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XifengGuo / DEC-keras

Keras implementation for Deep Embedding Clustering (DEC)
MIT License
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TypeError: 'float' object cannot be interpreted as an integer #1

Closed iamkaram closed 6 years ago

iamkaram commented 6 years ago

Getting the error with the following message run DEC.py mnist Using TensorFlow backend. Namespace(ae_weights=None, batch_size=256, dataset='mnist', gamma=0.1, maxiter=20000.0, n_clusters=10, save_dir='results', tol=0.001, update_interval=140) MNIST samples (70000, 784) No pretrained ae_weights given, start pretraining... Pretraining the 1th layer... learning rate = 0.1 Traceback (most recent call last):

File "C:\Projects\ProvidersSimilarity\code\DEC-2\DEC-keras-master\DEC.py", line 311, in x=x)

File "C:\Projects\ProvidersSimilarity\code\DEC-2\DEC-keras-master\DEC.py", line 170, in initialize_model sae.fit(x, epochs=400)

File "C:\Projects\ProvidersSimilarity\code\DEC-2\DEC-keras-master\SAE.py", line 133, in fit self.pretrain_stacks(x, epochs=epochs/2)

File "C:\Projects\ProvidersSimilarity\code\DEC-2\DEC-keras-master\SAE.py", line 102, in pretrain_stacks self.stacks[i].fit(features, features, batch_size=self.batch_size, epochs=epochs/3)

File "C:\Users\kaneja\AppData\Local\Continuum\Anaconda3\lib\site-packages\keras\models.py", line 867, in fit initial_epoch=initial_epoch)

File "C:\Users\kaneja\AppData\Local\Continuum\Anaconda3\lib\site-packages\keras\engine\training.py", line 1598, in fit validation_steps=validation_steps)

File "C:\Users\kaneja\AppData\Local\Continuum\Anaconda3\lib\site-packages\keras\engine\training.py", line 1130, in _fit_loop for epoch in range(initial_epoch, epochs):

TypeError: 'float' object cannot be interpreted as an integer

XifengGuo commented 6 years ago

@iamkaram It's because of python 3. The newest code is adapted to python3.