self.epoch_entropy.append(epoch_entropy((_hr_out))) UnboundLocalError: local variable '_hr_out' referenced before assignment about talos HOT 12 CLOSED

@x94carbone the error message yes, we no longer swallow the actual error message. Closing here.

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Can you share the whole trace (the list of messages where the error appears) for the error.

from talos.

t = ta.Scan(x = x_train_analytical, y = x_train_experimental,
model = AE, grid_downsample = 0.01,
params = p, dataset_name ='model_data' , experiment_no='1', shuffle = False )
The model needs to have Return in format "return history, model"
Traceback (most recent call last):

File "", line 3, in
params = p, dataset_name ='model_data' , experiment_no='1', shuffle = False )

File "C:\ProgramData\Anaconda3\lib\site-packages\talos\scan.py", line 77, in init
self._null = self._run()

File "C:\ProgramData\Anaconda3\lib\site-packages\talos\scan.py", line 93, in _run
self.epoch_entropy.append(epoch_entropy((_hr_out)))

UnboundLocalError: local variable '_hr_out' referenced before assignment

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Thanks. Can you try the latest version:

pip uninstall talos 
pip install git+https://github.com/autonomio/talos.git@dev

You might still get the error after this, but it should be more descriptive and will help to identify what exactly it's wrong (it seems that there some issue in your model). The error message that says _hr_out is referenced before assignment means that 10 times out of 10.

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sorry getting this error when trying to pip install git+https
Error [WinError 2] The system cannot find the file specified while executing command git clone -q https://github.com/autonomio/talos.git C:\Users\xxxxxx\AppData\Local\Temp\pip-req-build-7542c4l0
Cannot find command 'git' - do you have 'git' installed and in your PATH?

from talos.

how did you install Talos initially on your system?

from talos.

Anaconda prompt.
pip install talos

from talos.

can you do

conda install git

and then try again.

from talos.

Thanks a lot. It worked now.
I ran the program again.
t = ta.Scan(x = x_train_analytical, y = x_train_experimental,
model = AE, grid_downsample = 0.01,
params = p, dataset_name ='model_data' , experiment_no='1', shuffle = False )
Traceback (most recent call last):

File "", line 3, in
params = p, dataset_name ='model_data' , experiment_no='1', shuffle = False )

File "C:\ProgramData\Anaconda3\lib\site-packages\talos\scan.py", line 195, in init
self._null = self._run()

File "C:\ProgramData\Anaconda3\lib\site-packages\talos\scan.py", line 208, in _run
_hr_out, self.keras_model = self._model()

File "C:\ProgramData\Anaconda3\lib\site-packages\talos\scan.py", line 239, in _model
self.params)

File "", line 8, in AE
activity_regularizer=regularizers.l1(regulariser_value))(Input_Experiment)

File "C:\ProgramData\Anaconda3\lib\site-packages\keras\engine\base_layer.py", line 431, in call
self.build(unpack_singleton(input_shapes))

File "C:\ProgramData\Anaconda3\lib\site-packages\keras\layers\core.py", line 861, in build
constraint=self.kernel_constraint)

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

File "C:\ProgramData\Anaconda3\lib\site-packages\keras\engine\base_layer.py", line 249, in add_weight
weight = K.variable(initializer(shape),

File "C:\ProgramData\Anaconda3\lib\site-packages\keras\initializers.py", line 209, in call
scale /= max(1., float(fan_in + fan_out) / 2)

TypeError: unsupported operand type(s) for +: 'int' and 'numpy.str_'

from talos.

-FYI,

This was the working code which I tried to wrap it with talos.
#Denoising Autoencoder

Input_Experiment = Input(shape=(500,))

encoded = Dense(encoding_dim, activation = activation_function_1,
activity_regularizer=regularizers.l1(regulariser_value))(Input_Experiment)

decoded = Dense(500, activation='tanh')(encoded)

autoencoder = Model(Input_Experiment, decoded)

encoder = Model(Input_Experiment, encoded)

encoded_input = Input(shape=(encoding_dim,))
decoder_layer = autoencoder.layers[-1]

decoder = Model(encoded_input, decoder_layer(encoded_input))

autoencoder.compile(optimizer='adadelta', loss='mean_squared_error')

from keras import callbacks
callback = callbacks.TensorBoard(log_dir=r'C:\Tensor Logs',
histogram_freq=0,
write_graph=True,
write_images=True)

autoencoder_anm_data = autoencoder.fit(x_train_ANM,x_train_EXP, epochs=epoch,
batch_size = batch, shuffle = True,
validation_data=(x_test_ANM,x_test_EXP),
callbacks=[callback])

Data Shape.
It is a time series data with each row containing 500 time stamps
x_train_ANM = [1199,500]
x_train_EXP = [1199,500]

from talos.

The issue in your model seems to be here:

File "", line 8, in AE activity_regularizer=regularizers.l1(regulariser_value))(Input_Experiment)

Maybe you can try without that line and see what happens (as that's what's causing the error).

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This is resolved in the latest version of master, correct @mikkokotila?

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