Question

AttributeError：“张量”对象没有属性“ _keras_shape”

我正在尝试运行此模型，但是由于基于此错误，我会遇到此错误：

  File "C:\ProgramData\Anaconda3\envs\py35\lib\site-packages\spyder\utils\site\sitecustomize.py", line 705, in runfile
    execfile(filename, namespace)

  File "C:\ProgramData\Anaconda3\envs\py35\lib\site-packages\spyder\utils\site\sitecustomize.py", line 102, in execfile
    exec(compile(f.read(), filename, 'exec'), namespace)

  File "C:/Users/hendy/Documents/All/LHP_Modell_Control/Validate_Closed_Loop_Controller.py", line 18, in <module>
    model = Model_object.structure(nn, depth, 32,inputs)

  File "C:\Users\hendy\Documents\All\LHP_Modell_Control\Model_LHP_stateful.py", line 52, in structure
    model = Model(inputs=[inp_ext, y_refeed, h_ext, c_ext], outputs=[out, h_out, c_out])

  File "C:\ProgramData\Anaconda3\envs\py35\lib\site-packages\keras\legacy\interfaces.py", line 91, in wrapper
    return func(*args, **kwargs)

  File "C:\ProgramData\Anaconda3\envs\py35\lib\site-packages\keras\engine\network.py", line 93, in __init__
    self._init_graph_network(*args, **kwargs)



    File "C:\ProgramData\Anaconda3\envs\py35\lib\site-packages\keras\engine\network.py", line 247, in _init_graph_network
        input_shapes=[x._keras_shape for x in self.inputs],

      File "C:\ProgramData\Anaconda3\envs\py35\lib\site-packages\keras\engine\network.py", line 247, in <listcomp>
        input_shapes=[x._keras_shape for x in self.inputs],

    AttributeError: 'Tensor' object has no attribute '_keras_shape'`enter code here`

我也尝试通过：

进行升级

pip3 install --upgrade tensorflow-gpu
and updated keras to 2.2.4

pip install Keras==2.2.4

我知道我们可以在代码中使用两种Keras。 Keras包或仅使用tf.keras。在这段代码中，我使用Keras软件包，即我尝试不混用！如您在代码中所见

import pandas as pds
import numpy as np
from keras.models import Model

from keras.layers import Input
from keras.layers import Dense
from keras.layers import add

from recurrentshop import LSTMCell
from recurrentshop import RecurrentModel


 def structure(self, node_number, depth, batch_shape, inputs):
        timesteps = self.timesteps
        inp_ext = Input(shape=(timesteps, inputs))
        y_refeed = Input(shape=(timesteps, inputs))
        h_ext = Input(shape=(inputs,))
        c_ext = Input(shape=(inputs,))

        inp = Input(batch_shape=(batch_shape, inputs))
        readout_input = Input(batch_shape=(batch_shape, inputs))
        h_tm1 = Input(batch_shape=(batch_shape, inputs))
        c_tm1 = Input(batch_shape=(batch_shape, inputs))


        lstms_input = add([inp, readout_input])

        cells = [LSTMCell(node_number) for _ in range(depth)]
        lstms_output = Dense(node_number)(lstms_input)
        h = Dense(node_number)(h_tm1)
        c = Dense(node_number)(c_tm1)
        for cell in cells:
            lstms_output, h, c = cell([lstms_output, h, c])

        lstms_output = Dense(inputs)(lstms_output)
        h = Dense(inputs)(h)
        c = Dense(inputs)(c)

        y = lstms_output

        rnn = RecurrentModel(input=inp, initial_states=[h_tm1, c_tm1], output=y, final_states=[h, c], readout_input=readout_input, return_sequences=True, return_states=True, name="RecurrentModel")
        out, h_out, c_out = rnn(inp_ext, ground_truth=y_refeed, initial_state=[h_ext, c_ext])
        model = Model(inputs=[inp_ext, y_refeed, h_ext, c_ext], outputs=[out, h_out, c_out])
        return model

'Tensor'对象没有属性'_keras_shape'

0 个答案: