error memanggil kembali data histori pada data training

# The LSTM model is being constructed and compiled for the training process to take place

# Since the model forecasts into the future, in this case there are no validation data and no use of

# keras callbacks ('EarlyStopping')

ini koding pemanggil data histori

initializer = tf.keras.initializers.he_uniform(seed=0)
model=Sequential()
model.add(LSTM(12,activation='relu',input_shape=(length,n_features),kernel_initializer=initializer,
                     bias_initializer=initializers.Constant(0.01)))
model.add(Dense(1,activation='linear',kernel_initializer=initializer,
                     bias_initializer=initializers.Constant(0.01)))
model.compile(optimizer=opt,loss='mse')

data_generator=TimeseriesGenerator(scaled_set,scaled_set,length=length,batch_size=1)

model.fit_generator(data_generator,epochs=100)

ini error nya

Epoch 1/100

<ipython-input-441-67e4ec443553>:15: UserWarning: `Model.fit_generator` is deprecated and will be removed in a future version. Please use `Model.fit`, which supports generators.
  model.fit_generator(data_generator,epochs=100)

---------------------------------------------------------------------------

KeyError                                  Traceback (most recent call last)

<ipython-input-441-67e4ec443553> in <cell line: 15>()
     13 data_generator=TimeseriesGenerator(scaled_set,scaled_set,length=length,batch_size=1)
     14
---> 15 model.fit_generator(data_generator,epochs=100)

2 frames

/usr/local/lib/python3.10/dist-packages/keras/engine/training.py in tf__train_function(iterator)
     13                 try:
     14                     do_return = True
---> 15                     retval_ = ag__.converted_call(ag__.ld(step_function), (ag__.ld(self), ag__.ld(iterator)), None, fscope)
     16                 except:
     17                     do_return = False

KeyError: in user code:

    File "/usr/local/lib/python3.10/dist-packages/keras/engine/training.py", line 1284, in train_function  *
        return step_function(self, iterator)
    File "/usr/local/lib/python3.10/dist-packages/keras/engine/training.py", line 1268, in step_function  **
        outputs = model.distribute_strategy.run(run_step, args=(data,))
    File "/usr/local/lib/python3.10/dist-packages/keras/engine/training.py", line 1249, in run_step  **
        outputs = model.train_step(data)
    File "/usr/local/lib/python3.10/dist-packages/keras/engine/training.py", line 1054, in train_step
        self.optimizer.minimize(loss, self.trainable_variables, tape=tape)
    File "/usr/local/lib/python3.10/dist-packages/keras/optimizers/optimizer.py", line 543, in minimize
        self.apply_gradients(grads_and_vars)
    File "/usr/local/lib/python3.10/dist-packages/keras/optimizers/optimizer.py", line 1174, in apply_gradients
        return super().apply_gradients(grads_and_vars, name=name)
    File "/usr/local/lib/python3.10/dist-packages/keras/optimizers/optimizer.py", line 650, in apply_gradients
        iteration = self._internal_apply_gradients(grads_and_vars)
    File "/usr/local/lib/python3.10/dist-packages/keras/optimizers/optimizer.py", line 1200, in _internal_apply_gradients
        return tf.__internal__.distribute.interim.maybe_merge_call(
    File "/usr/local/lib/python3.10/dist-packages/keras/optimizers/optimizer.py", line 1250, in _distributed_apply_gradients_fn
        distribution.extended.update(
    File "/usr/local/lib/python3.10/dist-packages/keras/optimizers/optimizer.py", line 1247, in apply_grad_to_update_var  **
        return self._update_step(grad, var)
    File "/usr/local/lib/python3.10/dist-packages/keras/optimizers/optimizer.py", line 232, in _update_step
        raise KeyError(

    KeyError: 'The optimizer cannot recognize variable lstm_24/lstm_cell_24/kernel:0. This usually means you are trying to call the optimizer to update different parts of the model separately. Please call `optimizer.build(variables)` with the full list of trainable variables before the training loop or use legacy optimizer `tf.keras.optimizers.legacy.Adam.'

avatar taufikhidayat_google_6855
@taufikhidayat_google_6855

1 Kontribusi 0 Poin

Diperbarui 9 bulan yang lalu

1 Jawaban:

<div>Kesalahan yang Anda dapatkan adalah KeyError, yang berarti optimizer tidak dapat menemukan variabel yang ingin diperbarui. Hal ini kemungkinan besar terjadi karena Anda mencoba memanggil optimizer untuk memperbarui bagian model secara terpisah. Untuk memperbaikinya, Anda perlu memanggil optimizer.build(variables) dengan daftar lengkap variabel yang dapat dilatih sebelum perulangan pelatihan.<br><br>Berikut ini adalah kode yang diperbarui:<br><br></div><pre>initializer = tf.keras.initializers.he_uniform(seed=0) model=Sequential() model.add(LSTM(12,activation='relu',input_shape=(length,n_features),kernel_initializer=initializer, bias_initializer=initializers.Constant(0.01))) model.add(Dense(1,activation='linear',kernel_initializer=initializer, bias_initializer=initializers.Constant(0.01))) model.compile(optimizer=opt,loss='mse')

data_generator=TimeseriesGenerator(scaled_set,scaled_set,length=length,batch_size=1)

Membangun optimizer dengan daftar lengkap variabel yang dapat dilatih

optimizer.build(model.trainable_variables)

Melatih model

model.fit_generator(data_generator,epochs=100)</pre><div><br>Hal ini seharusnya memperbaiki kesalahan dan memungkinkan Anda melatih model dengan sukses.</div>

avatar adamajalah27
@adamajalah27

119 Kontribusi 39 Poin

Dipost 9 bulan yang lalu

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