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Using TensorFlow backend.
Loading cora dataset...
Dataset has 2708 nodes, 5429 edges, 1433 features.
Using local pooling filters...
2020-05-05 21:10:48.564918: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2020-05-05 21:10:48.581495: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f9c91ca7aa0 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2020-05-05 21:10:48.581513: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version
Traceback (most recent call last):
File ".../train.py", line 78, in
batch_size=A.shape[0], epochs=1, shuffle=False, verbose=0)
File "/usr/local/lib/python3.7/site-packages/keras/engine/training.py", line 1239, in fit
validation_freq=validation_freq)
File "/usr/local/lib/python3.7/site-packages/keras/engine/training_arrays.py", line 196, in fit_loop
outs = fit_function(ins_batch)
File "/usr/local/lib/python3.7/site-packages/tensorflow_core/python/keras/backend.py", line 3727, in call
outputs = self._graph_fn(*converted_inputs)
File "/usr/local/lib/python3.7/site-packages/tensorflow_core/python/eager/function.py", line 1551, in call
return self._call_impl(args, kwargs)
File "/usr/local/lib/python3.7/site-packages/tensorflow_core/python/eager/function.py", line 1591, in _call_impl
return self._call_flat(args, self.captured_inputs, cancellation_manager)
File "/usr/local/lib/python3.7/site-packages/tensorflow_core/python/eager/function.py", line 1692, in _call_flat
ctx, args, cancellation_manager=cancellation_manager))
File "/usr/local/lib/python3.7/site-packages/tensorflow_core/python/eager/function.py", line 527, in call
(len(args), len(list(self.signature.input_arg))))
ValueError: Arguments and signature arguments do not match. got: 21, expected: 23
The text was updated successfully, but these errors were encountered:
I got the following error when running model.fit. How do I fix it?
environment: python3.7 scipy 1.4.1 tensorflow 2.1.0
The text was updated successfully, but these errors were encountered: