ValueError

[adeyris]

Hi ! Thanks for this contribution :)

I'm trying to run ann-visualizer on keras-RetinaNet, but I get this error :

ValueError: invalid literal for int() with base 10: 'Non'

Any idea of how to solve it ?

[RedaOps]

Can you provide a code sample?

[RedaOps]

It seems like keras-RetinaNet uses a DenseNet object to build the network. Our library only supports Sequential objects at this time.

[z2e2]

I run into the same issue. It says ValueError: invalid literal for int() with base 10: ''. I think it is because you try to parse the input shape using the following command:
str(input_shape).split(',')[1][1:-1]
But the problem with my keras is that my keras input shape is (None, 4, 125).
I don't think the code works for this case. Is my keras version different from yours?

[RedaOps]

@ZZHAOatEESI Are you passing the ann_viz() function a Model or a Sequential object?

[z2e2]

I passed a model object On Apr 24, 2018, at 3:53 PM, Tudor Gheorghiu <[email protected]<mailto:[email protected]>> wrote: @ZZHAOatEESI<https://na01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2FZZHAOatEESI&data=02%7C01%7Czz374%40drexel.edu%7C139c5922b698493b096d08d5aa1d09ae%7C3664e6fa47bd45a696708c4f080f8ca6%7C0%7C0%7C636601964055275819&sdata=r2oaATx5HHnFx9GresQgg6O6RSTj9i19qXwyYcEqGF8%3D&reserved=0> Are you passing the ann_viz() function a Model or a Sequential object? — You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub<https://na01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2FProdicode%2Fann-visualizer%2Fissues%2F7%23issuecomment-384058558&data=02%7C01%7Czz374%40drexel.edu%7C139c5922b698493b096d08d5aa1d09ae%7C3664e6fa47bd45a696708c4f080f8ca6%7C0%7C0%7C636601964055275819&sdata=j8%2FcGMLECrLRtvQI%2BjvcT00t7yCpik6aMQZaZsAvD1g%3D&reserved=0>, or mute the thread<https://na01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fnotifications%2Funsubscribe-auth%2FASUuoXOeeNWoC7isdgVEbag5C9yX1L-Xks5tr4KngaJpZM4TX-_G&data=02%7C01%7Czz374%40drexel.edu%7C139c5922b698493b096d08d5aa1d09ae%7C3664e6fa47bd45a696708c4f080f8ca6%7C0%7C0%7C636601964055275819&sdata=uK%2BWPVDTMRjVNLnTubIY9yMhzFo4EpG0FHQan0Os3mA%3D&reserved=0>.

[shivam05011996]

@Prodicode
I have a siamese network, trying to visualise it but got this error -

raise ValueError("ANN Visualizer: Layer not supported for visualizing");
ValueError: ANN Visualizer: Layer not supported for visualizing

I have tried various methods to make it visualise but nothing helps. Any help is appreciated.

Model Summary -

__________________________________________________________________________________________________
Layer (type)                    Output Shape         Param #     Connected to                     
==================================================================================================
input_1 (InputLayer)            (None, 300)          0                                            
__________________________________________________________________________________________________
input_2 (InputLayer)            (None, 300)          0                                            
__________________________________________________________________________________________________
sequential_1 (Sequential)       (None, 300)          564200      input_1[0][0]                    
                                                                 input_2[0][0]                    
__________________________________________________________________________________________________
lambda_1 (Lambda)               (None, 1)            0           sequential_1[1][0]               
                                                                 sequential_1[2][0]               
==================================================================================================
Total params: 564,200
Trainable params: 564,200
Non-trainable params: 0

[RedaOps]

@shivam-deepcompute Can you provide the piece of code where you build the keras Sequential model? (Layer by layer)

[shivam05011996]

@Prodicode

def _create_base_network(self, input_dim):
    a = 'softsign'
    network = Sequential()
    network.add(Dense(1000, input_shape=(input_dim,), activation=a)
    network.add(Dense(150, input_shape=(input_dim,), activation=a))
    network.add(Dense(250, input_shape=(input_dim,), activation=a))
    network.add(Dense(300, input_shape=(input_dim,), activation='sigmoid')
    return network

This is my base sequential network, which accepts two inputs, as mentioned in the model summary. I hope this what you asked.

[thpatty]

@Prodicode

hello, i use your example , but i met this error below, can you help me ?
i use windows 10 and jupyter notebook. i can see the two files in the same file directory with *.ipynb
i can open the network.gv.pdf with chrome, i just only can see the first two layers. what is wrong with it?

thanks firstly.

OSError Traceback (most recent call last)
in ()
50
51 model = build_cnn_model()
---> 52 ann_viz(model, title="")

C:\ProgramData\Anaconda3\lib\site-packages\ann_visualizer\visualize.py in ann_viz(model, view, filename, title)
204 g.edge_attr.update(arrowhead="none", color="#707070");
205 if view == True:
--> 206 g.view();

C:\ProgramData\Anaconda3\lib\site-packages\graphviz\files.py in view(self, filename, directory, cleanup)
201 """
202 return self.render(filename=filename, directory=directory, view=True,
--> 203 cleanup=cleanup)
204
205 def _view(self, filepath, format):

C:\ProgramData\Anaconda3\lib\site-packages\graphviz\files.py in render(self, filename, directory, view, cleanup)
180
181 if view:
--> 182 self._view(rendered, self._format)
183
184 return rendered

C:\ProgramData\Anaconda3\lib\site-packages\graphviz\files.py in _view(self, filepath, format)
216 raise RuntimeError('%r has no built-in viewer support for %r '
217 'on %r platform' % (self.class, format, backend.PLATFORM))
--> 218 view_method(filepath)
219
220 _view_darwin = staticmethod(backend.view.darwin)

C:\ProgramData\Anaconda3\lib\site-packages\graphviz\backend.py in view_windows(filepath)
227 def view_windows(filepath):
228 """Start filepath with its associated application (windows)."""
--> 229 os.startfile(os.path.normpath(filepath))

OSError: [WinError -2147221003] Application not found: 'network.gv.pdf'

import keras;
from keras.models import Sequential;
from keras.layers import Conv2D, Dense, Dropout, MaxPooling2D, Flatten;
from ann_visualizer.visualize import ann_viz

def build_cnn_model():
model = keras.models.Sequential()

model.add(
Conv2D(
32, (3, 3),
padding="same",
input_shape=(32, 32, 3),
activation="relu"))
model.add(Dropout(0.2))

model.add(
Conv2D(
32, (3, 3),
padding="same",
input_shape=(32, 32, 3),
activation="relu"))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Dropout(0.2))

model.add(
Conv2D(
64, (3, 3),
padding="same",
input_shape=(32, 32, 3),
activation="relu"))
model.add(Dropout(0.2))

model.add(
Conv2D(
64, (3, 3),
padding="same",
input_shape=(32, 32, 3),
activation="relu"))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Dropout(0.2))

model.add(Flatten())
model.add(Dense(512, activation="relu"))
model.add(Dropout(0.2))

model.add(Dense(10, activation="softmax"))

return model

model = build_cnn_model()
ann_viz(model, title="")

[LeandroRitter]

Hi!

I am using ANN Visualizer to display concatenated/merged layers but get errors, could you direct me how to properly visualize concatenated layers? Here is my code:

import keras;
from keras.models import Sequential;
from keras.layers import Dense, Concatenate, Merge;

network = Sequential();
network.add(Dense(units=6,
activation='relu',
kernel_initializer='uniform',
input_dim=11));

network.add(Dense(units=6,
activation='relu',
kernel_initializer='uniform'));

another_network = Sequential();
another_network.add(Dense(units=6,
activation='relu',
kernel_initializer='uniform',
input_dim=11));

#result = Sequential();
result = Merge([network, another_network], mode='concat')

#result.add(Dense(units=1,

activation='sigmoid',

kernel_initializer='uniform'));

from ann_visualizer.visualize import ann_viz;

ann_viz(result, title = "", view = True);

and here is the error:

---

ValueError Traceback (most recent call last)
in ()
28 from ann_visualizer.visualize import ann_viz;
29
---> 30 ann_viz(result, title = "Autoencoder", view = True);
31 #convert -density 200 network.gv.pdf network.gv.png

~/miniconda3/lib/python3.6/site-packages/ann_visualizer/visualize.py in ann_viz(model, view, filename, title)
121 c.node(str(n), label="Image\n"+pxls[1]+" x"+pxls[2]+" pixels\n"+clrmap, fontcolor="white");
122 else:
--> 123 raise ValueError("ANN Visualizer: Layer not supported for visualizing");
124 for i in range(0, hidden_layers_nr):
125 with g.subgraph(name="cluster_"+str(i+1)) as c:

ValueError: ANN Visualizer: Layer not supported for visualizing

[endolith]

Same error:

model = Sequential([
    Dense(2, input_shape=(N, 2), use_bias=False)
    ])

ann_viz(model)
Traceback (most recent call last):

  File "<ipython-input-79-02a59322b308>", line 1, in <module>
    ann_viz(model)

  File "C:\Anaconda3\lib\site-packages\ann_visualizer\visualize.py", line 42, in ann_viz
    input_layer = int(str(layer.input_shape).split(",")[1][1:-1]);

ValueError: invalid literal for int() with base 10: ''

[smholsen]

I am also having the same issue with the following model. Do you know how to fix this? :)

            self.base_model = Sequential()
            self.base_model.add(Conv2D(20, input_shape=(5, 25, 1), kernel_size=(3, 3), strides=(1, 1), padding='same', activation='relu'))
            self.base_model.add(Flatten())
            self.base_model.add(Dropout(.4))
            self.base_model.add(Dense(1))
            # Compile model
            # self.base_model.summary()
            self.base_model.compile(loss='mse', optimizer='adam')
            self.base_model.fit(X1, y1, epochs=500, batch_size=128)
            ann_viz(self.base_model, title="ANN Topology")

  File "...\venv\lib\site-packages\ann_visualizer\visualize.py", line 42, in ann_viz
    input_layer = int(str(layer.input_shape).split(",")[1][1:-1]);
ValueError: invalid literal for int() with base 10: ''

[thpatty]

sorry, i cant kill this problem.

…

On Wed, Nov 14, 2018 at 5:58 PM Simon Olsen ***@***.***> wrote: I am also having the same issue with the following model. Do you know how to fix this? :) self.base_model = Sequential() self.base_model.add(Conv2D(20, input_shape=(5, 25, 1), kernel_size=(3, 3), strides=(1, 1), padding='same', activation='relu')) self.base_model.add(Flatten()) self.base_model.add(Dropout(.4)) self.base_model.add(Dense(1)) # Compile model # self.base_model.summary() self.base_model.compile(loss='mse', optimizer='adam') self.base_model.fit(X1, y1, epochs=500, batch_size=128) ann_viz(self.base_model, title="ANN Topology") File "...\venv\lib\site-packages\ann_visualizer\visualize.py", line 42, in ann_viz input_layer = int(str(layer.input_shape).split(",")[1][1:-1]); ValueError: invalid literal for int() with base 10: '' — You are receiving this because you commented. Reply to this email directly, view it on GitHub <#7 (comment)>, or mute the thread <https://github.com/notifications/unsubscribe-auth/Adqn8eqYqnmCjsh00gONa4hdcE1VRsnlks5uu-kwgaJpZM4TX-_G> .

[Asrix-AI]

@shivam05011996 Did you get the solution?

[ShrikanthSingh]

<ipython-input-271-6323c76e75d0> in <module>()
    16 # load weights into new model
    17 model.load_weights("model.h5")
---> 18 ann_viz(model, title="Artificial Neural network - Model Visualization")

/usr/local/lib/python3.6/dist-packages/ann_visualizer/visualize.py in ann_viz(model, view, filename, title)
    40     for layer in model.layers:
    41         if(layer == model.layers[0]):
---> 42             input_layer = int(str(layer.input_shape).split(",")[1][1:-1]);
    43             hidden_layers_nr += 1;
    44             if (type(layer) == keras.layers.core.Dense):

ValueError: invalid literal for int() with base 10: ''```