lib/python3.6/dist-packages/kerassurgeon/surgeon.py in _rebuild_rec(node)
    216             # Check for replaced tensors before any other checks:
    217             # these are created by the surgery methods.
--> 218             if node_output in self._replace_tensors.keys():
    219                 logging.debug('bottomed out at replaced output: {0}'.format(
    220                     node_output))

>>/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py in __hash__(self)
    724     if (Tensor._USE_EQUALITY and executing_eagerly_outside_functions() and
    725         (g is None or g.building_function)):
--> 726       raise TypeError("Tensor is unhashable. "
    727                       "Instead, use tensor.ref() as the key.")
    728     else:

**TypeError: Tensor is unhashable. Instead, use tensor.ref() as the key.**
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min*_* ou 11

当我使用 GradientExplainer尝试深度学习示例时,我已经解决了类似的问题。这是版本不兼容造成的。
添加以下代码可能会有所帮助:

import tensorflow.compat.v1.keras.backend as K
import tensorflow as tf
tf.compat.v1.disable_eager_execution()
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tf 版本是 2.3.1
kerase 版本是 2.4.0
Shap 版本是 0.36


Nik*_*nna 1

我解决了这个错误。这是由于版本更改所致。使用 Kerassurgeon 而不是 tfkerassurgeon。

使用以下版本

tf 1.x , keras > 2.2 , kerassurgeon 
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