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KeyboardInterrupt Traceback (most recent call last)
<ipython-input-50-23b3449f387b> in <module>()
1 H = model.fit(trainX, trainY, validation_data=(testX, testY),
----> 2 epochs=EPOCHS, batch_size=32)
/usr/local/lib/python3.6/dist-packages/keras/engine/training.py in fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_freq, max_queue_size, workers, use_multiprocessing, **kwargs)
1176 steps_per_epoch=steps_per_epoch,
1177 validation_steps=validation_steps,
-> 1178 validation_freq=validation_freq)
1179
1180 def evaluate(self,
/usr/local/lib/python3.6/dist-packages/keras/engine/training_arrays.py in fit_loop(model, fit_function, fit_inputs, out_labels, batch_size, epochs, verbose, callbacks, val_function, val_inputs, shuffle, callback_metrics, initial_epoch, steps_per_epoch, validation_steps, validation_freq)
202 ins_batch[i] = ins_batch[i].toarray()
203
--> 204 outs = fit_function(ins_batch)
205 outs = to_list(outs)
206 for l, o in zip(out_labels, outs):
/usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py in __call__(self, inputs)
2977 return self._legacy_call(inputs)
2978
-> 2979 return self._call(inputs)
2980 else:
2981 if py_any(is_tensor(x) for x in inputs):
/usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py in _call(self, inputs)
2935 fetched = self._callable_fn(*array_vals, run_metadata=self.run_metadata)
2936 else:
-> 2937 fetched = self._callable_fn(*array_vals)
2938 return fetched[:len(self.outputs)]
2939
/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/client/session.py in __call__(self, *args, **kwargs)
1470 ret = tf_session.TF_SessionRunCallable(self._session._session,
1471 self._handle, args,
-> 1472 run_metadata_ptr)
1473 if run_metadata:
1474 proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)
KeyboardInterrupt: